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Cities would need to facilitate a multi-modal mobility platform, which provides travelers with a range of flexible mobility options, such as fixed-route or flex-route public transit, micro-transit, ride-sharing, car rentals, bike-sharing, scooters, and walking routes, some of which can be potentially served by automated vehicles. Those options altogether have potential to help residents reach businesses, employment, health care and other essential points of interest. This research acquires mobility service data to understand travel behavior in choosing mobility options, optimize design of such a platform by optimally placing mobility hubs with multiple mobility options, with the ultimate goals of improving system efficiency, increasing ridership, reducing system cost and enhancing travel safety.

Transportation agencies and researchers struggle with fragmented, incomplete, or unavailable mobility data, making it difficult to accurately model mobility patterns and predict future transportation demand. While various datasets exist—such as GPS trajectories, public transit records, traffic sensors, and household travel surveys—they are often disconnected, limited in scope, or proprietary, preventing cities from making fully informed planning decisions. These datasets, when properly integrated, have the potential to improve urban planning, transportation optimization, and system operations. This project aims to review available mobility data sources critical for mobility pattern analysis, build a mobility data fusion pipeline by using multiple cross-domain data sources, allowing for detailed synthesis and modeling of urban and rural activities, travel behavior, demand, and trajectories, as well as estimation/generation of network-wide travel patterns. Ultimately, this project will provide a scalable, transferable data fusion framework that agencies can use for demand prediction, transportation planning, and network optimization.

There is a significant interest in researching methods to improve V2X cost-benefit analysis (CBA) and the development of a decision support tool for deployment for different stakeholders. To develop a framework that allows the assessment of the safety and traffic impacts of V2X technology and provides actionable insights for deriving safety, reliability, and connectivity requirements.