驾驶模拟器
驾驶模拟
考试(生物学)
模拟
高级驾驶员辅助系统
汽车工业
汽车工程
方向盘
驾驶考试
作者
Prabhjot Kaur,Samira Taghavi,Zhaofeng Tian,Weisong Shi
标识
DOI:10.1109/metrocad51599.2021.00018
摘要
Rigorous and comprehensive testing plays a key role in training self-driving cars to handle a variety of situations that they are expected to see on public roads. The physical testing on public roads is unsafe, costly, and not always reproducible. This is where testing in simulation helps fill the gap. However, the problem with simulation testing is that it is only as good as the simulator used for testing and how representative the simulated scenarios are of the real environment. In this paper, we identify key requirements that a good simulator must have. Further, we provide a comparison of commonly used simulators. Our analysis shows that CARLA and LGSVL simulators are the current state-of-the-art simulators for end to end testing of self-driving cars for the reasons mentioned in this paper. Finally, we present current challenges that simulation testing continues to face as we march towards building fully autonomous cars.
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