Fusing a Bluetooth Traffic Monitoring System With Loop Detector Data for Improved Freeway Traffic Speed Estimation

Abstract

Anonymous probe vehicle monitoring systems are being developed to measure travel times on highways and arterials based on wireless signals available from technologies such as Bluetooth. Probe vehicle data can provide accurate measurements of current traffic speeds and travel times due to their excellent spatial coverage. However, presently probe vehicles are only a small portion of the vehicles that make up all of the traffic in the network. Alternatively, data from conventional loop detectors cover almost all the vehicles that have traveled along a road section, resulting in excellent temporal coverage. Unfortunately, loop detector measurements can be imprecise; their spatial sampling depends on the loop detector spacing, and they typically only represent traffic speed at the location of the detector and not over the entire road segment. With this complementarity in mind, this article explores several data fusion techniques for fusing data from these sources together. All methods are implemented and compared in terms of their ability to fuse data from loop detectors and probe vehicles to accurately estimate freeway traffic speeds. Data from a Bluetooth traffic monitoring system are fused with corresponding loop detector data and compared against GPS collected probe vehicle data on a stretch of Highway 401 in Toronto, Canada. The analysis shows that through data fusion, even a few probe vehicle measurements from a Bluetooth traffic monitoring system can improve the accuracy of traffic speed estimates traditionally obtained from loop detectors.