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 collected, and a survey focusing on three primary aspects was conducted: personal characteristics, travel characteristics, 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, travel purpose, and parking duration exhibit relatively significant absolute values, namely 0.467, 0.359, and 0.454 respectively. Conversely, when transfer frequency serves as the upper nest of the CNL model, income, travel purpose, and trip frequency demonstrate relatively substantial absolute values, namely 0.550, 0.579, and 0.642 respectively. The membership probabilities within the CNL models indicate that travelers are more likely to opt for P&R when transfer convenience 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 models 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.