Comparing Impacts of Access and Egress Distances on Transit Commute Mode Choices in Shanghai Based on the Zone-Based and Node-Based Measures

Abstract

Access/egress distance of public transit is a crucial metric for planning, modeling, and evaluating public transit networks. Commuters' willingness to use public transit is also influenced by access/egress distance. The traditional zone-based calculation method of access/egress distance, which aggregates all origins/destinations in a traffic analysis zone into the zone centroid, may lead to model estimation bias. To mitigate this bias, this study proposed a node-based method to measure access/egress distance by using the nearest road network nodes to substitute the actual origins/destinations. Corresponding to the zone-based and node-based access/egress distance calculation method, two multinomial logit models are developed to analyze the impact of access and egress distances on commuters' mode choice behavior. An empirical study is conducted based on Shanghai's web-based travel survey data and transportation networks. The results show that the node-based model has a better model performance than the zone-based model. The statistical distributions and impacts of access/egress distances vary in the two calculation methods. The findings demonstrate the overestimation of bus access/egress distances and the underestimation of rail egress distance calculated using the aggregated zone-based method when compared with the more refined disaggregated node-based method. The negative impacts of access distance and egress distance on the mode choice of rail and bus in the zone-based method are overestimated compared with the node-based method. Access distance shows a more significant negative effect than egress distance for rail. The proposed node-based method can be further applied in travel demand modeling, including mode choice and traffic assignment.