Identifying Critical Congestion Hotspots Using Network Approach: Smart Spatial Placement of Sensors
Identifying Critical Congestion Hotspots Using Network Approach: Smart Spatial Placement of Sensors
- Neue Suche nach: Tang, Junqing
- Neue Suche nach: Wan, Li
- Neue Suche nach: Nochta, Timea
- Neue Suche nach: Schooling, Jennifer
- Neue Suche nach: Tang, Junqing
- Neue Suche nach: Wan, Li
- Neue Suche nach: Nochta, Timea
- Neue Suche nach: Schooling, Jennifer
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.
Dokumentinformationen
Identifying Critical Congestion Hotspots Using Network Approach: Smart Spatial Placement of Sensors
20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)
CICTP 2020 ; 2349-2361
2020-08-12
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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