In this paper, a novel approach for identifying critical congestion hotspots based on network analysis using the automatic number plate recognition (ANPR) data in Cambridge, UK has been explored. This paper addresses use of conceptualized travel networks to reveal congestion patterns and the smart placement of camera sensors. The results of the study show that the travel network model can effectively identify critical congestion points. Using only 44% of the total cameras, the major congestion hotspots, including the junctions around the urban fringe were accurately captured. The current layout of the camera sensors was found to be redundant in several local areas. It is therefore suggested that, spatial optimization should be considered for sensor placement in the future. This study sheds new light on revealing urban mobility patterns in relation to travel networks and provide a heuristic tool for decision-makers for advancing smart digitalization in their cities.


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    Title :

    Identifying Critical Congestion Hotspots Using Network Approach: Smart Spatial Placement of Sensors


    Contributors:

    Conference:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Published in:

    CICTP 2020 ; 2349-2361


    Publication date :

    2020-08-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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