Trajectory Planning and Optimal Lateral Stability Control under Multiple Barriers for Intelligent Vehicle

Zhonghua Zhang, Xuecai Yu^*, Zhijie Jin, Yejun Ying, Rongwei Hua, Xuwei Lin

School of Engineering, Zhejiang Normal University, Jinhua, China.

DOI: 10.4236/wjet.2015.33011                

Abstract

Based on analysis and evaluation on the circular, cosine type, constant-speed offset type and ladder type lane change trajectory, this paper proposes an intelligent vehicle lane change trajectory model under multiple barriers, proposes its dynamic constraints in the light of the cellular automata theory, obtains the desired lane change trajectory using this method, and finally changes into a simple coefficient selection problem. Secondly, based on the quadratic optimal control theory, this paper proposes a state space analysis method of intelligent vehicle lateral control, and designs an optimal controller for lateral stability of H2 vehicles. The computer simulation results show that compared with other vehicle trajectory methods, the method in this paper is able to simply and rapidly describe the trajectory, and can describe the intelligent vehicle lane change trajectory under a variety of situations, wherein the controller is reliable and capable of fast convergence.

Keywords

Intelligent Vehicle, Motion Planning, Optimal Control, Cellular Automata, Computer Simulation

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Garnell, P. (1980) Guided Weapon Gontrol Systems. Pergamon Press, Oxford.
[2]	Jiang, Z.P. (1997) Tracking Control of Mobile Robots: A Case Study in Backstepping. Automation, 33, 1393-1399. http://dx.doi.org/10.1016/S0005-1098(97)00055-1
[3]	Frerro, R. (1995) Control of a Nonholorxrmic Mobile Robot: Backstepping Kinematics into Dynamics. IEEE Proceedings of 34th Conference on Decision and Control, 3805-3810.
[4]	Takemura, N., Nakamura, Y. and Ishiguro, H. (2011) A Path Planning Method for Human Tracking Agents Using Variable-Term Prediction Based on Dynamic K-Nearest Neighbor Algorithm. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, 25-30 September 2011, 2867-2872.
[5]	Tomar, R.S., Verma, S., Kushwah, R.S. and Tomar, G.S. (2013) Collision Avoidance Warning for Safe Lane Change. 2013 International Conference on Communication Systems and Network Technologies (CSNT), 385-389.
[6]	Vale, A., Fonte, D., Valente, F. and Ribeiro, I. (2014) Trajectory Optimization for Autonomous Mobile Robots in ITER. Robotics and Autonomous Systems, 62, 871-888. http://dx.doi.org/10.1016/j.robot.2014.01.007
[7]	You, F., Wang, R. and Zhang, R. (2013) Study of System Identification and Control Algorithm for Intelligent Vehicle. China Journal of Highway and Transport, 21, 111-116.
[8]	Zhang, R.H., Ge, P.S., Zhou, X., et al. (2013) An Method for Vehicle-Flow Detection and Tracking in Real-Time Based on Gaussian Mixture Distribution. Advances in Mechanical Engineering, 2013, Article ID: 861321.
[9]	You, F., Zhang, R.H., Wang, H.W., et al. (2014) Dynamic Model and Tracking Control of Tractor Semi-Trailer Vehicle with Underactuated System. Journal of Jilin University (Engineering and Technology Edition), 44, 1296-1302.
[10]	Kim, S., Oh, H., Suk, J. and Tsourdos, A. (2014) Coordinated Trajectory Planning for Efficient Communication Relay Using Multiple UAVs. Control Engineering Practice, 29, 42-49. http://dx.doi.org/10.1016/j.conengprac.2014.04.003