Print Email Facebook Twitter Modeling and Efficient Passenger-Oriented Control for Urban Rail Transit Networks Title Modeling and Efficient Passenger-Oriented Control for Urban Rail Transit Networks Author Liu, X. (TU Delft Team Bart De Schutter) Dabiri, A. (TU Delft Team Azita Dabiri) Wang, Yihui (Beijing Jiaotong University) De Schutter, B.H.K. (TU Delft Delft Center for Systems and Control) Department Delft Center for Systems and Control Date 2023 Abstract Real-time timetable scheduling is an effective way to improve passenger satisfaction and to reduce operational costs in urban rail transit networks. In this paper, a novel passenger-oriented network model is developed for real-time timetable scheduling that can model time-dependent passenger origin-destination demands with consideration of a balanced trade-off between model accuracy and computation speed. Then, a model predictive control (MPC) approach is proposed for the timetable scheduling problem based on the developed model. The resulting MPC optimization problem is a nonlinear non-convex problem. In this context, the online computational complexity becomes the main issue for the real-time feasibility of MPC. To reduce the online computational complexity, the MPC optimization problem is therefore reformulated into a mixed-integer linear programming (MILP) problem. The resulting MILP problem is exactly equivalent to the original MPC optimization problem and can be solved very efficiently by existing MILP solvers, so that we can obtain the solution very fast and realize real-time timetable scheduling. Numerical experiments based on a part of Beijing subway network show the effectiveness and efficiency of the developed model and the MILP-based MPC method. Subject Model predictive controlreal-time timetable schedulingtime-dependent passenger origin-destination demandurban rail transit To reference this document use: http://resolver.tudelft.nl/uuid:1ad6c54e-35b6-4479-b756-a3e6040d5cb4 DOI https://doi.org/10.1109/TITS.2022.3228340 ISSN 1524-9050 Source IEEE Transactions on Intelligent Transportation Systems, 24 (3), 3325-3338 Part of collection Institutional Repository Document type journal article Rights © 2023 X. Liu, A. Dabiri, Yihui Wang, B.H.K. De Schutter Files PDF Modeling_and_Efficient_Pa ... tworks.pdf 1.83 MB Close viewer /islandora/object/uuid:1ad6c54e-35b6-4479-b756-a3e6040d5cb4/datastream/OBJ/view