A Travel Time Fusion Algorithm Based on Point and Interval Detector Data

Up to now studies on the fusion of travel time from various detectors have been conducted based on the variance ratio of the intermittent data mainly collected by GPS or probe vehicles. The fusion model based on the variance ratio of intermittent data is not suitable for the license plate recognition AVIs that can deal with vast amount of data. This study was carried out to develop the fusion model based on travel time acquired from the license plate recognition AVIs and the point detectors. In order to fuse travel time acquired from the point detectors and the license plate recognition AVIs, the optimized fusion model and the proportional fusion model were developed in this study. As a result of verification, the optimized fusion model showed the superior estimation performance. The optimized fusion model is the dynamic fusion ratio estimation model on real time base, which calculates fusion weights based on real time historic data and applies them to the current time period. The results of this study are expected to be used effectively for National Highway Traffic Management System to provide traffic information in the future. However, there should be further studies on the proper distance for the establishment of the AVIs and the license plate matching rate according to the lanes for AVIs to be established. Keyword: Real-time travel time estimation, Point & Interval detector, AVI (Automatic Vehicle Identification), Fusion model, Fusion ratio.