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Empirical assessment of urban traffic congestion

Chow, AHF; Santacreu, A; Tsapakis, I; Tanasaranond, G; Cheng, T; (2014) Empirical assessment of urban traffic congestion. JOURNAL OF ADVANCED TRANSPORTATION , 48 (8) 1000 - 1016. 10.1002/atr.1241. Green open access

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Abstract

This paper presents an empirical assessment of urban traffic congestion in Central London, UK. Compared with freeways or motorways, urban networks are relatively less studied because of its complexity and availability of required traffic data. This paper introduces the use of automatic number plate recognition technology to analyze the characteristic of urban traffic congestion in Central London. We also present the use of linear regression to diagnose the observed congestion and attribute them to different causes. In particular, we distinguish the observed congestion into two main components: one due to recurrent factors and the other due to nonrecurrent factors. The methodologies are illustrated through a case study of Central London Area. It is found that about 15% of the observed congestion in the region is due to nonrecurrent factors such as accidents, roadwork, special events, and strikes. Given the significance of London, the study will be valuable for transport policy evaluation and appraisal in other global cities.

Type: Article
Title: Empirical assessment of urban traffic congestion
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/atr.1241
Publisher version: http://dx.doi.org/10.1002/atr.1241
Language: English
Keywords: automatic number plate recognition (ANPR), London Traffic Information System (LTIS), visualization, linear regression, congestion pie
UCL classification: UCL
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/1400264
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