A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks

ABSTRACT

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.

KEYWORDS:

• Trajectory restoration
• map-matching
• A* shortest path algorithm
• low-sampling-rate FCD
• complex road networks

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data and code availability statement

The data and codes that support the findings of this study are available at figshare.com at the permanent link with DOI https://doi.org/10.6084/m9.figshare.9989183.

Additional information

Funding

This work was supported by the National Key Research and Development Program of China [2017YFB0503500].

Notes on contributors

Bozhao Li

Bozhao Li is a PhD student in School of Resource and Environmental Sciences at Wuhan University. His research interests include transportation big data mining, GeoAI and GIS software application and development.

Zhongliang Cai

Zhongliang Cai is a professor in School of Resource and Environmental Sciences at Wuhan University. His research interests include cartographic automation, transportation data analysis, and mobile geo-computation and location based service.

Mengjun Kang

Mengjun Kang is an associate professor in School of Resource and Environmental Sciences at Wuhan University. His research interests include geocoding, urban addresses, and digital mapping.

Shiliang Su

Shiliang Su is a full professor of Cartography and GIScience at Wuhan University. His research interests include land use modeling, geocomputational social sciences and thematic map design.

Shanshan Zhang

Shanshan Zhang is a senior engineer working in the geographical information center of Urban Planning Survey & Design Research Institute in Guangzhou, she engaged in GIS software application and development.

Lili Jiang

Lili  Jiang is a senior engineer of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. Her main research direction is thematic mapping technology, cartography synthesis, and theory and method of atlas.

Yong Ge

Yong Ge is currently a professor with the State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, CAS. Her research interests broadly focus on the statistical aspects of spatial and spatio-temporal data.