Traffic trajectory history and drive path generation using GPS data cloud

摘要

This paper proposes a novel approach for extracting the traffic trajectory history, with the use of GPS data collected over a certain period of time, to be used as an input for driver models. In this approach, driving curvature is distinguished from actual road shape curvature with the use of real driving data. After sufficient amount of drive data has been collected, high degree polynomials are fitted to GPS point cloud. Traffic trajectory history is the tangential unit vectors and curvature values that are calculated from these polynomials. Then a single drivers driving path has been predicted with using traffic trajectory history and road shape curvature for comparison and validation. Experimental results show that the predictions made with categorized traffic trajectory history have less errors than the predictions made with road shape curvature.