Trajectory Tracking of Distributed-drive Self-driving Vehicle Based on Coordination Between Autonomous Steering and Differential Steering

被引：0
|
作者：
Xu X. [1 ,2 ]
Lu S. [1 ]
Chen L. [1 ,2 ]
Cai Y. [1 ,2 ]
Li Y. [1 ,2 ]
机构：
[1] School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang
[2] Automotive Engineering Research Institute, Jiangsu University, Zhenjiang
来源：
Qiche Gongcheng/Automotive Engineering | 2018年 / 40卷 / 04期
关键词：
Autonomous steering; Coordinated control; Differential steering; Distributed-drive self-driving vehicle; Trajectory tracking;
D O I：
10.19562/j.chinasae.qcgc.2018.04.015
中图分类号：
学科分类号：
摘要：
Distributed-drive self-driving vehicle can assure its trajectory tracking by the associated operation of differential steering and original autonomous steering. On the basis of 2 DOF vehicle kinetics model, a preview time adaptive trajectory tracking scheme is proposed based on model predictive control to meet the prediction requirements in both cornering and straight driving conditions. With consideration of the configuration features of distributed-drive self-driving vehicle and by using differential control between torques in left and right driving wheels based on reference yaw angle, the trajectory tracking can be realized under the condition of constant overall torque requirements of self-driving vehicle. For combining the advantages of above-mentioned two schemes, a coordinated control between trajectory trackings with autonomous steering and differential steering by adopting weighting procedure is put forward, and both Matlab-CarSim co-simulation and real vehicle verification test are conducted. The results show that coordinated control effectively improves the response speed and flexibility of steering, while enhancing the reliability and correctness in the trajectory tracking of self-driving vehicle. © 2018, Society of Automotive Engineers of China. All right reserved.
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页码：475 / 481
页数：6
相关论文
共 9 条
  • [1] Sato M., Yamaoto G., Guj D., Development of wireless in-wheel motor using magnetic resonance coupling, IEEE Transactions on Power Electronics, 31, 7, pp. 5270-5278, (2015)
  • [2] Perezj, Milanes V., Onieva E., Cascade architecture for lateral control in autonomous ground vehicles, IEEE Transactions on Power Electronics, 1, 12, pp. 73-82, (2011)
  • [3] Rastellia J.P., Penasb M.S., Fuzzy logic steering control of autonomous vehicles inside roundabouts, Applied Soft Computing, 35, pp. 662-669, (2015)
  • [4] Perez J., Gajate A., Milanes V., Et al., Design and implementation of a neuro-fuzzy system for longitudinal control of autonomous vehicles, IEEE World Congress on Computational Intelligence WCCI, pp. 1-5, (2010)
  • [5] Hu C., Jing H., Wang R., Et al., Robust H∞ output-feedback control for path following of autonomous ground vehicles, Mechanical Systems and Signal Processing, 70, 71, pp. 414-427, (2016)
  • [6] Falconc P., Borrclli F., Asgari J., Et al., Predictive active steering control for autonomous vehicle systems, IEEE Transactions on Control Systems Technology, 15, 3, pp. 566-580, (2007)
  • [7] Falcone P., Tseng H.E., Borrelli F., Et al., MPC-based yaw and lateral stabilisation via active front steering and braking, Vehicle System Dynamics, 46, pp. 611-628, (2008)
  • [8] Wang R.R., Hu C., Yan F.J., Et al., Composite nonlinear feedback control for path following of four-wheel independently actuated autonomous ground vehicles, IEEE Transactions on Control Systems Technology, 17, 7, pp. 2063-2074, (2016)
  • [9] Gong J., Xu W., Jiang Y., Et al., Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking, Journal of Beijimg Institute of Technology, 24, 4, pp. 441-448, (2015)
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