Learning From Naturalistic Driving Data for Human-Like Autonomous Highway Driving
IEEE Transactions on Intelligent Transportation Systems(2021)
摘要
Driving in a human-like manner is important for an autonomous vehicle to be a smart and predictable traffic participant. To achieve this goal, parameters of the motion planning module should be carefully tuned, which needs great effort and expert knowledge. In this study, a method of learning cost parameters of a motion planner from naturalistic driving data is proposed. The learning is achieved b...
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关键词
Trajectory,Planning,Cost function,Autonomous vehicles,Robots,Automobiles
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