基于障碍物衍生状态格的智能车避障轨迹规划*

doi:10.19562/j.chinasae.qcgc.2019.08.016

Abstract

Abstract: The obstacle avoidance process of intelligent vehicle is studied, a concept of derived state lattice is proposed, and on this basis, a trajectory planning algorithm for obstacle avoidance is determined. The algorithm combines the movement state and location information of target vehicle and obstacles, and converts the problem of seeking the desired obstacle avoidance trajectory in complex road environment into a trajectory planning one between target vehicle and state lattice. The obstacle avoidance trajectory generated by the corresponding algorithm is suitable for multi-obstacle environment with pertinent consideration of the state of obstacles, another concept of state lattice cost is also put forward, and the Dijkstra search algorithm is used to find the optimum from several feasible obstacle avoidance trajectories. The results of simulation show that both the yaw rate and lateral acceleration of vehicle meet the requirements of stability in its obstacle avoidance maneuver, verifying the feasibility of the algorithm. Finally, a CarSim/LabView hardware-in-the-loop test is also conducted to further verify the method proposed, with a conclusion basically agrees with simulation results

Key words: state lattice, obstacle avoidance, trajectory planning, cost of state lattice, search algorithm

Hu Yanping, Tian Bo, Chen Wuwei, Zhang Ruichen. Obstacle Avoidance Trajectory Planning for Intelligent VehicleBased on Derived State Lattice from Obstacle[J].Automotive Engineering, 2019, 41(8): 967-974.

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Obstacle Avoidance Trajectory Planning for Intelligent VehicleBased on Derived State Lattice from Obstacle

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