Fusing Public and Private Truck Data to Support Regional Freight Planning and Modeling

In the past, regional transportation planners primarily focused on passenger traffic demand and forecast modeling. Many metropolitan areas were unable to include freight in regional planning due to lacking of data. With the growing freight movement and its significant impact on regional and national economy, many planning agencies are investing more resources on integrating freight into transportation planning and using freight models to better support transportation decision making. Data is critical to derive parameters and support analysis processes in developing a model. However, freight data acquisition, due to the proprietary nature of data, has been an ongoing challenge. Existing public freight data is insufficient to support advanced freight modeling. Collecting additional data or identifying new data sources is essential to support effective freight modeling and planning. The FHWA has established a partnership with the American Transportation Research Institute (ATRI) to measure truck travel speed on freight-significant corridors since 2002. This paper explores the feasibility of generating truck performance measures that can be fed to freight models. As an example, 12-month of private truck GPS data from ATRI and traffic data from state DOTs were utilized to study trucking activity, level of congestion, and travel time reliability along the I94/90 corridor between the Twin Cities and Chicago. The data analysis methodology demonstrated the capability of using truck GPS data to generate performance measures for potential applications such as measuring truck travel time reliability, evaluating impact of congestion on cost of freight, identifying truck stop or parking facility needs, and studying the impact of traffic volume with respect to speed gap difference between passenger vehicles and trucks. Resulting performance indices can thereafter be utilized to support freight modeling, planning and decision making.