HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS
Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them pay...
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Format: | Article |
Language: | English |
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Copernicus Publications
2016-06-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/159/2016/isprs-archives-XLI-B2-159-2016.pdf |
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author | B. Anbaroglu B. Heydecker T. Cheng |
author_facet | B. Anbaroglu B. Heydecker T. Cheng |
author_sort | B. Anbaroglu |
collection | DOAJ |
description | Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London’s urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level. |
first_indexed | 2024-04-13T13:45:41Z |
format | Article |
id | doaj.art-777be012263b4743bbf14522ab460710 |
institution | Directory Open Access Journal |
issn | 1682-1750 2194-9034 |
language | English |
last_indexed | 2024-04-13T13:45:41Z |
publishDate | 2016-06-01 |
publisher | Copernicus Publications |
record_format | Article |
series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
spelling | doaj.art-777be012263b4743bbf14522ab4607102022-12-22T02:44:30ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342016-06-01XLI-B215916410.5194/isprs-archives-XLI-B2-159-2016HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKSB. Anbaroglu0B. Heydecker1T. Cheng2Hacettepe University, Dept. of Geomatics Engineering, 06800, Beytepe, Ankara, TurkeyCentre for Transport Studies, Civil, Environmental and Geomatic Engineering, University College London, Gower Street, London, WC1E 6BT UKSpaceTimeLab, Civil, Environmental and Geomatic Engineering, University College London, Gower Street, London, WC1E 6BT UKOccurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London’s urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/159/2016/isprs-archives-XLI-B2-159-2016.pdf |
spellingShingle | B. Anbaroglu B. Heydecker T. Cheng HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
title | HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS |
title_full | HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS |
title_fullStr | HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS |
title_full_unstemmed | HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS |
title_short | HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS |
title_sort | how travel demand affects detection of non recurrent traffic congestion on urban road networks |
url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/159/2016/isprs-archives-XLI-B2-159-2016.pdf |
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