标题: A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road network
作者: Bozhao Li, Zhongliang Cai, Mengjun Kang, Shiliang Su, Shanshan Zhang, Lili Jiang &Yong Ge
来源出版物: International Journal of Geographical Information Science DOI: 10.1080/13658816.2020.1825721 出版时间:20 Oct 2020
摘要: Low-sampling-rate floating car data (FCD) are more challenging than those with high-sampling-rate FCD for map matching (MM) algorithms. Some MM algorithms for low-sampling-rate FCD lack sufficient efficiency nor accuracy, especially related to complex urban road networks. This paper proposes a new method named the trajectory restoration algorithm, which is based on geometry MM algorithms to ensure efficiency and accuracy. The proposed algorithm adopts the modified A* shortest path algorithm to reduce the number of function calls and fully considers road network topology and historical matched points to improve its accuracy. We test the efficiency and accuracy of the trajectory restoration algorithm with FCD data for the complex urban road networks in Beijing. The results have strong continuity which greatly improves the utilization of FCD. We show that the proposed algorithm outperforms related MM methods in efficiency and accuracy and its robustness to restore trajectories of both high and low sampling rates in complex urban road networks.
作者关键词: Trajectory restoration, map-matching, A* shortest path algorithm, low-sampling-rate FCD, complex road networks
通讯作者电子邮件地址: Zhongliang Cai, email@example.com; mengjun Kang, firstname.lastname@example.org
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