Log In Sign Up

Learning Model-Based Vehicle-Relocation Decisions for Real-Time Ride-Sharing: Hybridizing Learning and Optimization

by   Enpeng Yuan, et al.

Large-scale ride-sharing systems combine real-time dispatching and routing optimization over a rolling time horizon with a model predictive control(MPC) component that relocates idle vehicles to anticipate the demand. The MPC optimization operates over a longer time horizon to compensate for the inherent myopic nature of the real-time dispatching. These longer time horizons are beneficial for the quality of the decisions but increase computational complexity. To address this computational challenge, this paper proposes a hybrid approach that combines machine learning and optimization. The machine-learning component learns the optimal solution to the MPC optimization on the aggregated level to overcome the sparsity and high-dimensionality of the MPC solutions. The optimization component transforms the machine-learning predictions back to the original granularity via a tractable transportation model. As a consequence, the original NP-hard MPC problem is reduced to a polynomial time prediction and optimization. Experimental results show that the hybrid approach achieves 27 MPC optimization, thanks to its ability to model a longer time horizon within the computational limits.


page 1

page 2

page 3

page 4


Learning Model Predictive Controllers for Real-Time Ride-Hailing Vehicle Relocation and Pricing Decisions

Large-scale ride-hailing systems often combine real-time routing at the ...

Learning from the Hindsight Plan -- Episodic MPC Improvement

Model predictive control (MPC) is a popular control method that has prov...

Parameterized and GPU-Parallelized Real-Time Model Predictive Control for High Degree of Freedom Robots

This work presents and evaluates a novel input parameterization method w...

Optimal Cost Design for Model Predictive Control

Many robotics domains use some form of nonconvex model predictive contro...

Contingency Model Predictive Control for Automated Vehicles

We present Contingency Model Predictive Control (CMPC), a novel and impl...