Assessing Urban Impact: Automated Mobility Districts

Major disruptive technologies are set to re-define the way in which people view travel, particularly in dense urban areas. Shared - automated - public mobility resulting from the cross-hybridization of AVs with on-demand mobility service will bring economic and system efficiencies. Along these lines, a concept called the Automated Mobility Districts (AMDs) has emerged which describes a campus-sized implementation of automated/connected vehicle technology to realize the full benefits of an automated-vehicle (AV) shared-mobility service within a confined geographic region or district. In an AMD, autonomous fleets of shuttles (electric or gasoline) are expected to serve a majority of mobility needs of the people in the district, thereby dissuading the use of personal vehicles. AMDs as are now certainly within the near to medium term planning horizon for dense urban settings. However, the availability of practical and efficient planning tools appropriate for analyzing the complexities of the AV fleet operations within AMDs is a significant issue. The breadth of options for operational planning of AMDs span from aggregate calculations, to advanced agent-based models. While aggregate back of the envelope calculations are an inexpensive solution, the estimates produced by such calculations would be too coarse for planning optimal deployment of fleets of AES vehicles. On the other hand, while agent-based travel models (ABMs) can produce precise results that can help plan the best possible deployment, developing and maintaining an ABM just for planning an AMD (which would be the order of a few square miles) would be too time-, and cost-consuming. This project aims to address this gap by developing a modeling and simulation toolkit that can be used for operational planning of shuttle services in an AMD. The AMD modeling and simulation toolkit is being developed with a view to be integrated as a special generator sub-model within existing travel models.