Conceptual Framework for Maximizing Service Catchment Area Between Rail Transit and Feeder Service Using Spatial Temporal Regression Technique

Abstract

Abstract The move towards a more sustainable transport mode is crucial in the Klang Valley by incorporating feeder services to rail network stations. Feeder services will complement the expanding rail transits network and deliver connectivity for areas not covered within rail stations. Past literatures found that feeder services were ineffective during rail breakdown as feeder service was not going or stopping to where it was intended to. Feeder service can be allocated more effectively if we have better idea of targeted service area. Urban planners now have access to a variety of urban analytics because of technological advancements and the rise of smart cities. Data generated are produced across numerous locations and at diverse time scales, providing a significant possibility for data mining to uncover insightful information when both space and time are considered. This study will attempt to assess the community’s accessibility to rail transit through feeder service in Klang Valley. In achieving this a conceptual framework is developed within the objectives of this study which are firstly, to identify built environment factors that influence ridership around transit stations. Secondly, to determine the spatial -temporal relationship between built environment and transit ridership of feeder service and rail transits. Next, the station-level spatial and temporal variability of ridership data between feeder service to rail network is examined. Finally, as the main finding of this study, a framework in maximizing a service catchment transportation service for feeder service and rail transit will be developed. In doing that, the conceptual framework approach is by addressing numerical analytical technique in geographic data, by using spatial temporal regression. This study aspires to provide planning departments and transit agencies with useful guidance to execute targeted policies and develop a sustainable and efficient feeder service coverage area to support rail transits by looking at both spatial and temporal scales.