A macroscopic traffic flow model for adverse weather conditions.

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dc.contributor.author Shah, Syed Abid Ali
dc.date.accessioned 2017-04-06T14:32:45Z
dc.date.available 2017-04-06T14:32:45Z
dc.date.copyright 2017 en_US
dc.date.issued 2017-04-06
dc.identifier.uri http://hdl.handle.net/1828/7881
dc.description.abstract Adverse weather has a direct effect on traffic congestion and the time delay on roads. Weather conditions today are changing rapidly and are more likely to have a severe effect on traffic in the future. Although different measures have been taken to mitigate these conditions, it is important to study the impact of these events on road conditions and traffic flow. For example, the surface of a road is affected by snow, compacted snow and ice. The objective of this thesis is to characterize the effect of road surface conditions on traffic flow. To date, traffic flow under adverse weather conditions has not been characterized. A macroscopic traffic flow model based on the transition velocity distribution is proposed which characterizes traffic behavior during traffic alignment under adverse weather conditions. The model proposed realistically characterizes the traffic flow based on snow, compacted snow, and ice. Results are presented which show that this model provides a more accurate characterization of traffic flow behavior than the well known Payne-Whitham model. en_US
dc.language English eng
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject Traffic Modelling en_US
dc.title A macroscopic traffic flow model for adverse weather conditions. en_US
dc.type Thesis en_US
dc.contributor.supervisor Gulliver, T. Aaron
dc.contributor.supervisor Kahn, Zawar
dc.degree.department Department of Electrical and Computer Engineering en_US
dc.degree.level Master of Applied Science M.A.Sc. en_US
dc.description.scholarlevel Graduate en_US

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