U.S. patent application number 16/108327 was filed with the patent office on 2020-02-27 for autonomous system operator cognitive state detection and alerting.
The applicant listed for this patent is NIO USA, Inc.. Invention is credited to James S. Higgins, Abhishek Singhal.
Application Number | 20200062275 16/108327 |
Document ID | / |
Family ID | 69584401 |
Filed Date | 2020-02-27 |
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United States Patent
Application |
20200062275 |
Kind Code |
A1 |
Higgins; James S. ; et
al. |
February 27, 2020 |
AUTONOMOUS SYSTEM OPERATOR COGNITIVE STATE DETECTION AND
ALERTING
Abstract
Autonomous systems, such as vehicles being operated in a
self-driving mode, may allow for human occupants to be inattentive
to the operation of the system. However, events may occur that
require a human user to perform an action. Systems and method are
provided that enable an autonomous system to determine whether the
system requires, or will require, a user action and whether the
user is or is not attentive. If an action is required and the human
is not attentive, an alerting protocol is executed to cause the
system to perform actions that enable the user to be alerted, such
as to enable the, now attentive, user to be able to perform the
action.
Inventors: |
Higgins; James S.; (San
Jose, CA) ; Singhal; Abhishek; (Santa Clara,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
NIO USA, Inc. |
San Jose |
CA |
US |
|
|
Family ID: |
69584401 |
Appl. No.: |
16/108327 |
Filed: |
August 22, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06K 9/00845 20130101;
G05D 1/0088 20130101; B60W 2050/146 20130101; B60W 2050/143
20130101; B60W 40/08 20130101; G05D 1/0061 20130101; B60W 2040/0818
20130101; B60W 50/14 20130101; G05D 2201/0213 20130101 |
International
Class: |
B60W 50/14 20060101
B60W050/14; B60W 40/08 20060101 B60W040/08; G05D 1/00 20060101
G05D001/00; G06K 9/00 20060101 G06K009/00 |
Claims
1. An alerting component for an autonomous system, comprising: a
user sensor configured to sense a cognition-indicating attribute of
a user utilizing the autonomous system and the user sensor is
further configured to output a user sensor signal in accord with
the sensed cognition-indicating attribute; a system state input
configured to receive a system state indicating whether the
autonomous system requires the attention of the user; a processor,
comprising a memory for storing instructions for execution by the
processor, and receiving the user sensor signal and the system
state sensor; and the processor, upon determining that each of the
system state indicates the autonomous system is in a state that
requires an action from the user and the user sensor signal
indicates the user is presently inattentive, executes an alerting
protocol; and wherein the processor, as an output of the execution
of the alerting protocol, signals the autonomous system to perform
an alerting action; and wherein the processor, having at least
initiated execution of the alerting protocol, fails to receive an
acknowledgement input to a device configured to receive an input
from the user, provides a subsequent alerting signal to the
autonomous system to perform an alerting action.
2. The alerting component for the autonomous system of claim 1,
wherein the cognition-indicating attribute comprises a signal of a
state of a component of the autonomous system.
3. The alerting component for the autonomous system of claim 1,
wherein the component of the autonomous system is operable to
indicate a usage by the user determinative, at least in part, of
attentiveness.
4. The alerting component for the autonomous system of claim 1,
wherein the processor signals the autonomous system to perform an
alerting action, further comprising signaling an output component
of the autonomous system to perform the alerting action.
5. The alerting component for an autonomous system of claim 1,
wherein the processor signals the autonomous system to perform an
alerting action, further comprising signaling a configuration
component of the autonomous system to perform the alerting action
comprising a reconfiguration of the configuration component.
6. The alerting component for the autonomous system of claim 1,
wherein the processor, having at least initiated execution of the
alerting protocol, receives either an updated value from the system
state input indicating the system state does not require the action
from the user or the user sensor signal indicating the user is not
presently inattentive, terminates the alerting protocol.
7. The alerting component for the autonomous system of claim 6,
wherein the processor determines the system state indicates the
autonomous system is not in the state that requires the action from
the user, when the system state indicates the autonomous system is
currently being operated by the user or not in an autonomous
mode.
8. The alerting component for the autonomous system of claim 1,
wherein the processor executes the alerting protocol modified by
configuration preferences and provides signals the autonomous
system to perform an alerting action in accord with the
configuration preferences.
9. The alerting component of the autonomous system of claim 1,
wherein the alerting component comprises a portion of the
autonomous system and the autonomous system is vehicle for
conveying the user.
10. (canceled)
11. A method for alerting a user utilizing an autonomous system,
comprising: sensing a cognition-indicating attribute of the user;
sensing an attention requiring attribute of the autonomous system;
upon determining that each of cognitive-indicating attribute of the
user indicates inattentiveness and attention requiring attribute of
the autonomous system indicates the autonomous system is in a state
that requires an action from the user, executing an alerting
protocol comprising outputting signals to the autonomous system to
cause the autonomous system to perform an alerting action; and upon
having at least initiated execution of the alerting protocol, and
failing to receive an acknowledgement input to a device configured
to receive an input from the user, providing a subsequent alerting
signal to the autonomous system to perform an alerting action.
12. The method of claim 11, wherein the cognition-indicating
attribute comprises a signal of a state of the component of the
autonomous system.
13. The method of claim 11, wherein outputting signals to the
autonomous system to cause the autonomous system to perform the
alerting action, further comprises outputting signals to the
autonomous system to cause a component of the autonomous system to
perform the alerting action.
14. The method of claim 11, wherein the alerting action, further
comprises an alerting action signaling a configuration component of
the autonomous system to perform the alerting action comprising a
reconfiguration of the configuration component.
15. The method of claim 11, further comprising, having at least
initiated execution of the alerting protocol, receiving either an
updated value from the system state input indicating the system
state does not require the action from the user or the user sensor
signal indicating the user is not presently inattentive, and in
response thereto, terminating the alerting protocol.
16. The method of claim 16, wherein receiving the updated value
from the system state indicating the autonomous system is not in
the state that requires the action from the user, comprising the
system state indicates the autonomous system is currently being
operated by the user or not in an autonomous mode.
17. The method of claim 11, wherein the alerting protocol is
determined, at least in part, in accord with configured
preferences.
18. The method of claim 11, wherein the alerting component
comprises a portion of the autonomous system and the autonomous
system is vehicle for conveying the user.
19. An autonomous vehicle, comprising: a processor configured to
operate the vehicle in an autonomous mode and a non-autonomous
mode, comprising providing all control inputs to vehicle control
components and operate the vehicle in a non-autonomous mode wherein
a user input to a user input component provides at least one of the
all control inputs to at least one of the vehicle control
components; a user sensor configured to sense a
cognition-indicating attribute of the user utilizing the vehicle
and, in response thereto, output a user sensor signal to the
processor; the processor, comprising a memory for storing
instructions for execution by the processor, and receiving the user
sensor signal; and the processor, upon determining that the vehicle
is in the autonomous mode and the user sensor signal indicates the
user is presently inattentive, executes an alerting protocol; and
wherein the processor, as an output of the execution of the
alerting protocol, signals the vehicle to perform an alerting
action; and wherein the processor, having at least initiated
execution of the alerting protocol, fails to receive an
acknowledgement input to a device configured to receive an input
from the user, provides a subsequent alerting signal to the
autonomous system to perform an alerting action.
20. The autonomous vehicle of claim 19, wherein: the user sensor
further comprises a configuration sensor to output the sensor
signal indicating a configuration of a user-configured component of
the vehicle; and the processor, upon determining the sensor signal
indicates the user-configured component of the vehicle is
configured in a manner that hinders the user from being attentive,
further determining the user sensor indicates the user is presently
inattentive.
Description
FIELD
[0001] The present disclosure is generally directed to vehicle
systems, in particular, toward autonomous vehicle systems.
BACKGROUND
[0002] In recent years, transportation methods have changed
substantially. This change is due in part to a concern over the
limited availability of natural resources, a proliferation in
personal technology, traffic safety, and a societal shift to adopt
more environmentally friendly transportation solutions. These
considerations have encouraged the development of a number of new
flexible-fuel vehicles, hybrid-electric vehicles, and electric
vehicles.
[0003] Generally, drivers must remain alert to drive a vehicle. If
the driver falls asleep or is distracted, the possibility of an
accident is severely increased. Thus, some systems have been
created to alert a driver when they fall asleep or become
distracted. Additionally, autonomous and semi-autonomous vehicles
are becoming more readily available. Unfortunately, these systems
ignore the desires and cognitive capacities of the user, namely, to
fall asleep or pay attention to something other than driving.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 shows a vehicle in accordance with embodiments of the
present disclosure;
[0005] FIG. 2 shows a plan view of the vehicle in accordance with
at least some embodiments of the present disclosure;
[0006] FIG. 3A is a block diagram of an embodiment of a
communication environment of the vehicle in accordance with
embodiments of the present disclosure;
[0007] FIG. 3B is a block diagram of an embodiment of interior
sensors within the vehicle in accordance with embodiments of the
present disclosure;
[0008] FIG. 3C is a block diagram of an embodiment of a navigation
system of the vehicle in accordance with embodiments of the present
disclosure;
[0009] FIG. 4 shows an embodiment of the instrument panel of the
vehicle according to one embodiment of the present disclosure;
[0010] FIG. 5 is a block diagram of an embodiment of a
communications subsystem of the vehicle;
[0011] FIG. 6 is a block diagram of a computing environment
associated with the embodiments presented herein;
[0012] FIG. 7 is a block diagram of a computing device associated
with one or more components described herein;
[0013] FIG. 8A shows a visual representation of an embodiment of a
vehicle localization system in accordance with embodiments of the
present disclosure;
[0014] FIG. 8B shows another visual representation of an embodiment
of a sensor API in accordance with embodiments of the present
disclosure;
[0015] FIG. 8C shows another visual representation of a cognitive
state determiner in accordance with embodiments of the present
disclosure;
[0016] FIG. 8D shows another visual representation of an embodiment
of an alert system in accordance with embodiments of the present
disclosure;
[0017] FIG. 8E shows another visual representation of an embodiment
of a state engine in accordance with embodiments of the present
disclosure;
[0018] FIG. 9A is a diagram of an embodiment of a data store that
stores localization data in accordance with embodiments of the
present disclosure;
[0019] FIG. 9B is a diagram of an embodiment of a data structure
that stores localization data in accordance with embodiments of the
present disclosure;
[0020] FIG. 10 is a diagram of an embodiment of a component with a
display in accordance with embodiments of the present
disclosure;
[0021] FIG. 11 is a process diagram of an embodiment in accordance
with embodiments of the present disclosure;
[0022] FIG. 12 is a process diagram of an embodiment in accordance
with embodiments of the present disclosure;
[0023] FIG. 13 is a process diagram of an embodiment in accordance
with embodiments of the present disclosure; and
[0024] FIG. 14 is a process diagram of an embodiment in accordance
with embodiments of the present disclosure.
DETAILED DESCRIPTION
[0025] Embodiments of the present disclosure will be described in
connection with a vehicle, and in some embodiments, a self-driving
vehicle. Methods and systems herein can let an operator of an
autonomous vehicle ignore the need to drive the vehicle. Thus, the
driver can fall asleep, become distracted, or experience other
cognitive or neural events that cause the driver to lose
consciousness or the ability to control a motor vehicle. However,
at appropriate times, rather that whenever the driver is asleep or
distracted, the vehicle can alert the driver that their attention
is required or wake the driver up. The alerts ensure the safe
operation of the vehicle while allowing the driver to do what they
are able and desire.
[0026] Until autonomous vehicles became a reality, drivers have
never been able to safely sleep, close their eyes, mind wander, or
otherwise engage in an alternative task (e.g. watching a movie)
while the vehicle was moving. This is similar across many domains
where people no longer actively control a system but instead
monitor and intervene. In accordance with embodiments of the
present disclosure, methods and systems are disclosed for detecting
and measuring an operator of an autonomous system (e.g. an operator
or passenger of an autonomous vehicle) who has their eyes closed,
is fully asleep, or is engaging in an alternative task, and
alerting or waking them up at appropriate or required times (e.g.
they have reached their destination or the system state has
changed). All known previous methods and systems have focused on
preventing operators from becoming disengaged or falling asleep.
Methods and system described herein allow operators to sleep or
become otherwise disengaged from their primary operating task and
ensures they are alerted or woken up at the appropriate time.
[0027] While operating an autonomous system an operator may
cognitively disengage from operating or monitoring the system.
Alternatively, the operator may purposely or inadvertently fall
asleep during normal operations or monitoring. In accordance with
embodiments of the present disclosure, the system, making use of a
collection of diverse sensors in one or more sensor packages, a
central processing system, and a collection of alarms/alerts will
be able to detect driver state, determine whether it conflicts with
the system's needs, and finally wake-up or alert the driver in the
most effective way for the situation.
[0028] The sensor package is made up of a collection of sensors
that either alone, or in combination with other sensors, can detect
the appropriate behavioral or physiological indices of cognitive
states that may conflict with the current needs of the system. Some
examples of sensors that may be used individually, or in
combination, are cameras that can be used for computer vision
algorithms to detect face, eye, or other body positions of the
autonomous system operator. Pressure or weight sensors in a seat
may also be able to determine operator movement or position.
Vehicle or other system data can also be used to determine how the
driver is behaving. Additionally, if the system can be in frequent
physical contact with the operator many physiological sensors may
become practical. These can include (but are not limited to)
electromyographs, goniometers, electrocardiography, capacitive skin
sensors, electroencephalograph, functional near infrared
spectroscopy, temperature, or other sensors that can acquire
information about human physiology, cognition, or behavior.
[0029] Sensor outputs are processed by a central processing system.
This processing consists of both basic signal processing (Fourier
transformations, band pass filtering, etc.) in order to filter,
clean, and/or combine the data for cognitive/behavioral state
prediction through machine learning, neural net, or other
processing algorithms. Once the operator's cognitive state is
predicted it is considered in combination with system state
information (system faults, etc.) and environment state (time of
day, location, etc.) to decide whether the operator should be
alerted/woken; if the operator should not be alerted/woken, what
course of action should the autonomous system take; and what is the
most appropriate method for alerting/waking the operator (e.g.
quickly waking the operator vs. a low priority gentle wake-up
sequence). The system described herein can also be used to provide
additional system behaviors appropriate for the operator state. For
example, the driver may have fallen unconscious and does not
respond to the alerts. The system could then contact an emergency
contact and/or change the automation state.
[0030] Once the system decides to wake/alert the system operator,
the system then uses a combination of alerting modalities that can
be used alone, in combination, or in a staged manner. For example,
an autonomous vehicle reaches its destination and attempts to wake
the operator by first turning on the interior lights of the vehicle
(if it is night time), then plays an audible alert if the driver
does not respond to the lights turning on, and finally a louder
alert is played followed by the driver's seat automatically
inclining. Alternatively, if the autonomous system encounters a
critical error and requires the currently sleeping operator to take
control, the system may first play a gentle auditory alert followed
by vibrating the operator's seat. Once the operator has awoken or
became responsive, they are prompted to respond to a confirmation
prompt, which may be required in order to keep the vehicle from
taking an action based on a non-responsive operator. If the
operator has been asleep for an extended time the system may also
suggest actions to refresh the operator, such as a by taking a
break or obtaining a caffeinated food or beverage.
[0031] Methods and systems described herein are not solely focused
on detecting and waking a sleeping driver, providing localized
delivery of services, or heart rate monitoring and transmission.
Rather, in accordance with embodiments of the present disclosure,
the methods and systems may provide a detection and alerting
capability for autonomous systems that determines whether there is
a system event that requires attention; determines an autonomous
system (e.g. automated car, automated train, aircraft, powerplant
control system, industrial monitoring system, etc.) operator's
cognitive state (i.e. attentive, distracted, or asleep); determines
the most appropriate course of action to get the desired response
from the operator; confirms that the operator has responded or is
able to respond to the system request; and/or potentially change
the behavior of the automated system to accommodate the inattentive
or sleeping operator if they are not alerted or woken up.
[0032] The methods and systems described herein provide methods of
monitoring autonomous system operator's cognitive and behavioral
states to alert or wake them at an appropriate time to respond to
system prompts, monitor a situation, or take control of the system.
Additionally, the system can determine the most appropriate way of
waking or alerting the operator.
[0033] FIG. 1 shows a perspective view of a vehicle 100 in
accordance with embodiments of the present disclosure. The electric
vehicle 100 comprises a vehicle front 110, vehicle aft or rear 120,
vehicle roof 130, at least one vehicle side 160, a vehicle
undercarriage 140, and a vehicle interior 150. In any event, the
vehicle 100 may include a frame 104 and one or more body panels 108
mounted or affixed thereto. The vehicle 100 may include one or more
interior components (e.g., components inside an interior space 150,
or user space, of a vehicle 100, etc.), exterior components (e.g.,
components outside of the interior space 150, or user space, of a
vehicle 100, etc.), drive systems, controls systems, structural
components, etc.
[0034] Although shown in the form of a car, it should be
appreciated that the vehicle 100 described herein may include any
conveyance or model of a conveyance, where the conveyance was
designed for the purpose of moving one or more tangible objects,
such as people, animals, cargo, and the like. The term "vehicle"
does not require that a conveyance moves or is capable of movement.
Typical vehicles may include but are in no way limited to cars,
trucks, motorcycles, busses, automobiles, trains, railed
conveyances, boats, ships, marine conveyances, submarine
conveyances, airplanes, space craft, flying machines, human-powered
conveyances, and the like.
[0035] In some embodiments, the vehicle 100 may include a number of
sensors, devices, and/or systems that are capable of assisting in
driving operations, e.g., autonomous or semi-autonomous control.
Examples of the various sensors and systems may include, but are in
no way limited to, one or more of cameras (e.g., independent,
stereo, combined image, etc.), infrared (IR) sensors, radio
frequency (RF) sensors, ultrasonic sensors (e.g., transducers,
transceivers, etc.), RADAR sensors (e.g., object-detection sensors
and/or systems), LIDAR (Light Imaging, Detection, And Ranging)
systems, odometry sensors and/or devices (e.g., encoders, etc.),
orientation sensors (e.g., accelerometers, gyroscopes,
magnetometer, etc.), navigation sensors and systems (e.g., GPS,
etc.), and other ranging, imaging, and/or object-detecting sensors.
The sensors may be disposed in an interior space 150 of the vehicle
100 and/or on an outside of the vehicle 100. In some embodiments,
the sensors and systems may be disposed in one or more portions of
a vehicle 100 (e.g., the frame 104, a body panel, a compartment,
etc.).
[0036] The vehicle sensors and systems may be selected and/or
configured to suit a level of operation associated with the vehicle
100. Among other things, the number of sensors used in a system may
be altered to increase or decrease information available to a
vehicle control system (e.g., affecting control capabilities of the
vehicle 100). Additionally or alternatively, the sensors and
systems may be part of one or more advanced driver assistance
systems (ADAS) associated with a vehicle 100. In any event, the
sensors and systems may be used to provide driving assistance at
any level of operation (e.g., from fully-manual to fully-autonomous
operations, etc.) as described herein.
[0037] The various levels of vehicle control and/or operation can
be described as corresponding to a level of autonomy associated
with a vehicle 100 for vehicle driving operations. For instance, at
Level 0, or fully-manual driving operations, a driver (e.g., a
human driver) may be responsible for all the driving control
operations (e.g., steering, accelerating, braking, etc.) associated
with the vehicle. Level 0 may be referred to as a "No Automation"
level. At Level 1, the vehicle may be responsible for a limited
number of the driving operations associated with the vehicle, while
the driver is still responsible for most driving control
operations. An example of a Level 1 vehicle may include a vehicle
in which the throttle control and/or braking operations may be
controlled by the vehicle (e.g., cruise control operations, etc.).
Level 1 may be referred to as a "Driver Assistance" level. At Level
2, the vehicle may collect information (e.g., via one or more
driving assistance systems, sensors, etc.) about an environment of
the vehicle (e.g., surrounding area, roadway, traffic, ambient
conditions, etc.) and use the collected information to control
driving operations (e.g., steering, accelerating, braking, etc.)
associated with the vehicle. In a Level 2 autonomous vehicle, the
driver may be required to perform other aspects of driving
operations not controlled by the vehicle. Level 2 may be referred
to as a "Partial Automation" level. It should be appreciated that
Levels 0-2 all involve the driver monitoring the driving operations
of the vehicle.
[0038] At Level 3, the driver may be separated from controlling all
the driving operations of the vehicle except when the vehicle makes
a request for the operator to act or intervene in controlling one
or more driving operations. In other words, the driver may be
separated from controlling the vehicle unless the driver is
required to take over for the vehicle. Level 3 may be referred to
as a "Conditional Automation" level. At Level 4, the driver may be
separated from controlling all the driving operations of the
vehicle and the vehicle may control driving operations even when a
user fails to respond to a request to intervene. Level 4 may be
referred to as a "High Automation" level. At Level 5, the vehicle
can control all the driving operations associated with the vehicle
in all driving modes. The vehicle in Level 5 may continually
monitor traffic, vehicular, roadway, and/or environmental
conditions while driving the vehicle. In Level 5, there is no human
driver interaction required in any driving mode. Accordingly, Level
5 may be referred to as a "Full Automation" level. It should be
appreciated that in Levels 3-5 the vehicle, and/or one or more
automated driving systems associated with the vehicle, monitors the
driving operations of the vehicle and the driving environment.
[0039] As shown in FIG. 1, the vehicle 100 may, for example,
include at least one of a ranging and imaging system 112 (e.g.,
LIDAR, etc.), an imaging sensor 116A, 116F (e.g., camera, IR,
etc.), a radio object-detection and ranging system sensors 116B
(e.g., RADAR, RF, etc.), ultrasonic sensors 116C, and/or other
object-detection sensors 116D, 116E. In some embodiments, the LIDAR
system 112 and/or sensors may be mounted on a roof 130 of the
vehicle 100. In one embodiment, the RADAR sensors 116B may be
disposed at least at a front 110, aft 120, or side 160 of the
vehicle 100. Among other things, the RADAR sensors may be used to
monitor and/or detect a position of other vehicles, pedestrians,
and/or other objects near, or proximal to, the vehicle 100. While
shown associated with one or more areas of a vehicle 100, it should
be appreciated that any of the sensors and systems 116A-K, 112
illustrated in FIGS. 1 and 2 may be disposed in, on, and/or about
the vehicle 100 in any position, area, and/or zone of the vehicle
100.
[0040] Referring now to FIG. 2, a plan view of a vehicle 100 will
be described in accordance with embodiments of the present
disclosure. In particular, FIG. 2 shows a vehicle sensing
environment 200 at least partially defined by the sensors and
systems 116A-K, 112 disposed in, on, and/or about the vehicle 100.
Each sensor 116A-K may include an operational detection range R and
operational detection angle. The operational detection range R may
define the effective detection limit, or distance, of the sensor
116A-K. In some cases, this effective detection limit may be
defined as a distance from a portion of the sensor 116A-K (e.g., a
lens, sensing surface, etc.) to a point in space offset from the
sensor 116A-K. The effective detection limit may define a distance,
beyond which, the sensing capabilities of the sensor 116A-K
deteriorate, fail to work, or are unreliable. In some embodiments,
the effective detection limit may define a distance, within which,
the sensing capabilities of the sensor 116A-K are able to provide
accurate and/or reliable detection information. The operational
detection angle may define at least one angle of a span, or between
horizontal and/or vertical limits, of a sensor 116A-K. As can be
appreciated, the operational detection limit and the operational
detection angle of a sensor 116A-K together may define the
effective detection zone 216A-D (e.g., the effective detection
area, and/or volume, etc.) of a sensor 116A-K.
[0041] In some embodiments, the vehicle 100 may include a ranging
and imaging system 112 such as LIDAR, or the like. The ranging and
imaging system 112 may be configured to detect visual information
in an environment surrounding the vehicle 100. The visual
information detected in the environment surrounding the ranging and
imaging system 112 may be processed (e.g., via one or more sensor
and/or system processors, etc.) to generate a complete 360-degree
view of an environment 200 around the vehicle. The ranging and
imaging system 112 may be configured to generate changing
360-degree views of the environment 200 in real-time, for instance,
as the vehicle 100 drives. In some cases, the ranging and imaging
system 112 may have an effective detection limit 204 that is some
distance from the center of the vehicle 100 outward over 360
degrees. The effective detection limit 204 of the ranging and
imaging system 112 defines a view zone 208 (e.g., an area and/or
volume, etc.) surrounding the vehicle 100. Any object falling
outside of the view zone 208 is in the undetected zone 212 and
would not be detected by the ranging and imaging system 112 of the
vehicle 100.
[0042] Sensor data and information may be collected by one or more
sensors or systems 116A-K, 112 of the vehicle 100 monitoring the
vehicle sensing environment 200. This information may be processed
(e.g., via a processor, computer-vision system, etc.) to determine
targets (e.g., objects, signs, people, markings, roadways,
conditions, etc.) inside one or more detection zones 208, 216A-D
associated with the vehicle sensing environment 200. In some cases,
information from multiple sensors 116A-K may be processed to form
composite sensor detection information. For example, a first sensor
116A and a second sensor 116F may correspond to a first camera 116A
and a second camera 116F aimed in a forward traveling direction of
the vehicle 100. In this example, images collected by the cameras
116A, 116F may be combined to form stereo image information. This
composite information may increase the capabilities of a single
sensor in the one or more sensors 116A-K by, for example, adding
the ability to determine depth associated with targets in the one
or more detection zones 208, 216A-D. Similar image data may be
collected by rear view cameras (e.g., sensors 116G, 116H) aimed in
a rearward traveling direction vehicle 100.
[0043] In some embodiments, multiple sensors 116A-K may be
effectively joined to increase a sensing zone and provide increased
sensing coverage. For instance, multiple RADAR sensors 116B
disposed on the front 110 of the vehicle may be joined to provide a
zone 216B of coverage that spans across an entirety of the front
110 of the vehicle. In some cases, the multiple RADAR sensors 116B
may cover a detection zone 216B that includes one or more other
sensor detection zones 216A. These overlapping detection zones may
provide redundant sensing, enhanced sensing, and/or provide greater
detail in sensing within a particular portion (e.g., zone 216A) of
a larger zone (e.g., zone 216B). Additionally or alternatively, the
sensors 116A-K of the vehicle 100 may be arranged to create a
complete coverage, via one or more sensing zones 208, 216A-D around
the vehicle 100. In some areas, the sensing zones 216C of two or
more sensors 116D, 116E may intersect at an overlap zone 220. In
some areas, the angle and/or detection limit of two or more sensing
zones 216C, 216D (e.g., of two or more sensors 116E, 116J, 116K)
may meet at a virtual intersection point 224.
[0044] The vehicle 100 may include a number of sensors 116E, 116G,
116H, 116J, 116K disposed proximal to the rear 120 of the vehicle
100. These sensors can include, but are in no way limited to, an
imaging sensor, camera, IR, a radio object-detection and ranging
sensors, RADAR, RF, ultrasonic sensors, and/or other
object-detection sensors. Among other things, these sensors 116E,
116G, 116H, 116J, 116K may detect targets near or approaching the
rear of the vehicle 100. For example, another vehicle approaching
the rear 120 of the vehicle 100 may be detected by one or more of
the ranging and imaging system (e.g., LIDAR) 112, rear-view cameras
116G, 116H, and/or rear facing RADAR sensors 116J, 116K. As
described above, the images from the rear-view cameras 116G, 116H
may be processed to generate a stereo view (e.g., providing depth
associated with an object or environment, etc.) for targets visible
to both cameras 116G, 116H. As another example, the vehicle 100 may
be driving and one or more of the ranging and imaging system 112,
front-facing cameras 116A, 116F, front-facing RADAR sensors 116B,
and/or ultrasonic sensors 116C may detect targets in front of the
vehicle 100. This approach may provide critical sensor information
to a vehicle control system in at least one of the autonomous
driving levels described above. For instance, when the vehicle 100
is driving autonomously (e.g., Level 3, Level 4, or Level 5) and
detects other vehicles stopped in a travel path, the sensor
detection information may be sent to the vehicle control system of
the vehicle 100 to control a driving operation (e.g., braking,
decelerating, etc.) associated with the vehicle 100 (in this
example, slowing the vehicle 100 as to avoid colliding with the
stopped other vehicles). As yet another example, the vehicle 100
may be operating and one or more of the ranging and imaging system
112, and/or the side-facing sensors 116D, 116E (e.g., RADAR,
ultrasonic, camera, combinations thereof, and/or other type of
sensor), may detect targets at a side of the vehicle 100. It should
be appreciated that the sensors 116A-K may detect a target that is
both at a side 160 and a front 110 of the vehicle 100 (e.g.,
disposed at a diagonal angle to a centerline of the vehicle 100
running from the front 110 of the vehicle 100 to the rear 120 of
the vehicle). Additionally or alternatively, the sensors 116A-K may
detect a target that is both, or simultaneously, at a side 160 and
a rear 120 of the vehicle 100 (e.g., disposed at a diagonal angle
to the centerline of the vehicle 100).
[0045] FIGS. 3A-3C are block diagrams of an embodiment of a
communication environment 300 of the vehicle 100 in accordance with
embodiments of the present disclosure. The communication system 300
may include one or more vehicle driving vehicle sensors and systems
304, sensor processors 340, sensor data memory 344, vehicle control
system 348, communications subsystem 350, control data 364,
computing devices 368, display devices 372, and other components
374 that may be associated with a vehicle 100. These associated
components may be electrically and/or communicatively coupled to
one another via at least one bus 360. In some embodiments, the one
or more associated components may send and/or receive signals
across a communication network 352 to at least one of a navigation
source 356A, a control source 356B, or some other entity 356N.
[0046] In accordance with at least some embodiments of the present
disclosure, the communication network 352 may comprise any type of
known communication medium or collection of communication media and
may use any type of protocols, such as SIP, TCP/IP, SNA, IPX,
AppleTalk, and the like, to transport messages between endpoints.
The communication network 352 may include wired and/or wireless
communication technologies. The Internet is an example of the
communication network 352 that constitutes an Internet Protocol
(IP) network consisting of many computers, computing networks, and
other communication devices located all over the world, which are
connected through many telephone systems and other means. Other
examples of the communication network 352 include, without
limitation, a standard Plain Old Telephone System (POTS), an
Integrated Services Digital Network (ISDN), the Public Switched
Telephone Network (PSTN), a Local Area Network (LAN), such as an
Ethernet network, a Token-Ring network and/or the like, a Wide Area
Network (WAN), a virtual network, including without limitation a
virtual private network ("VPN"); the Internet, an intranet, an
extranet, a cellular network, an infra-red network; a wireless
network (e.g., a network operating under any of the IEEE 802.9
suite of protocols, the Bluetooth.RTM. protocol known in the art,
and/or any other wireless protocol), and any other type of
packet-switched or circuit-switched network known in the art and/or
any combination of these and/or other networks. In addition, it can
be appreciated that the communication network 352 need not be
limited to any one network type, and instead may be comprised of a
number of different networks and/or network types. The
communication network 352 may comprise a number of different
communication media such as coaxial cable, copper cable/wire,
fiber-optic cable, antennas for transmitting/receiving wireless
messages, and combinations thereof.
[0047] The driving vehicle sensors and systems 304 may include at
least one navigation 308 (e.g., global positioning system (GPS),
etc.), orientation 312, odometry 316, LIDAR 320, RADAR 324,
ultrasonic 328, camera 332, infrared (IR) 336, and/or other sensor
or system 338. These driving vehicle sensors and systems 304 may be
similar, if not identical, to the sensors and systems 116A-K, 112
described in conjunction with FIGS. 1 and 2.
[0048] The navigation sensor 308 may include one or more sensors
having receivers and antennas that are configured to utilize a
satellite-based navigation system including a network of navigation
satellites capable of providing geolocation and time information to
at least one component of the vehicle 100. Examples of the
navigation sensor 308 as described herein may include, but are not
limited to, at least one of Garmin.RTM. GLO.TM. family of GPS and
GLONASS combination sensors, Garmin.RTM. GPS 15x.TM. family of
sensors, Garmin.RTM. GPS 16x.TM. family of sensors with
high-sensitivity receiver and antenna, Garmin.RTM. GPS 18x OEM
family of high-sensitivity GPS sensors, Dewetron DEWE-VGPS series
of GPS sensors, GlobalSat 1-Hz series of GPS sensors, other
industry-equivalent navigation sensors and/or systems, and may
perform navigational and/or geolocation functions using any known
or future-developed standard and/or architecture.
[0049] The orientation sensor 312 may include one or more sensors
configured to determine an orientation of the vehicle 100 relative
to at least one reference point. In some embodiments, the
orientation sensor 312 may include at least one pressure
transducer, stress/strain gauge, accelerometer, gyroscope, and/or
geomagnetic sensor. Examples of the navigation sensor 308 as
described herein may include, but are not limited to, at least one
of Bosch Sensortec BMX 160 series low-power absolute orientation
sensors, Bosch Sensortec BMX055 9-axis sensors, Bosch Sensortec
BMI055 6-axis inertial sensors, Bosch Sensortec BMI160 6-axis
inertial sensors, Bosch Sensortec BMF055 9-axis inertial sensors
(accelerometer, gyroscope, and magnetometer) with integrated Cortex
M0+ microcontroller, Bosch Sensortec BMP280 absolute barometric
pressure sensors, Infineon TLV493D-A1B6 3D magnetic sensors,
Infineon TLI493D-W1B6 3D magnetic sensors, Infineon TL family of 3D
magnetic sensors, Murata Electronics SCC2000 series combined gyro
sensor and accelerometer, Murata Electronics SCC1300 series
combined gyro sensor and accelerometer, other industry-equivalent
orientation sensors and/or systems, which may perform orientation
detection and/or determination functions using any known or
future-developed standard and/or architecture.
[0050] The odometry sensor and/or system 316 may include one or
more components that is configured to determine a change in
position of the vehicle 100 over time. In some embodiments, the
odometry system 316 may utilize data from one or more other sensors
and/or systems 304 in determining a position (e.g., distance,
location, etc.) of the vehicle 100 relative to a previously
measured position for the vehicle 100. Additionally or
alternatively, the odometry sensors 316 may include one or more
encoders, Hall speed sensors, and/or other measurement
sensors/devices configured to measure a wheel speed, rotation,
and/or number of revolutions made over time. Examples of the
odometry sensor/system 316 as described herein may include, but are
not limited to, at least one of Infineon TLE4924/26/27/28C
high-performance speed sensors, Infineon TL4941plusC(B) single chip
differential Hall wheel-speed sensors, Infineon TL5041plusC Giant
Magnetoresistance (GMR) effect sensors, Infineon TL family of
magnetic sensors, EPC Model 25SP Accu-CoderPro.TM. incremental
shaft encoders, EPC Model 30M compact incremental encoders with
advanced magnetic sensing and signal processing technology, EPC
Model 925 absolute shaft encoders, EPC Model 958 absolute shaft
encoders, EPC Model MA36S/MA63S/SA36S absolute shaft encoders,
Dynapar.TM. F18 commutating optical encoder, Dynapar.TM. HS35R
family of phased array encoder sensors, other industry-equivalent
odometry sensors and/or systems, and may perform change in position
detection and/or determination functions using any known or
future-developed standard and/or architecture.
[0051] The LIDAR sensor/system 320 may include one or more
components configured to measure distances to targets using laser
illumination. In some embodiments, the LIDAR sensor/system 320 may
provide 3D imaging data of an environment around the vehicle 100.
The imaging data may be processed to generate a full 360-degree
view of the environment around the vehicle 100. The LIDAR
sensor/system 320 may include a laser light generator configured to
generate a plurality of target illumination laser beams (e.g.,
laser light channels). In some embodiments, this plurality of laser
beams may be aimed at, or directed to, a rotating reflective
surface (e.g., a mirror) and guided outwardly from the LIDAR
sensor/system 320 into a measurement environment. The rotating
reflective surface may be configured to continually rotate 360
degrees about an axis, such that the plurality of laser beams is
directed in a full 360-degree range around the vehicle 100. A
photodiode receiver of the LIDAR sensor/system 320 may detect when
light from the plurality of laser beams emitted into the
measurement environment returns (e.g., reflected echo) to the LIDAR
sensor/system 320. The LIDAR sensor/system 320 may calculate, based
on a time associated with the emission of light to the detected
return of light, a distance from the vehicle 100 to the illuminated
target. In some embodiments, the LIDAR sensor/system 320 may
generate over 2.0 million points per second and have an effective
operational range of at least 100 meters. Examples of the LIDAR
sensor/system 320 as described herein may include, but are not
limited to, at least one of Velodyne.RTM. LiDAR.TM. HDL-64E
64-channel LIDAR sensors, Velodyne.RTM. LiDARTM HDL-32E 32-channel
LIDAR sensors, Velodyne.RTM. LiDAR.TM. PUCK.TM. VLP-16 16-channel
LIDAR sensors, Leica Geosystems Pegasus:Two mobile sensor platform,
Garmin.RTM. LIDAR-Lite v3 measurement sensor, Quanergy M8 LiDAR
sensors, Quanergy S3 solid state LiDAR sensor, LeddarTech.RTM.
LeddarVU compact solid state fixed-beam LIDAR sensors, other
industry-equivalent LIDAR sensors and/or systems, and may perform
illuminated target and/or obstacle detection in an environment
around the vehicle 100 using any known or future-developed standard
and/or architecture.
[0052] The RADAR sensors 324 may include one or more radio
components that are configured to detect objects/targets in an
environment of the vehicle 100. In some embodiments, the RADAR
sensors 324 may determine a distance, position, and/or movement
vector (e.g., angle, speed, etc.) associated with a target over
time. The RADAR sensors 324 may include a transmitter configured to
generate and emit electromagnetic waves (e.g., radio, microwaves,
etc.) and a receiver configured to detect returned electromagnetic
waves. In some embodiments, the RADAR sensors 324 may include at
least one processor configured to interpret the returned
electromagnetic waves and determine locational properties of
targets. Examples of the RADAR sensors 324 as described herein may
include, but are not limited to, at least one of Infineon RASIC.TM.
RTN7735PL transmitter and RRN7745PL/46PL receiver sensors, Autoliv
ASP Vehicle RADAR sensors, Delphi L2C0051TR 77 GHz ESR
Electronically Scanning Radar sensors, Fujitsu Ten Ltd. Automotive
Compact 77 GHz 3D Electronic Scan Millimeter Wave Radar sensors,
other industry-equivalent RADAR sensors and/or systems, and may
perform radio target and/or obstacle detection in an environment
around the vehicle 100 using any known or future-developed standard
and/or architecture.
[0053] The ultrasonic sensors 328 may include one or more
components that are configured to detect objects/targets in an
environment of the vehicle 100. In some embodiments, the ultrasonic
sensors 328 may determine a distance, position, and/or movement
vector (e.g., angle, speed, etc.) associated with a target over
time. The ultrasonic sensors 328 may include an ultrasonic
transmitter and receiver, or transceiver, configured to generate
and emit ultrasound waves and interpret returned echoes of those
waves. In some embodiments, the ultrasonic sensors 328 may include
at least one processor configured to interpret the returned
ultrasonic waves and determine locational properties of targets.
Examples of the ultrasonic sensors 328 as described herein may
include, but are not limited to, at least one of Texas Instruments
TIDA-00151 automotive ultrasonic sensor interface IC sensors,
MaxBotix.RTM. MB8450 ultrasonic proximity sensor, MaxBotix.RTM.
ParkSonar.TM.-EZ ultrasonic proximity sensors, Murata Electronics
MA40H1S-R open-structure ultrasonic sensors, Murata Electronics
MA40S4R/S open-structure ultrasonic sensors, Murata Electronics
MA58MF14-7N waterproof ultrasonic sensors, other
industry-equivalent ultrasonic sensors and/or systems, and may
perform ultrasonic target and/or obstacle detection in an
environment around the vehicle 100 using any known or
future-developed standard and/or architecture.
[0054] The camera sensors 332 may include one or more components
configured to detect image information associated with an
environment of the vehicle 100. In some embodiments, the camera
sensors 332 may include a lens, filter, image sensor, and/or a
digital image processer. It is an aspect of the present disclosure
that multiple camera sensors 332 may be used together to generate
stereo images providing depth measurements. Examples of the camera
sensors 332 as described herein may include, but are not limited
to, at least one of ON Semiconductor.RTM. MT9V024 Global Shutter
VGA GS CMOS image sensors, Teledyne DALSA Falcon2 camera sensors,
CMOSIS CMV50000 high-speed CMOS image sensors, other
industry-equivalent camera sensors and/or systems, and may perform
visual target and/or obstacle detection in an environment around
the vehicle 100 using any known or future-developed standard and/or
architecture.
[0055] The infrared (IR) sensors 336 may include one or more
components configured to detect image information associated with
an environment of the vehicle 100. The IR sensors 336 may be
configured to detect targets in low-light, dark, or poorly-lit
environments. The IR sensors 336 may include an IR light emitting
element (e.g., IR light emitting diode (LED), etc.) and an IR
photodiode. In some embodiments, the IR photodiode may be
configured to detect returned IR light at or about the same
wavelength to that emitted by the IR light emitting element. In
some embodiments, the IR sensors 336 may include at least one
processor configured to interpret the returned IR light and
determine locational properties of targets. The IR sensors 336 may
be configured to detect and/or measure a temperature associated
with a target (e.g., an object, pedestrian, other vehicle, etc.).
Examples of IR sensors 336 as described herein may include, but are
not limited to, at least one of Opto Diode lead-salt IR array
sensors, Opto Diode OD-850 Near-IR LED sensors, Opto Diode
SA/SHA727 steady state IR emitters and IR detectors, FLIR.RTM. LS
microbolometer sensors, FLIR.RTM. TacFLIR 380-HD InSb MWIR FPA and
HD MWIR thermal sensors, FLIR.RTM. VOx 640.times.480 pixel detector
sensors, Delphi IR sensors, other industry-equivalent IR sensors
and/or systems, and may perform IR visual target and/or obstacle
detection in an environment around the vehicle 100 using any known
or future-developed standard and/or architecture.
[0056] The vehicle 100 can also include one or more interior
sensors 337. Interior sensors 337 can measure characteristics of
the inside environment of the vehicle 100. The interior sensors 337
may be as described in conjunction with FIG. 3B.
[0057] A navigation system 302 can include any hardware and/or
software used to navigate the vehicle either manually or
autonomously. The navigation system 302 may be as described in
conjunction with FIG. 3C.
[0058] In some embodiments, the driving vehicle sensors and systems
304 may include other sensors 338 and/or combinations of the
sensors 306-337 described above. Additionally or alternatively, one
or more of the sensors 306-337 described above may include one or
more processors configured to process and/or interpret signals
detected by the one or more sensors 306-337. In some embodiments,
the processing of at least some sensor information provided by the
vehicle sensors and systems 304 may be processed by at least one
sensor processor 340. Raw and/or processed sensor data may be
stored in a sensor data memory 344 storage medium. In some
embodiments, the sensor data memory 344 may store instructions used
by the sensor processor 340 for processing sensor information
provided by the sensors and systems 304. In any event, the sensor
data memory 344 may be a disk drive, optical storage device,
solid-state storage device such as a random access memory ("RAM")
and/or a read-only memory ("ROM"), which can be programmable,
flash-updateable, and/or the like.
[0059] The vehicle control system 348 may receive processed sensor
information from the sensor processor 340 and determine to control
an aspect of the vehicle 100. Controlling an aspect of the vehicle
100 may include presenting information via one or more display
devices 372 associated with the vehicle, sending commands to one or
more computing devices 368 associated with the vehicle, and/or
controlling a driving operation of the vehicle. In some
embodiments, the vehicle control system 348 may correspond to one
or more computing systems that control driving operations of the
vehicle 100 in accordance with the Levels of driving autonomy
described above. In one embodiment, the vehicle control system 348
may operate a speed of the vehicle 100 by controlling an output
signal to the accelerator and/or braking system of the vehicle. In
this example, the vehicle control system 348 may receive sensor
data describing an environment surrounding the vehicle 100 and,
based on the sensor data received, determine to adjust the
acceleration, power output, and/or braking of the vehicle 100. The
vehicle control system 348 may additionally control steering and/or
other driving functions of the vehicle 100.
[0060] The vehicle control system 348 may communicate, in
real-time, with the driving sensors and systems 304 forming a
feedback loop. In particular, upon receiving sensor information
describing a condition of targets in the environment surrounding
the vehicle 100, the vehicle control system 348 may autonomously
make changes to a driving operation of the vehicle 100. The vehicle
control system 348 may then receive subsequent sensor information
describing any change to the condition of the targets detected in
the environment as a result of the changes made to the driving
operation. This continual cycle of observation (e.g., via the
sensors, etc.) and action (e.g., selected control or non-control of
vehicle operations, etc.) allows the vehicle 100 to operate
autonomously in the environment.
[0061] In some embodiments, the one or more components of the
vehicle 100 (e.g., the driving vehicle sensors 304, vehicle control
system 348, display devices 372, etc.) may communicate across the
communication network 352 to one or more entities 356A-N via a
communications subsystem 350 of the vehicle 100. Embodiments of the
communications subsystem 350 are described in greater detail in
conjunction with FIG. 5. For instance, the navigation sensors 308
may receive global positioning, location, and/or navigational
information from a navigation source 356A. In some embodiments, the
navigation source 356A may be a global navigation satellite system
(GNSS) similar, if not identical, to NAVSTAR GPS, GLONASS, EU
Galileo, and/or the BeiDou Navigation Satellite System (BDS) to
name a few.
[0062] In some embodiments, the vehicle control system 348 may
receive control information from one or more control sources 356B.
The control source 356 may provide vehicle control information
including autonomous driving control commands, vehicle operation
override control commands, and the like. The control source 356 may
correspond to an autonomous vehicle control system, a traffic
control system, an administrative control entity, and/or some other
controlling server. It is an aspect of the present disclosure that
the vehicle control system 348 and/or other components of the
vehicle 100 may exchange communications with the control source 356
across the communication network 352 and via the communications
subsystem 350.
[0063] Information associated with controlling driving operations
of the vehicle 100 may be stored in a control data memory 364
storage medium. The control data memory 364 may store instructions
used by the vehicle control system 348 for controlling driving
operations of the vehicle 100, historical control information,
autonomous driving control rules, and the like. In some
embodiments, the control data memory 364 may be a disk drive,
optical storage device, solid-state storage device such as a random
access memory ("RAM") and/or a read-only memory ("ROM"), which can
be programmable, flash-updateable, and/or the like.
[0064] In addition to the mechanical components described herein,
the vehicle 100 may include a number of user interface devices. The
user interface devices receive and translate human input into a
mechanical movement or electrical signal or stimulus. The human
input may be one or more of motion (e.g., body movement, body part
movement, in two-dimensional or three-dimensional space, etc.),
voice, touch, and/or physical interaction with the components of
the vehicle 100. In some embodiments, the human input may be
configured to control one or more functions of the vehicle 100
and/or systems of the vehicle 100 described herein. User interfaces
may include, but are in no way limited to, at least one graphical
user interface of a display device, steering wheel or mechanism,
transmission lever or button (e.g., including park, neutral,
reverse, and/or drive positions, etc.), throttle control pedal or
mechanism, brake control pedal or mechanism, power control switch,
communications equipment, etc.
[0065] FIG. 3B shows a block diagram of an embodiment of interior
sensors 337 for a vehicle 100. The interior sensors 337 may be
arranged into one or more groups, based at least partially on the
function of the interior sensors 337. For example, the interior
space of a vehicle 100 may include environmental sensors, user
interface sensor(s), and/or safety sensors. Additionally or
alternatively, there may be sensors associated with various devices
inside the vehicle (e.g., smart phones, tablets, mobile computers,
wearables, etc.)
[0066] Environmental sensors may comprise sensors configured to
collect data relating to the internal environment of a vehicle 100.
Examples of environmental sensors may include one or more of, but
are not limited to: oxygen/air sensors 301, temperature sensors
303, humidity sensors 305, light/photo sensors 307, and more. The
oxygen/air sensors 301 may be configured to detect a quality or
characteristic of the air in the interior space 108 of the vehicle
100 (e.g., ratios and/or types of gasses comprising the air inside
the vehicle 100, dangerous gas levels, safe gas levels, etc.).
Temperature sensors 303 may be configured to detect temperature
readings of one or more objects, users 216, and/or areas of a
vehicle 100. Humidity sensors 305 may detect an amount of water
vapor present in the air inside the vehicle 100. The light/photo
sensors 307 can detect an amount of light present in the vehicle
100. Further, the light/photo sensors 307 may be configured to
detect various levels of light intensity associated with light in
the vehicle 100.
[0067] User interface sensors may comprise sensors configured to
collect data relating to one or more users (e.g., a driver and/or
passenger(s)) in a vehicle 100. As can be appreciated, the user
interface sensors may include sensors that are configured to
collect data from users 216 in one or more areas of the vehicle
100. Examples of user interface sensors may include one or more of,
but are not limited to: infrared sensors 309, motion sensors 311,
weight sensors 313, wireless network sensors 315, biometric sensors
317, camera (or image) sensors 319, audio sensors 321, and
more.
[0068] Infrared sensors 309 may be used to measure IR light
irradiating from at least one surface, user, or other object in the
vehicle 100. Among other things, the Infrared sensors 309 may be
used to measure temperatures, form images (especially in low light
conditions), identify users 216, and even detect motion in the
vehicle 100.
[0069] The motion sensors 311 may detect motion and/or movement of
objects inside the vehicle 100. Optionally, the motion sensors 311
may be used alone or in combination to detect movement. For
example, a user may be operating a vehicle 100 (e.g., while
driving, etc.) when a passenger in the rear of the vehicle 100
unbuckles a safety belt and proceeds to move about the vehicle 10.
In this example, the movement of the passenger could be detected by
the motion sensors 311. In response to detecting the movement
and/or the direction associated with the movement, the passenger
may be prevented from interfacing with and/or accessing at least
some of the vehicle control features. As can be appreciated, the
user may be alerted of the movement/motion such that the user can
act to prevent the passenger from interfering with the vehicle
controls. Optionally, the number of motion sensors in a vehicle may
be increased to increase an accuracy associated with motion
detected in the vehicle 100.
[0070] Weight sensors 313 may be employed to collect data relating
to objects and/or users in various areas of the vehicle 100. In
some cases, the weight sensors 313 may be included in the seats
and/or floor of a vehicle 100. Optionally, the vehicle 100 may
include a wireless network sensor 315. This sensor 315 may be
configured to detect one or more wireless network(s) inside the
vehicle 100. Examples of wireless networks may include, but are not
limited to, wireless communications utilizing Bluetooth.RTM.,
Wi-Fi.TM., ZigBee, IEEE 802.11, and other wireless technology
standards. For example, a mobile hotspot may be detected inside the
vehicle 100 via the wireless network sensor 315. In this case, the
vehicle 100 may determine to utilize and/or share the mobile
hotspot detected via/with one or more other devices associated with
the vehicle 100.
[0071] Biometric sensors 317 may be employed to identify and/or
record characteristics associated with a user. It is anticipated
that biometric sensors 317 can include at least one of image
sensors, IR sensors, fingerprint readers, weight sensors, load
cells, force transducers, heart rate monitors, blood pressure
monitors, and the like as provided herein.
[0072] The camera sensors 319 may record still images, video,
and/or combinations thereof. Camera sensors 319 may be used alone
or in combination to identify objects, users, and/or other
features, inside the vehicle 100. Two or more camera sensors 319
may be used in combination to form, among other things, stereo
and/or three-dimensional (3D) images. The stereo images can be
recorded and/or used to determine depth associated with objects
and/or users in a vehicle 100. Further, the camera sensors 319 used
in combination may determine the complex geometry associated with
identifying characteristics of a user. For example, the camera
sensors 319 may be used to determine dimensions between various
features of a user's face (e.g., the depth/distance from a user's
nose to a user's cheeks, a linear distance between the center of a
user's eyes, and more). These dimensions may be used to verify,
record, and even modify characteristics that serve to identify a
user. The camera sensors 319 may also be used to determine movement
associated with objects and/or users within the vehicle 100. It
should be appreciated that the number of image sensors used in a
vehicle 100 may be increased to provide greater dimensional
accuracy and/or views of a detected image in the vehicle 100.
[0073] The audio sensors 321 may be configured to receive audio
input from a user of the vehicle 100. The audio input from a user
may correspond to voice commands, conversations detected in the
vehicle 100, phone calls made in the vehicle 100, and/or other
audible expressions made in the vehicle 100. Audio sensors 321 may
include, but are not limited to, microphones and other types of
acoustic-to-electric transducers or sensors. Optionally, the
interior audio sensors 321 may be configured to receive and convert
sound waves into an equivalent analog or digital signal. The
interior audio sensors 321 may serve to determine one or more
locations associated with various sounds in the vehicle 100. The
location of the sounds may be determined based on a comparison of
volume levels, intensity, and the like, between sounds detected by
two or more interior audio sensors 321. For instance, a first audio
sensor 321 may be located in a first area of the vehicle 100 and a
second audio sensor 321 may be located in a second area of the
vehicle 100. If a sound is detected at a first volume level by the
first audio sensors 321 A and a second, higher, volume level by the
second audio sensors 321 in the second area of the vehicle 100, the
sound may be determined to be closer to the second area of the
vehicle 100. As can be appreciated, the number of sound receivers
used in a vehicle 100 may be increased (e.g., more than two, etc.)
to increase measurement accuracy surrounding sound detection and
location, or source, of the sound (e.g., via triangulation,
etc.).
[0074] The safety sensors may comprise sensors configured to
collect data relating to the safety of a user and/or one or more
components of a vehicle 100. Examples of safety sensors may include
one or more of, but are not limited to: force sensors 325,
mechanical motion sensors 327, orientation sensors 329, restraint
sensors 331, and more.
[0075] The force sensors 325 may include one or more sensors inside
the vehicle 100 configured to detect a force observed in the
vehicle 100. One example of a force sensor 325 may include a force
transducer that converts measured forces (e.g., force, weight,
pressure, etc.) into output signals. Mechanical motion sensors 327
may correspond to encoders, accelerometers, damped masses, and the
like. Optionally, the mechanical motion sensors 327 may be adapted
to measure the force of gravity (i.e., G-force) as observed inside
the vehicle 100. Measuring the G-force observed inside a vehicle
100 can provide valuable information related to a vehicle's
acceleration, deceleration, collisions, and/or forces that may have
been suffered by one or more users in the vehicle 100. Orientation
sensors 329 can include accelerometers, gyroscopes, magnetic
sensors, and the like that are configured to detect an orientation
associated with the vehicle 100.
[0076] The restraint sensors 331 may correspond to sensors
associated with one or more restraint devices and/or systems in a
vehicle 100. Seatbelts and airbags are examples of restraint
devices and/or systems. As can be appreciated, the restraint
devices and/or systems may be associated with one or more sensors
that are configured to detect a state of the device/system. The
state may include extension, engagement, retraction, disengagement,
deployment, and/or other electrical or mechanical conditions
associated with the device/system.
[0077] The associated device sensors 323 can include any sensors
that are associated with a device in the vehicle 100. As previously
stated, typical devices may include smart phones, tablets, laptops,
mobile computers, and the like. It is anticipated that the various
sensors associated with these devices can be employed by the
vehicle control system 348. For example, a typical smart phone can
include, an image sensor, an IR sensor, audio sensor, gyroscope,
accelerometer, wireless network sensor, fingerprint reader, and
more. It is an aspect of the present disclosure that one or more of
these associated device sensors 323 may be used by one or more
subsystems of the vehicle 100.
[0078] FIG. 3C illustrates a GPS/Navigation subsystem(s) 302. The
navigation subsystem(s) 302 can be any present or future-built
navigation system that may use location data, for example, from the
Global Positioning System (GPS), to provide navigation information
or control the vehicle 100. The navigation subsystem(s) 302 can
include several components, such as, one or more of, but not
limited to: a GPS Antenna/receiver 331, a location module 333, a
maps database 335, etc. Generally, the several components or
modules 331-335 may be hardware, software, firmware, computer
readable media, or combinations thereof.
[0079] A GPS Antenna/receiver 331 can be any antenna, GPS puck,
and/or receiver capable of receiving signals from a GPS satellite
or other navigation system. The signals may be demodulated,
converted, interpreted, etc. by the GPS Antenna/receiver 331 and
provided to the location module 333. Thus, the GPS Antenna/receiver
331 may convert the time signals from the GPS system and provide a
location (e.g., coordinates on a map) to the location module 333.
Alternatively, the location module 333 can interpret the time
signals into coordinates or other location information.
[0080] The location module 333 can be the controller of the
satellite navigation system designed for use in the vehicle 100.
The location module 333 can acquire position data, as from the GPS
Antenna/receiver 331, to locate the user or vehicle 100 on a road
in the unit's map database 335. Using the road database 335, the
location module 333 can give directions to other locations along
roads also in the database 335. When a GPS signal is not available,
the location module 333 may apply dead reckoning to estimate
distance data from sensors 304 including one or more of, but not
limited to, a speed sensor attached to the drive train of the
vehicle 100, a gyroscope, an accelerometer, etc. Additionally or
alternatively, the location module 333 may use known locations of
Wi-Fi hotspots, cell tower data, etc. to determine the position of
the vehicle 100, such as by using time difference of arrival (TDOA)
and/or frequency difference of arrival (FDOA) techniques.
[0081] The maps database 335 can include any hardware and/or
software to store information about maps, geographical information
system (GIS) information, location information, etc. The maps
database 335 can include any data definition or other structure to
store the information. Generally, the maps database 335 can include
a road database that may include one or more vector maps of areas
of interest. Street names, street numbers, house numbers, and other
information can be encoded as geographic coordinates so that the
user can find some desired destination by street address. Points of
interest (waypoints) can also be stored with their geographic
coordinates. For example, a point of interest may include speed
cameras, fuel stations, public parking, and "parked here" (or "you
parked here") information. The maps database 335 may also include
road or street characteristics, for example, speed limits, location
of stop lights/stop signs, lane divisions, school locations, etc.
The map database contents can be produced or updated by a server
connected through a wireless system in communication with the
Internet, even as the vehicle 100 is driven along existing streets,
yielding an up-to-date map.
[0082] The vehicle control system 348, when operating in L4 or L5
and based on sensor information from the external and interior
vehicle sensors, can control the driving behavior of the vehicle in
response to the current vehicle location, sensed object
information, sensed vehicle occupant information, vehicle-related
information, exterior environmental information, and navigation
information from the maps database 335.
[0083] The sensed object information refers to sensed information
regarding objects external to the vehicle. Examples include animate
objects such as animals and attributes thereof (e.g., animal type,
current spatial location, current activity, etc.), and pedestrians
and attributes thereof (e.g., identity, age, sex, current spatial
location, current activity, etc.), and the like and inanimate
objects and attributes thereof such as other vehicles (e.g.,
current vehicle state or activity (parked or in motion or level of
automation currently employed), occupant or operator identity,
vehicle type (truck, car, etc.), vehicle spatial location, etc.),
curbs (topography and spatial location), potholes (size and spatial
location), lane division markers (type or color and spatial
locations), signage (type or color and spatial locations such as
speed limit signs, yield signs, stop signs, and other restrictive
or warning signs), traffic signals (e.g., red, yellow, blue, green,
etc.), buildings (spatial locations), walls (height and spatial
locations), barricades (height and spatial location), and the
like.
[0084] The sensed occupant information refers to sensed information
regarding occupants internal to the vehicle. Examples include the
number and identities of occupants and attributes thereof (e.g.,
seating position, age, sex, gaze direction, biometric information,
authentication information, preferences, historic behavior patterns
(such as current or historical user driving behavior, historical
user route, destination, and waypoint preferences), nationality,
ethnicity and race, language preferences (e.g., Spanish, English,
Chinese, etc.), current occupant role (e.g., operator or
passenger), occupant priority ranking (e.g., vehicle owner is given
a higher ranking than a child occupant), electronic calendar
information (e.g., Outlook.TM.), and medical information and
history, etc.
[0085] The vehicle-related information refers to sensed information
regarding the selected vehicle. Examples include vehicle
manufacturer, type, model, year of manufacture, current geographic
location, current vehicle state or activity (parked or in motion or
level of automation currently employed), vehicle specifications and
capabilities, currently sensed operational parameters for the
vehicle, and other information.
[0086] The exterior environmental information refers to sensed
information regarding the external environment of the selected
vehicle. Examples include road type (pavement, gravel, brick,
etc.), road condition (e.g., wet, dry, icy, snowy, etc.), weather
condition (e.g., outside temperature, pressure, humidity, wind
speed and direction, etc.), ambient light conditions (e.g.,
time-of-day), degree of development of vehicle surroundings (e.g.,
urban or rural), and the like.
[0087] In a typical implementation, the automated vehicle control
system 348, based on feedback from certain sensors, specifically
the LIDAR and radar sensors positioned around the circumference of
the vehicle, constructs a three-dimensional map in spatial
proximity to the vehicle that enables the automated vehicle control
system 348 to identify and spatially locate animate and inanimate
objects. Other sensors, such as inertial measurement units,
gyroscopes, wheel encoders, sonar sensors, motion sensors to
perform odometry calculations with respect to nearby moving
exterior objects, and exterior facing cameras (e.g., to perform
computer vision processing) can provide further contextual
information for generation of a more accurate three-dimensional
map. The navigation information is combined with the
three-dimensional map to provide short, intermediate and long range
course tracking and route selection. The vehicle control system 348
processes real-world information as well as GPS data, and driving
speed to determine accurately the precise position of each vehicle,
down to a few centimeters all while making corrections for nearby
animate and inanimate objects.
[0088] The vehicle control system 348 can process in substantial
real time the aggregate mapping information and models (or
predicts) behavior of occupants of the current vehicle and other
nearby animate or inanimate objects and, based on the aggregate
mapping information and modeled behavior, issues appropriate
commands regarding vehicle operation. While some commands are
hard-coded into the vehicle, such as stopping at red lights and
stop signs, other responses are learned and recorded by profile
updates based on previous driving experiences. Examples of learned
behavior include a slow-moving or stopped vehicle or emergency
vehicle in a right lane suggests a higher probability that the car
following it will attempt to pass, a pot hole, rock, or other
foreign object in the roadway equates to a higher probability that
a driver will swerve to avoid it, and traffic congestion in one
lane means that other drivers moving in the same direction will
have a higher probability of passing in an adjacent lane or by
driving on the shoulder.
[0089] FIG. 4 shows one embodiment of the instrument panel 400 of
the vehicle 100. The instrument panel 400 of vehicle 100 comprises
a steering wheel 410, a vehicle operational display 420 (e.g.,
configured to present and/or display driving data such as speed,
measured air resistance, vehicle information, entertainment
information, etc.), one or more auxiliary displays 424 (e.g.,
configured to present and/or display information segregated from
the operational display 420, entertainment applications, movies,
music, etc.), a heads-up display 434 (e.g., configured to display
any information previously described including, but in no way
limited to, guidance information such as route to destination, or
obstacle warning information to warn of a potential collision, or
some or all primary vehicle operational data such as speed,
resistance, etc.), a power management display 428 (e.g., configured
to display data corresponding to electric power levels of vehicle
100, reserve power, charging status, etc.), and an input device 432
(e.g., a controller, touchscreen, or other interface device
configured to interface with one or more displays in the instrument
panel or components of the vehicle 100. The input device 432 may be
configured as a joystick, mouse, touchpad, tablet, 3D gesture
capture device, etc.). In some embodiments, the input device 432
may be used to manually maneuver a portion of the vehicle 100 into
a charging position (e.g., moving a charging plate to a desired
separation distance, etc.).
[0090] While one or more of displays of instrument panel 400 may be
touch-screen displays, it should be appreciated that the vehicle
operational display may be a display incapable of receiving touch
input. For instance, the operational display 420 that spans across
an interior space centerline 404 and across both a first zone 408A
and a second zone 408B may be isolated from receiving input from
touch, especially from a passenger. In some cases, a display that
provides vehicle operation or critical systems information and
interface may be restricted from receiving touch input and/or be
configured as a non-touch display. This type of configuration can
prevent dangerous mistakes in providing touch input where such
input may cause an accident or unwanted control.
[0091] In some embodiments, one or more displays of the instrument
panel 400 may be mobile devices and/or applications residing on a
mobile device such as a smart phone. Additionally or alternatively,
any of the information described herein may be presented to one or
more portions 420A-N of the operational display 420 or other
display 424, 428, 434. In one embodiment, one or more displays of
the instrument panel 400 may be physically separated or detached
from the instrument panel 400. In some cases, a detachable display
may remain tethered to the instrument panel.
[0092] The portions 420A-N of the operational display 420 may be
dynamically reconfigured and/or resized to suit any display of
information as described. Additionally or alternatively, the number
of portions 420A-N used to visually present information via the
operational display 420 may be dynamically increased or decreased
as required, and are not limited to the configurations shown.
[0093] FIG. 5 illustrates a hardware diagram of communications
componentry that can be optionally associated with the vehicle 100
in accordance with embodiments of the present disclosure.
[0094] The communications componentry can include one or more wired
or wireless devices such as a transceiver(s) and/or modem that
allows communications not only between the various systems
disclosed herein but also with other devices, such as devices on a
network, and/or on a distributed network such as the Internet
and/or in the cloud and/or with another vehicle(s).
[0095] The communications subsystem 350 can also include inter- and
intra-vehicle communications capabilities such as hotspot and/or
access point connectivity for any one or more of the vehicle
occupants and/or vehicle-to-vehicle communications.
[0096] Additionally, and while not specifically illustrated, the
communications subsystem 350 can include one or more communications
links (that can be wired or wireless) and/or communications busses
(managed by the bus manager 574), including one or more of CANbus,
OBD-II, ARCINC 429, Byteflight, CAN (Controller Area Network), D2B
(Domestic Digital Bus), FlexRay, DC-BUS, IDB-1394, IEBus, I2C, ISO
9141-1/-2, J1708, J1587, J1850, J1939, ISO 11783, Keyword Protocol
2000, LIN (Local Interconnect Network), MOST (Media Oriented
Systems Transport), Multifunction Vehicle Bus, SMARTwireX, SPI, VAN
(Vehicle Area Network), and the like or in general any
communications protocol and/or standard(s).
[0097] The various protocols and communications can be communicated
one or more of wirelessly and/or over transmission media such as
single wire, twisted pair, fiber optic, IEEE 1394, MIL-STD-1553,
MIL-STD-1773, power-line communication, or the like. (All of the
above standards and protocols are incorporated herein by reference
in their entirety).
[0098] As discussed, the communications subsystem 350 enables
communications between any of the inter-vehicle systems and
subsystems as well as communications with non-collocated resources,
such as those reachable over a network such as the Internet.
[0099] The communications subsystem 350, in addition to well-known
componentry (which has been omitted for clarity), includes
interconnected elements including one or more of: one or more
antennas 504, an interleaver/deinterleaver 508, an analog front end
(AFE) 512, memory/storage/cache 516, controller/microprocessor 520,
MAC circuitry 522, modulator/demodulator 524, encoder/decoder 528,
a plurality of connectivity managers 534, 558, 562, 566, GPU 540,
accelerator 544, a multiplexer/demultiplexer 552, transmitter 570,
receiver 572 and additional wireless radio components such as a
Wi-Fi PHY/Bluetooth.RTM. module 580, a Wi-Fi/BT MAC module 584,
additional transmitter(s) 588 and additional receiver(s) 592. The
various elements in the device 350 are connected by one or more
links/busses 5 (not shown, again for sake of clarity).
[0100] The device 350 can have one more antennas 504, for use in
wireless communications such as multi-input multi-output (MIMO)
communications, multi-user multi-input multi-output (MU-MIMO)
communications Bluetooth.RTM., LTE, 4G, 5G, Near-Field
Communication (NFC), etc., and in general for any type of wireless
communications. The antenna(s) 504 can include, but are not limited
to one or more of directional antennas, omnidirectional antennas,
monopoles, patch antennas, loop antennas, microstrip antennas,
dipoles, and any other antenna(s) suitable for communication
transmission/reception. In an exemplary embodiment,
transmission/reception using MIMO may require particular antenna
spacing. In another exemplary embodiment, MIMO
transmission/reception can enable spatial diversity allowing for
different channel characteristics at each of the antennas. In yet
another embodiment, MIMO transmission/reception can be used to
distribute resources to multiple users for example within the
vehicle 100 and/or in another vehicle.
[0101] Antenna(s) 504 generally interact with the Analog Front End
(AFE) 512, which is needed to enable the correct processing of the
received modulated signal and signal conditioning for a transmitted
signal. The AFE 512 can be functionally located between the antenna
and a digital baseband system to convert the analog signal into a
digital signal for processing and vice-versa.
[0102] The subsystem 350 can also include a
controller/microprocessor 520 and a memory/storage/cache 516. The
subsystem 350 can interact with the memory/storage/cache 516 which
may store information and operations necessary for configuring and
transmitting or receiving the information described herein. The
memory/storage/cache 516 may also be used in connection with the
execution of application programming or instructions by the
controller/microprocessor 520, and for temporary or long-term
storage of program instructions and/or data. As examples, the
memory/storage/cache 520 may comprise a computer-readable device,
RAM, ROM, DRAM, SDRAM, and/or other storage device(s) and
media.
[0103] The controller/microprocessor 520 may comprise a general
purpose programmable processor or controller for executing
application programming or instructions related to the subsystem
350. Furthermore, the controller/microprocessor 520 can perform
operations for configuring and transmitting/receiving information
as described herein. The controller/microprocessor 520 may include
multiple processor cores, and/or implement multiple virtual
processors. Optionally, the controller/microprocessor 520 may
include multiple physical processors. By way of example, the
controller/microprocessor 520 may comprise a specially configured
Application Specific Integrated Circuit (ASIC) or other integrated
circuit, a digital signal processor(s), a controller, a hardwired
electronic or logic circuit, a programmable logic device or gate
array, a special purpose computer, or the like.
[0104] The subsystem 350 can further include a transmitter(s) 570,
588 and receiver(s) 572, 592 which can transmit and receive
signals, respectively, to and from other devices, subsystems and/or
other destinations using the one or more antennas 504 and/or
links/busses. Included in the subsystem 350 circuitry is the medium
access control or MAC Circuitry 522. MAC circuitry 522 provides for
controlling access to the wireless medium. In an exemplary
embodiment, the MAC circuitry 522 may be arranged to contend for
the wireless medium and configure frames or packets for
communicating over the wired/wireless medium.
[0105] The subsystem 350 can also optionally contain a security
module (not shown). This security module can contain information
regarding but not limited to, security parameters required to
connect the device to one or more other devices or other available
network(s), and can include WEP or WPA/WPA-2 (optionally +AES
and/or TKIP) security access keys, network keys, etc. The WEP
security access key is a security password used by Wi-Fi networks.
Knowledge of this code can enable a wireless device to exchange
information with an access point and/or another device. The
information exchange can occur through encoded messages with the
WEP access code often being chosen by the network administrator.
WPA is an added security standard that is also used in conjunction
with network connectivity with stronger encryption than WEP.
[0106] In some embodiments, the communications subsystem 350 also
includes a GPU 540, an accelerator 544, a Wi-Fi/BT/BLE
(Bluetooth.RTM. Low-Energy) PHY module 580 and a Wi-Fi/BT/BLE MAC
module 584 and optional wireless transmitter 588 and optional
wireless receiver 592. In some embodiments, the GPU 540 may be a
graphics processing unit, or visual processing unit, comprising at
least one circuit and/or chip that manipulates and changes memory
to accelerate the creation of images in a frame buffer for output
to at least one display device. The GPU 540 may include one or more
of a display device connection port, printed circuit board (PCB), a
GPU chip, a metal-oxide-semiconductor field-effect transistor
(MOSFET), memory (e.g., single data rate random-access memory
(SDRAM), double data rate random-access memory (DDR) RAM, etc.,
and/or combinations thereof), a secondary processing chip (e.g.,
handling video out capabilities, processing, and/or other functions
in addition to the GPU chip, etc.), a capacitor, heatsink,
temperature control or cooling fan, motherboard connection,
shielding, and the like.
[0107] The various connectivity managers 534, 558, 562, 566 manage
and/or coordinate communications between the subsystem 350 and one
or more of the systems disclosed herein and one or more other
devices/systems. The connectivity managers 534, 558, 562, 566
include a charging connectivity manager 534, a vehicle database
connectivity manager 558, a remote operating system connectivity
manager 562, and a sensor connectivity manager 566.
[0108] The charging connectivity manager 534 can coordinate not
only the physical connectivity between the vehicle 100 and a
charging device/vehicle, but can also communicate with one or more
of a power management controller, one or more third parties and
optionally a billing system(s). As an example, the vehicle 100 can
establish communications with the charging device/vehicle to one or
more of coordinate interconnectivity between the two (e.g., by
spatially aligning the charging receptacle on the vehicle with the
charger on the charging vehicle) and optionally share navigation
information. Once charging is complete, the amount of charge
provided can be tracked and optionally forwarded to, for example, a
third party for billing. In addition to being able to manage
connectivity for the exchange of power, the charging connectivity
manager 534 can also communicate information, such as billing
information to the charging vehicle and/or a third party. This
billing information could be, for example, the owner of the
vehicle, the driver/occupant(s) of the vehicle, company
information, or in general any information usable to charge the
appropriate entity for the power received.
[0109] The vehicle database connectivity manager 558 allows the
subsystem to receive and/or share information stored in the vehicle
database. This information can be shared with other vehicle
components/subsystems and/or other entities, such as third parties
and/or charging systems. The information can also be shared with
one or more vehicle occupant devices, such as an app (application)
on a mobile device the driver uses to track information about the
vehicle 100 and/or a dealer or service/maintenance provider. In
general, any information stored in the vehicle database can
optionally be shared with any one or more other devices optionally
subject to any privacy or confidentially restrictions.
[0110] The remote operating system connectivity manager 562
facilitates communications between the vehicle 100 and any one or
more autonomous vehicle systems. These communications can include
one or more of navigation information, vehicle information, other
vehicle information, weather information, occupant information, or
in general any information related to the remote operation of the
vehicle 100.
[0111] The sensor connectivity manager 566 facilitates
communications between any one or more of the vehicle sensors
(e.g., the driving vehicle sensors and systems 304, etc.) and any
one or more of the other vehicle systems. The sensor connectivity
manager 566 can also facilitate communications between any one or
more of the sensors and/or vehicle systems and any other
destination, such as a service company, app, or in general to any
destination where sensor data is needed.
[0112] In accordance with one exemplary embodiment, any of the
communications discussed herein can be communicated via the
conductor(s) used for charging. One exemplary protocol usable for
these communications is Power-line communication (PLC). PLC is a
communication protocol that uses electrical wiring to
simultaneously carry both data, and Alternating Current (AC)
electric power transmission or electric power distribution. It is
also known as power-line carrier, power-line digital subscriber
line (PDSL), mains communication, power-line telecommunications, or
power-line networking (PLN). For DC environments in vehicles PLC
can be used in conjunction with CAN-bus, LIN-bus over power line
(DC-LIN) and DC-BUS.
[0113] The communications subsystem can also optionally manage one
or more identifiers, such as an IP (Internet Protocol) address(es),
associated with the vehicle and one or other system or subsystems
or components and/or devices therein. These identifiers can be used
in conjunction with any one or more of the connectivity managers as
discussed herein.
[0114] FIG. 6 illustrates a block diagram of a computing
environment 600 that may function as the servers, user computers,
or other systems provided and described herein. The computing
environment 600 includes one or more user computers, or computing
devices, such as a vehicle computing device 604, a communication
device 608, and/or more 612. The computing devices 604, 608, 612
may include general purpose personal computers (including, merely
by way of example, personal computers, and/or laptop computers
running various versions of Microsoft Corp.'s Windows.RTM. and/or
Apple Corp.'s Macintosh.RTM. operating systems) and/or workstation
computers running any of a variety of commercially-available
UNIX.RTM. or UNIX-like operating systems. These computing devices
604, 608, 612 may also have any of a variety of applications,
including for example, database client and/or server applications,
and web browser applications. Alternatively, the computing devices
604, 608, 612 may be any other electronic device, such as a
thin-client computer, Internet-enabled mobile telephone, and/or
personal digital assistant, capable of communicating via a network
352 and/or displaying and navigating web pages or other types of
electronic documents or information. Although the exemplary
computing environment 600 is shown with two computing devices, any
number of user computers or computing devices may be supported.
[0115] The computing environment 600 may also include one or more
servers 614, 616. In this example, server 614 is shown as a web
server and server 616 is shown as an application server. The web
server 614, which may be used to process requests for web pages or
other electronic documents from computing devices 604, 608, 612.
The web server 614 can be running an operating system including any
of those discussed above, as well as any commercially-available
server operating systems. The web server 614 can also run a variety
of server applications, including SIP (Session Initiation Protocol)
servers, HTTP(s) servers, FTP servers, CGI servers, database
servers, Java.RTM. servers, and the like. In some instances, the
web server 614 may publish operations available operations as one
or more web services.
[0116] The computing environment 600 may also include one or more
file and or/application servers 616, which can, in addition to an
operating system, include one or more applications accessible by a
client running on one or more of the computing devices 604, 608,
612. The server(s) 616 and/or 614 may be one or more general
purpose computers capable of executing programs or scripts in
response to the computing devices 604, 608, 612. As one example,
the server 616, 614 may execute one or more web applications. The
web application may be implemented as one or more scripts or
programs written in any programming language, such as Java.RTM., C,
C#.RTM., or C++, and/or any scripting language, such as Perl,
Python, or TCL, as well as combinations of any
programming/scripting languages. The application server(s) 616 may
also include database servers, including without limitation those
commercially available from Oracle.RTM., Microsoft.RTM.,
Sybase.RTM., IBM.RTM. and the like, which can process requests from
database clients running on a computing device 604, 608, 612.
[0117] The web pages created by the server 614 and/or 616 may be
forwarded to a computing device 604, 608, 612 via a web (file)
server 614, 616. Similarly, the web server 614 may be able to
receive web page requests, web services invocations, and/or input
data from a computing device 604, 608, 612 (e.g., a user computer,
etc.) and can forward the web page requests and/or input data to
the web (application) server 616. In further embodiments, the
server 616 may function as a file server. Although for ease of
description, FIG. 6 illustrates a separate web server 614 and
file/application server 616, those skilled in the art will
recognize that the functions described with respect to servers 614,
616 may be performed by a single server and/or a plurality of
specialized servers, depending on implementation-specific needs and
parameters. The computer systems 604, 608, 612, web (file) server
614 and/or web (application) server 616 may function as the system,
devices, or components described in FIGS. 1-6.
[0118] The computing environment 600 may also include a database
618. The database 618 may reside in a variety of locations. By way
of example, database 618 may reside on a storage medium local to
(and/or resident in) one or more of the computers 604, 608, 612,
614, 616. Alternatively, it may be remote from any or all of the
computers 604, 608, 612, 614, 616, and in communication (e.g., via
the network 352) with one or more of these. The database 618 may
reside in a storage-area network ("SAN") familiar to those skilled
in the art. Similarly, any necessary files for performing the
functions attributed to the computers 604, 608, 612, 614, 616 may
be stored locally on the respective computer and/or remotely, as
appropriate. The database 618 may be a relational database, such as
Oracle 20i.RTM., that is adapted to store, update, and retrieve
data in response to SQL-formatted commands.
[0119] FIG. 7 illustrates one embodiment of a computer system 700
upon which the servers, user computers, computing devices, or other
systems or components described above may be deployed or executed.
The computer system 700 is shown comprising hardware elements that
may be electrically coupled via a bus 704. The hardware elements
may include one or more central processing units (CPUs) 708; one or
more input devices 712 (e.g., a mouse, a keyboard, etc.); and one
or more output devices 716 (e.g., a display device, a printer,
etc.). The computer system 700 may also include one or more storage
devices 720. By way of example, storage device(s) 720 may be disk
drives, optical storage devices, solid-state storage devices such
as a random access memory ("RAM") and/or a read-only memory
("ROM"), which can be programmable, flash-updateable and/or the
like.
[0120] The computer system 700 may additionally include a
computer-readable storage media reader 724; a communications system
728 (e.g., a modem, a network card (wireless or wired), an
infra-red communication device, etc.); and working memory 736,
which may include RAM and ROM devices as described above. The
computer system 700 may also include a processing acceleration unit
732, which can include a DSP, a special-purpose processor, and/or
the like.
[0121] The computer-readable storage media reader 724 can further
be connected to a computer-readable storage medium, together (and,
optionally, in combination with storage device(s) 720)
comprehensively representing remote, local, fixed, and/or removable
storage devices plus storage media for temporarily and/or more
permanently containing computer-readable information. The
communications system 728 may permit data to be exchanged with a
network and/or any other computer described above with respect to
the computer environments described herein. Moreover, as disclosed
herein, the term "storage medium" may represent one or more devices
for storing data, including read only memory (ROM), random access
memory (RAM), magnetic RAM, core memory, magnetic disk storage
mediums, optical storage mediums, flash memory devices and/or other
machine readable mediums for storing information.
[0122] The computer system 700 may also comprise software elements,
shown as being currently located within a working memory 736,
including an operating system 740 and/or other code 744. It should
be appreciated that alternate embodiments of a computer system 700
may have numerous variations from that described above. For
example, customized hardware might also be used and/or particular
elements might be implemented in hardware, software (including
portable software, such as applets), or both. Further, connection
to other computing devices such as network input/output devices may
be employed.
[0123] Examples of the processors 340, 708 as described herein may
include, but are not limited to, at least one of Qualcomm.RTM.
Snapdragon.RTM. 800 and 801, Qualcomm.RTM. Snapdragon.RTM. 620 and
615 with 4G LTE Integration and 64-bit computing, Apple.RTM. A7
processor with 64-bit architecture, Apple.RTM. M7 motion
coprocessors, Samsung.RTM. Exynos.RTM. series, the Intel.RTM.
Core.TM. family of processors, the Intel.RTM. Xeon.RTM. family of
processors, the Intel.RTM. Atom.TM. family of processors, the Intel
Itanium.RTM. family of processors, Intel.RTM. Core.RTM. i5-4670K
and i7-4770K 22 nm Haswell, Intel.RTM. Core.RTM. i5-3570K 22 nm Ivy
Bridge, the AMD.RTM. FX.TM. family of processors, AMD.RTM. FX-4300,
FX-6300, and FX-8350 32 nm Vishera, AMD.RTM. Kaveri processors,
Texas Instruments.RTM. Jacinto C6000.TM. automotive infotainment
processors, Texas Instruments.RTM. OMAP.TM. automotive-grade mobile
processors, ARM.RTM. Cortex.TM.-M processors, ARM.RTM. Cortex-A and
ARM926EJ-STM processors, other industry-equivalent processors, and
may perform computational functions using any known or
future-developed standard, instruction set, libraries, and/or
architecture.
[0124] FIG. 8A illustrates an embodiment of a system 800 for
determining cognitive state of a user and alerting that user, when
required, in accordance with embodiments of the disclosure. The
system 800 can be hardware and/or software as described herein,
including being executed on a processor 708 in a vehicle 100. The
system 800 can include one or more of, but is not limited to, a
sensor application programming interface (API) 804, a cognitive
state determiner 808, an alert system 812, a state engine 816, user
preferences data store or database 820, etc. There may be
connections to both the user interface 372/716 and/or sensors 304.
The various components 804-820 may be as described hereinafter in
FIGS. 8B-9B.
[0125] An embodiment of the sensor API 804 is illustrated in FIG.
8B. The sensor API 804 can be any hardware or software as described
herein for processing sensor information or sensor signals from
sensors 304. The sensor API 804 can include one or more of a
computer vision processing 824, a movement and position processing
828, and/or physiological data processing 832. There may be more or
fewer components to the sensor API 804, as shown in FIG. 8B.
[0126] The computer vision processing 824 can process visual
signals from sensors 304. Visual sensors can include infrared
sensors 309, motion sensors 311, light photo sensors 307, camera
sensors 319, and possibly other sensors described in conjunction
with FIG. 3B. The computer vision processing 824 can provide
information about the sensor data to the cognitive state determiner
808. This information can include the state of a person, for
example, whether the person is awake or sleeping, whether the
person is paying attention to the road, whether the person is
actively paying attention to a phone or other device, and/or
conducting some other type of operation or event. This information
may then be provided to cognitive state determiner 808 to determine
what the state of the user is.
[0127] The movement and position processing 828 can process any
movement sensor information. Thus, the movement and position
processing 828 can interpret signals from the motion sensors 311,
the orientation sensors 329, force sensors 325, or other sensors
such as the weight sensor 313, etc. This information may then be
used to determine whether a user is sitting in a position for
driving or in some other position, such as laying down. This
information may also be provided to the cognitive state determiner
808 to determine the attentiveness or state of the user.
[0128] Attentiveness is the ability for the driver to be aware of
the present state of the vehicle and/or environment as may be
observed with human senses (e.g., hear, see, and feel) and an
ability to provide an appropriate response to the state observed.
An appropriate response may be one to best address the observed
state to preserve the health and safety of the driver, passengers,
and other humans, animals, and property inside and outside vehicle
100 and/or to comply with a current condition or event on the
roadway, operational issue with the vehicle, lawful operation, etc.
An appropriate response may also have a timeliness aspect. For
example, an object on the roadway may require an appropriate
response (e.g., braking and/or steering) to either avoid the object
or to minimize the impact with the object, as well as timeliness
(e.g., initiate braking and/or steering in 0.5 seconds or less).
Other appropriate responses may have a different timeliness aspect.
For example, low fuel or battery charge may result in vehicle 100
becoming incapacitated within the next fifty miles of use.
Accordingly, the appropriate response (e.g., charging/swapping
batteries, obtaining fuel) is required before traveling more than
fifty miles or traveling beyond the ability to reach a
fueling/charging station. Similarly, an appropriate response may
further require a degree of response (e.g., hard braking/steering
in response to an object fifty feet ahead while traveling at
seventy-five miles-per-hour, gradual braking/steering in response
to an object fifty feet ahead while traveling at five
miles-per-hour, etc.).
[0129] While a driver may be aware of the present state of the
vehicle and/or environment and have the ability to make an
appropriate response--humans are error prone and may either
misjudge the present state of vehicle 100 and/or environment and/or
react inappropriately. However, when the driver has the present
ability to determine the state of vehicle 100 and/or environment
and the ability to appropriately respond, the driver may be
considered attentive or alert. In contrast, if the driver lacks the
present ability to determine the state of vehicle 100 and/or
environment and/or lacks the ability to appropriately respond, the
driver may be considered inattentive or not alert.
[0130] Attentiveness may be determined by responsiveness (e.g.,
user is actively providing driving inputs to vehicle 100, user is
responding correctly to alertness prompts, user indicates knowledge
of the present state of vehicle 100 and/or environment, or active
monitoring of the driver with eye tracking, etc.) and/or
inattentiveness may also be determined. Inattentiveness may be
determined by one or more sensor 304 determining the user state is
inattentive, such as by observing the user sleeping, having eyes
closed or directed towards a non-operational aspect of the vehicle
100 (e.g., infotainment system, personal entertainment device,
etc.), a head and/or body position known to make attentiveness
difficult or impossible (e.g., driver's seat fully reclined, seat
sensor indicates the no weight in the operator's seat, etc.).
[0131] In one embodiment, sensor 304 is embodied as a user sensor.
Sensor 304, when embodied as a user sensor senses at least one
cognition-indicating attribute of a user, such as a driver of
vehicle 100.
[0132] Further, the sensor API 804 can also include a physiological
data processing 832 that also connects to or otherwise communicates
with sensors 304. The physiological data processing 832 can obtain
information from one or more user sensors, including but not
limited to, oxygen air sensors 301, temperature sensors 303,
humidity sensors 305, restraint sensors 331, weight sensors 313,
motion sensors 311, biometric sensors 317, force sensors 325,
orientation sensors 329, etc. and/or other component that may
produce detect a cognition-indicating attribute of a user and
output a user sensor signal in accord with the sensed
cognition-indicating attribute. This information can then be used
to determine what the physiological state of the user is. For
example, if a user is sleeping, the user's heart rate may be lower,
temperature may be cooler, or may be experiencing other
physiological symptoms. These symptoms may be determined or
recognized by the physiological data processing 832 to provide to
the cognitive state determiner.
[0133] An embodiment of the cognitive state determiner 808 is
illustrated in FIG. 8C. The cognitive state determiner 808 can be
any type of hardware or software used to determine the cognitive
state of the user. The cognitive state may be determined to be what
level of focus the user is having on driving or on some other event
or task not related to driving. Further, the cognitive state
determiner 808 can determine whether the user is sleeping,
inebriated, having a medical condition or some other function.
Cognitive state determiner 808 can include one or more of a data
fusion component 836, state processor 840. There may be more or
fewer components to the cognitive state determiner 808 than those
shown in FIG. 8C. In one embodiment, cognitive state determiner 808
may prompts user for an action as one means to determine a
cognitive state. For example, a light on instrument panel 400 may
illuminate or flash and monitor the eyes of the driver to determine
if the user noticed and/or responded to the light. Similarly, music
playing may be turned up or down, the interior temperature may be
turned up or down, the operator's seat may move or vibrate, etc.
and determine whether or not the user appeared to notice and/or
respond to the prompting. Additionally or alternatively, the user
may be a more explicit prompted, such as by a displayed and/or
audio message asking the user to self-assess their state, such as
by textually and/or audibly asking, "Are you awake?", "How alert
(tired/sleepy) do you feel?", etc. And the user's response, or lack
of, as observed by one or more interior sensors 337 then used by
the cognitive state determiner 808 to determine the user's
cognitive state.
[0134] The data fusion component 836 can take sensor data or data
from other components through the sensor API 804 and fuse that data
into a common information stream. Thus, the data fusion component
836 may change, manipulate, or transform any type of data from one
format to another format. Further, the data fusion component 836
can put several different items of information from different
sensors 304 into a common table or format for review by the state
processor 840.
[0135] The state processor 840 can determine the state of the user
based on sensor information provided from the data fusion component
836. The state processor can compare the information in the data
fusion component 836 to previous state information or other types
of information to determine if the user is currently paying
attention to driving, sleeping, participating in a phone call,
distracted, viewing multimedia, or some other activity. Further,
the state processor 840 can also determine the state by determining
eye positions, heart rate, temperature of the user, voice
recognition information, or other types of sensor data. The state
information may then be passed on to the alert system 812.
[0136] An embodiment of the alert system 812 may be as shown in
FIG. 8D. The alert system 812 can include one or more of, but is
not limited to, an alert decision algorithm 844 and alert type
processor 848. There may be more or fewer components in the alert
system 812 than those shown in FIG. 8D. In one embodiment, alert
decision algorithm 844 is or is a component of an alerting
protocol.
[0137] The alert decision algorithm 844 determines whether an alert
should be provided to the user through user interface 372/716.
Here, the alert decision algorithm 844 can determine from
information in the state processor 840 what the state of the user
is. If the user is determined to be alert or otherwise paying
attention, there may be no need to initiate or continue an alert or
otherwise prompt the user to pay attention to operating the
vehicle. However, if the user is not alert, the alert decision
algorithm 844 can determine whether an alert may be sent based on
the state of the user or if the alert should be delayed. If it is
determined that the state of the user provided by the state
processor 840 does not require an alert at this time, the alert
algorithm may not send signal to send an alert. However, at some
time thereinafter based on a change of circumstances with the
vehicle or the user, an alert may be decided and then a signal may
be sent to the alert type processor 848.
[0138] The alert type processor 848, may then determine and/or
execute an alerting protocol. In accordance with the alerting
protocol, alert type processor 848 may then send a signal(s) to the
user interface 372/716 or some other system to carry out the
alert(s) associated with the alerting protocol. The alert type
processor 848 may determine the type of alert needed. For example,
the alert type processor 848 can determine if the alert should be
visual, audio, tactile, or some other type of alert. Further, the
alert type processor 848 can determine whether the alert should be
a combination and determine the forcefulness or aggressiveness of
the alert. For example, if the user needs to wake up immediately,
the alert may be louder, brighter, etc. than if the alert is waking
a sleeping user slowly for the end of a trip or process. These
types of situations may be determined by user preferences 820,
which may store information about what type of alert the user may
want depending on a situation. These user preferences 820 can be
predetermined by a vehicle manufacturer or may be set by a
user.
[0139] A state engine 816 may be as shown in FIG. 8E. The state
engine can include one or more of, but is not limited to, an
autonomous state engine 852, an environment state engine 856. There
may be more or fewer components to the state engine 816 than those
shown in FIG. 8E. The state engine 816 determines the state of the
vehicle. Thus, the autonomous state engine 852 can determine if the
vehicle is in the autonomous driving mode or some form of
autonomous driving. This information of the level of autonomy for
the vehicle may be determined based on sensor information or input
from the driving system 348. This information may be provided to
the alert system 812 so that the alert decision algorithm 844 can
determine if an alert is needed based on some kind of change or
information about the autonomous state.
[0140] The environment state engine 856 can determine the driving
environment for the vehicle 100. Thus, the environment state engine
856 can receive information from the sensors 304 or from driving
system 348 to determine what the environment is or if there has
been a change in the environment. For example, if the environment
changed to heavy traffic or bad weather, the environment state
engine 856 can change that information and alert the alert system
812 as to the change in environment to determine whether an alert
needs to be sent to the user to react to the change in environment.
The environment state engine 856 may then determine a system state
of the autonomous system, such vehicle 100. The environment state
engine 856 may then output a system state indicating whether a
user's attention is, or will be, required, such as to manual
operate 100 or a portion thereof that may have previously been
operated autonomously. For example, vehicle 100 may be unable to
maintain autonomous operation due to an anomaly navigation, hazard
on the roadway, component anomaly, etc. that vehicle 100 is, or
will, not be able to accommodate to maintain operation of vehicle
100 within the acceptable parameters of operation. A user's
attention may be required for a user-specific event, such as to
alert or wake the user to exit vehicle 100 upon arriving at the
intended destination.
[0141] An embodiment of information used for user preferences or
other information in determining whether an alert needs to be given
to a user based on the driving environment, user cognitive state,
or some other information may be as shown in FIGS. 9A and 9B. FIG.
9A shows the navigation source as part of the vehicle control
system 356. The navigation source may include GIS information 902,
or other data, which provides for information about the driving
system, traffic, weather, location, destination, waypoints,
etc.
[0142] FIG. 9B can be user preference information that may be
stored in user preferences data store 820. The user preferences
data store 820 can include a data structure 904 that includes
information about preferences for an operator. There may be more or
fewer data structures 904 based on how many operators may use the
vehicle 100, as represented by ellipses 922. The data structure can
include one or more of, but is not limited to, an operator
identifier (ID) 906, cognitive state information 908, wake
preferences 910, wake condition one 912, wake condition two 914,
and/or metadata 916. There may be more or fewer fields within each
data structure 904, as represented by ellipses 920. Further, there
may be more than two wake conditions 912, 914 within each data
structure, as represented by ellipses 918. In one embodiment, one
or more wave preferences 910 and/or wake conditions 912, 914 may
form a portion of an alerting protocol. An alerting protocol may
initiate a first wake condition (e.g., wake condition 914), in
response to a first system state requiring the user's attention,
such as to play a soft tone, return a reclined seat to an upright
position, etc. The alerting protocol may have additional and/or
alternative actions, such as in response to a user not responding
(e.g., not indicating attentiveness, indicating inattentiveness)
and/or a system state has become more urgent, a second wake
condition (e.g., wake condition 914) may be performed. For example,
the second wake condition may be more aggressive (e.g., play an
alarm, vibrate the seat, drop the interior temperature., etc.). In
another embodiment, vehicle 100, if unable to operate autonomously
and not able to be operated by an attentive user, may execute a
portion of an alerting protocol wherein vehicle 100 is shut down
(e.g., a safe parking area is identified and vehicle 100 navigates
to the area), notify emergency personnel (e.g., when unable to
revive user), drive to a hospital, drive to a service facility,
etc.
[0143] The operator ID 906 can be any type of ID to identify the
operator. For example, the operator ID 906 can be a numeric,
alphanumeric, globally unique identifier (GUID), or some other type
of ID that uniquely identifies the user of the vehicle. Further,
the operator ID 906 can include biometric or other information
specific to the identity of the user. For example, the operator ID
906 can include facial recognition, voice recognition, fingerprint
recognition, or other types of biometric or user-specific
information.
[0144] The cognitive state information 908 can be a determination
or information of past cognitive states and their associated sensor
information. For example, if the user was sleeping previously on a
previous trip, the cognitive state information 908 can include what
sensor readings were included during that time and identification
that the user was sleeping during that period. This cognitive state
information 908 can then be used by the cognitive state determiner
808 to determine the state of the user based on past information.
In other configurations, at least a portion of the cognitive state
information 908 can be based off predetermined information or
information from other users. Thus, the standard sensor readings
for an average person in a certain cognitive state may be also
stored and used to compare. This predetermined information may be
used initially until a more exact representation of that user's
cognitive states can be recorded and stored by the system.
[0145] Wake preferences 910 can include any type of information
about how the user wishes to be woken or have their cognitive state
changed based on a change in environment or activity. Thus, the
wake preferences 910 can provide information to the alert type
processor 848 about what type of alarm or alert is needed based on
the change in condition. Accordingly, the wake preferences 910 can
provide what type of alarm and associate that alarm type with an
event or other thing that may be changed or occur for the user.
[0146] Wake conditions 912, 914 can be a determination of when the
user should be woken or their cognitive state should be changed.
These conditions can include, for example, what type of environment
change, for example an increase of 50% more traffic, a change in
weather from sunny to rainy or sunny to snowy, or some other type
of change. If those wake conditions are elicited, then the user
should have their cognitive state changed. While the wake
conditions 912, 914 are listed as a wake condition, these can be
conditions to change any type of cognitive state, including
distracted driving or other types of conditions. Thus, for each
type of condition and user state, there may be a different
condition. These wake conditions can be predetermined by a vehicle
manufacturer, a third party, or may be set by a user.
[0147] Metadata 916 can be any information about previous cognitive
states or driving information that may be useful in determining
when a user should be alerted. This metadata can include the
changes in the user or how the user receives such an alert when
woken in previous situations. Further, the metadata 916 can be
associated with certain times, dates, or locations for waking
preferences.
[0148] An embodiment of a user interface that may be provided in a
user interface 420B of instrument panel 400, or other user
interface, is illustrated in FIG. 10. The user interface 420B may
include a waking alert window 1002 or some other display within a
user interface. The window 1002 can include a pop-up notification
1004 that includes an alert 1008. Here, the alert is to wake the
user. This user interface notification 1004 can flash and be
accompanied with one or more other types of alerts provided by one
or more components of the vehicle. For example, a chime, buzz,
beep, etc. can be played through the speakers of the vehicle. The
horn can be honked by the vehicle to wake the user. In other
confirmations, there may also be a tactile alert such as a
vibration of the seat, steering wheel, or other type of tactile
alert. Further, the vehicle control system 348 can change the
current environment of the vehicle, including turning on the air
conditioning to cool the vehicle or causing some other kind of
change that may cause discomfort and change of cognitive state of
the user. The notification 1004 can also include a user interface
device 1012 that can be selected by a user through the user
interface 420B. This device may be an acknowledged wake signal
input that allows the vehicle control system 348 to understand that
the user has changed their cognitive state and recognizes the wake
notification 1004.
[0149] An embodiment of a method 1100 for providing alerts or
change of cognitive state of the user may be as shown in FIG.
11.
[0150] The method may start at 1104 and a user may begin travel in
step 1108. Here, the vehicle may be started and the user can
proceed along a route. During this time, the cognitive state system
800 may monitor the driver during travel in step 1112. For example,
as explained in conjunction with FIGS. 8A-8D, the cognitive state
determiner 808 can receive sensor information 304 through a sensor
API 804. This sensor information may be used to determine by the
state processor 840 what the state of the driver is. Thus, the
sensor API 804 can receive sensor information and modify that
information with the computer vision processing component 824, the
movement and position processing component 828, the physiological
data processing component 832, and provide that information to the
data fusion component 836. The data fusion component 836 can modify
any of this information from the sensor API and provide it into a
single data structure or stream to the state processor 840. The
state processor 840 can then monitor what the state of the user or
driver is during the travel.
[0151] The state processor 840 then can determine whether the
driver is inattentive in step 1116. Here, the state processor 840
may compare the state of the user to the cognitive state
information 908 in data structure 904 to determine if the user's
cognitive state is distracted or inattentive. If there is a
comparison, the method 1100 proceeds YES to step 1120. However, if
it appears that the user is not distracted or is attentive and
driving normally, the method 1100 may proceed NO back to step 1112.
Thus, the state processor can continually determine whether the
driver is distracted or inattentive in step 1116.
[0152] In step 1120, the state engine 816 can determine whether the
vehicle is in autonomous mode. Thus, the autonomous state engine
852 can receive information from the vehicle control system 348 to
determine whether the vehicle is currently in autonomous mode. If
the vehicle is in autonomous mode, the method 1100 may proceed YES
to step 1128. However, if the vehicle is not in autonomous mode as
determined by the autonomous state engine 852, a method 1100 may
proceed NO to step 1136. Thus, the autonomous state engine 852 can
send a signal to the alert system 812 if the vehicle is in or out
of autonomous mode.
[0153] While in autonomous mode, the alert system 812 can determine
whether to alert the driver in step 1128. As such, the vehicle may
continue in autonomous mode and can make a determination of whether
or not the cognitive state of the user is pertinent to the current
driving situation. Thus, the alert decision algorithm 844 can
receive information from sensors, user preferences 820, etc. to
determine if the driver should be alerted while in autonomous mode.
If the user does not need to be alerted during autonomous mode,
then the alert decision algorithm 844 can determine that no alert
is needed and the method 1100 can proceed NO to step 1132. In step
1132, the alert system 812 can determine whether a trip is ended.
This may be determined by receiving information from the navigation
system or from reaching the destination as provided by the user. If
the trip has ended, then the method proceeds YES to step 1136. If
the trip has not ended, the method 1100 proceeds NO back to step
1116 to continue to monitor the driver and the mode of the vehicle.
During this loop, if there is a state change signal 1130, that may
be introduced to decision 1128 produced by the alert system. A
state change can be any change provided by the cognitive state
determiner 808 through sensor information and produced by the state
processor 840. Further, there may be changes in the autonomous
state provided by the autonomous state engine 852 or in the driving
environment provided by environment state engine 856. Any state
change signal either to the vehicle or the driver may be generated
in step 1130 and provided to the alert system 812, which may then
again determine whether or not to alert the driver in step 1128.
However, if the state change does not require an alert of the
driver, the method again proceeds NO to step 1132. However, if at
any time that the alert decision algorithm 844 determines that the
driver should be alerted, the method 1100 proceed YES from step
1128 to step 1136. In step 1136, the alert decision algorithm 844
determines that the vehicle must produce an alert. The type of
alert may be determined by the alert type processor 848. The alert
system 812 may then send a signal to the user interface 372/716 or
to one or more other vehicle systems through the vehicle control
system 348. The user interface wake alert 1002 as provided in FIG.
10 may be provided on a user interface such as user interface 420B.
Further audible or tactile alarms may be provided to produce the
alert 1136 to change the cognitive state of the user. These alarms
may continue until the user's cognitive state is changed. Thus, the
method 1100 allows for the user to be distracted or fall asleep
during autonomous mode driving and does not necessarily need to
produce an alarm every time the cognitive state of the user changes
or is detrimental to the driving experience as the vehicle can
provide for autonomous driving while the user is distracted.
[0154] An embodiment of a method 1200 for determining a change in
driver state may be as shown in FIG. 12. The method 1200 may being
at step 1204 and the cognitive state determiner 808 can receive
sensor signals in step 1208. Here, a sensor API 804 can receive
sensor signals from sensors 304. The sensor API can then compute or
modify the signals through the computer vision processing component
824, the movement and position processing component 828, and the
physiological data processing component 832. Thus, based on the
type of type of sensor, one of the components 824-832 can process
the signal. This information may then be consolidated and sent to
the cognitive state determiner 808. The data fusion component 836
or the cognitive state determiner 808 can then fuse the data from
the various processing functions 824-832. This information, as a
consolidated stream, can be sent to the state processor 840. The
state processor 840 can then determine whether the driver's state
has changed in step 1212. Here, the processing or the information
from the data fusion component 836 can be compared to data 908 to
determine if a different cognitive state has been sensed. For
example, if the user's eyes are open but were previously closed,
the user may be awake when they were previously sleeping. Other
types of changes may have occurred that may be evaluated by the
state processor 840. If the state of the user has changed, the
method flows YES to step 1216. However, if the state has not
changed, the method 1200 proceeds NO back to step 1208 to continue
to monitor the state of the driver.
[0155] In step 1216, the state processor may send a signal to the
alert system 812 to signal the change in state. This signal can be
an interrupt or some other type of signal that may be received by
the alert system 812 in step 1130.
[0156] An embodiment of a method 1300 for determining by the alert
system 812 whether an alert is needed may be as shown in FIG. 13.
In one embodiment, method 1300 may be being at 1304 and the alert
system 812 can receive a state change signal in step 1308. Here, as
explained in conjunction with FIGS. 11 and 12, the cognitive state
determiner 808 can send a signal in step 1130 which may be received
by the alert system 812 in step 1308. This signal may be sent to
the alert decision algorithm 844. Further, the state engine 816 may
also send a signal of a change in the state of the vehicle or in
the environment the vehicle is driving in. One of these signals may
then be used to determine whether a state change matches an alert
criterion in step 1312.
[0157] Here, the alert decision algorithm may compare the state
change or the change in data or current state and other information
to user preferences 820. For example, the user preferences can
include wake preferences 910 or wake conditions 912, 914. The
situation or the data received, including the state change, may be
compared to such data 910-914. If one of the wake preferences or
wake conditions is met, the method 1300 will proceed YES to step
1316. However, if the state change does not match any of the alert
criteria in data 910-914, the method 1300 may proceed NO back to
receiving a state change signal 1308 to react to the next state
change signal received by the alert system 812.
[0158] In step 1316, if an alert is required, the decision
algorithm 844 instructs the alert type processor 848 to send the
alert or signal that an alert is required. The alert type processor
848 can determine the type of alert and instruct the user interface
372/716 or other devices within the vehicle through the vehicle
control system 348 to provide the alert. Thus, the signal provided
for the alert can provide what type of alert, when the alert should
be sent, how, how it should be responded to, and other
information.
[0159] FIG. 14 illustrates process 1400 in accordance with
embodiments of the present discloser. In one embodiment, process
1400 is executed by a processor, such as one or more of CPU(s) 708.
Process 1402 is the operation of an autonomous system, such as
driving vehicle 100. Steps 1404 and 1406 may be performed in series
or parallel. Step 1404 performs a test to determine the user's
current state, such as by the processor receiving an output signal
from one or more user sensors, such as sensor 337 when configured
to observe at least one cognition-indicating attribute. Step 1406
performs a test to determine the system's state, such as whether
vehicle 100 requires or will require an input from the user. Test
1408 determines if both the user is inattentive and the system
requires attention and, if true, executes step 1410 whereby the
alerting protocol is initiate. If the alerting protocol is already
initiated step 1410 may continue the alerting protocol. Alerting
protocol 1410 may have one or more alternative or additional
alerting options such as to escalate the waking in accordance with
an urgency, failure to wake the user after a predetermined period
of time, etc. If step 1408 is determined in the negative, step 1412
may then execute to perform no action, such as when the alerting
protocol is not being executed, or to discontinue the alerting
protocol, when the alerting protocol is being executed.
[0160] The exemplary systems and methods of this disclosure have
been described in relation to vehicle systems and electric
vehicles. However, to avoid unnecessarily obscuring the present
disclosure, the preceding description omits a number of known
structures and devices. This omission is not to be construed as a
limitation of the scope of the claimed disclosure. Specific details
are set forth to provide an understanding of the present
disclosure. It should, however, be appreciated that the present
disclosure may be practiced in a variety of ways beyond the
specific detail set forth herein.
[0161] Furthermore, while the exemplary embodiments illustrated
herein show the various components of the system collocated,
certain components of the system can be located remotely, at
distant portions of a distributed network, such as a LAN and/or the
Internet, or within a dedicated system. Thus, it should be
appreciated, that the components of the system can be combined into
one or more devices, such as a server, communication device, or
collocated on a feature vector node of a distributed network, such
as an analog and/or digital telecommunications network, a
packet-switched network, or a circuit-switched network. It will be
appreciated from the preceding description, and for reasons of
computational efficiency, that the components of the system can be
arranged at any location within a distributed network of components
without affecting the operation of the system.
[0162] Furthermore, it should be appreciated that the various links
connecting the elements can be wired or wireless links, or any
combination thereof, or any other known or later developed
element(s) that is capable of supplying and/or communicating data
to and from the connected elements. These wired or wireless links
can also be secure links and may be capable of communicating
encrypted information. Transmission media used as links, for
example, can be any suitable carrier for electrical signals,
including coaxial cables, copper wire, and fiber optics, and may
take the form of acoustic or light waves, such as those generated
during radio-wave and infra-red data communications.
[0163] While the flowcharts have been discussed and illustrated in
relation to a feature vector sequence of events, it should be
appreciated that changes, additions, and omissions to this sequence
can occur without materially affecting the operation of the
disclosed embodiments, configuration, and aspects.
[0164] A number of variations and modifications of the disclosure
can be used. It would be possible to provide for some features of
the disclosure without providing others.
[0165] In yet another embodiment, the systems and methods of this
disclosure can be implemented in conjunction with a special purpose
computer, a programmed microprocessor or microcontroller and
peripheral integrated circuit element(s), an ASIC or other
integrated circuit, a digital signal processor, a hard-wired
electronic or logic circuit such as discrete element circuit, a
programmable logic device or gate array such as PLD, PLA, FPGA,
PAL, special purpose computer, any comparable means, or the like.
In general, any device(s) or means capable of implementing the
methodology illustrated herein can be used to implement the various
aspects of this disclosure. Exemplary hardware that can be used for
the present disclosure includes computers, handheld devices,
telephones (e.g., cellular, Internet enabled, digital, analog,
hybrids, and others), and other hardware known in the art. Some of
these devices include processors (e.g., a single or multiple
microprocessors), memory, nonvolatile storage, input devices, and
output devices. Furthermore, alternative software implementations
including, but not limited to, distributed processing or
component/object distributed processing, parallel processing, or
virtual machine processing can also be constructed to implement the
methods described herein.
[0166] In yet another embodiment, the disclosed methods may be
readily implemented in conjunction with software using object or
object-oriented software development environments that provide
portable source code that can be used on a variety of computer or
workstation platforms. Alternatively, the disclosed system may be
implemented partially or fully in hardware using standard logic
circuits or VLSI design. Whether software or hardware is used to
implement the systems in accordance with this disclosure is
dependent on the speed and/or efficiency requirements of the
system, the feature vector function, and the feature vector
software or hardware systems or microprocessor or microcomputer
systems being utilized.
[0167] In yet another embodiment, the disclosed methods may be
partially implemented in software that can be stored on a storage
medium, executed on programmed general-purpose computer with the
cooperation of a controller and memory, a special purpose computer,
a microprocessor, or the like. In these instances, the systems and
methods of this disclosure can be implemented as a program embedded
on a personal computer such as an applet, JAVA.RTM. or CGI script,
as a resource residing on a server or computer workstation, as a
routine embedded in a dedicated measurement system, system
component, or the like. The system can also be implemented by
physically incorporating the system and/or method into a software
and/or hardware system.
[0168] Although the present disclosure describes components and
functions implemented in the embodiments with reference to feature
vector standards and protocols, the disclosure is not limited to
such standards and protocols. Other similar standards and protocols
not mentioned herein are in existence and are considered to be
included in the present disclosure. Moreover, the standards and
protocols mentioned herein and other similar standards and
protocols not mentioned herein are periodically superseded by
faster or more effective equivalents having essentially the same
functions. Such replacement standards and protocols having the same
functions are considered equivalents included in the present
disclosure.
[0169] The present disclosure, in various embodiments,
configurations, and aspects, includes components, methods,
processes, systems and/or apparatus substantially as depicted and
described herein, including various embodiments, subcombinations,
and subsets thereof. Those of skill in the art will understand how
to make and use the systems and methods disclosed herein after
understanding the present disclosure. The present disclosure, in
various embodiments, configurations, and aspects, includes
providing devices and processes in the absence of items not
depicted and/or described herein or in various embodiments,
configurations, or aspects hereof, including in the absence of such
items as may have been used in previous devices or processes, e.g.,
for improving performance, achieving ease, and/or reducing cost of
implementation.
[0170] The foregoing discussion of the disclosure has been
presented for purposes of illustration and description. The
foregoing is not intended to limit the disclosure to the form or
forms disclosed herein. In the foregoing Detailed Description for
example, various features of the disclosure are grouped together in
one or more embodiments, configurations, or aspects for the purpose
of streamlining the disclosure. The features of the embodiments,
configurations, or aspects of the disclosure may be combined in
alternate embodiments, configurations, or aspects other than those
discussed above. This method of disclosure is not to be interpreted
as reflecting an intention that the claimed disclosure requires
more features than are expressly recited in each claim. Rather, as
the following claims reflect, inventive aspects lie in less than
all features of a single foregoing disclosed embodiment,
configuration, or aspect. Thus, the following claims are hereby
incorporated into this Detailed Description, with each claim
standing on its own as a separate preferred embodiment of the
disclosure.
[0171] Moreover, though the description of the disclosure has
included description of one or more embodiments, configurations, or
aspects and certain variations and modifications, other variations,
combinations, and modifications are within the scope of the
disclosure, e.g., as may be within the skill and knowledge of those
in the art, after understanding the present disclosure. It is
intended to obtain rights, which include alternative embodiments,
configurations, or aspects to the extent permitted, including
alternate, interchangeable and/or equivalent structures, functions,
ranges, or steps to those claimed, whether or not such alternate,
interchangeable and/or equivalent structures, functions, ranges, or
steps are disclosed herein, and without intending to publicly
dedicate any patentable subject matter.
[0172] Embodiments include a vehicle, comprising: a sensor to sense
an environment surrounding the vehicle, wherein a feature vector
describes at least a portion of the environment at a current
location of the vehicle on a route; a processor in communication
with the sensor, the processor to: receive information from the
sensor regarding the feature vector; retrieve feature vector
information associated with two or more segments of a route of
travel for the vehicle; compare the received feature vector to the
retrieved feature vector information; determine if the received
feature vector to the retrieved feature vector information match;
and if the received feature vector to the retrieved feature vector
information match, determine that the current location of the
vehicle is at a segment location of the segment associated with the
retrieved feature vector information.
[0173] Any of the one or more above aspects, wherein the feature
vector is a portion of a machine view of the environment obtained
by the sensor.
[0174] Any of the one or more above aspects, wherein the received
feature vector is compared visually to the retrieved feature vector
information.
[0175] Any of the one or more above aspects, wherein the route is
delineated into two or more segments.
[0176] Any of the one or more above aspects, wherein each segment
has a known segment location.
[0177] Any of the one or more above aspects, further comprising the
processor to determine a preliminary location to reduce a number of
segments retrieved to compare to the received feature vector.
[0178] Any of the one or more above aspects, wherein the
preliminary location is determined by a GPS signal, by dead
reckoning, by visual odometry, and/or by particle filtering.
[0179] Any of the one or more above aspects, further comprising the
processor to determine a next segment to compare to a next received
feature vector based on a vector of travel for the vehicle.
[0180] Any of the one or more above aspects, wherein the next
received feature vector is obtained by the sensor after the vehicle
has traveled to a next location.
[0181] Any of the one or more above aspects, further comprising the
processor to repeat one or more of: receive next information from
the sensor regarding the next feature vector; retrieve next feature
vector information associated with two or more next segments of the
route of travel for the vehicle; compare the next received feature
vector to the next retrieved feature vector information; determine
if the next received feature vector to the next retrieved feature
vector information match; and if the next received feature vector
to the next retrieved feature vector information match, determine
that a next current location of the vehicle is at a next segment
location of the next segment associated with the next retrieved
feature vector information.
[0182] Any of the one or more above aspects, further comprising the
processor to, after determining the segment location, determine a
new feature vector in view of the sensor.
[0183] Any of the one or more above aspects, further comprising the
processor to characterize the new feature vector.
[0184] Any of the one or more above aspects, further comprising the
processor to provide the new feature vector to another vehicle to
aid the other vehicle in determining the location at the
segment.
[0185] Embodiments further include a method comprising:
determining, by a processor, a preliminary location of a vehicle on
a route of travel, wherein the route of travel is delineated into
two or more segments. receiving, by the processor, information,
from a sensor, wherein the sensor senses an environment surrounding
the vehicle, wherein the information comprises a feature vector,
wherein the feature vector describes at least a portion of the
environment at a current location of the vehicle; retrieving
feature vector information associated with the two or more segments
of the route of travel for the vehicle; comparing the received
feature vector to the retrieved feature vector information;
determine if the received feature vector to the retrieved feature
vector information match; and if the received feature vector and
the retrieved feature vector information match, determining that
the current location of the vehicle is at a segment location of the
segment associated with the retrieved feature vector
information.
[0186] Any of the one or more above aspects, wherein the feature
vector is a portion of a machine view of the environment obtained
by the sensor, and wherein the received feature vector is compared
visually to the retrieved feature vector information.
[0187] Any of the one or more above aspects, wherein the route is
delineated into two or more segments, and wherein each segment has
a known segment location.
[0188] Any of the one or more above aspects, wherein determining
the preliminary location of the vehicle reduces a number of
segments retrieved to compare to the received feature vector, and
wherein the preliminary location is determined by a GPS signal, by
dead reckoning, by visual odometry, and/or by particle
filtering.
[0189] Any of the one or more above aspects, further comprising:
determine a next segment to compare to a next received feature
vector based on a vector of travel for the vehicle, wherein the
next received feature vector is obtained by the sensor after the
vehicle has traveled to a next location; repeating one or more of:
receiving next information from the sensor regarding the next
feature vector; by retrieving next feature vector information
associated with two or more next segments of the route of travel
for the vehicle; comparing the next received feature vector to the
next retrieved feature vector information; determining if the next
received feature vector to the next retrieved feature vector
information match; and if the next received feature vector to the
next retrieved feature vector information match, determining that a
next current location of the vehicle is at a next segment location
of the next segment associated with the next retrieved feature
vector information.
[0190] Any of the one or more above aspects, further comprising:
after determining the segment location, determining a new feature
vector in view of the sensor; characterizing the new feature
vector; and providing the new feature vector to another vehicle to
aid the other vehicle in determining the location at the
segment.
[0191] Embodiments further include a non-transitory computer
readable medium having instructions stored thereon that when
executed by a processor of a vehicle cause the processor to perform
a method, the method comprising: determining, by a processor, a
preliminary location of a vehicle on a route of travel, wherein the
route of travel is delineated into two or more segments; receiving,
by the processor, information, from a sensor, wherein the sensor
senses an environment surrounding the vehicle, wherein the
information comprises a feature vector, wherein the feature vector
describes at least a portion of the environment at a current
location of the vehicle; retrieving feature vector information
associated with the two or more segments of the route of travel for
the vehicle; comparing the received feature vector to the retrieved
feature vector information; determine if the received feature
vector to the retrieved feature vector information match; if the
received feature vector and the retrieved feature vector
information match, determining that the current location of the
vehicle is at a segment location of the segment associated with the
retrieved feature vector information; after determining the segment
location, determining a new feature vector in view of the sensor;
characterizing the new feature vector; and providing the new
feature vector to another vehicle to aid the other vehicle in
determining the location at the segment.
[0192] Any one or more of the aspects/embodiments as substantially
disclosed herein.
[0193] Any one or more of the aspects/embodiments as substantially
disclosed herein optionally in combination with any one or more
other aspects/embodiments as substantially disclosed herein.
[0194] One or means adapted to perform any one or more of the above
aspects/embodiments as substantially disclosed herein.
[0195] The phrases "at least one," "one or more," "or," and
"and/or" are open-ended expressions that are both conjunctive and
disjunctive in operation. For example, each of the expressions "at
least one of A, B and C," "at least one of A, B, or C," "one or
more of A, B, and C," "one or more of A, B, or C," "A, B, and/or
C," and "A, B, or C" means A alone, B alone, C alone, A and B
together, A and C together, B and C together, or A, B and C
together.
[0196] The term "a" or "an" entity refers to one or more of that
entity. As such, the terms "a" (or "an"), "one or more," and "at
least one" can be used interchangeably herein. It is also to be
noted that the terms "comprising," "including," and "having" can be
used interchangeably.
[0197] The term "automatic" and variations thereof, as used herein,
refers to any process or operation, which is typically continuous
or semi-continuous, done without material human input when the
process or operation is performed. However, a process or operation
can be automatic, even though performance of the process or
operation uses material or immaterial human input, if the input is
received before performance of the process or operation. Human
input is deemed to be material if such input influences how the
process or operation will be performed. Human input that consents
to the performance of the process or operation is not deemed to be
"material."
[0198] Aspects of the present disclosure may take the form of an
embodiment that is entirely hardware, an embodiment that is
entirely software (including firmware, resident software,
micro-code, etc.) or an embodiment combining software and hardware
aspects that may all generally be referred to herein as a
"circuit," "module," or "system." Any combination of one or more
computer-readable medium(s) may be utilized. The computer-readable
medium may be a computer-readable signal medium or a
computer-readable storage medium.
[0199] A computer-readable storage medium may be, for example, but
not limited to, an electronic, magnetic, optical, electromagnetic,
infrared, or semiconductor system, apparatus, or device, or any
suitable combination of the foregoing. More specific examples (a
non-exhaustive list) of the computer-readable storage medium would
include the following: an electrical connection having one or more
wires, a portable computer diskette, a hard disk, a random access
memory (RAM), a read-only memory (ROM), an erasable programmable
read-only memory (EPROM or Flash memory), an optical fiber, a
portable compact disc read-only memory (CD-ROM), an optical storage
device, a magnetic storage device, or any suitable combination of
the foregoing. In the context of this document, a computer-readable
storage medium may be any tangible medium that can contain or store
a program for use by or in connection with an instruction execution
system, apparatus, or device.
[0200] A computer-readable signal medium may include a propagated
data signal with computer-readable program code embodied therein,
for example, in baseband or as part of a carrier wave. Such a
propagated signal may take any of a variety of forms, including,
but not limited to, electro-magnetic, optical, or any suitable
combination thereof. A computer-readable signal medium may be any
computer-readable medium that is not a computer-readable storage
medium and that can communicate, propagate, or transport a program
for use by or in connection with an instruction execution system,
apparatus, or device. Program code embodied on a computer-readable
medium may be transmitted using any appropriate medium, including,
but not limited to, wireless, wireline, optical fiber cable, RF,
etc., or any suitable combination of the foregoing.
[0201] The terms "determine," "calculate," "compute," and
variations thereof, as used herein, are used interchangeably and
include any type of methodology, process, mathematical operation or
technique.
[0202] The term "electric vehicle" (EV), also referred to herein as
an electric drive vehicle, may use one or more electric motors or
traction motors for propulsion. An electric vehicle may be powered
through a collector system by electricity from off-vehicle sources,
or may be self-contained with a battery or generator to convert
fuel to electricity. An electric vehicle generally includes a
rechargeable electricity storage system (RESS) (also called Full
Electric Vehicles (FEV)). Power storage methods may include:
chemical energy stored on the vehicle in on-board batteries (e.g.,
battery electric vehicle or BEV), on board kinetic energy storage
(e.g., flywheels), and/or static energy (e.g., by on-board
double-layer capacitors). Batteries, electric double-layer
capacitors, and flywheel energy storage may be forms of
rechargeable on-board electrical storage.
[0203] The term "hybrid electric vehicle" refers to a vehicle that
may combine a conventional (usually fossil fuel-powered) powertrain
with some form of electric propulsion. Most hybrid electric
vehicles combine a conventional internal combustion engine (ICE)
propulsion system with an electric propulsion system (hybrid
vehicle drivetrain). In parallel hybrids, the ICE and the electric
motor are both connected to the mechanical transmission and can
simultaneously transmit power to drive the wheels, usually through
a conventional transmission. In series hybrids, only the electric
motor drives the drivetrain, and a smaller ICE works as a generator
to power the electric motor or to recharge the batteries.
Power-split hybrids combine series and parallel characteristics. A
full hybrid, sometimes also called a strong hybrid, is a vehicle
that can run on just the engine, just the batteries, or a
combination of both. A mid hybrid is a vehicle that cannot be
driven solely on its electric motor, because the electric motor
does not have enough power to propel the vehicle on its own.
[0204] The term "rechargeable electric vehicle" or "REV" refers to
a vehicle with on board rechargeable energy storage, including
electric vehicles and hybrid electric vehicles.
* * * * *