Simulation on Obstacle Avoidance Tracking of Intelligent Vehicle Based on Model Predictive Control

Authors

Deng Tao, 1. School of Mechatronics & Automobile Engineering, Chongqing Jiaotong University, Chongqing 400074, China;;2. Institute of Aeronautics, Chongqing Jiaotong University, Chongqing 400074, China;
Li Xin, 1. School of Mechatronics & Automobile Engineering, Chongqing Jiaotong University, Chongqing 400074, China;;

Abstract

Abstract: Aiming at the obstacle avoidance and path tracking control of intelligent vehicle, a model predictive controller (MPC) is designed. A layered structure is used in the controller. The high-level layer carries out the local path planning based on non-linear vehicle point mass model and the low-level layer realizes the path tracking based on monorail vehicle dynamics model. Through the joint simulation of Carsim and Matlab software, the controller parameters are optimized on-line by using Particle Swarm Optimization, and the performance of the controller is tested at different speeds. Simulation results show that the controller has good robustness, real-time performance and small tracking error. In the case of single and multiple obstacles, the hierarchical controller could avoid obstacles smoothly and re-track the original path in high accuracy.

Recommended Citation

Tao, Deng and Xin, Li (2020) "Simulation on Obstacle Avoidance Tracking of Intelligent Vehicle Based on Model Predictive Control," Journal of System Simulation: Vol. 32: Iss. 8, Article 16.
DOI: 10.16182/j.issn1004731x.joss.18-0865
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss8/16

First Page

1556

Revised Date

2019-03-03

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.18-0865

Last Page

1566

CLC

U46

Recommended Citation

Deng Tao, Li Xin. Simulation on Obstacle Avoidance Tracking of Intelligent Vehicle Based on Model Predictive Control[J]. Journal of System Simulation, 2020, 32(8): 1556-1566.

DOI

10.16182/j.issn1004731x.joss.18-0865