Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.684303
Title: Understanding the variability in vehicle dynamics and emissions at urban obstacles
Author: Thiyagarajah, Aravinth
ISNI:       0000 0004 5920 7890
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Abstract:
Roadworks are a feature of the road network that can cause vehicles to deviate from their desired speed or trajectory. This may negatively impact traditional measures of network performance such as travel time, or result in changes to tailpipe emission rates. The impact of roadworks on tailpipe emission rates is of interest due to the harmful pollutants that are released during the combustion process. Pollutants such as nitrogen oxides (NOx) are toxic to humans, and carbon dioxide (CO2) is a greenhouse believed to influence human-induced global climate change. In order to investigate methods of reducing the environmental impact of roadworks and other obstacles in the road network, modelling tools may be used. However, it is essential that the tools are appropriate for modelling these features of the road network. In order to assess the suitability of existing traffic and emission modelling tools, an understanding of the variability in vehicle dynamics and emissions at urban obstacles is first required. In this thesis, a dataset that contains real-world tailpipe emissions and vehicle dynamics data, from vehicles in the vicinity of urban obstacles such as roadworks, is assembled. This is achieved using a portable emission measurement system (PEMS) and a high-resolution trajectory monitoring platform developed as part of this research. Through analysis of the acceleration behaviour and tailpipe emission rates at different urban obstacles and from different vehicles, an understanding of the variability is formed. The findings from the analysis of behaviours observed in the vicinity of urban obstacles are then used to adapt existing traffic and emissions modelling tools. The error between measured and modelled emissions is shown to reduce from over 30% to under 12% for CO2 emissions. Based on the findings of a roadworks case study, recommendations are made to policy makers and the modelling community.
Supervisor: Polak, John ; Ochieng, Washington ; Bell, Michael Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.684303  DOI: Not available
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