Spatiotemporal Traffic Speed Reconstruction from Travel Time Measurements Using Bluetooth Detection

Traffic state reconstruction gets more and more attention for various important applications such as traffic optimization, traffic control, and congestion avoidance. There exist several approaches to detect traffic parameters like speed, flow, and density. A quite common approach in the past was to use stationary detectors like induction loops. An emerging technology is to handle traffic state by floating-car data (probe vehicles) with a high resolution of time and location measurements via GPS. A third methodology is to detect vehicles using the recognition of in-use Bluetooth devices and to derive an average travel time between two Bluetooth detectors. For the first two approaches, several traffic state reconstruction methods exist. This paper aims at reconstructing the prevailing traffic situation out of low-resolution travel times based on Bluetooth captions. A methodology is developed on how to reconstruct the traffic speed and is applied to three months of data from a German autobahn equipped with Bluetooth detectors.