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Metro trains stop operation during midnight for the maintenance of vehicles and tracks in most cities, where passengers heavily rely on the metro for their daily life. Thus, passengers may miss the last trains when they travel by metro at late night. However, the last trains are especially important because they are the last chances for many passengers to travel by metro. If passengers miss the last trains, they have to choose buses, taxies, or other transport modes to complete their trips. Consequently, it is necessary to optimize the schedule of the last train coordination to meet the demand of passengers at transfer stations during midnight. The passenger demand for last trains is a vital input to deal with the coordination of last train transfers. This paper focuses on forecasting the potential passenger demand of last trains from public transport data including taxi (FCD data) and bus (GPS/smart data) systems. A solution for taxi and bus data is developed to calculate the potential passenger demand for all the transfer directions of the target stations. Then, a model for the coordination of last train transfers based on the potential passenger demand is proposed. The genetic algorithm is applied to solve the model. The effectiveness of the proposed method is evaluated using the Shenzhen metro network with several data on a typical Friday. The research is to provide theoretical guidance and technical reference for the metro operation when to compile the last train schedule. It is supposed to improve the modern operation management level of metro systems.

Coordination of Last Train Transfers Using Potential Passenger Demand From Public Transport Modes