Development of Two-Step Model Predictive Control for an Adaptive Cruise Control System
Article Sidebar
Main Article Content
Abstract
This paper introduces an adaptive cruise control (ACC) of a vehicle based on Model Predictive Control (MPC) as a high-level controller of the ACC system. This high-level controller calculates the desired acceleration for a low-level controller. Also, this paper presents a longitudinal dynamic model of a vehicle consisting of the dynamics of the powertrain and the dynamics of external forces. In addition to establishing a steady spacing distance between two vehicles, avoiding collision, and keeping the acceleration calculation within permitted limits, a method is proposed to speed up the algorithm and reduce the computational effort. Finally, two driving scenarios were used to validate the proposed method, and a comparison of the performance between the original MPC and the speedup MPC was introduced. The simulation results showed that the host vehicle tracked the preceding vehicle accurately for the proposed controller without collision. Moreover, it showed that the execution time required for the proposed method was less than that of the original MPC controller.
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY LICENSE http://creativecommons.org/licenses/by/4.0/
Funding data
-
University of Baghdad
Grant numbers Postgraduate Research Grant (PGRG) No. (18س/211) in (10/01/2023.)
Plaudit
References
Sun C, Chu L, Guo J, Shi D, Li T, Jiang Y. Research on Adaptive Cruise Control Strategy of Pure Electric Vehicle with Braking Energy Recovery. Advances in Mechanical Engineering 2017; 9(11): 1–12. DOI: https://doi.org/10.1177/1687814017734994
Shaleesh IS, Almohammedi AA, Mohammad NI, Ahmad AA, Shepelev V. Cooperation and Radio Silence Strategy in Mix Zone to Protect Location Privacy of Vehicle in VANET. Tikrit Journal of Engineering Sciences 2021; 28(1): 31–39. DOI: https://doi.org/10.25130/tjes.28.1.04
Gustavsson P, Aust ML. In-Vehicle Nudging for Increased Adaptive Cruise Control Use: A Field Study. Journal on Multimodal User Interfaces 2024; 18(1): 1–12. DOI: https://doi.org/10.1007/s12193-024-00434-z
Mohammed D, Nagy V, Márton L, Jagicza M, Józsa D, Horváth B. Efficiency of Adaptive Cruise Control in Commercial Vehicles. Pollack Periodica 2024; 19(1): 1–7. DOI: https://doi.org/10.1556/606.2024.00970
Bageshwar VL, Garrard WL, Rajamani R. Model Predictive Control of Transitional Maneuvers for Adaptive Cruise Control Vehicles. IEEE Transactions on Vehicular Technology 2004; 53(5): 1573–1585. DOI: https://doi.org/10.1109/TVT.2004.833625
Shakouri P, Ordys A, Laila DS, Askari MR. Adaptive Cruise Control System: Comparing Gain-Scheduling PI and LQ Controllers. In: Proceedings of the 18th IFAC World Congress. Milano, Italy; 2011. pp. 12956–12961. DOI: https://doi.org/10.3182/20110828-6-IT-1002.02250
Zhu Z, Bei S, Li B, Liu G, Tang H, Zhu Y, Gao C. Research on Robust Control of Intelligent Vehicle Adaptive Cruise. World Electric Vehicle Journal 2023; 14(5): 127. DOI: https://doi.org/10.3390/wevj14100268
Ahmed DF, Abed IA. Model Predictive Control of a Double Effect Evaporator Via Simulation. Tikrit Journal of Engineering Sciences 2021; 28(1): 49–63. DOI: https://doi.org/10.25130/tjes.28.1.06
Alkareem MS, Abbas NH. Model Predictive Control Design for Electric Vehicle Based on Improved Physics-Inspired Optimization Algorithms. Tikrit Journal of Engineering Sciences 2023; 30(4): 118–126. DOI: https://doi.org/10.25130/tjes.30.4.12
Ali LM, Al-Zughaibi AI. Investigation of Control Behavior via Active Suspension System Considering Time-Delay and Variable Masses. Journal of Engineering 2024; 30(11): 108–127. DOI: https://doi.org/10.31026/j.eng.2024.11.07
Mahadika P, Subiantoro A, Kusumoputro B. Neural Network Predictive Control Approach Design for Adaptive Cruise Control. International Journal of Technology 2020; 11(7): 1451–1462. DOI: https://doi.org/10.14716/ijtech.v11i7.4592
Jai Y, Jibrin R, Itoh Y, Gorges D. Energy-Optimal Adaptive Cruise Control for Electric Vehicles in Both Space Domain based on Model Predictive Control. IFAC-PapersOnLine 2019; 52(5): 316–321. DOI: https://doi.org/10.1016/j.ifacol.2019.09.003
Feng S, Zhao Y, Deng H, Wang Q. Binary Search Tree-Based Explicit MPC Controller Design with Kalman Filter for Vehicular Adaptive Cruise System. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 2021; 235(13): 3183–3196.
Yang Z, Wang Z, Yan M. An Optimization Design of Adaptive Cruise Control System Based on MPC and ADRC. Actuators 2021; 10(7): 144. DOI: https://doi.org/10.3390/act10060110
Zhan Y, Zhai C, Long X, Wang B, Chen H, Chen C. Robust Optimal Adaptive Cruise Control Based on ADP for Intelligent Vehicles under Bounded Disturbances. In: 2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI). IEEE; 2023. pp. 1–6. DOI: https://doi.org/10.1109/CVCI59596.2023.10397428
Mahdinia I, Arvin R, Khattak AJ, Ghiasi A. Safety, Energy, and Emissions Impacts of Adaptive Cruise Control and Cooperative Adaptive Cruise Control. Transportation Research Record: Journal of the Transportation Research Board 2020; 2674(4): 253–267. DOI: https://doi.org/10.1177/0361198120918572
Shakouri P, Ordys A. Nonlinear Model Predictive Control Approach in Design of Adaptive Cruise Control with Automated Switching to Cruise Control. Control Engineering Practice 2014; 26: 160–177. DOI: https://doi.org/10.1016/j.conengprac.2014.01.016
Guo L, Ge P, Sun D, Qiao Y. Adaptive Cruise Control Based on Model Predictive Control with Constraints Softening. Applied Sciences 2020; 10(6): 2117. DOI: https://doi.org/10.3390/app10051635
Nie Z, Farzaneh H. Adaptive Cruise Control for Eco-Driving Based on Model Predictive Control Algorithm. Applied Sciences 2020; 10(15): 5271. DOI: https://doi.org/10.3390/app10155271
Capuano A, Spano M, Musa A, Toscano G, Misul D. Development of an Adaptive Model Predictive Control for Platooning Safety in Battery Electric Vehicles. Energies 2021; 14(13): 3912. DOI: https://doi.org/10.3390/en14175291
Villarreal O, Rossiter JA. A Shifting Strategy for Efficient Block-based Nonlinear Model Predictive Control Using Real-Time Iterations. IET Control Theory & Applications 2020; 14(19): 3275–3284. DOI: https://doi.org/10.1049/iet-cta.2019.0369
Cho D, Hedrick JK. Automotive Powertrain Modeling for Control. Journal of Dynamic Systems, Measurement, and Control 1989; 111(4): 568–576. DOI: https://doi.org/10.1115/1.3153093
Rajamani R. Vehicle Dynamics and Control. 2nd ed. Springer: New York, USA; 2012. DOI: https://doi.org/10.1007/978-1-4614-1433-9
Wong JY. Theory of Ground Vehicles. 4th ed. John Wiley & Sons: Hoboken, NJ, USA; 2008.
Pacejka HB. Tire and Vehicle Dynamics. 3rd ed. Butterworth-Heinemann: Oxford, UK; 2012.
Memon Z, Unar MA, Pathan DK. Parametric Study of Nonlinear Adaptive Cruise Control for a Road Vehicle Model by MPC. Mehran University Research Journal of Engineering & Technology 2012; 31(2): 301–314.
Wang L. Model Predictive Control System Design and Implementation Using MATLAB®. Springer: London, UK; 2009.