Imbalance in Mobility-on-Demand Systems: A Stochastic Model and Distributed Control Approach

摘要

The control of large-scale mobility-on-demand systems is an emerging topic that has been considered from a system theoretical, transportation scientific, and algorithmic point of view. Existing formulations model mobility-on-demand systems in a queuing theoretical, network flow-based, or continuous, kinematic framework. In this work, we model a mobility-on-demand system as a stochastic differential equation that represents a generalization of previous approaches. Based on the model, we define system imbalance as the difference of the stochastic processes of service request arrival and vehicle arrival. We formally derive the first moment of the system imbalance for an imbalance control strategy that consists of a feedforward control approach (reference trajectory) and an additional feedback component. A distributed feedback control policy is defined that averages the imbalance across the system and therefore aims at a uniform quality of service distribution. Finally, we verify our results in a high-fidelity and large-scale agent-based simulation of a hypothetical mobility-on-demand system.