Real-Time Estimation of Arterial Travel Times with Spatial Travel Time Covariance Relationships

Abstract

This paper investigates the use of real-time automatic vehicle identification (AVI) data and an offline travel time database for real-time estimation of arterial travel times in Hong Kong, China. The offline database consists of average link travel times and spatial link travel time covariance matrices by time of day, day of week, and week of month. Three-month historical travel time estimates and real-time AVI data are adopted for calibration and updating of the spatial covariance relationships of link travel times on Hong Kong arterial roads. A case study has been carried out on a selected path in a Hong Kong urban area to evaluate the performance of three alternative methods for real-time estimation of arterial travel times: fixed offline database (Method 1), continuously updated offline database (Method 2), and continuously updated offline database generated by the nonparametric regression method (Method 3). The validation results show that the travel time estimation errors of Methods 2 and 3 are significantly reduced when compared with those using the fixed offline database.