Travel Time Estimation Based on Fused Traffic State Data: Case Studies in US and South Korea

Abstract

The goal of Advance Traveler Information System (ATIS) is to improve traffic flow and safety by providing up-to-date information of traffic network. In this paper, traffic information (travel time) estimation based on fused traffic state data is presented. A centralized architecture is used to fuse the traffic sate data from different sensors based fusion by averaging and fusion by median and to estimate the travel time based on the simultaneous travel time estimation model accordingly. Two case studies are selected to investigate the performance of fusion models based on freeway data in the United States of America (USA) and the arterial road data in South Korea. The results show that the fusion by median performs best. The model is able to eliminate outliers in the data with less effort of complex mathematical process. It can be used as a benchmark for comparison with other advanced fusion models.