Estimation of Daily Vehicle Flows for Urban Freight Deliveries

Abstract

Given its contribution to congestion, pollution, and energy consumption and the complex and changing characteristics of delivery routes, the modeling of urban freight transport is a difficult, highly data-demanding and often unreliable task. Extending other previous works that focused only on the morning peak hour, the authors have developed a trip generation model by using the available data to their maximum extent and adding other parameters that can be found through simple surveys. This trip generation model is then included as part of a four-stage process, with the trip distribution solved through entropy maximization and resulting in the estimation of an origin-destination matrix for freight transport in a city. The application to a case study in the city of Seville and the validation with on-street vehicle counts shows reasonably robust results and provides a simple and effective tool to analyze urban freight deliveries from a macroscopic point of view.