The potential use of big vehicle GPS data for estimations of annual average daily traffic for unmeasured road segments
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A promising methodology is proposed to estimate reliable annual average daily traffic (AADT) volumes for no-surveyed road sections using probe volumes collected by a vehicle global positioning system (GPS). This research was inspired by the obvious concept that probe counts are a direct portion of AADT from the viewpoint of vehicle trip behavior. The method converts the probe volume of target road section to AADT using the nonlinear relationship between geographical neighborhoods composed of observed AADT volumes and annual average daily probe volumes. The relationship is determined with a locally weighted power-curve model. A feasibility of the proposed method was demonstrated through a case study using real-world data. Analysis results show that the proposed method is a practical and cost-effective way to estimate reliable AADT for unmeasured road segments. This indicates that there exists a strong relationship between AADT values and vehicle-GPS probe values from the trip characteristics of a road network.
KeywordsUnmeasured road section Direct traffic demand estimation Large-scale vehicle-GPS data Direct expansion method Weighted power curve
We are very grateful to the three anonymous reviewers for their constructive comments and suggestions. We owe many parts of this paper to them. Two reviewers provided helpful suggestions and offered useful guidelines and comments on the modeling and its contributions. The third reviewer offered sound ideas for academic and practical contributions. The reviewers are gratefully acknowledged.
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