Modelling and Analysis of Walk and Intelligent Feeder Service Based Last Mile Connectivity to Metro Stations.

Last mile connectivity refers to the critical link that connects commuters from their homes or workplaces to the nearest public transportation hubs, enhancing accessibility and reducing reliance on private vehicles. Existing last mile connectivity solutions to access public transportation often face limitations such as limited coverage areas, inefficient routing and lack of integration with different modes, poor quality of service for commuters, hindering seamless and efficient commuting experience. In this paper, an intelligent feeder service is designed to enhance last mile connectivity to metro stations. An online algorithm is developed to recommend suitable boarding junctions for commuters to join shared rides. The algorithm also assists vehicles in navigating the road network by suggesting starting junctions, en route stops, and diversions that maximize the likelihood of picking up commuters, while satisfying the constraints related to the walk distance and additional time required in a shared ride. The performance of proposed system is evaluated for the amount of walking, travel time and waiting time of commuters, and the vehicle occupancy using large scale numeric simulations. The simulation results are encouraging and demonstrate better qualitative performance of the proposed service than other typical feeder or shuttle services.