An Analysis of Park and Ride Choice Behavior around Rail Stations Based on Cross-Nested Logit Model
This study aims to optimize the configuration and operation of park and ride(P&R)facilities around rail stations by investigating traveler choice behavior at rail stations in Nanjing.The data on P&R facility usage was col-lected,and a survey focusing on three primary aspects was conducted:personal characteristics,travel characteris-tics,and P&R intentions.Utilizing this data,nine key variables influencing P&R choice behavior were identified.The study incorporates factors such as transfer mode,time,and distance to examine the nuances of traveler choices.Cross-nested Logit(CNL)models with transfer convenience and times as the primary nests were developed to analyze these behaviors under varying conditions.The analysis reveals that income and travel purpose significantly impact P&R choice,with the magnitude of these effects varying between models prioritizing transfer convenience versus those emphasizing transfer times.When transfer convenience is the upper nest of the CNL model,parameters for income,trav-el purpose,and parking duration exhibit relatively significant absolute values,namely 0.467,0.359,and 0.454 respective-ly.Conversely,when transfer frequency serves as the upper nest of the CNL model,income,travel purpose,and trip fre-quency demonstrate relatively substantial absolute values,namely 0.550,0.579,and 0.642 respectively.The member-ship probabilities within the CNL models indicate that travelers are more likely to opt for P&R when transfer conve-nience moderately increases or transfer frequency moderately decreases,with the highest membership degrees being 0.399 and 0.464,respectively.This suggests a preference for balanced transfer conditions.Furthermore,the CNL mod-els demonstrate an approximately 10%improvement in prediction accuracy over nested and multiple Logit models,underscoring their efficacy in capturing travelers'sensitivities to different transfer scenarios.
urban rail transitpark and ridechoice behaviorcross-nested Logit model
国家科技期刊平台
NSTL
万方数据
