Spatiotemporal Segmentation of Home-based Trips by the Demand Responsive Transportation Accessible Vehicles: a Case Study of Toronto

In order to improve accessible transportation services to individuals with disability, first we need to understand what services are currently provided to them. This research is concerned with the scale of such services provided to individuals with disability and their spatial dynamics in the City of Toronto based on Wheel-Trans customer trip data. In particular, I look at the home-based trips and segmenting them based on the three most widely used vehicle types within the context of a demand responsive transportation system. The temporal segmentation of the data is based on the monthly number of trips which identifies a seasonal pattern in the utilization of all three services. Spatial analysis of the points of origin and destination is performed using Moran’s I and Getis-Ord General G which identifies presence of spatial autocorrelation. Then local Moran’s I was employed to find local clusters in the data with respect to each of the services as well as the overall pattern. This study identifies that the spatial patterns in downtown Toronto follow a non-random process, and therefore it is always marked as the significant destination for the majority of the trips made by customers of Wheel-Trans. Additionally, this study finds that majority of the mobility services supplied to people with disabilities in the City of Toronto are supplied by non-municipal mobility service providers operating under contract with the Toronto Transit Commission using smaller accessible vehicles.