A Travel Time Estimation Algorithm Based on Point and Interval Detector Data over the National Highway Section

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 which 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. 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. As a result of verification, the optimized fusion model showed the superior estimation performance.