Simulation Evaluation of Filtering Method for Improving Pedestrian Positioning Accuracy Using Signal Strengths

In recent years, we have been able to use various services using the position information of smartphones and tablets. In addition, research on intelligent transport systems (ITS) has been actively conducted. To consider reducing traffic accidents by exchanging position information between pedestrians and vehicles by vehicle-to-pedestrian communication, we require accurate position information for pedestrians and vehicles. The GPS (global positioning system) is the most widely used method for acquiring position information. However, in urban areas, the GPS signal is affected by the surrounding buildings, which increases the positioning error. In this study, a method to improve the positioning accuracy of pedestrians using the signal strengths from vehicles and beacons was proposed. First, a Kalman filter was applied to the signal strength. Then, the path loss index was dynamically calculated using vehicle-to-vehicle communication. Finally, the position of a pedestrian was obtained using weighted centroid localization (WCL) after filtering the nodes. The positioning accuracy was evaluated using a simulator and demonstrated the superiority of the proposed method.