Abstract
The escalating frequency of fatal crashes has led to an enhanced focus on road safety, resulting in the creation of diverse driver assistance systems. Several instances of these systems encompass active braking, lane departure warning, cruise control, lane maintaining, and numerous additional examples. However, the primary objective of this research is to examine the effectiveness and reliability of a model predictive control (MPC) and a proportional integral derivative (PID) control in executing lane keeping maneuvers within an autonomous vehicle. In this paper, a custom controller for autonomous lane-changing maneuvers is developed by utilizing the Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) controllers. Different trajectory models are employed to assess the overall effectiveness of the designed model, showcasing its superiority over existing models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmed, H.U., Huang, Y., Lu, P., Bridgelall, R.: Technology Developments and Impacts of Connected and Autonomous Vehicles: An Overview. 1, 382–404, Smart Cities 5, USA (2022)
Yun, H., Park, D.: Virtualization of Self-Driving Algorithms by Interoperating Embedded Controllers on a Game Engine for a Digital Twining Autonomous Vehicle. 17, 2102, Electronics 10, USA (2021)
Cui, H., et al.: Deep kinematic models for kinematically feasible vehicle trajectory predictions. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 10563–10569. IEEE, Paris (2020)
Sazid, M.M., Haider, I., Rahman, M.E., Nuhel, A.K., Islam, S., Islam, M.R.: Developing a solar powered agricultural robot for autonomous thresher and crop cutting. In: 2022 12th International Conference on Electrical and Computer Engineering (ICECE), pp. 144–147, IEEE Dhaka, Bangladesh (2022)
Ganga, G., Dharmana, M.M.: MPC controller for trajectory tracking control of quadcopter. In: 2017 International Conference on Circuit Power and Computing Technologies (ICCPCT), pp. 1–6. IEEE, Kollam, India (2017)
Zohu, Z., Rother, C., Chen, J.: MPC Controller for trajectory tracking control of quadcopter. In: ICCPCT, pp.1–6, IEEE (2017)
Chen, S., Chen, H., Negrut, D.: Implementation of MPC-based path tracking for autonomous vehicles considering three vehicle dynamics models with different fidelities. Automotive Innovation 3, 386–399 (2020)
Nuhel, A.K., Sazid, M.M., Bhuiyan, M.N.M., Arif, A.I., Roy, P.H., Islam, M.R.: Developing a Self-Driving Autonomous Car using Artificial Intelligence Algorithm. In: 2022 6th International Conference on Electronics, Communication and Aerospace Technology, pp. 1240–1249. IEEE, India (2022)
Alcalá, E., Puig, V., Quevedo, J.: LPV-MPC control for autonomous vehicles. IFAC-PapersOnLine 52(28), 106–113 (2019)
Massaro, M., Limebeer, D.J.N.: Minimum-lap-time optimisation and simulation. Veh. Syst. Dyn. 59(7), 1069–1113 (2021)
Nuhel, A.K., Sazid, M.M., Bhuiyan, M.N.M., Arif, A.I.: Designing and performance- analysis of a 3 DOF robotic manipulator arm and its higher order integration for 7 DOF robotic arm. In: 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1–6, IEEE, Dhaka, Bangladesh (2022)
Mozaffari, S., Al-Jarrah, O.Y., Dianati, M., Jennings, P., Mouzakitis, A.: Deep learning-based vehicle behavior prediction for autonomous driving applications: a review. IEEE Trans. Intell. Transp. Syst. 23(1), 33–47 (2020)
Peicheng, S., Li, L., Ni, X., Yang, A.: Intelligent vehicle path tracking control based on improved MPC and hybrid PID. IEEE Access 10, 94133–94144 (2022)
Williams, T., et al.: Transportation planning implications of automated/connected vehicles on Texas highways. No. FHWA/TX-16/0–6848–1. Texas A&M Transportation Institute (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Nuhel, A.K., Al Amin, M., Paul, D., Bhatia, D., Paul, R., Sazid, M.M. (2024). Model Predictive Control (MPC) and Proportional Integral Derivative Control (PID) for Autonomous Lane Keeping Maneuvers: A Comparative Study of Their Efficacy and Stability. In: Pareek, P., Gupta, N., Reis, M.J.C.S. (eds) Cognitive Computing and Cyber Physical Systems. IC4S 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 537. Springer, Cham. https://doi.org/10.1007/978-3-031-48891-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-48891-7_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48890-0
Online ISBN: 978-3-031-48891-7
eBook Packages: Computer ScienceComputer Science (R0)