Scenario Generation for Autonomous Vehicles with Deep-Learning-Based Heterogeneous Driver Models: Implementation and Verification

Virtual testing requires hazardous scenarios to effectively test autonomous vehicles (AVs). Existing studies have obtained rarer events by sampling methods in a fixed scenario space. In reality, heterogeneous drivers behave differently when facing the same situation. To generate more realistic and e...

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Bibliographic Details

Published in:	Sensors
Main Authors:	Li Gao , Rui Zhou, Kai Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2023-05-01
Subjects:	scenario generation heterogeneous driver model deep learning autonomous-driving testing
Online Access:	https://www.mdpi.com/1424-8220/23/9/4570