Comparative study on GPS and cellular probe techniques for freeway travel speed estimations

Abstract

Traffic data, such as travel speed and travel time, is by nature stochastic. In order to deploy Intelligent Transportation Systems successfully, efficient, accurate, and sufficient collection of traffic data in a timely manner without interrupting the traffic flows is one of the imperative first steps. It is evident that travel speed estimates by gathering traffic data with moving vehicles is more representative of highway performance than the point estimates of speed from fixed detectors. Recently, GPS and cellular probe techniques have been researched and practiced in academic and industrial areas all around the world. The use of GPS and cellular probes for obtaining traffic data appears to be technically feasible. Still, there is little evidence to demonstrate that either system can be practically implemented. The comparative study conducted in this paper has integrated the possible real attributes of GPS and cellular probe systems, such as location accuracy, probe penetration rate and update frequency, into simulation on a real transportation network, and has developed methods for freeway travel speed estimation. The findings from simulation show that either of these two techniques has its own pros and cons. Cellular probe has wider probe penetration rate than GPS, which relieves the dependency on location accuracy, but the low update frequency reduces the coverage and accuracy of link travel speed estimation in the network. The GPS probe has a high update frequency, but the low probe penetration rate and the subsequent strong dependency on location accuracy are big obstacles to obtaining enough samples for link travel speed estimation. Thus, combining these two technologies of wide cellular probe rate and high GPS update frequency should provide better estimation of traffic conditions.