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Unlicensed taxi detection algorithm based on traffic surveillance data

Published: 30 July 2020 Publication History

Abstract

Unlicensed taxi services severely disrupt traffic management and threaten passengers' safety. Traditional approaches to detect unlicensed taxis rely highly on manual work like collecting on-site evidence. However, these approaches are ineffective and inefficient. As to address this hardship, we propose an unlicensed taxi detection algorithm using pass-records data collected from surveillance cameras. First, based on spatio-temporal analysis, we propose path irregularity and time irregularity to distinguish commercial vehicles from non-commercial vehicles. Then, we evaluate the algorithm based on the actual vehicle pass-records data of Guiyang. The results show that our algorithm outperforms baselines in terms of accuracy and running time.

References

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Yong Ge, Hui Xiong, Chuanren Liu, and Zhi-Hua Zhou. 2011. A taxi driving fraud detection system. In 2011 IEEE 11th International Conference on Data Mining. IEEE, 181--190.
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Luca Rossi and Mirco Musolesi. 2014. It's the way you check-in: identifying users in location-based social networks. In Proceedings of the second ACM conference on Online social networks. ACM, 215--226.
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Yujie Wang, Xiaoliang Fan, Xiao Liu, Chuanpan Zheng, Longbiao Chen, Cheng Wang, and Jonathan Li. 2017. Unlicensed taxis detection service based on large-scale vehicles mobility data. In 2017 IEEE International Conference on Web Services (ICWS). IEEE, 857--861.
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Wei Yuan, Pan Deng, Tarik Taleb, Jiafu Wan, and Chaofan Bi. 2016. An unlicensed taxi identification model based on big data analysis. IEEE Transactions on Intelligent Transportation Systems 17, 6 (2016), 1703--1713.
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Yu Zheng. 2015. Trajectory data mining: an overview. ACM Transactions on Intelligent Systems and Technology (TIST) 6, 3 (2015), 29.

Cited By

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  • (2022)Unlicensed Taxi Detection Model Based on Graph EmbeddingElectronics10.3390/electronics1120341011:20(3410)Online publication date: 20-Oct-2022
  • (2021)Detecting and analyzing unlicensed taxis: A case study of Chongqing CityPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2021.126324584(126324)Online publication date: Dec-2021

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    Published In

    cover image ACM Conferences
    EM-GIS '19: Proceedings of the 5th ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management
    November 2019
    103 pages
    ISBN:9781450369657
    DOI:10.1145/3356998
    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 ACM 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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    Publication History

    Published: 30 July 2020

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    Author Tags

    1. path irregularity
    2. time irregularity
    3. unlicensed taxi
    4. urban computing
    5. vehicle classification

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    • (2022)Unlicensed Taxi Detection Model Based on Graph EmbeddingElectronics10.3390/electronics1120341011:20(3410)Online publication date: 20-Oct-2022
    • (2021)Detecting and analyzing unlicensed taxis: A case study of Chongqing CityPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2021.126324584(126324)Online publication date: Dec-2021

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