基于客流推算的城市轨道交通出行效用函数参数标定方法OA

To address the lack of reliable support for parameter calibration of utility functions in urban rail transit passenger flow assignment models and the insufficient consideration of heterogeneity in pas-senger travel behavior,this study proposes a parameter calibration method for the travel utility func-tion based on passenger flow estimation.First,feasible routes are identified by integrating the network structure and train timetables,and passenger flow path inference is conducted using Auto Fare Collec-tion(AFC)data.Then,the factors influencing route choice in urban rail transit are analyzed,and a generalized cost function incorporating travel time,number of intermediate stations,and number of transfers is constructed.An optimization model is developed to calibrate utility function parameters,and the Logit model is adopted for passenger flow assignment.Finally,multiple sets of parameters are calibrated using both observed survey data and estimated passenger flow data,and the assignment per-formance under different data sources and calibration strategies is compared.The applicability of the proposed method under different passenger flow characteristics is also evaluated.The research results show that parameter calibration based on AFC-derived passenger flow estimation yields significantly higher assignment accuracy than calibration based on survey data.Grouping Oorigin-Destination(OD)pairs by travel duration for parameter calibration effectively reduces discrepancies in bidirectional sec-tion flows and total network transfer volume.In the case study,the average discrepancy rates of bidi-rectional section passenger flows of the target lines decrease from 3.79%and 2.70%to 3.65%and 1.86%,respectively,while the discrepancy rate of total network transfer volume is reduced from 5.59%to 5.16%,indicating improved model accuracy.The proposed calibration method demon-strates strong accuracy and stability under different passenger flow patterns and path selection rules on both weekdays and holidays,making it adaptable to diverse urban rail transit travel scenarios.