Sun, Hao;
(2025)
Model Predictive Control for Future Interconnected and Green Vehicles.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Urbanization and the steady increase in vehicle numbers are pushing transportation to its limits, resulting in congestion, higher emissions and energy consumption, and safety issues. These have promoted legislation and technologies for cleaner, safer and more efficient transport. Connected and autonomous vehicle (CAV) technology is set to play a major role in the ongoing transport revolution. This thesis focuses on the control design for various CAV control problems with a particular emphasis on model predictive control (MPC). MPC is notable for its ability to effectively handle strict constraints on controls and states, such as powertrain limits, collision avoidance constraints and traffic regulation constraints while achieving near-optimal performance according to an objective function specified by the designer. The first part of this thesis focuses on developing a robust car-following strategy for a single CAV, which achieves the best trade-off between performance optimality and computational efficiency through a novel MPC design. Next, the problem is extended to a platooning problem which involves multiple CAVs in the one-dimensional space. A distributed robust MPC algorithm is designed for platoon formation control. The final part of the thesis focuses on the coordination of multiple vehicles within a two-dimensional space. A hierarchical planning and control framework is developed to solve this, where the motion planner is based on the artificial potential field method, and the control layer employs distributed MPC. Numerical results of all proposed methods are given with comprehensive comparisons with state-of-the-art methods.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Model Predictive Control for Future Interconnected and Green Vehicles |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10203332 |
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