Tongji University

Aijing Kong

Jian Sun

Peng Hang

The present invention proposes an autonomous driving testing method based on multi-alliance cluster confrontation, aiming to improve the efficiency and accuracy of autonomous driving simulation test, and comprising S—initialization of testing environment of autonomous driving; S—decision-making for dividing background vehicle clusters; S—decision-making for confrontation behaviors of the background vehicles; S—trajectory planning for the background vehicles; and S—looping through the steps S, S, and Suntil cluster confrontation testing tasks are completed. The method of the present invention uses reinforcement learning and alliance games to dynamically generate testing scenarios that are highly confrontational to vehicles being tested, which can find dangerous boundary scenarios for autonomous driving more quickly and improve the efficiency of simulation testing.

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Shanghai, China

Aijing Kong