A Control-Oriented Model for Mobility on Demand Systems

In this paper, we propose a control-oriented model for mobility-on-demand systems (MOD). The system is first described through dynamical stochastic state-space equations in discrete time, and then suitably simplified in order to obtain a control-oriented model, on which a control strategy based on Model Predictive Control (MPC) is devised. The control strategy aims at maintaining the average number of vehicles at stations within prescribed bounds. Relevant features of the proposed model are: i) the possibility of considering stochasticity and heterogeneity in the system parameters; ii) a state space structure, which makes the model suitable for implementation of effective parameter identification and control strategies; and iii) the possibility of weighting the control effort, leading to control solutions that may trade off efficiency and cost. Simulation results on a synthetic network corroborate the validity of our approach under several operational conditions.