Road centreline and lane reconstruction from pervasive GPS tracking on motorways

Abstract

Abstract A lane-based Routable Digital Map is a basis for construction of a floating-car dataset for lane-based traffic analysis. We proposed an algorithm that is capable of identifying lanes in highway segments based on GPS trajectories collected by mobile phones. The algorithm consists of three main steps. First, we identify nodes within the test site, and divide the network into segments. Second, the central line of each segment is identified based on a dissimilarity matrix computed based on Dynamic Time Warping criteria. Finally, the Gaussian Mixture Method is used to identify the lanes. This allows the width of the lanes to remain constant throughout the segment. The results have been validated by comparing the share of traffic volume in each lane based on the trajectory points in the identified lanes and the loop detectors’ data. The results show that the proposed algorithm can determine the lanes with acceptable accuracy. Estimating the traffic volume and its speed based on floating car data provides a big step in enabling data fusion from multiple sources more accurately and to estimate traffic state more precisely.