Mixed Freight Dynamic Routing Using a Co-Simulation Optimization Approach

Abstract

The current freight transportation network is highly unbalanced as routing decisions are made by individual users without coordination. Certain routes may become congested when chosen based on current traffic information without any anticipation that if other users do the same, these routes may become congested. In this paper we show how a centrally coordinated load balancing system that considers all vehicles to be diesel can take into account electric trucks as mixed fleets. The electric trucks impose additional constraints due to the limitation of range, charging time of batteries as well as the dependency of the battery charge on traffic conditions. The use of a co-simulation approach as part of the system accounts for these nonlinear dependencies and provides more realistic cost estimates for the optimization part. Traffic simulation results using a realistic road network reveal the benefits of applying load balancing and show that as the number of electric trucks increases, the emissions reduce; however, due to the cost of charging, their operational costs are not necessarily less than those of the corresponding diesel trucks. For the electric trucks to compete with diesel, charging should occur when drivers are off duty since the cost of charging includes the labor cost of the waiting driver. It is also shown that a centrally coordinated truck routing system that considers the characteristics of electric trucks in mixed fleets can reduce the operational cost of trucks and encourage the deployment of electric trucks in order to reduce emissions and improve air quality.