Two-step Passenger-to-Train and Route Assignment Model for Urban Rail Transit

Abstract

Accurate passenger flow assignment results are crucial for the operational organization of urban rail transit. However, because of barrier-free transfer, the transfer information of passengers is not recorded. The paper proposes the two-step passenger-to-train and route assignment (TPTRA) model to address this issue. Each passenger is assigned to the trains and one route considering the complex transfer situation using TPTRA compared with the existing passenger-to-train model. Constraints on passengers, trains, and routes are constructed based on a large amount of real automatic fare collection data, train schedules, and metro topology networks to improve accuracy and transferability over traditional survey-based methods. The generalized logistic is first used to evaluate the egress time, access time, and transfer time distributions. Finally, TPTRA is developed based on the constraints and distributions. The model estimates the probability of passengers choosing the feasible routes and boarding the first train. It also calculates transfer passenger flow values and the probability of passengers being left behind. The analysis demonstrates a notable enhancement in the accuracy of the egress time distribution fitting using the generalized logistic distribution, with an improvement of 84.41% compared with the lognormal distribution and 15.78% compared with the normal distribution. Furthermore, the model’s effectiveness is validated through sectional passenger flow comparisons, yielding R-squared values between 0.847 and 0.902, indicating the effectiveness and reliability of the TPTRA model.

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