Journal
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
Volume 91, Issue -, Pages 192-208Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2018.04.007
Keywords
Markov decision process; Sharing economy; Dynamic dial-a-ride problem; Multi-server queue; Dynamic pricing; Flexible transit services
Categories
Funding
- National Science Foundation [CMMI-1462289]
- Natural Science Foundation of China (NSFC) [71428001]
- Lloyd's Register Foundation, UK
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We propose a competitive on-demand mobility model using a multi-server queue system under infinite-horizon look-ahead. The proposed approach includes a novel dynamic optimization algorithm which employs a Markov decision process (MDP) and provides opportunities to revolutionize conventional transit services that are plagued by high cost, low ridership, and general inefficiency, particularly in disadvantaged communities and low-income areas. We use this model to study the implications it has for such services and investigate whether it has a distinct cost advantage and operational improvement. We develop a dynamic pricing scheme that utilizes a balking rule that incorporates socially efficient level and the revenue-maximizing price, and an equilibrium joining threshold obtained by imposing a toll on the customers who join the system. Results of numerical simulations based on actual New York City taxicab data indicate that a competitive on-demand mobility system supported by the proposed model increases the social welfare by up to 37% on average compared to the single-server queuing system. The study offers a novel design scheme and supporting tools for more effective budget/resource allocation, planning, and operation management of flexible transit systems.
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