IP Library › Granted Patent US 11,984,028
Granted Patent B2
US 11,984,028 · App. 17/623,550 · Granted May 14, 2024

Method, device and electronic equipment for vehicle cooperative decision-making and computer storage medium

Inventors: Keqiang Li (Beijing, CN); Wenbo Chu (Beijing, CN); Qiuchi Xiong (Beijing, CN); Qiqige Wuniri (Beijing, CN); Guanfu Huang (Beijing, CN); Xiaoping Du (Beijing, CN)
Assignees: China Intelligent and Connected Vehicles (Beijing) Research Institute Co., Ltd; Tsinghua University
G08G1/096725G06V20/54G08G1/096811
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Quick Facts
Patent No.
US 11,984,028
App. No.
17/623,550
Granted
May 14, 2024
Kind
B2
Abstract

The application provides a method, device, electronic device for vehicle cooperative decision-making as well as a computer storage medium. The method for vehicle cooperative decision-making applied at a cloud server includes: receiving a cooperative decision request sent by a roadside device, wherein the cooperative decision request is a request sent by the roadside device after it is recognized that a road is congested based on acquired real-time road information; acquiring information of a road scene included in the cooperative decision request; determining a congestion scene type based on the information of the road scene; calculating multi-vehicle oriented decision planning schemes using a preset scene cooperative decision model based on the congestion scene type; and sending the decision planning schemes to respective vehicles, so that the vehicles perform respective driving operations according to the decision planning schemes.

Claims (37)

1. A method for vehicle cooperative decision-making, applied at a cloud server and comprising:

receiving a cooperative decision request sent by a roadside device, wherein the cooperative decision request is a request sent by the roadside device after it is recognized that a road is congested based on acquired real-time road information;

acquiring information of a road scene included in the cooperative decision request;

determining a congestion scene type based on the information of the road scene and identifying one of a plurality of preset scene cooperative decision models based on the congestion scene type;

calculating multi-vehicle oriented decision planning schemes using the identified preset scene cooperative decision model; and

sending the decision planning schemes to respective vehicles on the road, so that the vehicles perform respective driving operations according to the decision planning schemes.

2. The method for vehicle cooperative decision-making according to claim 1 , wherein the calculation of the multi-vehicle oriented decision planning schemes using the identified preset scene cooperative decision model comprises:

acquiring road restriction information and real-time vehicle state information corresponding to the congestion scene type; and

calculating the multi-vehicle oriented decision planning schemes using the identified preset scene cooperative decision model based on the road restriction information and the real-time vehicle state information.

3. The method for vehicle cooperative decision-making according to claim 2 , wherein the acquisition of the real-time vehicle state information comprises:

receiving at least one of vehicle speed, acceleration, angular velocity, wheel steering, braking information, a relative distance to a leading/following vehicle, destination information, and a ratio of traveled path to planned path sent by each of the vehicles.

4. The method for vehicle cooperative decision-making according to claim 2 , wherein the acquisition of the real-time vehicle state information comprises:

receiving at least one of traffic light state information, relative sequence information of the vehicles, and location information of a pedestrian in the road scene sent by the roadside device.

5. The method for vehicle cooperative decision-making according to claim 2 , wherein the road restriction information comprises at least one of: allowable vehicle speed range, number of lanes, lane width, and available road sections.

6. The method for vehicle cooperative decision-making according to claim 1 , wherein the preset scene cooperative decision model is a time slot allocation model designed based on a game theory matching method.

7. The method for vehicle cooperative decision-making according to claim 1 , wherein the decision planning schemes comprise at least one of a driving priority distribution scheme, a vehicle path change scheme, and a vehicle next-state driving operation scheme.

8. An electronic device, comprising:

a processor; and

a memory storing computer program instructions,

wherein the processor is configured to execute the computer program instructions to perform the method for vehicle cooperative decision-making according to claim 1 .

9. A computer storage medium having computer program instructions stored thereof, wherein the computer program instructions, when executed by a processor, cause the processor to perform the method for vehicle cooperative decision-making according to claim 1 .

10. A device for vehicle cooperative decision-making, applied at a cloud server and comprising:

a reception module configured to receive a cooperative decision request sent by a roadside device, wherein the cooperative decision request is a request sent by the roadside device after it is recognized that a road is congested based on acquired real-time road information;

an acquisition module configured to acquire information of a road scene included in the cooperative decision request;

a recognition module configured to recognize a congestion scene type based on the information of the road scene and identify one of a plurality of preset scene cooperative decision models based on the congestion scene type;

a calculation module configured to calculate multi-vehicle oriented decision planning schemes using the identified preset scene cooperative decision model; and

a sending module configured to send the decision planning schemes to respective vehicles on the road, so that the vehicles perform respective driving operations according to the decision planning schemes.

11. The device for vehicle cooperative decision-making according to claim 10 , wherein the calculation module comprises:

an acquisition unit configured to acquire road restriction information and real-time vehicle state information corresponding to the congestion scene type; and

a calculation unit configured to calculate the multi-vehicle oriented decision planning schemes using the identified preset scene cooperative decision model based on the road restriction information and the real-time vehicle state information.

12. The device for vehicle cooperative decision-making according to claim 11 , wherein the acquisition unit comprises:

a first reception subunit configured to receive at least one of vehicle speed, acceleration, angular velocity, wheel steering, braking information, a relative distance to a leading/following vehicle, destination information, and a ratio of traveled path to planned path sent by each of the vehicle.

13. The device for vehicle cooperative decision-making according to claim 11 , wherein the acquisition unit comprises:

a second reception subunit configured to receive at least one of traffic light state information, relative sequence information of the vehicles, and location information of a pedestrian in the road scene sent by the roadside device.

14. The device for vehicle cooperative decision-making according to claim 11 , wherein the road restriction information comprises at least one of: allowable vehicle speed range, number of lanes, lane width, and available road sections.

15. The device for vehicle cooperative decision-making according to claim 10 , wherein the preset scene cooperative decision model is a time slot allocation model designed based on a game theory matching method.

16. The device for vehicle cooperative decision-making according to claim 10 , wherein the decision planning schemes comprise at least one of a driving priority distribution scheme, a vehicle path change scheme, and a vehicle next-state driving operation scheme.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 28, 2021
From: LI, KEQIANG; CHU, WENBO; XIONG, QIUCHI; WUNIRI, QIQIGE; HUANG, GUANFU; DU, XIAOPING
To: CHINA INTELLIGENT AND CONNECTED VEHICLES (BEIJING) RESEARCH; TSINGHUA UNIVERSITY
Reel/Frame 058494/0135 →
Priority Claims (1)
CN 202011439868.3 · Dec 11, 2020 · national
Continuity (1)
Related Publication 20230252895A1 · Aug 10, 2023
Cited By (1)
US 12,456,210