The evolution and future of urban road incident detection algorithms
The evolution and future of urban road incident detection algorithms
Only a small minority of road incident detection algorithms (IDAs) have been designed for use in urban road networks. A review of the literature conducted by the authors revealed that approximately 10% of published papers on novel IDAs are designed specifically for urban networks. Urban networks present many challenges that are not faced on highways, such as signalized junctions causing queuing similar to that of an incident. This paper reviews the progress made in urban incident detection research and highlights where improvements are needed. It is found that few algorithms have been implemented or tested on real-world data, and so few have been sufficiently evaluated or compared. Those that have been implemented often find difficulty in differentiating disruption from incidents and contextual factors such as sporting events or public holidays. This has caused unnecessary false alerts to be triggered, leading to dissatisfied operators. Progress could be made if more research data and IDAs were published, allowing for thorough evaluations and comparisons of algorithm performance on real-world data. Further research is required to improve IDAs’ ability to differentiate between incidents and contexts, particularly in complex urban networks.
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Evans, Jonny Rhys Alexander
fa85f2a7-dd18-4b43-9b40-d0f40bb7363d
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Hamilton, Andrew
12ead9ac-0af5-4773-a657-906b4d89772b
1 June 2020
Evans, Jonny Rhys Alexander
fa85f2a7-dd18-4b43-9b40-d0f40bb7363d
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Hamilton, Andrew
12ead9ac-0af5-4773-a657-906b4d89772b
Evans, Jonny Rhys Alexander, Waterson, Ben and Hamilton, Andrew
(2020)
The evolution and future of urban road incident detection algorithms.
Journal of Transportation Engineering Part A: Systems, 146 (6), , [03120001].
(doi:10.1061/JTEPBS.0000362).
Abstract
Only a small minority of road incident detection algorithms (IDAs) have been designed for use in urban road networks. A review of the literature conducted by the authors revealed that approximately 10% of published papers on novel IDAs are designed specifically for urban networks. Urban networks present many challenges that are not faced on highways, such as signalized junctions causing queuing similar to that of an incident. This paper reviews the progress made in urban incident detection research and highlights where improvements are needed. It is found that few algorithms have been implemented or tested on real-world data, and so few have been sufficiently evaluated or compared. Those that have been implemented often find difficulty in differentiating disruption from incidents and contextual factors such as sporting events or public holidays. This has caused unnecessary false alerts to be triggered, leading to dissatisfied operators. Progress could be made if more research data and IDAs were published, allowing for thorough evaluations and comparisons of algorithm performance on real-world data. Further research is required to improve IDAs’ ability to differentiate between incidents and contexts, particularly in complex urban networks.
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Accepted/In Press date: 26 November 2019
e-pub ahead of print date: 28 March 2020
Published date: 1 June 2020
Additional Information:
Publisher Copyright:
© 2020 American Society of Civil Engineers.
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Local EPrints ID: 439496
URI: http://eprints.soton.ac.uk/id/eprint/439496
ISSN: 2473-2907
PURE UUID: 1439ea01-4cbe-42ef-8b1d-d8191a207ecb
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Date deposited: 24 Apr 2020 16:30
Last modified: 17 Mar 2024 02:46
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Author:
Jonny Rhys Alexander Evans
Author:
Andrew Hamilton
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