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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Li Gao , Rui Zhou, Kai Zhang
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2023-05-01
Sarja:	Sensors
Aiheet:	scenario generation heterogeneous driver model deep learning autonomous-driving testing
Linkit:	https://www.mdpi.com/1424-8220/23/9/4570
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