Abstract

Subway systems are an example of how underground space can contribute to developing more sustainable cities. Their use can be encouraged by integrating other urban transportation modes to provide easy access to the stations, thus facilitating intermodal connectivity. However, few studies have addressed data and modeling issues with multiple modes. This gap, mainly due to the lack of appropriate methods, explains why relationships between traditional and emerging modes remain poorly understood; there is still debate about whether they are complementary or competitive. This paper investigates this question by examining interactions between three alternative modes (bikesharing, free-floating carsharing and taxi) and the Montreal (Quebec, Canada) subway over two months. To this end, several operational passive datasets are merged. A two-level growth model, including both fixed and random effects, is then developed based on time series of daily numbers of boardings at subway stations. This longitudinal model quantifies the effect of various variables (calendar, weather, socio-demographic and economic, network connectivity, land use and built environment attributes) on each station use. The correlations between subway boardings and alternative mode destinations are also measured to detect potential intermodal relations. Finally, a further categorical analysis is conducted by period and station type to specify these interactions in time and space. Results reveal that alternative modes tend to complement the subway in the network periphery (as possible access mode to the subway stations), but may compete with the subway in areas closer to the city center. Such findings could help policymakers determine the location of the mobility services to enhance first-mile subway access, as well as the best mode integration around subway stations in planning strategies.

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