Seminar

Abstract

Shared mobility has emerged to fill gaps in today’s transportation networks. Its applications encompass bike sharing, car sharing, ride sharing, on-demand ride services, last-mile delivery, and other shared-use mobility options. The goals of shared mobility are to enable users or goods to gain short-term on-demand access to transportation modes, to reduce traffic congestion, and to promote environmental sustainability. While the concept of shared mobility has the potential to drive transportation systems more efficient, there are new operational challenges. The many users and transportation service providers and their complex connectivity require novel methodologies to achieve the goals. The large volumes of data captured from transportation networks call for novel data-driven techniques. This study aims to establish a new data-driven framework for shared mobility systems. Planning problems and operational issues will be explored and tackled.  In this talk, preliminary research on the development of a demand clustering method for understanding the users’ demands and spatiotemporal travel patterns and a case study of a real-world bike-sharing system will be presented.