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How Travel Demand Affects Detection Of Non-recurrent Traffic Congestion On Urban Road Networks

Anbaroglu, B; Heydecker, B; Cheng, T; (2016) How Travel Demand Affects Detection Of Non-recurrent Traffic Congestion On Urban Road Networks. In: Halounova, L and Li, S and Safar, V and Tomkova, M and Rapant, P and Brazdil, K and Shi, W, (eds.) XXIII ISPRS Congress: Commission II [Proceedings]. (pp. pp. 159-164). Copernicus Gesellschaft MBH Green open access

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Abstract

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.

Type: Proceedings paper
Title: How Travel Demand Affects Detection Of Non-recurrent Traffic Congestion On Urban Road Networks
Event: XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic
Location: Prague, CZECH REPUBLIC
Dates: 12 July 2016 - 19 July 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/isprsarchives-XLI-B2-159-2016
Publisher version: http://www.int-arch-photogramm-remote-sens-spatial...
Language: English
Additional information: Published under the Creative Common Attribution 3.0 License (http://creativecommons.org/licenses/by/3.0/)
Keywords: Non-recurrent congestion, space-time clustering, space-time scan statistics, urban road network, travel demand
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1514407
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