Truck Parking utilization analysis using GPS data

Abstract

Unavailability of sufficient parking spaces during various periods at rest areas results in illegal and unsafe parking at on/off-ramps and other unauthorized areas, which may lead to traffic safety hazards. In this research, the authors attempt to understand truck parking utilization by developing econometric models by using truck global positioning system (GPS) data to predict truck parking utilization at rest areas to improve truck parking management and ensure proper use of parking spaces. Count models, including Poisson and negative binomial models, were developed in addition to generalized ordered-response probit (GORP) models to understand the factors that affect truck parking utilization. The GORP model that subsumes the Poisson model as a special case was found to provide the best data fit. The model results suggest that several factors positively contribute to truck parking utilization (e.g., truck volume on the adjacent roadway, number of lanes) at rest areas, whereas factors such as on/off-ramp violations decrease truck parking utilization. In addition, parking utilization was found to vary considerably throughout the day.