YIN Jichong, WU Fang, LI Anping, DU Jiawei, LIU Chengyi. Trajectory Matching Considering Speed and Heading Information[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1774-1781. DOI: 10.13203/j.whugis20210058
Citation: YIN Jichong, WU Fang, LI Anping, DU Jiawei, LIU Chengyi. Trajectory Matching Considering Speed and Heading Information[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1774-1781. DOI: 10.13203/j.whugis20210058

Trajectory Matching Considering Speed and Heading Information

  •   Objectives  Trajectory matching is the process of matching location data to the corresponding position in the road network. It is a necessary processing step for many related applications based on global navigation satellite system (GNSS) trajectory data analysis and position analysis.
      Methods  We propose a trajectory matching method considering speed and heading information to solve the problem that existing trajectory matching methods have low accuracy and efficiency for complex road network data. Firstly, we consider constraint criteria such as distance, heading, speed, topology and mileage to optimize the selection process of matching sections. Secondly, considering the continuity of the trajectory in the construction of the candidate road set, a rectangular buffer is added to avoid missing matches. Moreover, the proposed method improves the judgment criterion of initial position and uses the subsequent matching position to correct the judgment of initial position, and to avoid the accumulation of error transmission caused by the matching error of initial position in traditional topology matching method, and improves the matching accuracy. Finally, the speed and time information are used to determine the matching position in the matching section and to improve the matching efficiency. To evaluate the performance of our proposed method, a number of real route data sets with different complexity are used to compare the proposed method with the geometric matching method and topological matching method.
      Results  Experimental results show that the proposed method has a good matching effect for urban road networks with different levels of complexity. It can match the correct road for special road sections such as overpasses, intersections, and parallel sections. And the accuracy of the method can reach 93.53%, which outperforms the existing two methods.
      Conclusions  Our proposed method can meet the needs of positioning and navigation in terms of matching efficiency.
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