关键词: 人工鱼群算法, 车联网, 轨迹规划, 安全驾驶, 速度诱导

Abstract: Concerning large fluctuation in velocity and trajectory of typical vehicle trajectory planning methods in the Internet of Vehicles (IoV) environment, a new vehicle trajectory planning method based on improved artificial fish swarm algorithm was proposed. Using Delicated Short Range Communications (DSRC) application scenario as a design platform, taking the optimal speed as the core calculation basis, the optimal trajectory of the vehicle was analyzed and achieved. Firstly, the advantages and disadvantages of artificial fish swarm algorithm in the application scene of IoV were analyzd, and an improved artificial fish swarm algorithm was proposed by introducing universal gravitational model and obstacle avoidance mode control. Secondly, the force constraints of the vehicle in the IoV application scenario were analyzd, and the self-organizing behavior control strategy of networked vehicle was used to derive the optimal speed. Finally, real-time trajectory guidance and trajectory obstacle avoidance control planning for the vehicles was realized based on the optimal speed. The simulation results show that after using the trajectory planning model, the driving speed of the vehicle is more stable, the trajectory is less fluctuating, and zero collision can be achieved. In the case of multi-vehicle encounters, when the number of test vehicles is between 2 and 40, compared to the original artificial fish swarm algorithm and firefly algorithm, the iteration number of vehicular trajectory planning method using the improved artificial fish swarm algorithm was reduced,and iteration efficiency increased by 3 to 7 times and 4 to 8 times. The more vehicles, the more obvious the improvement of iteration efficiency.

Key words: artificial fish algorithm, Internet of vehicles, trajectory planning, safe driving, induced velocity