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Integrated Transit System Design with Autonomous Vehicle Fleet Services: Mathematical Formulation, Solution Approach and Large-Scale Application

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Providing quality transit service to travelers is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and heuristic solution approach are presented.The problem definition, modeling and solution of the JTNR-SFSDP are presented to recommend frequencies for existing transit lines and SAMS fleet size (level of service supplied), allowing the complete removal of existing lines. It demonstrates robustness of the proposed model with a sensitivity analysis at the design level, and shares takeaways from a large-scale application. It also proposes an agent-based model to capture travelers’ mode choices and the system-level performance of the integrated transit-SAMS system in terms of travelers’ simulated wait and travel times, transfers, shared rides in SAMS and denied transit boardings. This part is referred to as the dynamic combined mode choice and traveler assignment problem (DCMC-TAP). Results indicate the modeling framework can improve the travel experience of transit users in terms of average user waiting time as well as generalized travel costs, while under comparable operating subsidy constraints by reducing inefficient services and reallocating resources between transit and SAMS.

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