The growth of E-commerce and increasingly sophisticated supply chain management strategies used by today’s businesses require truck travel demand forecasting tools that are capable of capturing the effects of those market and economic forces on trucks’ trip making behaviors. As the first step toward the development of such model, this study tackled the most fundamental but often neglected component of truck travel demand forecasting process, trip generation. Our effort focused on building prototype models for one specific type of facility, retail stores.
Truck trip generation (TTG) analysis is a study to estimate the number of trucks coming in and out of a study area (e.g., a store, a shopping mall, or an industrial park). Thus, the TTG analysis provides transportation planners and public agencies with fundamental information, namely the usage of infrastructure in the vicinity of various businesses by trucks. This information is useful, for making transportation asset management decisions. Our approach for developing the new generation of TTG modeling is founded upon the observation that in order to capture the effects of supply chain strategies, it is necessary to construct a model at the individual facility level as opposed to at zonal level. In addition, it is necessary to identify the variables (preferably observable) that can be used to capture the characteristics of supply chain strategies employed at each facility.
Please click on the link below to download the complete “Business and Site Specific Trip Generation Methodology for Truck Trips” report.
Author / Presenter:
Kazuya Kawamura, Hyeon-shic Shin and Sue McNeil
Presentation Date / Publication Date: