Traveling Officer Problem: Managing Car Parking Violations Efficiently Using Sensor Data

Publication Year: 2018 Publication Type : JournalArticle


The on-street parking system is an indispensable part of civil projects, which provides travellers and shoppers with parking spaces. With the recent in-ground sensors deployed throughout the city, there is a significant problem on how to use the sensor data to manage parking violations and issue infringement notices in a short time-window efficiently. In this paper, we use a large real-world dataset with on-street parking sensor data from the local city council, and establish a formulation of the Travelling Officer Problem with a general probabilitybased model. We propose two solutions using a spatio-temporal probability model for parking officers to maximize the number of infringing cars caught with limited time cost. Using real-world parking sensor data and Google Maps road network information, the experimental results show that our proposed algorithms outperform the existing patrolling routes.


    author = {Wei Shao and Flora D. Salim and Tao Gu and Ngoc-Thanh Dinh and Jeffrey Chan},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    doi = {10.1109/JIOT.2017.2759218},
    journal = {IEEE Internet Things J.},
    number = {2},
    pages = {802--810},
    timestamp = {Mon, 08 Jun 2020 01:00:00 +0200},
    title = {Traveling Officer Problem: Managing Car Parking Violations Efficiently Using Sensor Data},
    url = {},
    volume = {5},
    year = {2018}


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