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作 者:Tangyike Zhang Junxiang Zhan Jiamin Shi Jingmin Xin Nanning Zheng
机构地区:[1]National Key Laboratory of Human-Machine Hybrid Augmented Intelligence,National Engineering Research Center for Visual Information and Applications,Xi’an 710049 [2]Institute of Artificial Intelligence and Robotics,Xi’an Jiaotong University,Xi’an 710049,China [3]Momenta,Shanghai 201804,China
出 处:《IEEE/CAA Journal of Automatica Sinica》2023年第10期1905-1917,共13页自动化学报(英文版)
基 金:supported by the National Key R&D Program of China (2022YFB2502900);the National Natural Science Foundation of China (62088102, 61790563)。
摘 要:With the maturation of autonomous driving technology, the use of autonomous vehicles in a socially acceptable manner has become a growing demand of the public. Human-like autonomous driving is expected due to the impact of the differences between autonomous vehicles and human drivers on safety.Although human-like decision-making has become a research hotspot, a unified theory has not yet been formed, and there are significant differences in the implementation and performance of existing methods. This paper provides a comprehensive overview of human-like decision-making for autonomous vehicles. The following issues are discussed: 1) The intelligence level of most autonomous driving decision-making algorithms;2) The driving datasets and simulation platforms for testing and verifying human-like decision-making;3) The evaluation metrics of human-likeness;personalized driving;the application of decisionmaking in real traffic scenarios;and 4) The potential research direction of human-like driving. These research results are significant for creating interpretable human-like driving models and applying them in dynamic traffic scenarios. In the future, the combination of intuitive logical reasoning and hierarchical structure will be an important topic for further research. It is expected to meet the needs of human-like driving.
关 键 词:Autonomous vehicles DECISION-MAKING driving behavior human-like driving
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