Traveling officer problem: Managing car parking violations efficiently using sensor data

Publication Year: 2017 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 = {Shao, Wei and Salim, Flora D and Gu, Tao and Dinh, Ngoc-Thanh and Chan, Jeffrey},
    journal = {IEEE Internet of Things Journal},
    number = {2},
    pages = {802--810},
    publisher = {IEEE},
    title = {Traveling officer problem: Managing car parking violations efficiently using sensor data},
    volume = {5},
    year = {2017}


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