Abstract
Reconstructing vehicle trajectories is an essential step in obtaining high-precision vehicle trajectory data owing to observation errors. Although considerable efforts have been made to reconstruct trajectories on road segments, it is still challenging to reconstruct two-dimensional vehicle trajectories at intersections. In this study, a three-step vehicle trajectory reconstruction method for intersections was proposed to correct abnormal velocities and direction angles in raw trajectories. First, outliers were identified by wavelet transform. They were then filtered out and interpolated using Gaussian kernel-based locally weighted linear regression. Finally, the trajectories were smoothed using a Savitzky-Golay filter. The proposed method was validated using empirical trajectory data collected at 15 intersections in Shanghai, China. The results demonstrate that the proposed trajectory reconstruction method performs well in terms of trajectory rationality and consistency. The mean outlier rate and root mean square error of the reconstructed trajectories are 3% and 0.821 m, respectively.
Acknowledgements
Thank Dr. Jan-Dirk Schmoecker from Kyoto University for providing us with insightful suggestions during the study.
Disclosure statement
No potential conflict of interest was reported by the author(s).