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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Detalles Bibliográficos
Autores principales: Gao , Li, Zhou, Rui, Zhang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181674/
https://www.ncbi.nlm.nih.gov/pubmed/37177774
http://dx.doi.org/10.3390/s23094570

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181674/
https://www.ncbi.nlm.nih.gov/pubmed/37177774
http://dx.doi.org/10.3390/s23094570

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