Research on Joint Optimization of Single Train's Delay Reduction and Energy-Saving Operation Trajectory

This study focuses on optimizing urban rail transit operations during emergencies, aiming to reduce train traction energy consumption and expedite delay recovery by jointly optimizing arrival/departure times at each station and the operational trajectory between stations. A 3D STS (Space-Time-Speed) network is created to merge macroscopic train timetable scheduling with microscopic train operation trajectory optimization. By appropriately setting dimension resolutions, the system approximates the train's position, speed, and acceleration, transforming the complex train operation problem into a more manageable path planning challenge. Propose dual objectives: minimize net traction energy and delay time, aiming to reduce overall train operating costs and delays. Weighted summation combines objectives into a single nonlinear optimization. Dynamic programming then tackles the transformed path planning problem. The simulation results of Beijing Yizhuang Line show that while delay increases energy consumption, judicious selection of train operation trajectory can significantly reduce the energy consumption of the train. Factoring in energy consumption yields a 15.43% reduction compared to disregarding it, ensuring more efficient energy use without disrupting normal train operations.