RHEA: Demand-supply asymmetRy mitigation witH modular Electric bus plAtforms

Research Project, 2021 – 2022

The “asymmetry” between spatiotemporally varying passenger demand and fixed-capacitated public
transit supply has been a long-standing problem for public transit planning, design and operations. The
concept of modular vehicles (MV) by “NEXT Future Transportation Inc.” can be considered as an elastic
medium reconciling the above-mentioned asymmetry. Although it sounds promising, there are several
fundamental 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-based
docking pods, we investigate macroscopic MV fleet management problems constrained to battery
capacity 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 methods
to solve it. For the microscopic optimal coordination at urban bottlenecks, optimally coupling/decoupling
of modules and optimal route related passenger movements will be solved via low level optimization
(such as tree search algorithms).