Map matching method for floating car trajectories based on traffic rule constraints

Yafeng Cai; Haiping Wei; Liang Zhang; Xueman Li

doi:10.1117/12.2673079

14 April 2023 Map matching method for floating car trajectories based on traffic rule constraints

Yafeng Cai, Haiping Wei, Liang Zhang, Xueman Li

Proceedings Volume 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022); 1261212 (2023) https://doi.org/10.1117/12.2673079
Event: International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 2022, Zhuhai, China

Abstract

Existing map matching methods determine the best driving paths for floating cars according to the constraints of the roads in the trajectory while ignoring the influence of traffic rules, which reduces the road path matching accuracy and increases road mismatch in complex situations with large road networks. In view of this phenomenon, this paper proposes a floating car trajectory map matching method based on traffic rule constraints that uses floating car retrograde and speeding behaviors and floating car positioning errors to match trajectory points. Four floating car trajectory sequences in Futian District, Shenzhen City, with a total length of 44.437 km are selected for verification, yielding 296 trajectory points. The experimental results show that the average matching accuracy of the proposed method in a complex road environment is 92.91%, which is approximately 7% higher than that of traditional methods. The proposed method meets user position accuracy requirements in floating car trajectory big data analyses and applications.

Citation Download Citation

Yafeng Cai, Haiping Wei, Liang Zhang, and Xueman Li "Map matching method for floating car trajectories based on traffic rule constraints", Proc. SPIE 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 1261212 (14 April 2023); https://doi.org/10.1117/12.2673079

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