SceGAN: A Method for Generating Autonomous Vehicle Cut-In Scenarios on Highways Based on Deep Learning

• Published in: Journal of intelligent and connected vehicles Vol. 6; no. 4; pp. 264 - 274
• Main Authors: Yang, Lan, Yuan, Jiaqi, Zhao, Xiangmo, Fang, Shan, He, Zeyu, Zhan, Jiahao, Hu, Zhiqiang, Li, Xia
• Format: Journal Article
• Language: English
• Published: Tsinghua University Press 01.12.2023
• Subjects: autonomous vehicles testing; cut-in; generative adversarial network (gan); scenario generation; transformer

With the increasing level of automation of autonomous vehicles, it is important to conduct comprehensive and extensive testing before releasing autonomous vehicles into the market. Traditional public road and closed-field testing failed to meet the requirements of high testing efficiency and scenari...