Abstract
With the continuous progress of computer technology and sensor technology, the automobile has gradually developed into an agent with the functions of interaction, perception, planning, and execution, which has laid a foundation for the rapid development of the automobile industry in the direction of vehicle intelligent networking with automatic driving as the core. Based on explicit MPC, this paper studies and analyzes the local path planning (LPP) and path tracking (PT) control of autonomous vehicles, and discusses the local obstacle avoidance path planning of autonomous vehicles based on MPC and the PT design of autonomous vehicles based on MPC. Through the simulation experiment, combined with the current vehicle state information, the optimal control quantity sequence is calculated to realize the vehicle tracking the local obstacle avoidance reference path. The experimental results show that MPC can improve the tracking accuracy when it is applied to PT.
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