Active Obstacle Avoidance Trajectory Planning for Vehicles Based on Obstacle Potential Field and MPC in V2P Scenario
Author:
Pan Ruoyu1ORCID, Jie Lihua1ORCID, Zhao Xinyu1, Wang Honggang1, Yang Jingfeng2ORCID, Song Jiwei3
Affiliation:
1. School of Communications and Information Engineering and School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710121, China 2. Guangzhou Institute of Industrial Intelligence, Guangzhou 511458, China 3. China Electronics Standardization Institute, Beijing 100007, China
Abstract
V2P (vehicle-to-pedestrian) communication can improve road traffic efficiency, solve traffic congestion, and improve traffic safety. It is an important direction for the development of smart transportation in the future. Existing V2P communication systems are limited to the early warning of vehicles and pedestrians, and do not plan the trajectory of vehicles to achieve active collision avoidance. In order to reduce the adverse effects on vehicle comfort and economy caused by switching the “stop–go” state, this paper uses a PF (particle filter) to preprocess GPS (Global Positioning System) data to solve the problem of poor positioning accuracy. An obstacle avoidance trajectory-planning algorithm that meets the needs of vehicle path planning is proposed, which considers the constraints of the road environment and pedestrian travel. The algorithm improves the obstacle repulsion model of the artificial potential field method, and combines it with the A* algorithm and model predictive control. At the same time, it controls the input and output based on the artificial potential field method and vehicle motion constraints, so as to obtain the planned trajectory of the vehicle’s active obstacle avoidance. The test results show that the vehicle trajectory planned by the algorithm is relatively smooth, and the acceleration and steering angle change ranges are small. Based on ensuring safety, stability, and comfort in vehicle driving, this trajectory can effectively prevent collisions between vehicles and pedestrians and improve traffic efficiency.
Funder
Key Industry Innovation Chain Project of Shaanxi Province Science and Technology Plan Project of Shaanxi Province Key Research and Development plan of Shaanxi Province Scientific Research Program funded by the Shaanxi Provincial Education Department Science and Technology Plan Project of Xi’an National Innovation and Entrepreneurship Training Program for College Students Guangzhou Nansha District Innovation Team Project
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
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