High-Accuracy Off-Line Map-Matching of Trajectory Network Division Based on Weight Adaptation HMM

Abstract

In this paper, an accurate off-line map-matching (OM2) system is designed for complex trajectory networks. It is difficult to complex trajectories input into the hidden Markov model (HMM) directly. OM2 includes three key modules that are pre-processing, map-matching based on weight adaptation HMM (WA-HMM), and post-processing. The pre-processing module divides complex multi-trajectory into single-trajectory sets based on the self-defined trajectory division model (TDM) of crossroads. Another core module is the WA-HMM based on Boxplot, which is used to balance efficiency and accuracy of off-line map-matching. The post-processing is used to map the points of the crossroads so as to further improve the map-matching accuracy. OM2 employs the actual GPS trajectories of the internet company and road map of Sichuan province police GIS (PGIS). Our evaluation results show that the accuracy is about 98%, which is suitable for off-line map-matching and solves the problem of complex trajectory network matching being difficult and time-consuming.

Keywords

• Map-matching
• off-line
• complex trajectory division
• hidden Markov model
• weight adaptation