Friction-Adaptive Integrated Position Control for Vehicles on Curved Paths
محورهای موضوعی : robotics
Hadi Sazgar
1
,
ali keymasi khalaji
2
1 - Department of Mechanical Engineering, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran
2 - Department of Mechanical Engineering, Faculty of Engineering,University of Kharazmi, Tehran, Iran
کلید واژه: Integrated Longitudinal and Lateral Control, Kinetic Control, Kinematic Control, Nonlinear Tire, Seven Degrees of Freedom Dynamic Model, Tire-Road Friction Estimation,
چکیده مقاله :
In critical manoeuvres where the maximum tire-road friction capacity is used, the vehicle's dynamic behaviour is highly nonlinear, and there are strong couplings between longitudinal and lateral dynamics. If the tire-road friction conditions change suddenly during these manoeuvres, the vehicle control will be very complicated. The innovation of this research is a control algorithm to manage vehicles on a curved path with sudden tire-road friction change. The main advantage of the proposed controller is that it is robust to the change of the friction coefficient and other unmodeled uncertainties and ensures vehicle stability with low computational volume. The evaluation of the proposed adaptive controller has been done using the full vehicle model in CarSim software and by defining three different manoeuvres, moving at a constant speed on a curved road, lane-change, and lane-change with braking. Also, in the obtained results, the noise of the yaw speed signals and longitudinal and lateral accelerations are considered. The estimation of the longitudinal and lateral velocities is also done using these data. The obtained results showed that the proposed integrated control can manage the highly nonlinear dynamics of the vehicle in the existence of a sudden and significant change in the friction coefficient.
In critical manoeuvres where the maximum tire-road friction capacity is used, the vehicle's dynamic behaviour is highly nonlinear, and there are strong couplings between longitudinal and lateral dynamics. If the tire-road friction conditions change suddenly during these manoeuvres, the vehicle control will be very complicated. The innovation of this research is a control algorithm to manage vehicles on a curved path with sudden tire-road friction change. The main advantage of the proposed controller is that it is robust to the change of the friction coefficient and other unmodeled uncertainties and ensures vehicle stability with low computational volume. The evaluation of the proposed adaptive controller has been done using the full vehicle model in CarSim software and by defining three different manoeuvres, moving at a constant speed on a curved road, lane-change, and lane-change with braking. Also, in the obtained results, the noise of the yaw speed signals and longitudinal and lateral accelerations are considered. The estimation of the longitudinal and lateral velocities is also done using these data. The obtained results showed that the proposed integrated control can manage the highly nonlinear dynamics of the vehicle in the existence of a sudden and significant change in the friction coefficient.
[1] Thorpe, C., Herbert, M., Kanade, T., and Shafter, S., Toward Autonomous Driving: the CMU Navlab, II. Architecture and Systems, IEEE Expert, Vol. 6, No. 4, pp. 44-52, 1991, doi: 10.1109/64.85920.
[2] Dickmanns E. D., Zapp, A., Autonomous High Speed Road Vehicle Guidance by Computer Vision1, IFAC Proceedings Volumes, Vol. 20, No. 5, Part. 4, pp. 221-226, 1987/07/01/ 1987, doi: https://doi.org/10.1016/S1474-6670(17)55320-3.
[3] Ni, J., Hu, J., and Xiang, C., A Review for Design and Dynamics Control of Unmanned Ground Vehicle, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 235, No. 4, pp. 1084-1100, 2021, doi: 10.1177/0954407020912097.
[4] Road Traffic Injuries, https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries accessed.
[5] Administration, N. H. T. S., Motor Vehicle Crashes: Overview, Traffic Safety Facts: Research Note, Vol. 2016, 2016, pp. 1-9.
[6] You, F., Zhang, R., Lie, G., Wang, H., Wen, H., and Xu, J., Trajectory Planning and Tracking Control for Autonomous Lane Change Maneuver Based on The Cooperative Vehicle Infrastructure System, Expert Systems with Applications, Vol. 42, No. 14, pp. 5932-5946, 2015.
[7] Dixit S., et al., Trajectory Planning and Tracking for Autonomous Overtaking: State-of-The-Art and Future Prospects, Annual Reviews in Control, Vol. 45, pp. 76-86, 2018/01/01/ 2018, doi: https://doi.org/10.1016/j.arcontrol.2018.02.001.
[8] Wang, L., Zhao, X., Su, H., and Tang, G., Lane Changing Trajectory Planning and Tracking Control for Intelligent Vehicle on Curved Road, SpringerPlus, Vol. 5, No. 1, 2016, pp. 1150.
[9] Kayacan, E., Ramon, H., and Saeys, W., Robust Trajectory Tracking Error Model-Based Predictive Control for Unmanned Ground Vehicles, IEEE/ASME Transactions on Mechatronics, Vol. 21, No. 2, 2016, pp. 806-814, doi: 10.1109/TMECH.2015.2492984.
[10] Petrov P., Nashashibi, F., Modeling and Nonlinear Adaptive Control for Autonomous Vehicle Overtaking, IEEE Transactions on Intelligent Transportation Systems, Vol. 15, No. 4, pp. 1643-1656, 2014, doi: 10.1109/TITS.2014.2303995.
[11] Wnag, C., Zhao, W., Xu, Z., and Zhou, G., Path Planning and Stability Control of Collision Avoidance System Based on Active Front Steering, Science China Technological Sciences, Vol. 60, No. 8, pp. 1231-1243, 2017.
[12] Rasekhipour, Y., Khajepour, A., Chen, S. K., and Litkouhi, B., A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles, IEEE Transactions on Intelligent Transportation Systems, Vol. 18, No. 5, pp. 1255-1267, 2016.
[13] Suh, J., Chae, H., and Yi, K., Stochastic Model-Predictive Control for Lane Change Decision of Automated Driving Vehicles, IEEE Transactions on Vehicular Technology, Vol. 67, No. 6, pp. 4771-4782, 2018, doi: 10.1109/TVT.2018.2804891.
[14] Cai, J., Jiang, H., Chen, L., Liu, J., Cai, Y., and Wang, J., Implementation and Development of a Trajectory Tracking Control System for Intelligent Vehicle, Journal of Intelligent & Robotic Systems, 2018/05/09 2018, doi: 10.1007/s10846-018-0834-4.
[15] Feng, P., Jin, H., Zhao, L., and Lu, M., Active Lane-Changing Control of Intelligent Vehicle on Curved Section of Expressway, Modelling and Simulation in Engineering, Vol. 2022, 2022.
[16] Xiong, L., Yang, X., Leng, B., Zhang, R., Fu, Z., and Zhuo, G., Integrated longitudinal and lateral control for autonomous vehicles with active load transfer strategy at the handling limits, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 235, No. 4, 2021, pp. 961-974.
[17] Wang, H., Zhang, T., Zhang, X., and Li, Q., Observer-Based Path Tracking Controller Design for Autonomous Ground Vehicles with Input Saturation, IEEE/CAA Journal of Automatica Sinica, Vol. 9, 2022, pp. 1-13.
[18] Hossain, T., Habibullah, H., and Islam, R., Steering and Speed Control System Design for Autonomous Vehicles by Developing an Optimal Hybrid Controller to Track Reference Trajectory, Machines, Vol. 10, No. 6, 2022, pp. 420.
[19] Guo, J., Hu, P., and Wang, R., Nonlinear Coordinated Steering and Braking Control of Vision-Based Autonomous Vehicles in Emergency Obstacle Avoidance, IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No. 11, 2016, pp. 3230-3240, doi: 10.1109/TITS.2016.2544791.
[20] Choi, J., Yi, K., Suh, J., and Ko, B., Coordinated Control of Motor-Driven Power Steering Torque Overlay and Differential Braking for Emergency Driving Support, IEEE Transactions on Vehicular Technology, Vol. 63, No. 2, 2014, pp. 566-579, doi: 10.1109/TVT.2013.2279719.
[21] Funke, J., Brown, M., Erlien, S. M., and Gerdes, J. C., Collision Avoidance and Stabilization for Autonomous Vehicles in Emergency Scenarios, IEEE Transactions on Control Systems Technology, Vol. 25, No. 4, 2017, pp. 1204-1216, doi: 10.1109/TCST.2016.2599783.
[22] Song, J., Development and Comparison of Integrated Dynamics Control Systems with Fuzzy Logic Control and Sliding Mode Control, J. Mech Sci Technol, Vol. 27, No. 6, 2013, pp. 1853-1861.
[23] Zhang, Z., Wang, C., Zhao, W., and Feng, J., Longitudinal and Lateral Collision Avoidance Control Strategy for Intelligent Vehicles, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2022, pp. 09544070211024048.
[24] Chen, R., Chen, Z., Duan, Y., Wu, DJ., and Zhang, Y., Coupled Longitudinal and Lateral Control for Trajectory Tracking of Autonomous Vehicle Based on LTV-MPC Approach, SAE Technical Paper, 0148-7191, 2022.
[25] Li, Z., Chen, Liu, H., Wang, P., and Gong, X., Integrated Longitudinal and Lateral Vehicle Stability Control for Extreme Conditions With Safety Dynamic Requirements Analysis, IEEE Transactions on Intelligent Transportation Systems, 2022.
[26] Li, Z., Wang, P., Cai, S., Hu, X., and Chen, H., NMPC-Based Controller for Vehicle Longitudinal and Lateral Stability Enhancement Under Extreme Driving Conditions, ISA Transactions, Vol. 135, 2023, pp. 509-523.
[27] Attia, R., Orjuela, R., and Basset, M., Combined Longitudinal and Lateral Control for Automated Vehicle Guidance, Vehicle System Dynamics, Vol. 52, No. 2, 2014, pp. 261-279, doi: 10.1080/00423114.2013.874563.
[28] Liu, Y., Pei, Guo X., Chen, C., and Zhou, H., An Integration Planning and Control Method of Intelligent Vehicles Based on The Iterative Linear Quadratic Regulator, Journal of the Franklin Institute, Vol. 361, No. 1, 2024, pp. 265-282.
[29] Jin, X., Wang, Q., Yan, Z., Yang, H., and Yin, G., Integrated Robust Control of Path Following and Lateral Stability for Autonomous in-Wheel-Motor-Driven Electric Vehicles, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2024, pp. 09544070241227266.
[30] Sazgar, H., Azadi, S., and Kazemi, R., and Khalaji, A. K., Integrated Longitudinal and Lateral Guidance of Vehicles in Critical High Speed Maneuvers, Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, Vol. 233, No. 4, 2019, pp. 994-1013, doi: 10.1177/1464419319847916.
[31] Sazgar, H., Azadi, S., and Kazemi, R., Trajectory Planning and Combined Control Design for Critical High-Speed Lane Change Maneuvers, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 234, No. 2-3, 2020, pp. 823-839, doi: 10.1177/0954407019845253.
[32] Sazgar, H., Khalaji, A. K., Nonlinear Integrated Control with Friction Estimation for Automatic Lane Change on The Highways, Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, Vol. 236, No. 3, 2022, pp. 453-469.
[33] Rajamani, R., Vehicle Dynamics and Control. Springer Science & Business Media, 2011.
[34] Kiencke, U., Nielsen, L., Automotive Control Systems: for Engine, Driveline, and Vehicle, ed: IOP Publishing, 2000.
[35] Pacejka H., Besselink, I., Tire, and Vehicle Dynamics. Elsevier Science, 2012.
[36] Hwan J. J., et al., Optimal Motion Planning with the Half-Car Dynamical Model for Autonomous High-Speed Driving, in 2013 American Control Conference, Vol. 17-19, 2013, pp. 188-193, doi: 10.1109/ACC.2013.6579835.
[37] Velenis, E., Tsiotras, P., and Lu, J., Optimality Properties and Driver Input Parameterization for Trail-Braking Cornering, European Journal of Control, Vol. 14, No. 4, 2008, pp. 308-320.
[38] Bakker, E., Nyborg, L., and Pacejka, H. B., Tyre Modelling for Use in Vehicle Dynamics Studies, 1987. [Online], Available: https://doi.org/10.4271/870421.
[39] Milanés, V., González, C., Naranjo, J., Onieva, E., and De Pedro, T., Electro-Hydraulic Braking System for Autonomous Vehicles, International Journal of Automotive Technology, Vol. 11, No. 1, 2010, pp. 89-95.
[40] Khaleghian, S., Emami, A., and Taheri, S., A Technical Survey on Tire-Road Friction Estimation, Friction, Vol. 5, No. 2, 2017, pp. 123-146.
[41] Singh, K. B., Arat, M. A., and Taheri, S., Literature Review and Fundamental Approaches for Vehicle and Tire State Estimation, Vehicle System Dynamics, 2018, pp. 1-23.
[42] Guo, H., Yin, Z., Cao, D., Chen, H., and Lv, C., A Review of Estimation for Vehicle Tire-Road Interactions Toward Automated Driving, IEEE Transactions on Systems, Man, and Cybernetics: Systems, No. 99, 2018, pp. 1-17.
[43] Peng, Y., Chen, J., and Ma, Y., Observer-Based Estimation of Velocity and Tire-Road Friction Coefficient for Vehicle Control Systems, Nonlinear Dynamics, Journal article, Vol. 96, No. 1, 2019, pp. 363-387, doi: 10.1007/s11071-019-04794-0.
[44] Beal, C. E., Rapid Road Friction Estimation using Independent Left/Right Steering Torque Measurements, Vehicle System Dynamics, 2019, pp. 1-27, doi: 10.1080/00423114.2019.1580377.
[45] Cerone, V., Milanese, M., and D. Regruto, Combined Automatic Lane-Keeping and Driver's Steering through a 2-DOF Control Strategy, IEEE Transactions on Control Systems Technology, Vol. 17, No. 1, 2008, pp. 135-142.
