A Model for Improving Connectivity and Accessibility of Public Transport via Two-way Car-Sharing Systems

The origins and destinations of users in a transport network are connected by the available Public Transport (PT) means. Therefore, the role of PT of a region in terms of providing a connection from each origin to destination in a PT network is critical which directly affects the efficiency of PT systems. However, even efficient PT systems cannot guarantee the desired performance and service levels as well as equity to users unless they are well interconnected and accessible to the maximum possible population. In this connection, the geographical location of PT stops are also important since the connection to/from PT is provided through PT stops. Such a task is often challenging whenever the considered regions have a sparse geographical structure, such as medium-large sized cities located in mountainous areas. In such cases, the provision of new PT systems or extension of existing lines is not always a viable solution due to challenging topographical conditions or low budget availability. Alternatively, integrating PT systems with other cost-effective mobility systems (such as car-sharing systems, carpooling, ride-sharing, etc.) can significantly enhance the performance of the existing PT systems in terms of accessibility, connectivity, and flexibility. In this framework, this thesis develops a methodology for the optimal design of two-way Car Sharing (CS) systems in the least accessible and the least connected areas of a region by means of PT through the determination of the best locations of CS depots. The specific goal of the proposed approach is to improve the values of suitably defined accessibility and connectivity indexes (CAI) for integrated PT/CS systems. In this context, the operation of CS system should guarantee the efficient distribution of resources such that regions with the lowest values of CAI should be provided with at least one depot to maintain the equity while at the same time maximizing and equalizes the total values of CAI for integrated PT/CS systems. In doing so, the optimization problem has been designed as a Mixed Integer Linear Programming Model (MILP) under a given set of constraints to guarantee efficient resource distribution. To test the capabilities of the proposed approach over medium to large size cities, real-world case studies of the PT systems of the city of Trento (Italy) and Genova (Italy), representing the case of medium size and large size cities, respectively, are evaluated.