Optimal Train Skip-Stop Operation at Urban Rail Transit Transfer Stations for Nonrecurrent Extreme Passenger Flow Mitigation

Abstract

Urban rail transit transfer stations are key facilities for gathering and switching passenger flow. High passenger demand coupled with nonrecurrent events (e.g., train delays) may cause extreme passenger flow and density within the station, resulting in high risks of disastrous consequences (e.g., stampedes). This paper proposes multiline coordinated train skip-stop strategies to prevent extreme passenger flow and densities at transfer stations. A binary programming model is developed and solved by the genetic algorithm (GA) to best plan the multiline skip-stop strategy. Case studies using real passenger demand and train data are performed to verify the model and the algorithm. Results indicate that the application of the proposed skip-stop strategy can significantly reduce the total passenger waiting and delay time at transfer stations, therefore lowering the risk of disastrous consequences.