Optimal Lane Change Control of Intelligent Vehicle Based on MPC

被引：0
|
作者：
Zhong, Yihe [1 ,2 ]
Guo, Lulu [1 ,2 ]
Zhang, Yuxiang [1 ,2 ]
Liu, Qifang [1 ,2 ]
Chen, Hong [1 ,2 ]
机构：
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130000, Peoples R China
[2] Jilin Univ, Dept Control Sci & Engn, Changchun 130000, Peoples R China
来源：
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
关键词：
Intelligent vehicle; lane change; nonlinear model predictive control(NMPC); multiple constraints; trajectory planning;
D O I：
10.1109/ccdc.2019.8833003
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper mainly focuses on optimal lane change problem of intelligent vehicles. The multi-constraint model predictive control method is employed to implement real-time trajectory planning without a pre-defined trajectory. The lane change problem can be formulated as a nonlinear optimization problem with multiple constraints and can be solved by real-time optimization of MPC-based controller. To verify the effectiveness of the proposed optimal lane change control controller, Simulink and Carsim co-simulations are conducted in two lane change scenarios under three different working conditions. The simulation results demonstrate that the proposed optimal lane change control controller controller is enough sustainable and applicable for many driving conditions.
引用
收藏
页码：1468 / 1473
页数：6
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