Performance period: 1/1/2016 to 12/31/2018

Project description

The concept of "Freight Landscape," the basis for a modeling approach for urban freight traffic estimation using commonly available datasets, was proposed by Giuliano et al., 2015, applying it to the Los Angeles metropolitan area. To extend the scope of their research, we conduct another case study, using data from the Paris region, France. We estimate spatial lag models using population, employment or establishment, transportation accessibilities as explanatory variables and network-based truck traffic as the dependent variable, modifying Giuliano et al.'s approach. We identify similarities and differences between the case studies of Los Angeles and Paris. For Paris, the estimated models highlight the most important factors that characterize urban freight traffic in the region, including the distance to autoroutes (controlled-access highways) and jobs in trade, manufacturing of electrical products and machines, and the transportation industry. While the models estimated for the Paris region give us beneficial insights on the relations between Freight Landscape indicators and urban freight traffic, the model validation underlines the needs of further research for a modeling framework that enables unbiased estimation of urban freight traffic.