Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios

Autonomous vehicles must be comprehensively evaluated before deployed in cities and highways. However, most existing evaluation approaches for autonomous vehicles are static and lack adaptability, so they are usually inefficient in generating challenging scenarios for tested vehicles. In this paper,...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 23; H. 8; S. 10333 - 10342
Hauptverfasser:	Chen, Baiming, Chen, Xiang, Wu, Qiong, Li, Liang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accidents Autonomous vehicle Autonomous vehicles Bayesian analysis Lane changing Performance degradation Reinforcement learning Safety Testing Training unsupervised learning vehicle evaluation Vehicles
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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