Truck routing and platooning optimization considering drivers’ mandatory breaks

Abstract

Truck platooning has been touted as one of the most promising technologies to improve fuel efficiency thanks to the reduced air drag of the digitally connected truck’s slipstream in a trainlike convoy. The benefits of truck platooning lie in the reduced fuel consumption and labor cost, and the enhanced driving experience. However, these benefits cannot be realized without an appropriate routing, scheduling, and platooning plan of trucks subject to practical constraints, especially the drivers’ break requirement for long-haul journeys. This study addresses the truck routing and platooning problem considering drivers’ mandatory breaks as well as other characteristics such as the state-and-position-dependent fuel-saving rates of platooning, trucks’ designated intermediate relays, and platoon size limit. The problem is to route the trucks to their respective destinations on time using the least amount of fuel by maximizing the formations of fuel-saving platoons over entire trips while satisfying the break time requirement of drivers. A mixed-integer linear programming (MILP) model is first developed for the proposed problem. A hybrid algorithm integrating the partial-MILP approach and iterated neighborhood search with tailored search operators is proposed to address the problem. Various randomly generated networks are used in numerical experiments to examine the effectiveness and efficiency of our proposed model and solution method. An extensive sensitivity analysis is also conducted to explore the impacts of several major influential factors, i.e., the drivers’ mandatory break times, the fuel reduction rate of the leading truck of platoons, as well as the width of the service time window, on the system performance and derive the managerial insights.