Electric truck routing and platooning problem considering vehicle charging and driver assignment on highway networks

Abstract

Driven by the development of electricity-powered trucks and the connected and autonomous vehicle (CAV) technology, the electric truck (ET) routing and platooning has received considerable attention. To reap the labor cost savings and environmental benefits, this study makes the first attempt to investigate the ET routing and platooning problem considering vehicle charging and flexible assignment of the drivers. The objective is to determine the optimal routes and schedules of the trucks and the drivers that minimize the total operational cost to complete a group of freight transportation tasks while considering the features of the electric trucks, i.e., the limited driving range and charging demands due to limited battery capacity. A mixed-integer linear programming (MILP) model that can effectively determine the itineraries of the trucks and drivers and incorporate specific characteristics of ET platooning is formulated for the proposed problem. By exploring the essential features of the platooning process and its optimal solution structures, a tailor-designed edge set covering algorithm dedicated to platooning-related optimization problem is proposed to address the problem. Numerical experiments are conducted to evaluate the proposed model and solution method against three benchmark methods and quantify the benefits of the ET platooning. Sensitivity analysis is also carried out to explore the impacts of several major influential factors on the system performance and derive managerial insights.