United States Department of Transportation
i
Ride-Sharing With Advanced Air Mobility
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2023-09-01
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[PDF-1.29 MB]
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Edition:Final report, Jan. 1 2021 – August 31 2023
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Abstract:The application of on-demand ridesharing services can improve the efficiency and usage of a metropolitan transportation system. Implementing air taxis service can reduce the number of required aerial vehicles, mitigate air pollution, increase the revenue of the transportation network companies, and boost local economics. In this report, we propose a comprehensive and efficient Mixed Integer Bilinear Programming (MIBLP) model that simultaneously solves two problems: (i) the optimal assignment between the air taxis and the users; and (ii) the optimal path of the air taxis. The study integrates a ground transportation system with air Mobility-on-Demand system using a MIBLP model that aims to minimize the waiting time of the users, operating cost of the air taxis, and the number of unserved ridesharing requests. The study considers dynamic capacities and two statuses (active and idle) of the air taxis, and proposes a batch optimization technique with rolling horizons for large-scale systems. Several scenarios are designed to evaluate the effectiveness and robustness of the proposed model. The results suggest that for a multimodal transportation network with the ridesharing service, optimal assignments between user groups and air taxis, and the optimal path of the air taxis, can be found with within two minutes on average.
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