Finding Most Frequent Path based on Stratified Urban Roads

Enquan Ge, Jian Xu, Ming Xu, Ning Zheng, Weige Wang, Xinyu Zhang

2016

Abstract

The path query based on big trajectory data has become a promising research direction due to the rapid development of the Internet. Previous studies mainly focus on searching paths in full road network and ignore the importance of stratified urban roads. It is observed that higher-level roads gather more trajectory points which means most drivers prefer the high-level road. In this paper, we study a new path query to find the most frequent path (MFP) based on road levels in large-scale historical trajectory data. We refer to this query as most frequent path based on road levels (RLMFP). Intuitively, selecting roads which are in line with local custom and choosing high-level roads such as high-way are people’s two common sense notions. Our query not only satisfies aforementioned sense, but also has two advantages in algorithm implementation. First, the road hierarchy can speed up the path query. Next, the trajectory data can find more reasonable upgrade points (e.g., path query based on road levels need to find the intersection between low-level roads and high-level roads). Experiments show the effectiveness and the efficiency of our method.

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Paper Citation


in Harvard Style

Ge E., Xu J., Xu M., Zheng N., Wang W. and Zhang X. (2016). Finding Most Frequent Path based on Stratified Urban Roads . In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-188-5, pages 51-60. DOI: 10.5220/0005880500510060


in Bibtex Style

@conference{gistam16,
author={Enquan Ge and Jian Xu and Ming Xu and Ning Zheng and Weige Wang and Xinyu Zhang},
title={Finding Most Frequent Path based on Stratified Urban Roads},
booktitle={Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2016},
pages={51-60},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005880500510060},
isbn={978-989-758-188-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Finding Most Frequent Path based on Stratified Urban Roads
SN - 978-989-758-188-5
AU - Ge E.
AU - Xu J.
AU - Xu M.
AU - Zheng N.
AU - Wang W.
AU - Zhang X.
PY - 2016
SP - 51
EP - 60
DO - 10.5220/0005880500510060