U.S. patent application number 09/839363 was filed with the patent office on 2001-11-15 for navigation device.
Invention is credited to Ishida, Akira, Sakamoto, Kiyomi, Ueyama, Yoshiki.
Application Number | 20010040505 09/839363 |
Document ID | / |
Family ID | 18633133 |
Filed Date | 2001-11-15 |
United States Patent
Application |
20010040505 |
Kind Code |
A1 |
Ishida, Akira ; et
al. |
November 15, 2001 |
Navigation device
Abstract
In a navigation device assisting a driver of a vehicle to drive
safely by presenting accurate information at the right time what is
going on around his/her vehicle, an obstacle detection part detects
any obstacle with the help of external information monitored by an
external monitor part. By utilizing the vehicle's current position
detected by an input part and a position detection part, and map
data stored in a map data storage part, a route selection part
searches for a route to a destination. Based on thus found route,
current position, map data, and the external information from the
obstacle detection part, a guiding part performs route guidance to
the destination. A map data arranging part refers to the map data,
information from the obstacle detection part and the input part,
and object model display information from the object model display
information storage part, and arranges any applicable object model
onto a map data space. A display accordingly displays guidance
information together with the resulting map image.
Inventors: |
Ishida, Akira; (Sakai,
JP) ; Ueyama, Yoshiki; (Sakai, JP) ; Sakamoto,
Kiyomi; (Ikoma, JP) |
Correspondence
Address: |
WENDEROTH, LIND & PONACK, L.L.P.
2033 K STREET N. W.
SUITE 800
WASHINGTON
DC
20006-1021
US
|
Family ID: |
18633133 |
Appl. No.: |
09/839363 |
Filed: |
April 23, 2001 |
Current U.S.
Class: |
340/435 ;
340/436; 340/995.2; 701/301; 701/436 |
Current CPC
Class: |
G01C 21/3697
20130101 |
Class at
Publication: |
340/435 ;
340/436; 340/995; 701/211; 701/301 |
International
Class: |
B60Q 001/00 |
Foreign Application Data
Date |
Code |
Application Number |
Apr 24, 2000 |
JP |
2000-122685 |
Claims
What is claimed is:
1. A navigation device of a vehicle-mounted type for detecting
circumstances around a vehicle, and if considers warning a user is
appropriate, arranging an applicable object model for display on a
map image, and making a guidance to a destination, said device
comprising: an input part for receiving the user's instruction; a
position detection part for detecting a current position of the
vehicle; a map data storage part for previously storing map data;
an object model display information storage part for previously
storing object model display information for displaying said object
model on said map image; a route selection part for selecting a
route to the destination based on said instruction provided by said
input part, said current position detected by said position
detection part, and said map data stored in said map data storage
part; an external monitor part for monitoring the circumstances
around the vehicle, and outputting resulting monitor information;
an obstacle detection part for detecting an obstacle observed
outside of the vehicle based on said monitor information provided
by said external monitor part, and outputting resulting external
information including position information of said obstacle; a map
data arranging part for creating said object model, if decided that
warning the user is appropriate, based on drive assistant
information including the position information as in the external
information and the object model display information for said
object model, and arranging the object model on said map image; a
guiding part for determining whether said obstacle requires the
user's attention based on said external information provided by
said obstacle detection part, and if requires, generating said
drive assistant information, and generating guidance information
including resulting map image outputted from said map data
arranging part in response to said route selected by said route
selection part, said current position detected by said position
detection part, and said map data provided by said map data storage
part; and a display part for displaying said guidance information
generated by said guiding part.
2. The navigation device according to claim 1, wherein said
external monitor part includes an image capture device for
capturing an image covering around the vehicle, and said obstacle
detection part detects, based on said monitor information including
said image received from said external monitor part, said obstacle
observed around the vehicle through the image.
3. The navigation device according to claim 2, wherein said
obstacle detection part determines a type of said obstacle, and
outputting the external information including type information of
said obstacle, and said guiding part determines whether said
obstacle requires the user's attention based on said type
information.
4. The navigation device according to claim 2, wherein said
obstacle detection part detects a predetermined sign attached to
said obstacle, and outputting the external information including
sign information of said obstacle, and said guiding part determines
whether said obstacle requires the user's attention based on said
sign information.
5. The navigation device according to claim 2, wherein said
obstacle detection part detects which side of blinkers is flashing
on and off, and outputting the external information including
directional information of said obstacle, and said guiding part
determines whether said obstacle requires the user's attention
based on said directional information.
6. The navigation device according to claim 1, wherein said guiding
part determines whether said vehicle is in a with-care state by
estimating any situational change possible for either the vehicle
or said object or both, and based on the with-care state,
determines whether said obstacle requires the user's attention.
7. The navigation device according to claim 6, wherein said guiding
part estimates said situational change by analyzing said route
selected by said route selection part, and determines whether said
vehicle is in said with-care state.
8. The navigation device according to claim 1, wherein said guiding
part generates said drive assistant information including a threat
attribute for said obstacle requiring the user's attention, and
said map data arranging part creates an object model corresponding
to said threat attribute based on said drive assistant information
and the object model display information for said object model
provided by said object model display information storage part.
9. The navigation device according to claim 1, wherein said map
data arranging part creates a vehicle object model corresponding to
said vehicle and a nearby vehicle object model corresponding to
said object.
10. The navigation device according to claim 9, wherein said map
data arranging part selects a display scale for said map image so
that said vehicle object model and said nearby vehicle object model
are displayed on said display part with a predetermined space
therebetween in consideration of a positional relationship
therebetween.
11. The navigation device according to claim 1, wherein said map
data arranging part comprises: an object model creation part for
creating said object model based on said drive assistant
information and the object model display information for the object
model provided by said object model display information storage
part; and a data arranging part for arranging said object model on
said map image.
12. The navigation device according to claim 11, wherein said map
data arranging part further comprises a 3D map generation part for
generating a 3D map based on 2D map data provided by said map data
storage part, and said data arranging part arranges said object
model onto the 3D map generated by said 3D map generation part.
13. The navigation device according to claim 11, wherein said map
data arranging part further comprises a 2D/3D coordinate
transformation part for transforming the object model, which is 2D,
created by said object model creation part to a 3D object model,
and said data arranging part arranges the 3D object model
transformed by said 2D/3D coordinate transformation part onto said
map image.
14. A navigation method for detecting circumstances around a
vehicle, and if considers warning a user is appropriate, arranging
an applicable object model for display on a map image, and making a
guidance to a destination, said method comprising: a receiving step
of receiving the user's instruction; a position detecting step of
detecting a current position of the vehicle; an external monitoring
step of monitoring the circumstances around the vehicle, and
outputting resulting monitor information; an obstacle detecting
step of detecting an obstacle observed outside of the vehicle based
on said monitor information, and generating external information
including position information of said obstacle; a route selecting
step of selecting a route to the destination based on said
instruction provided in said inputting step, said current position
detected in said position detecting step, and map data previously
provided; a map data arranging step of creating said object model,
if decided that warning the user is appropriate, according to drive
assistant information generated based on said external information
and the object model display information for the object model, and
arranging the object model on said map image; a guiding step of
generating guidance information including resulting map image
outputted in said map data arranging step in response to said route
selected in said route selecting step, said current position
detected in said position detecting step, and said map data; and a
displaying step of displaying said guidance information generated
in said guiding step.
15. The navigation method according to claim 14, wherein in said
external monitoring step, an image covering around the vehicle is
captured, and in said obstacle detecting step, based on said
monitor information including said image captured in said external
monitoring step, said obstacle observed around the vehicle is
detected through the image thereof.
16. The navigation method according to claim 14, wherein in said
guiding step, whether said vehicle is in a with-care state is
determined by estimating any situational change possible for either
the vehicle or said object or both, and based on the with-care
state, whether the obstacle requires the user's attention is
determined.
17. The navigation method according to claim 14, wherein in said
guiding step, said drive assistant information including a threat
attribute for said obstacle requiring the user's attention is
generated, and in said map data arranging step, an object model
corresponding to said threat attribute is created based on said
drive assistant information and said object model display
information for the object model.
18. The navigation method according to claim 14, wherein in said
map data arranging step, a vehicle object model corresponding to
said vehicle and a nearby vehicle object model corresponding to
said obstacle are created, and a display scale for said map image
is so selected that said vehicle object model and said nearby
vehicle object model are displayed with a predetermined space
therebetween in consideration of a positional relationship
therebetween.
19. The navigation method according to claim 14, wherein said map
data arranging step comprises: an object model creating step for
creating said object model based on said drive assistant
information and said object model display information; and a data
arranging step of arranging said object model on said map
image.
20. The navigation method according to claim 19, wherein said map
data arranging step further comprises a 3D map generating step of
generating a 3D map based on 2D map data, and in said data
arranging step, said object model is arranged on said map
image.
21. The navigation method according to claim 19, wherein said map
data arranging step further comprises a 2D/3D coordinate
transforming step of transforming the object model, which is 2D,
created in said object model creating step to a 3D object model,
and in said data arranging step, the 3D object model transformed in
said 2D/3D coordinate transforming step is arranged onto said map
image.
22. A computer readable recording medium having a program recorded
thereon to be run on a navigation device of a vehicle-mounted type
for detecting circumstances around a vehicle, and if considers
warning a user is appropriate, arranging an applicable object model
for display on a map image, and making a guidance to a destination,
said program comprising: a receiving step of receiving the user's
instruction; a position detecting step of detecting a current
position of the vehicle; an external monitoring step of monitoring
the circumstances around the vehicle, and outputting resulting
monitor information; an obstacle detecting step of detecting an
obstacle observed outside of the vehicle based on said monitor
information, and generating external information including position
information of said obstacle; a route selecting step of selecting a
route to the destination based on said instruction provided in said
inputting step, said current position detected in said position
detecting step, and map data previously provided; a map data
arranging step of creating said object model, if decided that
warning the user is appropriate, according to drive assistant
information generated based on said external information and the
object model display information for the object model, and
arranging the object model on said map image; a guiding step of
generating guidance information including resulting map image
outputted in said map data arranging step in response to said route
selected in said route selecting step, said current position
detected in said position detecting step, and said map data; and a
displaying step of displaying said guidance information generated
in said guiding step.
23. A program to be run on a navigation device of a vehicle-mounted
type for detecting circumstances around a vehicle, and if considers
warning a user is appropriate, arranging an applicable object model
for display on a map image, and making a guidance to a destination,
said program comprising: a receiving step of receiving the user's
instruction; a position detecting step of detecting a current
position of the vehicle; an external monitoring step of monitoring
the circumstances around the vehicle, and outputting resulting
monitor information; an obstacle detecting step of detecting an
obstacle observed outside of the vehicle based on said monitor
information, and generating external information including position
information of said obstacle; a route selecting step of selecting a
route to the destination based on said instruction provided in said
inputting step, said current position detected in said position
detecting step, and map data previously provided; a map data
arranging step of creating said object model, if decided that
warning the user is appropriate, according to drive assistant
information generated based on said external information and the
object model display information for the object model, and
arranging the object model on said map image; a guiding step of
generating guidance information including resulting map image
outputted in said map data arranging step in response to said route
selected in said route selecting step, said current position
detected in said position detecting step, and said map data; and a
displaying step of displaying said guidance information generated
in said guiding step.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention relates to navigation devices and,
more specifically, to a navigation device for assisting the driver
of a vehicle, in driving, by detecting and displaying him/her
information about what is going on around the vehicle.
[0003] 2. Description of the Background Art
[0004] There has been developed such system as monitoring around a
vehicle on the road, with a sensor, to see what is going on
therearound, and if collision with other vehicles is considered
highly possible, warning the driver. For example, disclosed in
Japanese Patent Laid-Open Publication No. 11-321494 (99-321494) is
such conventional technique as follows.
[0005] First of all, a video signal outputted from a camera is
subjected to image processing so as to detect if any vehicle is
approaching. If detected any, the driver of a vehicle is warned by
a beep. Also, as for the approaching vehicle, an image thereof is
square-marked and displayed on a display device. Accordingly, the
driver can spot on the display which vehicle is the one warned of
collision.
[0006] In the above conventional technique, however, the driver is
not provided much information when he/she is in danger, but offered
adequate information when no danger awaits him/her. Therefore, even
when the driver hears a warning beep, he/she may be annoyed as is
hardly knowing if any danger awaits him/her, and how dangerous it
actually is. Further, if the driver hears any route guidance while
driving, he/she may be distracted thereby and pay close attention
only to ahead but not to behind. In the conventional technique, no
consideration is given to such possibility.
SUMMARY OF THE INVENTION
[0007] Therefore, an object of the present invention is to provide
a navigation device for helping the driver of a vehicle drive
safely, without annoying the driver, by presenting him/her accurate
information at the right time what is going on around his/her
vehicle.
[0008] The present invention has the following features to attain
the object above.
[0009] An aspect of the present invention is directed to a
navigation device of a vehicle-mounted type for detecting the
circumstances around a vehicle, and if considers warning a user is
appropriate, arranging an applicable object model for display on a
map image, and making a guidance to a destination. In the present
navigation device, an external monitor part monitors the
circumstances around the vehicle, and outputs resulting monitor
information. Based on the monitor information, an obstacle
detection part detects any obstacle observed outside of the
vehicle, and outputs external information including position
information of the obstacle. Based on the external information, a
guiding part determines if the obstacle requires the user's
attention, and if requires, generates drive assistant information
including the position information of the obstacle as in the
external information. Based on thus generated drive assistant
information and object model display information for the obstacle,
a map data arranging part creates an object model for arrangement
on a map image. Further, the guiding part generates guidance
information including the resulting map image outputted from a map
data arranging part in response to the route selected by a route
selection part, the current position detected by a position
detection part, and map data from a map data storage part. Thus
generated guidance information is displayed on a display part for
the user.
[0010] These and other objects, features, aspects and advantages of
the present invention will become more apparent from the following
detailed description of the present invention when taken in
conjunction with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 is a block diagram showing the structure of a
navigation device according to an embodiment of the present
invention;
[0012] FIG. 2 is a diagram showing the structure of the navigation
device of FIG. 1, which is realized in a general computer
system;
[0013] FIG. 3 is a flowchart showing a basic flow of processing in
the present navigation device;
[0014] FIG. 4 is a flowchart showing the detailed process of
subroutine step S54;
[0015] FIG. 5 is a flowchart showing a basic flow of processing for
generating external information by an obstacle detection part
8;
[0016] FIG. 6 is a flowchart showing the detailed process of
subroutine step S120;
[0017] FIG. 7 is a flowchart showing the detailed process of
subroutine step S130;
[0018] FIG. 8 is a flowchart showing the detailed process of
subroutine step S140;
[0019] FIG. 9 is a table schematically showing the interrelation
between a with-care state and a with-care vehicle;
[0020] FIG. 10 is a schematic diagram exemplarily showing what
drive assistant information carries therein;
[0021] FIG. 11 is a flowchart showing the detailed process of
subroutine step S55;
[0022] FIG. 12 is a block diagram showing the detailed structure of
a map data arranging part 4, a resulting map image generated
thereby is of 2D landscape;
[0023] FIG. 13 is a schematic diagram showing an exemplary map
image displayed on a display 5;
[0024] FIG. 14 is a schematic diagram showing another example of
map image displayed on the display 5;
[0025] FIG. 15 is a schematic diagram showing still another example
of map image displayed on the display 5;
[0026] FIG. 16 is a block diagram showing the detailed structure of
the map data arranging part 4, a resulting map image generated
thereby is of a bird's eye view;
[0027] FIG. 17 is a diagram demonstrating a technique for creating
a bird's eye view by subjecting 2D map data to perspective
transformation;
[0028] FIG. 18 shows an exemplary map image of a bird's eye view
displayed on the display 5;
[0029] FIG. 19 is a block diagram showing the detailed structure of
the map data arranging part 4, a resulting image data generated
thereby is of a 3D landscape different from a bird's eye view;
[0030] FIG. 20 is a block diagram showing the detailed structure of
a 3D map data generation part 147;
[0031] FIG. 21 is a diagram exemplarily showing a case where
displayed on the 3D landscape are 3D object models, which indicate
a with-care vehicle and its direction being about to make a
rightward lane change;
[0032] FIG. 22 is a block diagram showing the detailed structure of
the map data arranging part 4, which receives 2D data from the
object model display information storage part 6 and 3D map data
from the map data storage part 3, and generates a map image of 3D
landscape;
[0033] FIG. 23 is a diagram exemplarily showing several image files
prepared as 2D shape information in object model display
information; and
[0034] FIG. 24 shows an exemplary map image of 3D landscape
generated by the map data arranging part 4 of FIG. 22.
DESCRIPTION OF THE PREFERRED EMBODIMENT
[0035] FIG. 1 is a block diagram showing the structure of a
navigation device according to an embodiment of the present
invention. In FIG. 1, the navigation device includes an input
device 2, a map data storage part 3, a map data arranging part 4, a
display 5, an object model display information storage part 6, an
external monitor part 7, an obstacle detection part 8, a position
detection part 9, a route selection part 10, and a guiding part
11.
[0036] The input part 2 is driver-operable, and used for functional
selection (e.g., processing item change, map switching,
hierarchical level change), point settings, and the like. Outputted
from the input part 2 is instruction information, which is
forwarded to the route selection part 10.
[0037] The position detection part 9 is composed of a GPS, radio
beacon receiver, vehicle-speed sensor, angular velocity sensor,
absolute azimuth sensor, or the like, and detects the vehicle's
current position. Outputted from the position detection part 9 is
information about the vehicle's current position, which is
forwarded to both the route selection part 10 and the guiding part
11.
[0038] The external monitor part 7 may be a CCD camera, laser
radar, ultrasound sensor, or the like, and monitors around the
vehicle to know, typically, whether any obstacle is observed or how
vehicles behind are behaving. The external monitor part 7 then
outputs resulting monitor information to the obstacle detection
part 8. Here, the external monitor part 7 may communicate with
other vehicles, a traffic control center, and the like, to monitor
around its own vehicle. To realize such monitoring, however, system
establishment is required and thus the cost is increased.
Accordingly, the external monitor part 7 is preferably structured
by a sensor, for example. An image capture device such as camera is
also a preferable possibility for the external monitor part 7 as is
competent to human eyes at perceiving things.
[0039] Based on the monitor information provided by the external
monitor part 7, the obstacle detection part 8 analyzes an obstacle,
and what type, position, speed, and the like, and outputs external
information, which will be described later. Here, such obstacle
includes anything requiring the driver's close attention or
disturbing him/her to drive. As examples, anything lying ahead on
the road, any vehicle approaching from behind, and any vehicle
recklessly behaving are all regarded as an obstacle.
[0040] The map data storage part 3 is composed of an optical disk
(e.g., CD, DVD), hard disk, semiconductor memory card (e.g., SD
card), or the like. The map data storage part 3 in advance stores
2D or 3D map data indicating a specific area by geographical
features, and in the area, intersections and road connections are
defined by coordinates, shape, attribute, regulation information,
and the like. The map data stored in the map data storage 3 is read
as appropriate, for usage, by the map data arranging part 4, the
route selection part 10, and the guiding part 11.
[0041] The route selection part 10 reads the map data from the map
data storage part 3 only for a required area according to the
instruction information provided by the input part 2. The route
selection part 10 then determines a starting point and a
destination based on point information included in the instruction
information, and the information about the vehicle's current
position provided by the position detection part 9. Thereafter, the
route selection part 10 searches for a route minimum in cost
between the starting point and the destination. A result obtained
thereby is outputted to the guiding part 11 as route
information.
[0042] Based on all of the route information from the route
selection part 10, the information about the vehicle's current
position from the position detection part 9, the map data from the
map data storage part 3, and the external information from the
obstacle detection part 8, the guiding part 11 generates guidance
information for guiding the vehicle to the destination. This
guidance information is provided to the display 5 for display
thereon.
[0043] The map data arranging part 4 arranges object models in a
map space. This arrangement is done based all on the map data
stored in the map data storage part 3, the information provided by
the obstacle detection part 8, and the information stored in the
object model display information storage part 6.
[0044] The display 5 is composed of a display device (e.g., liquid
crystal display, CRT display), speaker, and the like, and displays
the guidance information together with a resulting map image
provided by the map data arranging part 4. Alternatively, the
display 5 may output sounds for guidance with or without performing
display.
[0045] As is the map data storage part 3, the object model display
information storage part 6 is also composed of an optical disk,
hard disk, or the like. Stored therein is information about a
technique for presenting 2D or 3D object models on a map image
according to the information provided by the obstacle detection
part 8 or the input part 2. About the technique and the details of
the information are left for later description.
[0046] Such structured navigation device of FIG. 1 can be realized
in a general computer system. The structure of a navigation device
realized as such is shown in FIG. 2.
[0047] In FIG. 2, the navigation device includes a CPU 342, ROM
343, RAM 344, an output part 345, an input part 346, a position
detection part 349, and an external monitor part 348, all of which
are interconnected by a common bus or an external bus. Here,
presumably, the ROM 343 and the RAM 344 both possibly include a
storage device including an external storage medium.
[0048] In FIG. 2, the CPU 342 operates in accordance with programs
stored in either or both of the ROM 343 and the RAM 344. All of the
map data arranging part 4, the obstacle detection part 8, the route
selection part 10, and the guiding part 11 are functionally
realized by each corresponding program. In such case, a recording
medium typically storing such programs is implemented in the
navigation device. The program may be the one transmitted over a
communications circuit.
[0049] The ROM 343 typically includes the map data storage part 3
of FIG. 1, or the RAM 344 may do so entirely or partially.
Similarly, the RAM 344 typically includes the object model display
information storage part 6, or the ROM 343 may do so.
[0050] FIG. 3 is a flowchart showing a basic flow of processing in
the present navigation device. In step S51 of FIG. 3, with
driver-designated destination and map region provided by the input
part 2, and with a vehicle position provided by the position
detection part 9, the route selection part 10 accordingly performs
route search. A result obtained thereby is outputted to the guiding
part 11.
[0051] Next, in step S52, the guiding part 11 requests the map data
arranging part 4 for map data arrangement to display a map which
covers an area corresponding to the vehicle position detected by
the position detection part 9. In step S53, the map data arranging
part 4 reads map data from the map data storage part 3.
[0052] In subroutine step S54, the guiding part 11 reads external
information from the obstacle detection part 8 to see the
circumstances around the vehicle, for example, whether the vehicle
is about to make a right/left turn. Based on the external
information and the route search result, the guiding part 11
determines if the vehicle needs any drive assistant information,
and if needed, what kind of information. The details for this
subroutine step S54 are left for later description.
[0053] In subroutine step S55, according to the drive assistant
information and the information stored in the object model display
information storage part 6, the map data arranging part 4 creates a
2D or 3D object model for arrangement on the map data read from the
map data storage part 3. The details for this subroutine step S55
are also left for later description.
[0054] In step S56, the guidance part 11 has the display 5 display
the map image for guidance information or the map image wherein
object models are arranged. Herein, the guidance information is not
necessarily displayed on the map image, and the guiding part 11 may
be functionally substituted by the map data arranging part 4 for
this operation.
[0055] Lastly, in step S57, the guiding part 11 keeps providing
guidance until the vehicle reaches its destination. Thus, the
procedure returns to step S52 to repeat the processing until the
guiding part 11 determines the vehicle having reached its
destination.
[0056] FIG. 4 is a flowchart showing the detailed process of
subroutine step S54 of FIG. 3. In step S541 of FIG. 4, the guiding
part 11 reads from the obstacle detection part 8 the external
information, which is generated as appropriate by the obstacle
detection part 8 based on the monitor information from the external
monitor part 7.
[0057] Described in detail now is the operation of the obstacle
detection part 8 for generating the external information. FIG. 5 is
a flowchart showing a basic flow of processing in the obstacle
detection part 8 for the purpose. Herein, presumably, the external
monitor part 7 is structured by an image capture device such as CCD
camera, for example, and captures image data
[0058] In step S110 of FIG. 5, the obstacle detection part 8
receives image data from the external monitor part 7. Here, the
image data is typically a still picture, but may be two still
pictures captured by two cameras placed with a predetermined
distance therebetween, or moving pictures for a predetermined time
period.
[0059] In subroutine step S120, from the received image data, the
obstacle detection part 8 detects any lane, which is presumably
defined by a white line. By referring to FIG. 6, the detailed
processing in this subroutine step S120 is now described.
[0060] In step S121 of FIG. 6, as for the received image data, the
obstacle detection part 8 detects a maximum luminance in a
predetermined region thereof. With reference to thus detected
maximum value, and in consideration of luminance distribution, the
obstacle detection part 8 sets a threshold value considered optimal
for detection of the white line.
[0061] In step S122, the obstacle detection part 8 searches the
image for any pixel exceeding the threshold value. This is done on
the basis of pixel line, which is drawn between two predetermined
pixels on the image data, for example, from a center pixel on the
far left column to that on the far right column. Any consecutive
pixels all exceeding the threshold value are regarded as a part of
white line. In such manner, the image data is thoroughly searched,
and white lines are appropriately extracted therefrom. Here, edge
extraction is also a possibility by using an edge extraction filter
such as SOBEL filter.
[0062] In step S123, for linear approximation, the obstacle
detection part 8 sets a processing region wherein thus extracted
white lines are observed. For the linear approximation, for
example, a HOUGH transform algorithm is used. As a result, the
white lines appear linear on the image data.
[0063] In step S124, the obstacle detection part 8 detects, as a
lane, a triangle region formed by any two adjacent white lines and
the bottom side of the image. Assume here that two or more lanes
are to be detected.
[0064] Next, in subroutine step S130 of FIG. 5, the obstacle
detection part 8 extracts any vehicle region from the image data
received from the external monitor part 7. Here, the vehicle region
is typically defined by a closed curve, which is considered a
vehicle's contour. Here, for easy understanding, a vehicle having
the present navigation device mounted thereon is referred to simply
as "vehicle", and others observed therearound are as collectively
"nearby vehicle". The vehicle region is assigned a unique vehicle
ID, thus even if plurally extracted, each vehicle region can be
uniquely identified thereby. This subroutine step S130 is described
in more detail below with reference to FIG. 7.
[0065] In step S131 of FIG. 7, with respect to each of the lanes
detected in step S124, the obstacle detection part 8 performs edge
detection, and extracts any region wherein the nearby vehicle is
observed. To be specific, first detected from the image are
typically horizontal and vertical edges, and around a rectangular
region defined thereby, tangent lines are drawn for extraction.
[0066] In step S132, the obstacle detection part 8 searches vehicle
sample model database (not shown) for a most-analogous vehicle
model for overlay onto thus extracted rectangular region. If found,
the obstacle detection part 8 overlays the most-analogous vehicle
model onto the extracted region in such manner as to coincide both
barycenters.
[0067] In step S133, the obstacle detection part 8 extracts the
contour of the most-analogous vehicle model, and thus extracted
region within the contour is the vehicle region.
[0068] In step S134, the obstacle detection part 8 assigns the
vehicle region a unique vehicle ID, which is utilized as a part of
the external information.
[0069] In step S140 of FIG. 5, based on the vehicle region on the
image, the obstacle detection part 8 determines where the nearby
vehicle is on which lane. Then, detected are relative distance,
relative velocity, and relative acceleration to the vehicle. Here,
with an active sensor such as laser radar, it is easy to measure
where the nearby vehicle is, but with a camera, it requires
additional processing varied in manners. In this example, two
cameras are used to capture object images, and the actual distance
to the object is calculated, under principle of triangular
measurement, by utilizing parallax between those two images. This
subroutine step S140 is described in more detail with reference to
FIG. 8.
[0070] In step S141 of FIG. 8, the obstacle detection part 8
detects on which lane the nearby vehicle currently is. This
detection is done based on the lanes detected in step S124.
[0071] In step S142, the obstacle detection part 8 first extracts
any feature from each of those two object images to know the
correspondence therebetween. Here, the feature is, for example, an
edge or a vertex of a polyhedron. Then, with thus extracted
features, correspondence points are searched for using epipolar
constraint. From this pair of correspondence points, a parallax d
is first measured, and then the distance D is calculated by the
following equation (1).
D=L*f/d (1)
[0072] where L denotes the distance between those two cameras, and
f denotes a focal distance.
[0073] In step S143, from the distance D calculated in step S142,
the obstacle detection part 8 calculates space coordinates on a
camera coordinate system for the correspondence points so as to
calculate the position of the nearby vehicle. The resulting
position is temporarily stored as a historic record typically with
its vehicle ID and the time of calculation.
[0074] In step S144, with reference to the historic record, the
obstacle detection part 8 calculates the speed and acceleration of
the nearby vehicle. Here, the guiding part 11 may alternatively
perform such calculation. Thus calculated nearby-vehicle's
position, speed, and acceleration are included in the external
information together with its corresponding vehicle ID.
[0075] Next, in step S150 of FIG. 5, as for the nearby vehicle, the
obstacle detection part 8 determines the vehicle type thereof by
taking the vehicle region into consideration. Typically, to
determine the vehicle type, the obstacle detection part 8 performs
matching, in shape and size, among the vehicle region and vehicle
sample model in database (not shown). If the distance to the nearby
vehicle can be approximately measured from the size of the vehicle
region, the processing in step S140 may be omitted. Thus determined
vehicle type is also included in the external information together
with its corresponding vehicle ID.
[0076] In step S160, the obstacle detection part 8 refers to the
vehicle region to see if the nearby vehicle carries any sign
calling for the driver's attention (hereinafter, referred to as
"with-care" sign). Exemplified for such with-care sign is a
"not-yet-skilled sign", which is obligatory for a driver who just
got his/her driver's license for a certain time period. The
with-care sign reminds the drivers to be attentive to the vehicle
carrying the same, and for easy recognition, each predetermined in
shape and color. Accordingly, the obstacle detection part 8 first
extracts, from the vehicle region, any part having the same color
as any existing with-care signs. Then, the extracted part is
compared in shape with templates which are of the existing
with-care signs previously provided, and then finds the one
uniquely corresponding to any specific with-care sign. Then, the
result obtained thereby is included in the external information
together with the applicable vehicle ID.
[0077] In step S170, the obstacle detection part 8 refers to the
vehicle region if the blinkers of the nearby vehicle is on, and if
so, which side of the blinkers is flashing on and off. Here, since
the blinker is also predetermined in color as are the with-care
signs, the processing in step S160 can be executed to make such
determination. Alternatively, executed may be processing of
extracting any flashing region from a plurality of images which
have been captured at predetermined time intervals. The result
obtained thereby is included in the external information together
with the applicable vehicle ID.
[0078] In step S180, the obstacle detection part 8 determines
whether or not the image is thoroughly detected for every vehicle
region. If not yet, the procedure returns to subroutine step S130,
otherwise, this is the end of the processing. Note that, the
processing of FIG. 5 is repeated at regular intervals to
continually monitor the circumstances around the vehicle.
[0079] After going through such processing, the external
information is generated for every vehicle ID and read into the
guiding part 11. This is the end of processing in step S541 of FIG.
4.
[0080] Next, in step S542, the guiding part 11 refers to the
external information to determine whether or not there is any
with-care vehicle around the vehicle. Here, any nearby vehicle is
regarded as a with-care vehicle if seems dangerous in consideration
of its vehicle type, speed, distance to the vehicle, driving
manner, and the like. As typical examples, with respect to the
vehicle, a with-care vehicle is any nearby vehicle (motorcycle
included) rapidly approaching, staying behind, putting its blinker
flashing on and off, carrying a with-care sign, and moving
meanderingly. Emergency vehicles are also included, for
example.
[0081] Such with-care vehicles are easily recognizable by utilizing
the external information. In detail, to recognize any nearby
vehicle rapidly approaching or staying behind, utilized are the
relative distance, relative velocity, and the relative acceleration
to the vehicle detected in step S140 of FIG. 5 with the help of a
predetermined equation and table. Similarly, any nearby vehicle
moving meanderingly is also easily recognized by first calculating
a variation of a motion vector thereof, and then detecting its
degree of swinging with respect to the heading direction. Here, as
described in the foregoing, the vehicle type is detectable in step
S150, the care-with sign in step S160, and the blinker in step
S170.
[0082] If determined no with-care vehicle is observed, the
procedure returns to the processing of FIG. 3. If determined any,
the procedure goes to step S543.
[0083] In step S543, in consideration of thus detected with-care
vehicle, the guiding part 11 decides whether or not the vehicle is
in with-care state. Here, any state is regarded as the with-care
state if the nearby vehicle is considered a threat to the vehicle.
This determination is made based on how the route ahead looks like,
whether the vehicle needs to make a right/left turn or decelerate,
and the like. If determined that the vehicle is not in the
with-care state, the procedure returns to the processing of FIG. 3.
If determined Yes, the procedure goes to step S544.
[0084] Here, exemplarily described here is the interrelation
between the with-care vehicle and the with-care state. FIG. 9 is a
schematic table showing such interrelation. In the table, values
"0" denote "basically no threat", and values "1" denote "threat".
Although this table is exemplified for countries where vehicles
drive on the right (e.g., Japan), but becomes applicable to
countries where vehicles drive on the left only by switching
between "right" and "left".
[0085] In FIG. 9, shown by the column of the table are attributes
relevant to the threat type of the with-care vehicle. To be
specific, the with-care vehicle is defined as approaching the
vehicle, its blinker is on, carrying any with-care sign, moving
meanderingly, and by vehicle type other than vehicle such as
motorcycle and emergency vehicle. If the with-care vehicle is
defined as approaching, the table further indicates from which lane
the with-care vehicle is approaching, specifically, from the right
lane, the left lane, or right behind the vehicle. Similarly, if the
with-care vehicle is defined as putting its blinker on, the table
further indicates which side of the blinkers is flashing on and
off.
[0086] Shown by the row of the table are various with-care states,
specifically, if the vehicle needs to move to a right/left lane,
make a right/left turn, or brake or decelerate, and if the route
ahead is narrowed or curved, and if so, in which side.
[0087] Here, for easy prediction if the route ahead is narrowed or
curved, the map data in the map data storage part 3 may be referred
to only for a certain range of the route selected by the route
selection part 10. As such, by knowing in advance what the route
ahead looks like, the vehicle can be ready for other nearby
vehicles' possible behaviors, for example, lane change and sharp
turn.
[0088] Further, for easy prediction if the vehicle is changing
lanes, making a right/left turn, braking, or decelerating, realtime
monitoring of the vehicle's current position, steering wheel,
accelerator, brake, and the like, will do. Similarly, realtime
monitoring of the vehicle's blinker helps predict to which lane the
vehicle moves next. Further, the route selected by the route
selection part 10 is analyzed to know the vehicle's possible
behavior.
[0089] FIG. 9 shows, for example, if there is any near by vehicle
approaching from right lane, collision is considered possible if
the vehicle moves to the right lane or makes a right turn.
Therefore, applicable boxes in the table all show "1". Similarly,
in the case that the route selected by the route selection part 10
is narrowed ahead and the right lane is ended, any nearby vehicle
approaching from right lane may aggressively move into the same
lane and thus collision is considered likely. Also in the case that
the route is curved to the right with a certain curvature and more,
any nearby vehicle driving fast on the right lane may slide
therearound into the same lane. Accordingly, applicable boxes in
the table all show "1".
[0090] When there is any nearby vehicle approaching from behind,
there seems no harm if the vehicle makes a right/left turn.
However, the driver usually decreases the vehicle's speed to make a
right/left turn. Therefore, depending on the vehicle's relative
position, relative velocity, and relative acceleration to the
nearby vehicle, collision is considered likely. Thus, applicable
boxes in the table show all "1". On the other hand, even if any
nearby vehicle is approaching on the same lane from behind when the
vehicle is stationary, the nearby vehicle is expected to stop and
usually do so. Therefore, such case is considered no threat, and
thus applicable boxes in the table all show "0".
[0091] Considered next is a motorcycle positioning behind the
vehicle or on the left lane. When the vehicle makes a left turn,
such motorcycle may be easily in the vehicle's blind spot, and thus
requires some attention. Also, if the driver of the vehicle opens
the left door without paying much attention, the door might hit the
motorcycle. Thus, applicable boxes in the table all show "1". Here,
alternatively, the driver's hand detected on either door of the
vehicle may be possibly considered a threat.
[0092] As for the emergency vehicle, the vehicle is expected to
give way thereto, and in the course, the emergency vehicle may
cause some harm to the vehicle. Thus, applicable boxes in the table
all show "1". Here, alternatively, regardless of with-care states,
the drive assistant information may be generated whenever the
emergency vehicle is detected.
[0093] Here, FIG. 9 is by way of example only, and any other
various with-care states, with-care vehicles, and combination
thereof are surely possible. For example, any nearby vehicle is
regarded as a with-care vehicle if changing lanes without putting
its blinker on, or continuously increasing and decreasing the
vehicle's speed. Also, the obstacle detection part 8 may
additionally recognize the nearby vehicle's plate and vehicle type,
and if the nearby vehicle is a luxury type, the driver of the
vehicle may be warned, and if is found as a stolen vehicle or a
wanted vehicle, a call may automatically be made to the police.
[0094] In such manner, the interrelation between the with-care
vehicle and the with-care state can be measured. Here, FIG. 9 is by
way of example only, and thus such generic table is not always
necessary if some other techniques are applicable to measure the
above interrelation.
[0095] To be specific, the above-described threat level
correspondingly varies depending on the vehicle's and the nearby
vehicle's position, speed, acceleration, making turns or changing
lanes, and road shape, road surface condition, and the like.
Therefore, from such interrelation, derived is a predetermined
equation or a complex conditional expression with various
imaginable cases given into consideration. By using such equation
or complex expression, the interrelation between the with-care
vehicle and the with-care state can be measured.
[0096] As such, in step S543 of FIG. 4, the guiding part 11 decides
whether or not the vehicle is in with-care state in consideration
of the with-care vehicle.
[0097] Next, in step S544, to deal with the with-care vehicle, the
guiding part 11 generates drive assistant information. Here, the
drive assistant information is typically used to arrange an image
of the with-care vehicle onto the map image for display.
[0098] FIG. 10 is a schematic diagram showing what the drive
assistant information carries. In FIG. 10, the drive assistant
information includes a nearby vehicle ID 551, vehicle type
information 552, color information 553, relative position 554, and
one or more attributes relevant to threat level (hereinafter,
threat attributes) 555. The nearby vehicle ID 551 is an
identification number uniquely assigned to each nearby vehicle for
identification. The vehicle type information 552 and the color
information 553 are determined based on the external information
detected by the obstacle detection part 8. Here, the vehicle type
information 552 and the color information 553 are mainly used for
image display, and thus not necessarily included. Also, the
relative position 554 is also not always necessary if the
navigation device warns the driver only by sound without display on
the map image.
[0099] Here, the threat attributes 555 are the ones selectively
determined by the guiding part 11 as harmful in consideration of
the interrelation between the with-care vehicle and the with-care
state (for example, the value "1" in the table of FIG. 9).
[0100] Note that, when the guiding part 11 selectively determines
as such, the with-care state determined in step S543 is not the
only concern. For example, if the vehicle changes lanes to make a
turn while decreasing its speed, the vehicle is in three types of
with-care states. In such case, selected are every possible threat
attribute in consideration of the interrelation among those
with-care states and with-care vehicles.
[0101] Further, the with-care vehicle may accompany several threat
attributes. As an example, if a nearby vehicle with a with-care
sign is meanderingly approaching, the number of threat attributes
is at least three. In such case, selected are every possible threat
attribute relevant to the with-care vehicle.
[0102] As such, in step S544, the guiding part 11 selectively
determines every possible threat attribute for a certain with-care
vehicle by taking every known with-care state into consideration,
and correspondingly generates drive assistant information.
[0103] Next, in step S545, the guiding part 11 refers to the
external information to determine if there is any other with-care
vehicle. If determined Yes, the procedure returns to step S543 and
repeats the same processing as above until the drive assistant
information is generated for every with-care vehicle. If determined
No, the procedure returns to the processing of FIG. 3, and goes to
step S55.
[0104] FIG. 11 is a flowchart showing the detailed process of
subroutine step S55 of FIG. 3. In step S551 of FIG. 11, the map
data arranging part 4 determines whether or not there is the drive
assistant information generated by the guiding part 11 in
subroutine step S54. If determined No, the procedure returns to the
processing of FIG. 3, otherwise goes to step S552.
[0105] In step S552, the map data arranging part 4 reads, from the
object model display information storage part 6, object model
display information corresponding to certain drive assistant
information. Here, the object model display information is used to
display object models corresponding to the with-care vehicle and
its threat attributes.
[0106] In step S553, the map data arranging part 4 creates an
object model corresponding to thus read object model display
information, and dimensionally appropriately arranges the object
model on a map image in consideration of a display scale and map
space. The resulting map image is displayed by the display 5.
[0107] Here, the display scale is so set that the vehicle and other
with-care vehicles are displayed on the map image with appropriate
size and space in consideration of actual relative distance. For
example, in the present navigation device, four display scales are
provided. The first display scale is used for displaying a map
image covering 1.6 to 50 kilometers square, and such map image is
called a 3D satellite map. The second display scale is used for a
map image covering 100 to 800 meters square, and the map image is
generally called a 2D map. A map image for the third display scale
covers 25 to 100 meters square, and is called a virtual city map. A
map image for the fourth display scale covers 25 to 50 meters
square, and is called a front view map. In the virtual city map and
the front view map among those four, the vehicle and the with-care
vehicles look appropriate in size. Those four maps are generally
switched thereamong as appropriate. Accordingly, the drive
assistant information is presented with higher accuracy to the
driver of the vehicle in easy-to-see manner.
[0108] Here, the display scale is not limited to those four, and
may be continuously changed so that the vehicle and the with-care
vehicles look always appropriate in space thereamong. After setting
the display scale as such, another processing is carried out to
arrange thus created object model on the map image for display. The
details thereof are left for later description.
[0109] In step S554, the map data arranging part 4 determines
whether or not there is other drive assistant information generated
by the guiding part 11. If determined No, the procedure returns to
the processing of FIG. 3. If Yes, the procedure returns to step
S552 to repeat the same processing until every drive assistant
information is thoroughly displayed.
[0110] Described next is step S553 of FIG. 11 about how the map
data arranging part 4 generates a map image. First, described is a
case where a resulting map image is of a 2D landscape. FIG. 12 is a
diagram showing the detailed structure of the map data arranging
part 4 for such case. In FIG. 12, the map data arranging part 4
includes a 2D object model creation part 145, and a 2D data
arranging part 146.
[0111] The 2D object model creation part 145 receives the object
model display information from the object model display information
storage part 6, and creates a 2D object model. The 2D data
arranging part 146 receives thus created 2D object model and 2D map
data from the map data storage part 3, and generates a map image by
arranging those in accordance with 2D coordinates included in each
of those. FIG. 13 is a schematic diagram exemplarily showing an
exemplary map image displayed as such on the display 5.
[0112] In FIG. 13, on a road with two lanes each in the 2D map
image, arranged are a vehicle object model 301, a nearby vehicle
object 302, which is regarded as a with-care vehicle, and an arrow
object model 303, which corresponds to the threat attribute. Here,
the vehicle type and color of the nearby vehicle object 302 are
preferably displayed according to the drive assistant information.
The nearby object model 302 may be emphatically displayed to
indicate the near by vehicle is the with-care vehicle. For example,
the nearby object model 302 may be in red, flashing on and off, and
changing colors. Any manner will do as long as the driver is warned
thereby.
[0113] Assume here that the with-care vehicle is putting its front
right blinker on, and the vehicle is also about to move to the
right lane. In such case, as described in FIG. 9, collision between
those two vehicles is likely. Therefore, to warn the driver of the
vehicle that the with-care vehicle behind is moving to the right,
such arrow object model 303 as shown in FIG. 13 is displayed.
[0114] Here, even if the nearby vehicle is approaching from the
right lane, as shown in FIG. 9, the nearby vehicle is considered no
threat unless the vehicle moves to the right, makes a turn, and the
road is narrowed on the right side or curved to the right. As such,
if the nearby vehicle is determined as harmless, no drive assistant
information is generated, and thus no arrow object model 303 is
displayed.
[0115] FIG. 14 is a schematic diagram exemplarily showing another
example of map image displayed on the display 5. In FIG. 14,
arranged on the road are a vehicle object model 311, a nearby
vehicle object model 312, which is regarded as a with-care vehicle,
and a with-care sign object model 313, which corresponds to the
threat attribute. Assume here that the vehicle is about to make a
left turn and the with-care vehicle therebehind carries a with-care
sign. In such case, there seems some threat, and thus such
with-care sign object model 313 as shown in FIG. 14 is displayed to
warn the driver of the vehicle that the with-care vehicle behind is
with the with-care sign.
[0116] Here, the threat attribute may be indicated in plurality for
the nearby vehicle object model, and two or more object models may
be provided to indicate one threat attribute. FIG. 15 is a
schematic diagram exemplarily showing still another example of map
image displayed on the display 5. In FIG. 15, arranged on the road
are a vehicle object model 321, a nearby vehicle object model 322,
which is regarded as a with-care vehicle, a meandering sign object
model 323 and a speech bubble object model 324, both of which
correspond to the threat attribute. Assume here that the vehicle is
about to make a left turn and the with-care vehicle therebehind is
meandering. In such case, there seems some threat, and thus such
meandering sign object model 323 and the speech bubble object model
324 as shown in FIG. 15 are displayed to warn the driver of the
vehicle that the with-care vehicle behind is meandering. Here, the
speech bubble object model 324 has words of warning displayed
therein.
[0117] As such, by appropriately arranging the vehicle model object
and the nearby vehicle object models on a map image, the driver can
instantaneously understand the positional relationship thereamong.
Also, by creating each appropriate object model for every possible
threat attribute, the driver can instantaneously acknowledge its
threat level. Accordingly, information offered by the present
navigation device can appropriately help, in driving, the driver of
the vehicle with higher accuracy.
[0118] Described next is a case where a resulting map image
generated in the map data arranging part 4 is of a 3D landscape. In
such case, there is no need for an object model created from the
object model display information and map data stored in the map
data storage part 3 to be 3D. Exemplified now is a case where the
data provided by the object model display information storage part
6 to the map data arranging part 4 is 3D, and the map data by the
map data storage part 3 is 2D, and a resulting map image is of a 3D
landscape.
[0119] FIG. 16 is a block diagram showing the detailed structure of
the map data arranging part 4, which receives 3D data from the
object model display information storage part 6 and 2D map data
from the map data storage part 3. A resulting map image generated
thereby is of a bird's eye view.
[0120] In FIG. 16, the map data arranging part 4 includes a bird's
eye view transformation part 141, a 3D object model creation part
142, and a 3D data arranging part 143.
[0121] The bird's eye view transformation part 141 receives the 2D
map data from the map data storage part 3, and then transforms the
data to a bird's eye view. A technique for transforming 2D data to
a bird's eye view is disclosed in detail in "Development of a Car
Navigation System with a Bird's-eye View Map Display" (Society of
Automotive Engineers of Japan, Inc, Papers, 962 1996-5), for
example. Next below, a technique for transforming 2D data to a
bird's eye view is described.
[0122] FIG. 17 is a diagram demonstrating a technique for creating
a bird's eye view by subjecting 2D map data to perspective
transformation. In FIG. 17, a point V(Vx, Vy, Vz) indicates
viewpoint coordinates. A point S(Sx, Sy) indicates coordinates of a
bird's eye view image on a monitor, and a point M(Mx, My, Mz)
indicates coordinates on a 2D map image. Here, since the map data
is 2D data, Mz is 0. Points Ex, Ey, and Ez each indicate a relative
position to the point M in the viewpoint coordinates system. A
reference character .theta. denotes a look-down angle, while .phi.
indicates a direction angle of viewpoint. A reference character DS
indicates a theoretical distance between the viewpoint and the
image.
[0123] Here, with the viewpoint coordinates V(Vx, Vy, Vz),
look-down angle .theta., and direction angle .phi. specified in
value, the coordinates S(Sx, Sy) of the bird's eye view image can
be calculated with respect to the coordinates M(Mx, My, Mz) on the
2D map image. An equation (2) therefor is as follows: 1 E = [ 1 0 0
0 sin cos 0 - cos sin ] [ sin - cos 0 cos sin 0 0 0 1 ] ( M - V ) S
= DS - Ez ( Ex Ey ) ( 2 )
[0124] With the above equation (2), for example, the bird's eye
view transformation part 141 transforms the 2D map data provided by
the map data storage part 3 to a bird's eye view. The bird's eye
view of 3D data is forwarded to the 3D data arranging part 143.
[0125] The 3D object model creation part 142 receives the 3D data,
and then creates a 3D object model with the processing in
subroutine step S553 of FIG. 11. Thus created 3D object model is
forwarded to the 3D data arranging part 143.
[0126] The 3D data arranging part 143 arranges thus received 3D
data and object model data together for output to the display 5.
FIG. 18 shows exemplary data thus generated and displayed on the
display 5.
[0127] In FIG. 18, on the map image of the bird's eye view, there
include a vehicle model object 331, a nearby vehicle object model
332, which is regarded as a with-care vehicle, and a with-care sign
object model 333, which corresponds to the threat attribute.
Assumption made herein is the same as the case of FIG. 14, and thus
is not described again. In FIG. 18, presumably, these object models
are 3D of a type changing in shape with varying viewpoints even if
looked as 2D.
[0128] Exemplified now is a case where the data provided by the
object model display information storage part 6 is 3D, and the data
by the map data storage part 3 is 2D, and a resulting map image is
of a 3D landscape, which looks different from the bird's eye
view.
[0129] FIG. 19 is a block diagram showing the detailed structure of
the map data arranging part 4, which receives 3D data from the
object model display information storage part 6 and 2D map data
from the map data storage part 3. A resulting map image generated
thereby is of a 3D landscape, which is different from a bird's eye
view.
[0130] In FIG. 19, the map data arranging part 4 includes a 3D map
data generation part 147, the 3D object model creation part 142,
and the 3D data arranging part 143.
[0131] In FIG. 19, the 3D object model creation part 142 and the 3D
data arranging part 143 are similar in structure and operation to
those in FIG. 16. Thus, the 3D map data generation part 147 is
mainly described in structure and operation below.
[0132] FIG. 20 is a block diagram showing the detailed structure of
the 3D map data generation part 147. In FIG. 20, the 3D map data
generation part 147 includes a height/width information supply part
1471, and a 3D polygon creation part 1472. The height/width
information supply part 1471 supplies information about height and
width to the 3D polygon creation part 1472 responding to 2D map
data provided by the map data storage part 3. The 3D polygon
creation part 1472 then creates a 3D object model.
[0133] The height/width information supply part 1471 analyzes the
3D shape of a road, for example, with the help of the link type
(e.g., side-road link, elevated link) and information about
branching node included in the 2D map data, typically by applying a
predetermined pattern. With the analyzed result, the height/width
information supply part 1471 adds information about height and
width to the 2D data of the road, for example, so as to generate 3D
map data.
[0134] The 3D polygon creation part 1472 receives thus generated 3D
map data, and creates a 3D object model with a general technique
therefor. In the above manner, the map data arranging part 4 of
FIG. 19 generates a map image of 3D landscape, which looks
different from a bird's eye view.
[0135] FIG. 21 is a diagram exemplarily showing a case where
displayed on the 3D landscape are 3D object models, which indicate
a with-care vehicle and its direction being about to move to the
right lane. As shown in FIG. 21, by displaying both the nearby
vehicle object model moving to the right lane and the arrow object
model indicating its moving direction, the driver of the vehicle
can intuitively understand what the nearby vehicle behind is about
to do.
[0136] Exemplified next is a case where the data provided by the
object model display information storage part 6 to the map data
arranging part 4 is 2D, and the data by the map data storage part 3
is 3D, and a resulting map image is of a 3D landscape.
[0137] FIG. 22 is a block diagram showing the detailed structure of
the map data arranging part 4, which receives 2D data from the
object model display information storage part 6 and 3D map data
from the map data storage part 3. A resulting map image generated
thereby is a map image of 3D landscape.
[0138] In FIG. 22, the map data arranging part 4 includes a 2D
object model creation part 145, a 2D/3D coordinate transformation
part 144, and the 3D data arranging part 143.
[0139] In FIG. 22, the 2D object model creation part 145 receives
2D data from the object model display information storage part 6,
and then creates a 2D object model by going through subroutine step
S553 of FIG. 11.
[0140] To be specific, as already described, a plurality of image
files are prepared as 2D shape information included in the object
model display information. FIG. 23 is a diagram exemplarily showing
several image files prepared as such. In FIG. 23, images are
classified into "meandering vehicle", "motorcycle", and "vehicle
with with-care sign". Such image type corresponds to the object
model display information, and further classified into
"close-range", "medium-range", and "long-range".
[0141] The 2D object model creation part 145 first determines the
image type by referring to the object model display information.
The 2D object model creation part 145 then selects a distance range
for the determined image type among from those "close-range",
"medium-range", and "long-range". Here, as described above, the
object model display information includes position information
indicating the position of the object model by 3D coordinates. In
FIG. 23, selecting a distance range for each image is based on a
distance between such 3D coordinates and viewpoint coordinates.
Therefore, typically, the 2D object model creation part 145
calculates such distance to determine to which distance range thus
calculated distance applies.
[0142] As for a resulting 2D object model, the 2D/3D coordinate
transformation part 144 transforms 2D coordinates thereof to 3D
coordinates based on the corresponding position information. Then,
the resulting 3D object data is inputted into the 3D data arranging
part 143.
[0143] The 3D data arranging part 143 receives 3D map data from the
map data storage part 3. The 3D data arranging part 143 then
arranges the map data together with the 3D object model data
provided by the 2D/3D coordinate transformation part 144 to
generate a map image of 3D landscape. Thus generated map image is
forwarded to the display 5.
[0144] Here, in the map data arranging part 4 as above structured,
the 2D object model created by the 2D object model creation part
145 is transformed to 3D data by the 2D/3D coordinate
transformation part 144, and then arranged together with the 3D map
data in the 3D data arranging part 143. This is not restrictive,
and the 2D/3D coordinate transformation part 144 may be omitted,
and a 2D/3D image arranging part may be provided as an alternative
to the 3D data arranging part 143. If this is the case, the 2D/3D
image arranging part pastes a 2D object model created by the 2D
object model creation part 145 onto a map image of 3D landscape. In
more detail, the 2D/3D image arranging part first generates a map
image of 3D landscape by transforming 3D map data to screen
coordinates, calculates screen coordinates of a 2D object model,
and arranges 2D data as it is on a resulting map image of 3D
landscape. With such modified structure, an object model looks the
same even if viewed from various positions, and is displayed always
the same. Therefore, better viewability is offered.
[0145] FIG. 24 shows an exemplary map image of 3D landscape
generated by the map data arranging part 4 of FIG. 22. In FIG. 24,
the map image has an object model indicative of the vehicle
displayed in the middle, and on the right side thereof, object
models indicative of meandering vehicles on a road. As to those
object models indicative of meandering vehicles, the size thereof
is changed based on a distance from the viewpoint coordinates as
described above, thereby adding depth to the map image of 3D
landscape even if the object models are 2D.
[0146] Lastly, exemplified is a case where the data provided by the
object model display information storage part 6 to the map data
arranging part 4 is 2D, and the map data by the map data storage
part 3 is 2D, and a resulting map image is of a 3D landscape.
[0147] If this is the case, the map data arranging part 4 of FIG.
22 is additionally provided with the bird's eye view transformation
part 141 of FIG. 16, or the 3D map data generation part 147 of FIG.
19, both of which convert 2D map data into 3D map data. Also, in
such map data arranging part 4, the 3D data arranging part 143
performs data arrangement of the map data and the 2D object model
data from the 2D/3D coordinate transformation part 144. Here, the
components included therein operate similarly to those described
above.
[0148] In such case as a map image of 3D landscape being generated
from 2D data, the 2D data stored in the object model display
information storage part 6 is less in amount than 3D data.
Therefore, if storing object model data varying in type, the object
model display information storage part 6 can store the larger
number of types, and if storing the same type of object model data,
the capacity thereof can be reduced.
[0149] Further, in such case as a map image of 3D landscape being
generated from 2D data, the driver of the vehicle can intuitively
understand information even if object models are 2D. For example,
if there is a nearby vehicle meanderingly approaching, the driver
of the vehicle can easily and intuitively understand how the nearby
vehicle is behaving only by seeing an object model indicative of
meandering vehicle behind his/her vehicle.
[0150] While the invention has been described in detail, the
foregoing description is in all aspects illustrative and not
restrictive. It is understood that numerous other modifications and
variations can be devised without departing from the scope of the
invention.
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