No abstract

Internet-enabled technologies are becoming more widespread; users are constantly connected to the network in every place and daily activity. Access to transportation-related features—mobile payment systems, Global Positioning System connections, real-time public transit timetables or traffic congestion information, and so on—is easy. This access results in new ways to plan mobility. In the innovative mobility systems implemented and developed with these technologies, the new real-time capabilities of dynamic ridesharing, an extended version of traditional ridesharing, can play a key role if the relevant performance is improved. In other words, although ridesharing is not a new idea, recent technological advances should increase its popularity. In this paper, a proposed ridesharing system considers the interactions between drivers or riders and the system manager and the interactions between drivers and riders. The positions and speeds of the shared vehicles and the traffic flows in which such vehicles travel are omitted. To optimize the performance of the ridesharing system, a discrete event, dynamic pickup and delivery model that represents the considered dynamics and an optimal matching problem that optimally allocates an empty seat in a vehicle to a rider are proposed. The dynamic model represents the behavior of the ridesharing system and computes the relevant performance; the optimization problem finds the best match and path in the considered transportation network to minimize the difference between the desired departure and arrival times. In this paper, after the introduction of the ridesharing model, the discussion of the solution to the optimal matching problem, a simulation model is described. A real world case study is then presented and discussed

The continuous increase in traffic has put into evidence the need of research and investments in more effective solutions. In this framework, the design of any transportation infrastructure or service is in general performed assuming to know the present mobility demand and to be able to forecast the future one with the best accuracy as possible. The main aim of this paper is the definition of a suitable criterion, based on a Global Sensitivity Analysis of an a-priori chosen transportation performance index, which helps in resource planning and in decision-making. In the end, the proposed methodology is evaluated by means of a real world case study in Italy