Detection and counting of Powered Two Wheelers by laser scanner in real time on urban expressway

Abstract

The safety of Powered Two Wheelers (PTWs) is an issue of concern for public authorities and road administrators around the world. In 2011, the official figures show that the PTW is estimated to represent only 2% of the total traffic but represents 30% of the deaths on the roads in France. The ambiguity in the values is due to the fact that the PTWs are particularly difficult to detect because of their unknown interactions with the other vehicles on the road. To date, there is no overall definite solution to this problem that uses a single sensor to detect and count this category of vehicle in the traffic. In this paper we present a robust method for detecting and counting PTWs in real time and real traffic, named the Last Line Check (LLC) method. This method can adapt to the angle at which the laser scanner is tilted with respect to the road and can estimate the non-observed values in the data. We can obtain data with an accuracy, which eases the extraction process. After extraction, a Support Vector Machine (SVM) is used for classification of laser scanner data. The approach gives encouraging results even when the traffic moves at up to 130 km/h with a precision of 98.5%.