A rail transit simulation system for multi-modal energy-efficient routing applications
mode - rail, place - north america, operations - scheduling, planning - methods
Eco-routing, energy consumption, multi-modal, rail transit, simulation, smart mobility
The paper develops a continuous rail transit simulator (RailSIM) intended for multi-modal energy-efficient routing applications. RailSIM integrates sophisticated train dynamics and energy models to replicate train motion and energy consumption behavior, respectively. The simulator is calibrated using an off-line optimization procedure to match preprogramed railway schedules by optimizing three model parameters, namely; the segment target speed, the average deceleration level, and the brake force adjustment factor. The objective of the calibration procedure is to match the simulated and actual average running speed for each station-to-station pair. Upon calibration, RailSIM is applied to the Greater Los Angeles area and validated at both the instantaneous and aggregated levels. Results demonstrate that RailSIM is able to produce realistic train dynamics and energy consumption estimates producing a comfortable ride while simultaneously matching the railway schedule. RailSIM is also demonstrated to capture the impact of track gradient on energy outputs. The results also indicate that a perfect match to empirical energy estimates is achieved at an average grade of 1.8%, which is a reasonable approximation of the average track gradient of the testing area. The sensitivity of RailSIM to some of the metro rail parameters is also discussed to account for its applicability to rail transit systems in other cities. Finally, a pilot test of RailSIM implementation in the higher-level multi-modal eco-routing system is performed to demonstrate RailSIM’s feasibility of supporting energy-efficient travel.
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Wang, J., Ghanem, A., Rakha, H., & Du, J. (2021). A rail transit simulation system for multi-modal energy-efficient routing applications. International Journal of Sustainable Transportation, Vol. 15(3), pp. 187-202.