Data-Driven State-Increment Statistical Model and Its Application in Autonomous Driving

The aim of trajectory planning is to generate a feasible, collision-free trajectory to guide an autonomous vehicle from the initial state to the goal state safely. However, it is difficult to guarantee that the trajectory is feasible for the vehicle and the real path of the vehicle is collision-free...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2018-12, Vol.19 (12), p.3872-3882
Hauptverfasser:	Ma, Chao, Xue, Jianru, Liu, Yuehu, Yang, Jing, Li, Yongqiang, Zheng, Nanning
Format:	Artikel
Sprache:	eng
Schlagworte:	Actuators Autonomous vehicles Collision avoidance Collision dynamics Constraint modelling Curvature data-driven Errors experience cost Kinematics Mathematical model Modelling path prediction Predictive models Statistical analysis Statistical methods Statistical model Statistical models Subspaces Trajectory Trajectory analysis trajectory evaluation Trajectory planning
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