Young-Woo Seo and Maksim Lepikhin
18 March 2013
GPS signals, while typically noisy, can be very usefully exploited to help understand attributes of an underlying road network. In this paper we present the results of our GPS trace classification, a method that analyzes GPS signals collected around an intersection and categorizes its traffic-control system, such as stop-signs or a traffic-light. We represent an intersection as a feature vector of speed variations obtained from GPS traces and use these feature vectors to learn the models of different systems of traffic-control. In combination with a geographic distribution of intersections of different traffic-control systems, we assign a previously unseen intersection as the most probable traffic-control system. Experiments show a promising result of our classification task applied to real-world GPS trace data.