Method for Calculating Adaptability between Capability Supply and Passenger Demand in Urban Rail Transit

Abstract

The adaptability between capacity supply and passenger demand in urban rail transit is decreasing because of capability supply not accounting for the unbalanced spatial and temporal distribution of passenger flow. It is necessary to study a method for calculating adaptability to scientifically identify the spatial and temporal inconsistencies between capacity supply and passenger demand. We defined adaptability as consisting of four indicators indexes: the average load factor of the line, which is used to measure the level of capacity utilization, and the average ride comfort, the total number of people retention at the station, and the average waiting time, which are used to measure the level of passenger service. The criteria importance through intercriteria correlation (CRITIC)-technique for order preference by similarity to ideal solution (TOPSIS) method is used for a comprehensive assessment of adaptability. To calculate the above four indicators, a passenger-train interaction model is constructed to simulate the interaction process between passengers and trains. Validation is done with weekday train schedules and passenger flow data in the northbound direction of a line. Results indicate that the morning peak hours (6:00–7:00 and 9:00–10:00) and the evening peak hours (16:00–19:00 and 19:00–20:00) have an adaptation degree above 60%, indicating better adaptability. Other periods have an adaptation degree below 60%, indicating poorer adaptability. The paper proposes response strategies for the morning peak hours with lower adaptability, including adjusting train intervals and short turn mode, to improve adaptability between capacity and passenger flow.