Method for Detection and Classification of Turning Movements in Intersections Using Bluetooth Low-Energy Signals

Abstract

The study purpose is the development of a method for detection and classification of turning movements in intersections using Bluetooth Low-Energy signals emitted from turning vehicles. The method was developed to be applicable for areas in which the distances between the adjacent intersections are short. It utilizes the time profiles of the received signal strength indicator (RSSI) for signals emitted by transmitters mounted on moving vehicles. The signals are collected by an array of signal scanners carefully located on the intersection approaches and corners. Turning movements are classified by comparing signature points of the RSSI–time profiles and their occurrence moments. Effort was made to examine the accuracy and functionality of the method in six field experiments covering line-of-sight and non-line-of-sight signal transmission paths, different speeds, and motion-stop situations. The overall accuracy of the method in the experiments was 94.2%, demonstrating its functionality in different situations. Nevertheless, the results indicated that there are factors affecting the performance of the method. The presence of obstacles in the transmission paths of signals and increasing the vehicle speed reduced the accuracy, but intermittent motion at low speeds did not have negative impacts on the outcomes. It was found that a certain condition is required to achieve satisfactory accuracy in the determination of turning movements by the proposed method. The installation location of the signal scanners, road geometry, and vehicle speeds should provide a signal detection distance of less than 10 m on the intersection approaches when vehicles pass in front of the scanners. This is to ensure that at those moments, there are signals transmitted from the range with distinct RSSI values and appropriate for the identification of the turning movements.