U.S. patent application number 13/425707 was filed with the patent office on 2012-07-12 for system and method for automated updating of map information.
This patent application is currently assigned to ON TIME SYSTEMS, INC.. Invention is credited to PAUL A.C. CHANG, MATTHEW L. GINSBERG, KEVIN SCAVEZZE, BRYAN SMITH.
Application Number | 20120179358 13/425707 |
Document ID | / |
Family ID | 40432793 |
Filed Date | 2012-07-12 |
United States Patent
Application |
20120179358 |
Kind Code |
A1 |
CHANG; PAUL A.C. ; et
al. |
July 12, 2012 |
SYSTEM AND METHOD FOR AUTOMATED UPDATING OF MAP INFORMATION
Abstract
The characteristics of two intersecting roadways are compared to
determine whether an inference can be made as to whether there are
traffic controls (e.g., stop signs) on one of the roadways. If a
larger road with characteristically higher speed intersects with a
small road with lower speed, the small road is determined to have a
stop sign. A map database is updated with the information regarding
the inferred traffic control, and that information is then usable
for purposes such as trip planning.
Inventors: |
CHANG; PAUL A.C.;
(Springfield, OR) ; GINSBERG; MATTHEW L.; (Eugene,
OR) ; SCAVEZZE; KEVIN; (Eugene, OR) ; SMITH;
BRYAN; (Eugene, OR) |
Assignee: |
ON TIME SYSTEMS, INC.
Eugene
OR
|
Family ID: |
40432793 |
Appl. No.: |
13/425707 |
Filed: |
March 21, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11851953 |
Sep 7, 2007 |
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13425707 |
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Current U.S.
Class: |
701/119 ;
707/609; 707/E17.005 |
Current CPC
Class: |
G01C 21/3811 20200801;
G01C 21/32 20130101 |
Class at
Publication: |
701/119 ;
707/609; 707/E17.005 |
International
Class: |
G08G 1/00 20060101
G08G001/00; G06F 17/30 20060101 G06F017/30 |
Claims
1. A system for updating a map database, comprising: a data
reception module configured to obtain a first roadway size
characteristic associated with a first road and a second roadway
size characteristic associated with a second road, the first road
and the second road meeting at an intersection; and an inference
processor operably connected to the data reception module and
configured to derive from the first roadway size characteristic and
the second roadway size characteristic additional information not
already stored within the map database and automatically update the
map database to reflect the additional information, wherein the
additional information denotes presence of a traffic control
device.
2. A system, comprising: a map database comprising information
associated with roads; an input subsystem configured to provide
roadway characteristics; an information inference module configured
to derive from the roadway characteristics additional information
not already stored within the map database and automatically update
the map database to reflect the additional information.
3. The system of claim 2, wherein the information inference module
is further configured to determine presence or absence of a traffic
control based upon vehicle speeds on each of two roadways forming
an intersection, in order to derive the additional information.
4. The system of claim 2, wherein the vehicle speeds are derived
from GPS readings sent by vehicles.
5. The system of claim 2, wherein the vehicle speeds are derived
from speed limits on each of the two roadways.
6. The system of claim 2, wherein the vehicle speeds are derived
from operation of fixed roadway sensors.
7. The system of claim 2, wherein the information inference module
is further configured to determine a type of a traffic control
based upon vehicle speeds, in order to derive the additional
information.
8. The system of claim 7, wherein the type includes at least one of
the group consisting of: a stop sign, a traffic light, a
synchronized traffic light, a yield sign, a turn restriction
control, a lane restriction control, a railroad crossing control
and a pedestrian crossing control.
9. The system of claim 3, wherein the traffic control includes at
least one of the group consisting of: a stop sign, a traffic light,
a synchronized traffic light, a yield sign, a turn restriction
control, a lane restriction control, a railroad crossing control
and a pedestrian crossing control.
10. The system of claim 2, wherein the roadway characteristics
include at least one of the group consisting of: roadway
classification, roadway historical traffic volume, traffic signal
phasing, traffic signal state information, roadway sensor
information.
11. The system of claim 1, wherein the additional information
further denotes characteristics of the traffic control device.
12. A method for automatically updating a map database, comprising:
receiving map information from the map database, the map database
comprising information associated with roads; receiving roadway
characteristic information; deriving additional information not
already stored within the map database responsive to the roadway
characteristic information; and updating the map database to
reflect the derived additional information.
13. The method of claim 12, wherein deriving additional information
comprises determining presence or absence of a traffic control
based upon vehicle speeds on each of two roadways forming an
intersection.
14. The method of claim 12, wherein the vehicle speeds are derived
from GPS readings sent by vehicles.
15. The method of claim 12, wherein the vehicle speeds are derived
from speed limits on each of the two roadways.
16. The method of claim 12, wherein the vehicle speeds are derived
from operation of fixed roadway sensors.
17. The method of claim 12, wherein deriving additional information
includes determining a type of a traffic control based upon vehicle
speeds.
18. The method of claim 17, wherein the type includes at least one
of the group consisting of: a stop sign, a traffic light, a
synchronized traffic light, a yield sign, a turn restriction
control, a lane restriction control, a railroad crossing control
and a pedestrian crossing control.
19. The method of claim 12, wherein the traffic control includes at
least one of the group consisting of: a stop sign, a traffic light,
a synchronized traffic light, a yield sign, a turn restriction
control, a lane restriction control, a railroad crossing control
and a pedestrian crossing control.
20. The method of claim 12, wherein the roadway characteristics
include at least one of the group consisting of: roadway
classification, roadway historical traffic volume, traffic signal
phasing, traffic signal state information, roadway sensor
information.
Description
RELATED APPLICATIONS
[0001] This application is a continuation in part of co-pending
U.S. patent application Ser. No. 11/851,953, filed Sep. 7, 2007,
entitled "System and Method for Automated Updating of Map
Information", which is incorporated herein by reference.
BACKGROUND
[0002] 1. Field of Art
[0003] The present invention generally relates to updating and
correcting databases of road map information that can be used for
vehicle navigation or similar purposes.
[0004] 2. Description of the Related Art
[0005] Digital databases of road map information are essential
components of a variety of useful applications, such as vehicle
routing. The road map information databases used in vehicle routing
systems describe the geographical location and intersections of the
roads, or usage restrictions such as one-way restrictions or turn
restrictions. The road map information databases also contain other
metadata pertinent to vehicle routing, including traffic speeds
over the various road segments, the names and address ranges of the
roads, the road classification (residential, collector, arterial,
highway/freeway) and the like. In conjunction with real-time
location data, such as that provided by a satellite-based Global
Positioning System (GPS), such databases allow a vehicle routing
system to determine the location of a user's vehicle and to take
actions useful to the user, such as computing an optimal route from
the current location to a desired destination, providing detailed
directions for traversing a route, or providing an estimate of the
arrival time at the destination. Updates and augmentation of the
database further increase the accuracy and capabilities of the
applications using the database. For example, the addition to a
database of information regarding real-time traffic conditions
enables a vehicle routing application to compute a route that not
only minimizes overall distance, but also minimizes driving time as
well, based on the current traffic speeds associated with the
route.
[0006] However, databases frequently lack important categories of
information that applications could use to provide more accurate
results or entirely new categories of features. Some examples of
information that is not generally available are the locations of
stop signs and traffic signals, information about whether traffic
signals are pre-timed to coordinate with traffic flow, and turn
restrictions that may only be active at certain times of day. As an
example of the utility of such information, information about turn
restrictions that are active at certain times of day could be used
to detect that a route that was optimal at 11:00 AM would be
entirely prohibited at 6:00 PM, thus avoiding proposing an invalid
route to the user.
[0007] Of additional concern is the fact that database information
may contain inaccuracies due to human error on the part of those
creating the database, or due to failures to update the database to
reflect actual changes in the roads subsequent to the creation of
the database. For example, a database may erroneously indicate that
an intersection has no stop signs even months after stop signs have
been installed. Or, a crossing between two roads may be incorrectly
identified as an at-grade intersection where, in reality, the
crossing involves a bridge, overpass or tunnel.
[0008] Some commentators have discussed the possibility of using
in-vehicle GPS units to correct one of the deficiencies found in
many databases--the lack of real-time information on traffic
speeds--by aggregating the individual vehicle speeds recorded by
GPS units over many vehicles to obtain statistical information
about likely vehicle speeds on a particular road segment at a given
time. However, there remain many other database information
deficiencies for which no automated solutions have been discussed,
although the need to address these deficiencies becomes ever more
pressing as the number of related routing applications grows.
SUMMARY
[0009] As disclosed herein, map database information is augmented
using information obtained by recording the movements of a vehicle
equipped with a positioning system device, deriving additional map
details based upon those movements, and updating the database to
reflect the additional details. Alternatively, the information is
obtained by inference from related roadway characteristic
information, such as may be stored in a database.
[0010] Some embodiments of the invention augment a map database by
deriving entirely new categories of information not previously
tracked by the database. In one embodiment, the presence of stop
signs is detected by observed or otherwise obtained information
about relative sizes of intersecting roadways, vehicle speeds,
speed limits, or traffic volumes. Thus, embodiments of the
invention can be used to derive additional information about
characteristics of the roads themselves, independent of current
traffic conditions.
[0011] Certain road characteristics (e.g., presence of stop signs)
are inferred from other, already known road characteristics. For
instance, stop signs may reasonably be inferred for a small
two-lane road with a known 30 mph speed limit where it has an
at-grade intersection with a four-lane divided highway with a known
55 mph speed limit. Similarly, stop signs may also be inferred for
a residential road where it has an at-grade intersection with a
non-residential road. Certain turn restrictions may also be
inferred from either the geometry or type of road segment. For
instance, on-ramps onto the eastbound lanes of a freeway generally
cannot be used to maneuver a vehicle onto the westbound lanes. Or,
a short road segment which is used as a dedicated right turn lane
cannot be used for making left turns.
[0012] The features and advantages described in the specification
are not all inclusive and, in particular, many additional features
and advantages will be apparent to one of ordinary skill in the art
in view of the drawings, specification, and claims. Moreover, it
should be noted that the language used in the specification has
been principally selected for readability and instructional
purposes, and may not have been selected to delineate or
circumscribe the inventive subject matter.
BRIEF DESCRIPTION OF DRAWINGS
[0013] The disclosed embodiments have other advantages and features
which will be more readily apparent from the following detailed
description and the appended claims, when taken in conjunction with
the accompanying drawings, in which:
[0014] FIG. 1 is a flowchart illustrating high-level steps
performed according to one embodiment.
[0015] FIG. 2 is a high-level block diagram illustrating a
computing device for implementing a preferred embodiment.
[0016] FIG. 3 is a diagram of an intersection for which stop sign
information is inferred as described herein.
DETAILED DESCRIPTION
[0017] The figures and the following description relate to
preferred embodiments by way of illustration only. It should be
noted that from the following discussion, alternative embodiments
of the structures and methods disclosed herein will be readily
recognized as viable alternatives that may be employed without
departing from the principles of the claimed invention.
Method Overview
[0018] Embodiments of the invention perform various map database
augmentation and correction techniques to derive additional
information not currently within the map database. Such techniques
conform to the general pattern set forth in FIG. 1. At step 105 of
FIG. 1, roadway information is obtained. In one embodiment, such
information is obtained by receipt of vehicle readings provided,
for example, by conventional satellite-based GPS systems, and
include location (e.g. latitude and longitude) and velocity (e.g.
speed and heading) information for the vehicle to which they
correspond. As an alternative or additional step, if the map
database already includes pertinent road characteristic information
(e.g., classification of roadways as local as opposed to through
highways, speed limits, historical traffic volumes, number of
travel lanes) for roadway segments, such information for roadway
segments forming the intersection are fetched.
[0019] At step 110, the information thus obtained is analyzed to
determine whether it is reasonable to infer the presence of a
traffic control, for example a stop sign. To illustrate, if in step
105 it is determined that an east-west traffic segment has vehicles
traveling at 55 mph (whether determined by a database including the
speed limit for that segment or as observed using GPS readings from
actual vehicles), and it is also determined in the same manner that
a segment of an intersecting north-south road has vehicles
traveling at 30 mph, it is reasonable to infer the presence of stop
signs at the north-south road.
[0020] In many applications, it may not matter that the inference
of a stop sign is accurate. There may be a yield sign, a blinking
red or yellow light, or a full tri-color traffic light at the
intersection. For many applications, however, all that is important
is to recognize that traffic on, say, the east-west roadway will
likely not be slowed as much at the intersection as traffic on the
north-south roadway. Such inferences can be useful in situations
that involve estimated travel times for trip planning, for
computing routes that minimize delays caused by such traffic
controls, and the like. The amount of time spent at one such
traffic control may not be significant, but the accumulation of
such delays on a route that traverses 100 such intersections can
have a significant negative impact on the desirability or
optimality of this route. Another case where the inference of a
stop sign is useful, even though such an inference may be
incorrect, is to bias against routes that cut through residential
neighborhoods in order to avoid traffic jams or traffic signals. In
particular, inferred stop signs along the residential roads are
used to impede traffic flow through the residential
neighborhoods.
[0021] Finally, at step 115 the additional inferred information is
added to the database. For example, the database is updated to
reflect the inference that a pair of stop signs are controlling the
north-south road of the intersection. Some commercial road map
databases have existing fields that can be directly populated with
information such as the location and nature of a traffic control
device, such as a stop sign or traffic signal, and such information
is simply entered in the required manner. Other databases may not
have such a provision already available, and for such databases an
ancillary structure is created to allow for entry of such inferred
information. For instance, a new field may be created in the
database that associates a traffic control device with a particular
location and direction of travel. In still other embodiments, a
database is "augmented," "updated," or "modified" by creating an
entirely new instance of the database or, in some embodiments,
creating an entirely new type of database (e.g., as may be best
suited for the nature of information now to be included). Thus,
terms such as "updating" as used herein are to be interpreted
broadly to include any such manner of including such new
information in a database, as may be evident to those skilled in
the art.
System Architecture
[0022] FIG. 2 is a high-level block diagram illustrating a
computing device 200 for modifying map databases according to the
general technique set forth in FIG. 1. In one embodiment, user
device 200 is a general purpose computer programmed and configured
to provide the operations described herein. Processor 202 is
conventionally coupled to memory 206 and bus 204. Also coupled to
the bus 204 are memory 206, storage device 208, and data reception
unit 210. The data constituting the map database is contained in
storage device 208 and loaded into memory 206. The general
structure of a map database is well-known to those of skill in the
art, and conventionally involves storing a series of data objects
representing the series of road segments that describes the road,
including the spatial extent of the road segment and information
associated with the segment, such as speed limit.
[0023] In a typical embodiment, processor 202 is any general or
specific purpose processor such as an INTEL 386 compatible central
processing unit (CPU). Storage device 208 is any device capable of
persistently storing large amounts of data as required by the map
database, such as a hard drive or a high-capacity memory card.
Memory 206 holds instructions and data used by the processor 202.
The data reception unit 210 receives road characteristic
information, such as whether a road is classified as a local
residential street or a divided highway, from an external source
(not shown, e.g., a municipality's server site via the Internet).
Thus, data reception unit 210 can also be considered an input
subsystem providing roadway characteristics. The instructions
stored in the memory 206 and executed by the processor 202 allow
the derivation of additional map information based upon the vehicle
readings and the subsequent storing of the additional information
within the map database for later use by a navigation or other
program. Thus, processor 202 and memory 206 operating together can
also be considered an information inference module.
[0024] One of skill in the art would recognize that the above
described system is merely for purposes of example, and that many
other configurations for implementing the invention are equally
possible. For example, the above-disclosed user device 200 of FIG.
2 is implemented in one embodiment as a fixed computer (e.g., a
blade-type server accessed via a client computer with a web-based
user interface and a shared map database that is globally
accessible) and in another embodiment as a user device 200 that is
located within a vehicle, so that the map database is local. In one
embodiment, a separate computer hosts and provides a global version
of the map database, while user device 200 retains a local copy
thereof.
Database Updating Operations
[0025] The various map database augmentation and correction
techniques performed by embodiments of the invention as set forth
in FIG. 1 are now described in more detail below. As previously
discussed, one such approach applies the information, such as
vehicle speed, provided by a user device to existing information
stored in the map database, deriving additional information and
updating the database therewith.
[0026] In some environments, such as described in co-pending
commonly owned U.S. patent application Ser. No. 11/851,953,
published Mar. 12, 2009 as US 2009-0070031 (the contents of which
is hereby incorporated by reference as if fully set forth herein),
the presence or absence of traffic control devices such as stop
signs or traffic signals is detected by observing the speed of a
vehicle arriving at an intersection, and the nature/duration of
delay of the vehicle at an intersection (e.g., a consistent delay
of a few seconds suggests a stop sign, while a green/yellow/red
traffic light is suggested by vehicles sometimes being delayed by a
significant amount and sometimes not being delayed at all). Data
from vehicles may be too sparse in some circumstances to determine
whether vehicle stops occur frequently enough at an intersection to
warrant an inference of a stop sign. However, there may be
sufficient data indicating that traffic in the area regularly
travels at high speed on an east-west road and a significantly
lower speed on an intersecting north-south road. Alternatively, a
map database may be available that includes entries indicating a
significantly higher posted speed limit on the east-west road than
on the intersecting north-south road. Another usable parameter is
volume of traffic. The intersection of one roadway having
historically high traffic volumes with another, low-volume roadway
suggests there may be a traffic control on the low-volume roadway.
Still further, there may be information stored in a database as to
a classification for a roadway, such as "residential", "local",
"through road", "business route" or "federal highway", and
significant classification differences between two intersecting
roadways will in some embodiments support an inference of whether a
traffic control is present. While such information may not be
sufficient to predict with certainty the presence of any particular
traffic control device, for an application not requiring absolute
accuracy it may be sufficient to recognize a reasonable likelihood
that such a traffic control device is present.
[0027] In a related application, consider a map database that
includes stop sign information but does not currently indicate that
there are any stop signs at a particular intersection. If a
shopping center is built nearby, that may increase traffic flow
sufficiently that the municipality decides to put in a pair of stop
signs on one of the two roads forming the intersection. Review of
traffic volume data over time as described herein may lead to an
inference that a stop sign or traffic light has been added,
warranting a visual inspection of the intersection to confirm that
this is true. If such a stop sign has been added, then correction
of the old database information is appropriate, and can either be
done manually after the visual inspection or automatically in a
provisional manner (subject to verification by later visual
inspection).
[0028] Referring now to FIG. 3, there is illustrated an
intersection 300 between a large east-west roadway 310 and a
smaller north-south roadway 320. A commercial map database may
represent the larger road 310 differently than the smaller road
320, for instance indicating that the larger road is a four-lane
highway while the smaller road is only two lanes wide (or possibly
less). Assuming that the map database also indicates that the
intersection 300 is an at-grade intersection, as opposed to being
an intersection involving a bridge or other overpass or tunnel, the
difference in size of the roadways alone may be sufficient to infer
that the municipality or other controlling roadway authority has
installed stop signs 321 and 322 to control traffic on the
north-south roadway.
[0029] As a slight variation, instead of two intersecting
automobile roads, if a roadway intersects a railroad track at
grade, that almost certainly indicates a practical need for certain
types of vehicles (e.g., school buses, commercial vehicles) to stop
before crossing the railroad track. Therefore, for commercial route
planning purposes and the like, the addition of a virtual traffic
control (the mandatory stop at a railroad track for such vehicles)
to a map database allows more accurate navigational services such
as travel time planning.
[0030] The nature of each roadway is often usable as a factor in
how best to infer the type of traffic control. Where a small
country road intersects a large U.S. highway at grade level, it is
highly likely that there will be stop signs for the small road but
not for the U.S. highway. The presence of a divided highway (i.e.,
a boulevard or other roadway with a median strip separating travel
lanes) further increases the likelihood of such a traffic control
on an intersecting smaller roadway. Where a smaller road meets a
larger road with an arc-shaped segment rather than at a right
angle, there is an increased likelihood that a yield sign rather
than a stop sign is controlling traffic from the smaller
roadway.
[0031] Using the example illustrated in FIG. 3, a pseudo-code
representation of processing to infer presence of a stop sign in
one embodiment is:
[0032] Process Road 310: [0033] a. Augment Counter310 by number of
lanes [0034] b. Augment Counter310 if roadway is divided [0035] c.
Augment Counter310 by determined speed in mph/10 [0036] d. Augment
Counter310 if historical traffic volume>20% over average for
that type of road
[0037] Process Road 320: [0038] a. Augment Counter320 by number of
lanes [0039] b. Augment Counter320 if roadway is divided [0040] c.
Augment Counter320 by determined speed in mph/10 [0041] d. Augment
Counter320 if historical traffic volume>20% over average for
that type of road
[0042] If Counter310-Counter320>3, then infer stop sign on Road
320
[0043] If Counter320-Counter310>3, then infer stop sign on Road
310
[0044] As noted above, the determined speed for each roadway is
obtained either by observation of readings from GPS devices in
vehicles over time, or by reference to speed limit data (e.g., from
an existing database).
[0045] In many instances, each "arm" of an intersection is
considered separately, such that road 310 is processed separately
for its western arm ("310W") and eastern arm ("310E") and road 320
is likewise broken up into arms "320N" and "320S". This allows more
detailed processing that is expected, in various environments, to
be more accurate in inferring the presence of traffic controls. In
one embodiment, processing in this manner is implemented by
considering "local" roads to be those classified as residential or
having speed limits of 25 mph or less, while "nonlocal" roads are
those classified as "collectors" or having classifications higher
than "residential". Then, if a map database does not already
indicate that an intersection is signalized, processing is
implemented in one embodiment as:
[0046] Case: Intersection has both local and nonlocal arms [0047]
a. If there is only one incoming nonlocal arm, then [0048] i. If
there is a local arm which is a continuation of the non-local arm
(same road name or no turn from the non-local arm), then infer stop
signs are present on all other local arms [0049] ii. Otherwise,
infer stop signs on all arms. [0050] b. If there is more than one
incoming non-local arm, then infer stop signs on all local arms
[0051] i. If there is only one local arm and another non-local arm
that is a continuation of the local one, infer stop sign on the
non-local continuation arm as well.
[0052] Case: T-intersection involving non-local arms only [0053] a.
If the two "thru road" arms (i.e., the two arms that are collinear)
have a speed limit equal or higher than the "side" arm (i.e, the
arm that is orthogonal to the thru road arms), infer stop sign on
the side arm.
[0054] Case: Four-way intersection involving non-local roads only
[0055] a. If one road has a speed limit 10 mph or lower than the
other, infer stop signs on the lower speed limit road only;
otherwise infer stop signs on all arms.
[0056] Various other roadway and traffic control characteristics
can be inferred in a similar manner. Consider traffic light
characteristics, for example. Many traffic lights are synchronized
along a roadway and are coordinated with one another such that
vehicles traveling at a specified speed will be able to go through
many intersections without encountering a red signal. In some
implementations, the specified speed varies based on factors such
as traffic congestion levels. There may be no database record
indicating that certain lights are synchronized or what the
synchronization scheme is. Likewise, certain intersections have
phases of operation that vary based on congestion or time of day. A
green left turn signal may appear before a general green signal,
during the general green or after. Controller timing parameters may
be programmed by a municipality based on any number of factors. It
is not typical for municipalities to provide this detailed
information about phasing or timing patters of traffic lights in a
form readily usable by map databases. However, if the actual (i.e.,
real time) state information from each of the lights is available
from the municipality, as is now often the case, the phasing and
lighting patterns for each light and each intersection in general
can be derived from historical analysis of the concurrent states of
various lights, and in some instances comparison with other factors
such as time of day, congestion levels and the like.
[0057] In one embodiment, phasing of various traffic signals is
determined by comparison of real time state information among sets
of adjacent traffic signals. This is particularly straightforward
in the case of one-way streets.
[0058] In another embodiment, information from vehicles equipped
with GPS and communications devices serves as a proxy for such
real-time information about phasing. In some environments, sensor
information (e.g., from inductive loops embedded in roadways) is
available from municipalities that can likewise be used to track
movement of individual vehicles over time and thus provide a basis
for deriving traffic signal phasing information. For example,
vehicles routinely "bunch" at red lights and the size of a
particular bunch of vehicles can be used to track those vehicles as
a group to determine whether they stop only rarely on a roadway
with many signaled intersections (suggesting synchronized traffic
lights) or stop fairly frequently and in a somewhat random temporal
pattern (suggesting that the segment of roadway does not enjoy
synchronized traffic lights).
[0059] In still another embodiment, some municipalities provide
traffic phase mappings or related information (e.g., so-called
"ring diagrams") that likewise can be used to infer map database
information. For example, a municipality may mark an intersection
as subject to a generalized phase, such as "Phase 7--Pedestrian
Fully Protected". In this instance, inferences can be made that at
least during certain time periods, stopping times will be increased
for vehicles because they will be subject not only to red lights to
allow orthogonally-directed traffic to pass, but also red lights to
allow pedestrians to pass. Similarly, published information noting
signaling configuration for "inbound commute" suggests potential
use of center lane or breakdown lane restrictions that provide an
extra lane in the inbound direction or synchronized lights favoring
inbound traffic. All such information is available in various
embodiments to be used as factors for derivation of map database
information.
[0060] Those skilled in the art will readily recognize other
algorithms that may be employed in other embodiments or
environments to obtain reasonable map database inferences, for
instance where traffic controls such as stop signs are likely to be
located.
[0061] Thus, embodiments of the invention allow the capture of
numerous additional types of information not previously reflected
within the map database, leading to greater functionality and
greater accuracy for the increasing number of map applications that
rely on such information.
[0062] As used herein any reference to "one embodiment" or "an
embodiment" means that a particular element, feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment. The appearances of the phrase
"in one embodiment" in various places in the specification are not
necessarily all referring to the same embodiment.
[0063] As used herein, the terms "comprises," "comprising,"
"includes," "including," "has," "having" or any other variation
thereof, are intended to cover a non-exclusive inclusion. For
example, a process, method, article, or apparatus that comprises a
list of elements is not necessarily limited to only those elements
but may include other elements not expressly listed or inherent to
such process, method, article, or apparatus. Further, unless
expressly stated to the contrary, "or" refers to an inclusive or
and not to an exclusive or. For example, a condition A or B is
satisfied by any one of the following: A is true (or present) and B
is false (or not present), A is false (or not present) and B is
true (or present), and both A and B are true (or present).
[0064] In addition, the words "a" or "an" are employed to describe
elements and components of the invention. This is done merely for
convenience and to give a general sense of the invention. This
description should be read to include one or at least one and the
singular also includes the plural unless it is obvious that it is
meant otherwise.
[0065] Certain aspects of the present invention include process
steps and instructions described herein in the form of a method. It
should be noted that the process steps and instructions of the
present invention could be embodied in software, firmware or
hardware.
[0066] The computer program for deriving additional information is
preferably persistently stored in a computer readable storage
medium, such as, but is not limited to, any type of disk including
floppy disks, optical disks, CD-ROMs, magnetic-optical disks,
read-only memories (ROMs), random access memories (RAMs), EPROMs,
EEPROMs, magnetic or optical cards, application specific integrated
circuits (ASICs), or any type of media suitable for storing
electronic instructions, and each coupled to a computer system
bus.
[0067] Upon reading this disclosure, those of skill in the art will
appreciate still additional alternative structural and functional
designs for a system and a process for automated updating of a map
database through the disclosed principles herein. Thus, while
particular embodiments and applications have been illustrated and
described, it is to be understood that the present invention is not
limited to the precise construction and components disclosed herein
and that various modifications, changes and variations which will
be apparent to those skilled in the art may be made in the
arrangement, operation and details of the method and apparatus of
the present invention disclosed herein without departing from the
spirit and scope of the invention as defined in the appended
claims.
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