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Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System
April 16, 2024, 4:47 a.m. | Genjia Liu, Yue Hu, Chenxin Xu, Weibo Mao, Junhao Ge, Zhengxiang Huang, Yifan Lu, Yinda Xu, Junkai Xia, Yafei Wang, Siheng Chen
cs.CV updates on arXiv.org arxiv.org
Abstract: Vehicle-to-everything-aided autonomous driving (V2X-AD) has a huge potential to provide a safer driving solution. Despite extensive researches in transportation and communication to support V2X-AD, the actual utilization of these infrastructures and communication resources in enhancing driving performances remains largely unexplored. This highlights the necessity of collaborative autonomous driving: a machine learning approach that optimizes the information sharing strategy to improve the driving performance of each vehicle. This effort necessitates two key foundations: a platform capable …
abstract arxiv autonomous autonomous driving collaborative communication cs.cv driving everything highlights performances platform resources simulation solution support transportation type
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