Spatio-temporal Heterogeneity Analysis of Transportation Equity Based on GTWR

Online car-hailing services have become increasingly popular for their convenience and efficiency. However, this trend has presented challenges for the elderly population, who may struggle with smartphone usage and thus face difficulties accessing these services. This issue has the potential to worsen existing traffic inequalities. To address this issue, this paper analysis the spatial and temporal heterogeneity of urban transportation pattern of Chengdu City by utilizing traffic flow data and various sources of information such as online car-hailing order data and POI data. The LDA model has been employed to extract semantic and spatial-temporal information from ride-hailing users, which is then integrated into an enhanced spectral clustering algorithm to identify the specific needs of the elderly population. Furthermore, a travel equity index has been established to evaluate the fairness of travel opportunities. The study also investigates the spatio-temporal variations in travel difficulties faced by the elderly group and explores the diversity of factors that influence travel equity using the GTWR regression model. The research findings provide valuable insights into whether the current transportation infrastructure adequately caters to the travel requirements of the elderly group and offer effective recommendations for future transportation planning.