Affiliations: [a] School of Mechanical Engineering, Hebei University of Technology, Tianjin, China
| [b] Automotive Engineering Department, Xingtai Polytechnic College, Xingtai, China
| [c] Intelligent Network Department, Automotive Engineering Research Institute, China Automotive Technology and Research Center, Tianjin, China
| [d] Faculty of Computers and Information, Mansoura University, Egypt
Abstract: Specific to the trajectory planning of intelligent electric vehicles with multi-constraints in some unknown environment, using rolling optimization principle of predictive model control for reference, an online trajectory planning algorithm based on a rolling window is proposed. Making full use of the local environmental information measured in real-time by intelligent electric vehicle, the path of continuous curvature is generated in the planning window by the Quintic Bézier curve and is optimized by the sequential quadratic planning algorithm. Furthermore, the optimal speed sequence for a given path is planed using the S-shaped curve velocity algorithm. Combining with the actual application scenario of an intelligent electric vehicle, the algorithm is simulated, and the trajectory planning experiment is carried out based on the actual environmental data. The results show that a safe trajectory with continuous curvature and optimal speed can be produced by using this algorithm in some unknown environment scenarios.
Keywords: Intelligent electric vehicle, rolling window, trajectory planning, quintic
bézier curve, s-shaped curve
