Abstract
For urban rail transit, the spatial distribution of passenger flow in holiday usually differs from weekdays. Holiday destination choice behavior analysis is the key to analyze passengers’ destination choice preference and then obtain the OD (origin-destination) distribution of passenger flow. This paper aims to propose a holiday destination choice model based on AFC (automatic fare collection) data of urban rail transit system, which is highly expected to provide theoretic support to holiday travel demand analysis for urban rail transit. First, based on Guangzhou Metro AFC data collected on New Year’s day, the characteristics of holiday destination choice behavior for urban rail transit passengers is analyzed. Second, holiday destination choice models based on MNL (Multinomial Logit) structure are established for each New Year’s days respectively, which takes into account some novel explanatory variables (such as attractiveness of destination). Then, the proposed models are calibrated with AFC data from Guangzhou Metro using WESML (weighted exogenous sample maximum likelihood) estimation and compared with the base models in which attractiveness of destination is not considered. The results show that theρ2values are improved by 0.060, 0.045, and 0.040 for January 1, January 2, and January 3, respectively, with the consideration of destination attractiveness.
Highlights
Holiday travel demand has obvious characteristics and regularity which is different from weekdays
Based on the data collected by AFC system in Guangzhou Metro, using the weighted exogenous sample maximum likelihood (WESML) method, the destination choice models for the New Year’s days (i.e., January 1, January 2, and January 3) are estimated, respectively
Coefficients of in-vehicle travel time, transfer time, and number of transfers are all negative, which indicates that the values of these variables are inversely proportional to destination choice preference
Summary
Holiday travel demand has obvious characteristics and regularity which is different from weekdays. As passenger flow increases greatly and peak hours are extended during holidays, traffic congestion problems in many cities have become more and more serious. As an important component of urban integrated transport system, undertakes more and more person trips. To organize transportation and adjust operation plan effectively, it is necessary to master the origin-destination (OD) flow distribution firstly, especially when subway network changes and operation plan is adjusted. Since OD flow distribution is just the aggregated expression of individual’s destination choice result, study on holiday destination choice behavior for urban rail transit does great help to capture characteristics of holiday trips and provides theoretic support to holiday travel demand analysis. Holiday-related decision making and behavior are important study topics in the fields of transportation and tourism
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