The “asymmetry” between spatiotemporally varying passenger demand and fixed-capacitated publictransit supply has been a long-standing problem for public transit planning, design and operations. Theconcept of modular vehicles (MV) by “NEXT Future Transportation Inc.” can be considered as an elasticmedium reconciling the above-mentioned asymmetry. Although it sounds promising, there are severalfundamental problems that are in the focus of this project: 1) network (high- or macroscopic) and 2)intersection (microscopic) level coordination. For the macroscopic system scheduling of station-baseddocking pods, we investigate macroscopic MV fleet management problems constrained to batterycapacity and charging time. The decision variables include vehicle formation and time of each dispatch.We will focus on dynamic programming, back pressure algorithm, and reinforcement learning methodsto solve it. For the microscopic optimal coordination at urban bottlenecks, optimally coupling/decouplingof modules and optimal route related passenger movements will be solved via low level optimization(such as tree search algorithms).
Page manager Published: Wed 16 Sep 2020.
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