Data-Driven Mobility Hub Location Selection and Design: A GIS-Based Approach to Support Sustainable Travel Behavior

Abstract

Car dependency in urban areas remains a major challenge for sustainable transport planning, increasing the need for attractive alternative transport solutions, such as mobility hubs. Mobility hubs are strategically located and include private and shared transport modes with easy transfers, as well as the supporting services needed to simplify the daily life of its users. In this study, a location selection methodology is developed and presented in this study, along with design guidelines. The main objective of the study is to reduce car dependency for the commuting population by providing opportunities for multimodal travel along their current transport routes. Furthermore, factors that affect travel behavior in different sociodemographic groups and how they can be incorporated into the location selection process were of interest. A literature review was conducted where topics such as drivers for car commut ing, modal shift, sociodemographic factors, current mobility hub location selection processes and commonly included elements were researched. The findings were sub sequently applied in QGIS, where synthetic traffic flow data, infrastructure con nected to pedestrians, bicycles, cars, and public transport, and sociodemographic statistics are combined into a spatial scoring framework consisting of traffic flow, catchment potential, connectivity, and sociodemographic suitability. The findings include four specific locations within two corridors on major highways in western Gothenburg, indicating that intercepting commuters before entering the city center could contribute to reduced car dependency. The study highlights the importance of combining behavioral and sociodemographic factors with spatial accessibility when determining suitable locations for mobility hubs. The developed methodology can be adapted for use in other municipalities and planning contexts.