IP Library › Granted Patent US 12,460,942
Granted Patent B2
US 12,460,942 · App. 17/456,444 · Granted Nov 4, 2025

Map system, map generating program, storage medium, on-vehicle apparatus, and server

Inventors: Kentarou Shiota (Kariya, JP); Naoki Nitanda (Kariya, JP); Kazuma Ishigaki (Kariya, JP); Shinya Taguchi (Kariya, JP)
Assignee: DENSO CORPORATION
G01C21/3833G01C21/3822G01C21/387G01C21/3885
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Quick Facts
Patent No.
US 12,460,942
App. No.
17/456,444
Granted
Nov 4, 2025
Kind
B2
Abstract

A map system includes a vehicle apparatus that is mounted to a vehicle. The map system includes an imaging apparatus, a server, and an integrating unit. The imaging apparatus captures an image of a surrounding area of the vehicle. The server generates a map using data that corresponds to feature points extracted from the image captured by the imaging apparatus that is transmitted from the vehicle apparatus. The integrating unit weights the pieces of data that are transmitted from a plurality of vehicle apparatuses based on bias in the pieces of data and generates a map by integrating at least a portion of the plurality of pieces of data based on the weighting.

Claims (62)

1 . A map system that includes a vehicle apparatus that is mounted to each vehicle of a plurality of vehicles, the map system comprising:

an image sensor that is included in the vehicle apparatus of a respective vehicle of the plurality of vehicles and configured to capture an image of a surrounding area of the respective vehicle;

a server configured to

generate a probe map using data that is transmitted from the respective vehicle, the data corresponding to feature points extracted from the image captured by the image sensor that is transmitted from the vehicle apparatus of the respective vehicle;

determine bias in the data in which pieces of the data are biased by data of limited accuracy from the image sensor of the respective vehicle, the limited accuracy of the image sensor being determined based on at least one of (i) at least one of a mounting position, a mounting attitude, and a resolution and an angle of view of the image sensor, (ii) a traveling speed of the vehicle, and (iii) a brightness of a surrounding environment of the vehicle;

weight pieces of data of a plurality of data that is transmitted from the plurality of vehicles based on the determined bias in the pieces of the data; and

generate a map by integrating at least a portion of the pieces of data of the plurality of data that is transmitted from the plurality of vehicles based on the weighting,

wherein

the map is transmitted to at least one vehicle of the plurality of vehicles, and an actuator of the at least one vehicle performs a process for controlling the traveling of the at least one vehicle based on the map, wherein:

for a state in which an estimation accuracy of an own-vehicle behavior is determined to be relatively high, the server weights the pieces of data such that a priority level of the pieces of data is higher than a priority level of the data in which the estimation accuracy is determined to be relatively low; and

the estimation accuracy of the own-vehicle behavior being estimated (i) using the respective image that corresponds to the pieces of data and (ii) estimated using a Structure From Motion method.

2 . The map system according to claim 1 , wherein

the server determines bias in the pieces of data that is based on at least one of a mounting position, a mounting attitude, and specifications of the image sensor.

3 . The map system according to claim 1 , wherein

the server determines bias in the pieces of data that is based on a traveling speed of the vehicle.

4 . The map system according to claim 3 , wherein

the server weights the pieces of data such that a priority level of the data of which the traveling speed of the vehicle is relatively slow is higher than a priority level of the data of which the traveling speed of the vehicle is relatively fast, when accuracy related to a target object that is positioned in the vicinity of the vehicle is less than a predetermined determination accuracy based on the traveling speed of the vehicle.

5 . The map system according to claim 1 , wherein

the server determines bias in the pieces of data based on a surrounding environment of the vehicle.

6 . A non-transitory computer-readable storage medium storing a map generation program for causing at least either of a vehicle apparatus and a server to perform an integrating step, wherein

the vehicle apparatus is mounted to each vehicle of a plurality of vehicles and includes an image sensor that captures an image of a surrounding area of a respective vehicle,

the server generates a probe map using data that is transmitted from the respective vehicle, the data corresponding to feature points extracted from the image captured by the image sensor that is transmitted from the vehicle apparatus of the respective vehicle,

the integrating step comprises:

determining bias in the data in which pieces of the data are biased by data of limited accuracy from the image sensor of the respective vehicle, the limited accuracy of the image sensor being determined based on at least one of (i) at least one of a mounting position, a mounting attitude, and a resolution and an angle of view of the image sensor, (ii) a traveling speed of the vehicle, and (iii) a brightness of a surrounding environment of the vehicle;

weighting pieces of data of a plurality of data that is transmitted from the plurality of vehicles based on the determined bias in the pieces of the data; and

generating a map by integrating at least a portion of the pieces of data of the plurality of data that is transmitted from the plurality of vehicles based on the weighting,

wherein

the map is transmitted to at least one vehicle of the plurality of vehicles, and an actuator of the at least one vehicle performs a process for controlling the traveling of the at least one vehicle based on the map, wherein:

for a state in which an estimation accuracy of an own-vehicle behavior is determined to be relatively high, the server weights the pieces of data such that a priority level of the pieces of data is higher than a priority level of the data in which the estimation accuracy is determined to be relatively low, and

the estimation accuracy of the own-vehicle behavior being estimated using the respective image that corresponds to the pieces of data and estimated using a Structure From Motion method.

7 . A vehicle apparatus that is mounted to each vehicle of a plurality of vehicles, the vehicle apparatus comprising:

an image sensor that captures an image of a surrounding area of a respective vehicle of the plurality of vehicles, wherein:

the vehicle apparatus transmits, to a server, data that corresponds to feature points extracted from the image captured by the image sensor, the server is configured to:

determine bias in the data in which pieces of the data are biased by data of limited accuracy from the image sensor of the respective vehicle, the limited accuracy of the image sensor being determined based on at least one of (i) at least one of a mounting position, a mounting attitude, and a resolution and an angle of view of the image sensor, (ii) a traveling speed of the vehicle, and (iii) a brightness of a surrounding environment of the vehicle;

weight pieces of data of a plurality of data that is transmitted from the plurality of vehicles based on the determined bias in the pieces of the data; and

generate a map by integrating at least a portion of the pieces of data of the plurality of data that is transmitted from the plurality of vehicles based on the weighting,

wherein

the map is transmitted to at least one vehicle of the plurality of vehicles, and an actuator of the at least one vehicle performs a process for controlling the traveling of the at least one vehicle based on the map,

the vehicle apparatus further comprises:

a processor:

a non-transitory computer-readable storage medium; and

a set of computer-executable instructions stored on the non-transitory computer-readable storage medium that cause the processor to

attach reliability level information that is information related to a reliability level of the data that corresponds to the image, and

the set of computer-executable instructions further cause the processor to

evaluate the reliability level based on an estimation accuracy when an own-vehicle behavior, which is a behavior of the vehicle, is estimated using the image that corresponds to the data and estimated using a Structure From Motion method, and

generate the reliability level information based on evaluation results thereof.

8 . The vehicle apparatus according to claim 7 , wherein

the data that corresponds to the image is data that is related to imaging conditions of the image by the image sensor.

9 . The vehicle apparatus according to claim 7 , wherein

the set of computer-executable instructions further cause the processor to evaluate the reliability level based on estimation accuracy regarding a road gradient and generates the reliability level information based on evaluation results thereof.

10 . The vehicle apparatus according to claim 7 , wherein

the set of computer-executable instructions further cause the processor to evaluate the reliability level based on estimation accuracy regarding visibility of the image sensor and generates the reliability level information based on evaluation results thereof.

11 . The vehicle apparatus according to claim 7 , wherein

the set of computer-executable instructions further cause the processor to evaluate the reliability level based on information related to a landmark in an image that is detected based on an image that corresponds to the data and generates the reliability level information based on evaluation results thereof.

12 . A server that generates a map using data corresponding to feature points extracted from an image that is captured by an image sensor that is provided in a vehicle apparatus that is mounted to each vehicle of a plurality of vehicles, the image sensor being included in the vehicle apparatus of a respective vehicle and configured to capture an image of a surrounding area of the respective vehicle, the data being transmitted from the vehicle apparatus, the server being configured to:

determine bias in the data in which pieces of the data are biased by data of limited accuracy from the image sensor of the respective vehicle, the limited accuracy of the image sensor being determined based on at least one of (i) at least one of a mounting position, a mounting attitude, and a resolution and an angle of view of the image sensor, (ii) a traveling speed of the vehicle, and (iii) a brightness of a surrounding environment of the vehicle;

weight pieces of data of a plurality of data that is transmitted from the plurality of vehicles based on the determined bias in the pieces of the data; and

generate a map by integrating at least a portion of the pieces of data of the plurality of data that is transmitted from the plurality of vehicles based on the weighting,

wherein

the map is transmitted to at least one vehicle of the plurality of vehicles, and an actuator of the at least one vehicle performs a process for controlling the traveling of the at least one vehicle based on the map, wherein:

for a state in which an estimation accuracy of an own-vehicle behavior is determined to be relatively high, the server weights the pieces of data such that a priority level of the pieces of data is higher than a priority level of the data in which the estimation accuracy is determined to be relatively low, and

the estimation accuracy of the own-vehicle behavior being estimated using the respective image that corresponds to the pieces of data and estimated using a Structure From Motion method.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 24, 2022
From: SHIOTA, KENTAROU; NITANDA, NAOKI; ISHIGAKI, KAZUMA; TAGUCHI, SHINYA
To: DENSO CORPORATION
Reel/Frame 058747/0871 →
Priority Claims (2)
JP 2019-100268 · May 29, 2019 · national
JP 2020-089651 · May 22, 2020 · national
Continuity (2)
Continuation PCTJP2020021152 · May 28, 2020
Related Publication 20220082407A1 · Mar 17, 2022
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