Abstract
This paper uses data from a trucking origin/destination study conducted with global positioning system (GPS) technology to develop a truck trip generation model for medium sized urban communities—in this study taken to be communities between 200,000 and 1,000,000 people. The difficulty with developing truck trip generation equations centers on the limitation of data. For passenger transportation, data are collected from household surveys. For truck transportation, if available, data are typically collected from a small collection of shippers/businesses within the urban area and extrapolated to cover the entire study area. Because of the data limitations, truck transportation is typically indirectly modeled or as an after-thought. Increasing truck volumes, coupled with cost saving strategies such as just-in-time delivery systems, require that transportation policymakers analyze infrastructure needs and make investment decisions that explicitly include truck volumes as a component. This paper contains a case study using a medium sized urban area and a GPS collected set of truck origins and destinations to develop a truck specific trip generation equation using standard employment data. The paper presents the models developed and validates the models to the case study community. The paper concludes that the trip generation equations developed can be incorporated into medium sized community travel models to provide a framework for truck planning that can be used to improve resource allocation decisions.
Highlights
This paper examines the potential to use a database of freight origin/destination locations in a medium sized community to develop a calibrated truck trip generation equation
The employment data were combined with the global positioning system (GPS) data for truck origin/destinations in a geographic information system (GIS) to determine the number of trucks that stopped in each census block and distribution in employment for the block
To test the accuracy of the two 20 sector trip generation equations developed in this study, a comparison of the number of trucks observed on the roadways in Birmingham and the number of truck assigned to the Birmingham travel demand
Summary
To evaluate the best investment decisions, travel demand models, which are representations of the existing transportation infrastructure, are used to evaluate “what if” scenarios to future socio-economic growth and infrastructure decisions. This paper examines the potential to use a database of freight origin/destination locations in a medium sized community to develop a calibrated truck trip generation equation. The relationship between truck stops and employment was developed and tested to determine the validity of the equations for use in practice and the level of accuracy associated with the use in the community travel demand model. The paper concludes that using a 20 sector model for truck trip generation can provide the level of detail necessary to incorporate truck transportation needs into the travel demand models, improve the results, and potentially lead to improved investment decisions for the community
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