research-article

Accurate Detection of Road Network Anomaly by Understanding Crowd's Driving Strategies from Human Mobility

Authors:

Xiaohu QieAuthors Info & Claims

ACM Transactions on Spatial Algorithms and Systems (TSAS), Volume 5, Issue 2

Article No.: 11, Pages 1 - 17

https://doi.org/10.1145/3325913

Published: 08 August 2019 Publication History

Abstract

There are thousands of road closures and changed traffic rules that impact vehicle routing every day. Detecting the road closures and traffic rule changes is essential for dynamic route planning and navigation serving. In this article, we propose a driving-behavior modeling-based method for accurately and effectively detecting the road anomalies. In the first step, we detect the areas of anomalies by using the deviation between drivers’ actual and expected behaviors. To discover the cause of anomalies, we explore the drivers’ short-term destination and find the crucial link pairs in anomalous areas through a novel optimized link entanglement search algorithm, namely, the Select Link Entanglements (SELES) algorithm. Finally, we analyze the crowd's driving patterns to explain the road network anomalies further. Experiments on a very large GPS dataset demonstrate that the proposed approach outperforms the existing methods in terms of both accuracy and effectiveness.

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Cited By

Huang HHe SYang XTabatabaie M(2024) STICAP: Spatio-temporal Interactive Attention for Citywide Crowd Activity PredictionACM Transactions on Spatial Algorithms and Systems10.1145/360337510:1(1-22)Online publication date: 15-Jan-2024
https://dl.acm.org/doi/10.1145/3603375
Zhang HZhang XXie JWang Y(2020)Group Abnormal Behavior Detection Based on Fuzzy Clustering2020 3rd International Conference on Unmanned Systems (ICUS)10.1109/ICUS50048.2020.9274820(245-250)Online publication date: 27-Nov-2020
https://doi.org/10.1109/ICUS50048.2020.9274820

Index Terms

Accurate Detection of Road Network Anomaly by Understanding Crowd's Driving Strategies from Human Mobility
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems

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Published In

cover image ACM Transactions on Spatial Algorithms and Systems

ACM Transactions on Spatial Algorithms and Systems Volume 5, Issue 2

Special Issue on Urban Mobility: Algorithms and Systems

June 2019

133 pages

ISSN:2374-0353

EISSN:2374-0361

DOI:10.1145/3350424

Editor:
Walid G. Aref
Purdue University, USA

Issue’s Table of Contents

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 August 2019

Accepted: 01 April 2019

Revised: 01 April 2019

Received: 01 December 2018

Published in TSAS Volume 5, Issue 2

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Beijing Transportation Development Research Institute
National Key R&D program
National Natural Science Foundation Project
Beijing Science and Technology Commission
Beijing Municipal Science and Technology Project
Beijing Municipal Transportation Commission

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Cited By

Huang HHe SYang XTabatabaie M(2024) STICAP: Spatio-temporal Interactive Attention for Citywide Crowd Activity PredictionACM Transactions on Spatial Algorithms and Systems10.1145/360337510:1(1-22)Online publication date: 15-Jan-2024
https://dl.acm.org/doi/10.1145/3603375
Zhang HZhang XXie JWang Y(2020)Group Abnormal Behavior Detection Based on Fuzzy Clustering2020 3rd International Conference on Unmanned Systems (ICUS)10.1109/ICUS50048.2020.9274820(245-250)Online publication date: 27-Nov-2020
https://doi.org/10.1109/ICUS50048.2020.9274820

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