Adaptive Lane-Change Trajectory Planning and MPC-Based Tracking Control for Rear-End Collision Avoidance Under Varying Road Friction Conditions
Abstract
Rear-end collision avoidance is one of the most critical active safety features in modern vehicles. This paper proposes a steering-based rear-end collision avoidance strategy designed to enhance vehicle safety and stability under various driving conditions. Collision avoidance is achieved through lateral maneuvering using a smooth and feasible trajectory generated by a quintic polynomial. To ensure dynamic feasibility and vehicle stability, the minimum feasible lane change time is determined according to allowable lateral acceleration limited by the available tire-road friction. Unlike conventional approaches that assume a fixed lane-change time, the proposed method adapts the maneuver according to road conditions, thereby reducing the risk of instability, particularly on low-friction roads. To accurately track the generated trajectory, a Model Predictive Control (MPC) controller is employed. Simulation results using MATLAB/Simulink demonstrate that the proposed approach successfully achieves collision avoidance while maintaining vehicle stability and acceptable ride comfort under different driving conditions. Furthermore, a comparative analysis with a conventional fixed lane-change strategy shows that the proposed adaptive approach significantly improves vehicle stability and path tracking performance under low-friction road conditions. Specifically, at μ = 0.4, the adaptive strategy maintains tire slip angle within ±1.5°, well below the 3°–4° linear stability limit and reduces peak acceleration by 44% compared to the fixed lane-change strategy. The results confirm that the proposed approach effectively prevents excessive lateral acceleration and vehicle instability, ensuring safe obstacle avoidance on wet roads.
Keywords
References
- Elsagheer Mohamed SA, Alshalfan KA, Al-Hagery MA, Ben Othman MT. Safe driving distance and speed for collision avoidance in connected vehicles. Sensors. 2022;22(18):7051. https://doi.org/10.3390/s22187051
- Cui Q, Ding R, Wu X, Zhou B. A new strategy for rear-end collision avoidance via autonomous steering and differential braking in highway driving. Vehicle System Dynamics. 2020;58(6):955-986. https://doi.org/10.1080/00423114.2019.1602732
- Seyedi M, Koloushani M, Jung S, Vanli A. Safety assessment and a parametric study of forward collision-avoidance assist based on real-world crash simulations. Journal of Advanced Transportation. 2021;2021:4430730. https://doi.org/10.1155/2021/4430730
- Wang J, Teng F, Li J, Zang L, Fan T, Zhang J, et al. Intelligent vehicle lane change trajectory control algorithm based on weight coefficient adaptive adjustment. Advances in Mechanical Engineering. 2021;13(3):16878140211003393. https://doi.org/10.1177/16878140211003393
- Chen R, Hu J, Xu W. An RRT-Dijkstra-based path planning strategy for autonomous vehicles. Applied Sciences. 2022;12(23):11982. https://doi.org/10.3390/app122311982
- Zhu DD, Sun JQ. A new algorithm based on Dijkstra for vehicle path planning considering intersection attribute. IEEE Access. 2021;9:19761-19775. https://doi.org/10.1109/ACCESS.2021.3053169
- Chen J, Zhao P, Mei T, Liang H. Lane change path planning based on piecewise Bezier curve for autonomous vehicle. In: 2013 IEEE International Conference on Vehicular Electronics and Safety (ICVES); 2013 Jul 28-30. p. 17-22. https://doi.org/10.1109/ICVES.2013.6619595
- Wang Z, Deng W, Zhang S, Shi J. Vehicle automatic lane changing based on model predictive control. SAE International Journal of Passenger Cars - Electronic and Electrical Systems. 2016;9(1):231-236. https://doi.org/10.4271/2016-01-0142
Details
Primary Language
English
Subjects
Automotive Safety Engineering, Automotive Engineering (Other)
Journal Section
Research Article
Authors
Ali Abd-El-Tawwab
This is me
0009-0003-4497-988X
Egypt
Mostafa Makrahy
This is me
0000-0002-5599-049X
Egypt
Mohamed Hassan
This is me
0000-0002-1965-2821
Egypt
Publication Date
October 3, 2026
Submission Date
June 5, 2026
Acceptance Date
July 10, 2026
Published in Issue
Year 2026 Volume: 10 Number: 3
