IP Library Granted Patent US 10,814,884
Granted Patent B2
US 10,814,884 · App. 16/022,002 · Granted Oct 27, 2020

Autonomous vehicle site test method and apparatus, device and readable medium

Inventor: Song Zhang (Beijing, CN)
Assignee: BAIDU ONLINE NETWORK TECHNOLOGY (BEIJING) CO., LTD.
B60W50/045G01M17/007G05D1/0088G06K9/00798G07C5/008B60W2050/046B60W2554/00G05D2201/0213
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Quick Facts
Patent No.
US 10,814,884
App. No.
16/022,002
Granted
Oct 27, 2020
Kind
B2
Abstract

The present disclosure provides an autonomous vehicle site test method and apparatus, a device and a readable medium. The method comprises: in a site test, collecting state information of the autonomous vehicle in real time; according to the state information of the autonomous vehicle and a pre-obtained test demand, obtaining deployment information of a simulated obstacle needed in the test, wherein the deployment information of the simulated obstacle includes a simulated obstacle class, a deployment location of the simulated obstacle and a predetermined action of the simulated obstacle; according to the deployment information of the simulated obstacle, controlling the simulated obstacle corresponding to the simulated obstacle class to perform a predetermined action at the deployment location, to test the autonomous vehicle's response performance to the deployed simulated obstacle.

Claims (50)

1. An autonomous vehicle site test method, wherein the method comprises:

in a site test, collecting state information of the autonomous vehicle in real time on a real test site;

according to the state information of the autonomous vehicle and a pre-obtained test demand, obtaining deployment information of a real simulated obstacle needed in the test, wherein the deployment information of the real simulated obstacle includes at least a simulated obstacle class, a deployment location of the real simulated obstacle, and a predetermined action of the real simulated obstacle;

according to the deployment information of the real simulated obstacle, controlling the real simulated obstacle corresponding to the simulated obstacle class to perform a predetermined action at the deployment location on the real test site, to test the autonomous vehicle's response performance to the deployed real simulated obstacle.

2. The method according to claim 1 , wherein the obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and the pre-obtained test demand, comprises:

judging whether the state information of the autonomous vehicle reaches predetermined state information of the autonomous vehicle set in the test demand;

if the state information of the autonomous vehicle reaches the predetermined state information of the autonomous vehicle set in the test demand: obtaining, from the test demand, deployment information of the simulated obstacle needed in the test.

3. The method according to claim 1 , wherein the collecting state information of the autonomous vehicle in real time comprises:

receiving in real time at least one of the autonomous vehicle's location, travel speed, travel direction, and acceleration reported by the autonomous vehicle in real time.

4. The method according to claim 3 , wherein the collecting state information of the autonomous vehicle in real time further comprises:

receiving, in real time, a total number of lanes of the road where the autonomous vehicle travels, transmitted by an information collecting system arranged in the real test site, and an identifier of a lane where the autonomous vehicle is located.

5. The method according to claim 1 , wherein before obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and the pre-obtained test demand, the method further comprises:

receiving the test demand input by a tester through a human-machine interface module,

wherein the simulated obstacle class includes people, vehicles, or traffic lights.

6. The method according to claim 1 , wherein the step of, according to the deployment information of the real simulated obstacle, controlling the real simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location, comprises:

according to the deployment information of the real simulated obstacle, controlling, in a wireless communication manner, the real simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location.

7. A computer device, comprising:

one or more processors; and

a storage storing one or more programs that, when executed by said one or more processors, enable said one or more processors to implement an autonomous vehicle site test method, wherein the method comprises:

in a site test, collecting state information of the autonomous vehicle in real time on a real test site;

according to the state information of the autonomous vehicle and a pre-obtained test demand, obtaining deployment information of a real simulated obstacle needed in the test, wherein the deployment information of the real simulated obstacle includes at least a simulated obstacle class, a deployment location of the real simulated obstacle, and a predetermined action of the real simulated obstacle;

according to the deployment information of the real simulated obstacle, controlling the real simulated obstacle corresponding to the simulated obstacle class to perform a predetermined action at the deployment location on the real test site, to test the autonomous vehicle's response performance to the deployed real simulated obstacle.

8. The computer device according to claim 7 , wherein the obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and the pre-obtained test demand, comprises:

judging whether the state information of the autonomous vehicle reaches predetermined state information of the autonomous vehicle set in the test demand;

if the state information of the autonomous vehicle reaches the predetermined state information of the autonomous vehicle set in the test demand: obtaining, from the test demand, deployment information of the real simulated obstacle needed in the test.

9. The computer device according to claim 7 , wherein the collecting state information of the autonomous vehicle in real time comprises:

receiving in real time at least one of the autonomous vehicle's location, travel speed, travel direction, and acceleration reported by the autonomous vehicle in real time.

10. The computer device according to claim 9 , wherein the collecting state information of the autonomous vehicle in real time further comprises:

receiving, in real time, a total number of lanes of the road where the autonomous vehicle travels, transmitted by an information collecting system arranged in the real test site, and an identifier of a lane where the autonomous vehicle is located.

11. The computer device according to claim 7 , wherein before obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and the pre-obtained test demand, the method further comprises:

receiving the test demand input by a tester through a human-machine interface module,

wherein the simulated obstacle class includes people, vehicles, or traffic lights.

12. The computer device according to claim 7 , wherein the step of, according to the deployment information of the real simulated obstacle, controlling the mal simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location, comprises:

according to the deployment information of the real simulated obstacle, controlling, in a wireless communication manner, the real simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location.

13. A computer readable medium on which a computer program is stored, wherein the computer program, when executed by one or more processors, implements an autonomous vehicle site test method, wherein the method comprises:

in a site test, collecting state information of the autonomous vehicle in real time on a real test site;

according to the state information of the autonomous vehicle and a pre-obtained test demand, obtaining deployment information of a real simulated obstacle needed in the test, wherein the deployment information of the real simulated obstacle includes at least a simulated obstacle class, a deployment location of the real simulated obstacle, and a predetermined action of the real simulated obstacle;

according to the deployment information of the real simulated obstacle, controlling the real simulated obstacle corresponding to the simulated obstacle class to perform a predetermined action at the deployment location on the real test site, to test the autonomous vehicle's response performance to the deployed real simulated obstacle.

14. The computer readable medium according to claim 13 , wherein the obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and a pre-obtained test demand, comprises:

judging whether the state information of the autonomous vehicle reaches predetermined state information of the autonomous vehicle set in the test demand;

if the state information of the autonomous vehicle reaches the predetermined state information of the autonomous vehicle set in the test demand: obtaining, from the test demand, deployment information of the simulated obstacle needed in the test.

15. The computer readable medium according to claim 13 , wherein the collecting state information of the autonomous vehicle in real time comprises:

receiving in real time at least one of the autonomous vehicle's location, travel speed, travel direction, and acceleration reported by the autonomous vehicle in real time.

16. The computer readable medium according to claim 15 , wherein the collecting state information of the autonomous vehicle in real time further comprises:

receiving real time, a total number of lanes of the road where the autonomous vehicle travels, transmitted by an information collecting system arranged in the real test site, and an identifier of a lane where the autonomous vehicle is located.

17. The computer readable medium according to claim 13 , wherein before obtaining deployment information of the real simulated obstacle needed in the test, according to the state information of the autonomous vehicle and the pre-obtained test demand, the method further comprises:

receiving the test demand input by a tester through a human-machine interface module,

wherein the simulated obstacle class includes people, vehicles, or traffic lights.

18. The computer readable medium according to claim 13 , wherein the step of, according to the deployment information of the real simulated obstacle, controlling the real simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location, comprises:

according to the deployment information of the real simulated obstacle, controlling, in a wireless communication manner, the real simulated obstacle corresponding to the simulated obstacle class to perform the predetermined action at the deployment location.

Assignments (3)
CORRECTIVE ASSIGNMENT TO CORRECT THE APPLICANT NAME PREVIOUSLY RECORDED AT REEL: 057933 FRAME: 0812. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Dec 28, 2021
From: BAIDU ONLINE NETWORK TECHNOLOGY (BEIJING) CO., LTD.
To: APOLLO INTELLIGENT DRIVING TECHNOLOGY (BEIJING) CO., LTD.
Reel/Frame 058594/0836 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 13, 2021
From: BAIDU ONLINE NETWORK TECHNOLOGY (BEIJING) CO., LTD.
To: APOLLO INTELLIGENT DRIVING (BEIJING) TECHNOLOGY CO., LTD.
Reel/Frame 057933/0812 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 4, 2018
From: ZHANG, SONG
To: BAIDU ONLINE NETWORK TECHNOLOGY (BEIJING) CO., LTD.
Reel/Frame 046266/0069 →
Priority Claims (1)
CN 2017 1 05429708 · Jul 5, 2017 · national
Continuity (1)
Related Publication 20190009789A1 · Jan 10, 2019