Designing a road traffic model for the cross-sectoral analysis of future national infrastructure
Designing a road traffic model for the cross-sectoral analysis of future national infrastructure
This paper presents a UK national road traffic model developed as part of the ITRC MISTRAL - a large interdisciplinary project of the Infrastructure Transitions Research Consortium (ITRC). The proposed model includes passenger and freight vehicle flows on major UK roads and predicts future demand in the form of an inter-zonal origin-destination matrix, using and elasticity-based simulation approach. An important part of the model is the network assignment step during which predicted flows are assigned to the road network. This allows for the assessment of road capacity utilisation and facilitates the identification of "pinch points" where future infrastructure investments might be targeted. Several policy interventions are studied in the paper, including road expansion with additional lanes, new road development and vehicle electrification. The model also explicitly considers cross-sectoral interdependencies with other infrastructure networks, primarily with the energy sector where the transport sector is the largest consumer, the digital communications sector, water supply and waste management. In future extensions, the model will also be able to estimate the environmental footprint and assess the risk and resilience of the transport network. This model has the potential to inform policy makers about the long-term performance of UK road infrastructure, considering a range of possible future scenarios for population growth, technological innovation and climate change.
Lovric, Milan
64a3c876-4d8f-442f-9062-6dc491c773d1
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Preston, Jonathan
ef81c42e-c896-4768-92d1-052662037f0b
Lovric, Milan
64a3c876-4d8f-442f-9062-6dc491c773d1
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Preston, Jonathan
ef81c42e-c896-4768-92d1-052662037f0b
Lovric, Milan, Blainey, Simon and Preston, Jonathan
(2017)
Designing a road traffic model for the cross-sectoral analysis of future national infrastructure.
International Symposia for Next Generation Infrastructure, One Great George Street, London, United Kingdom.
11 - 13 Sep 2017.
(In Press)
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents a UK national road traffic model developed as part of the ITRC MISTRAL - a large interdisciplinary project of the Infrastructure Transitions Research Consortium (ITRC). The proposed model includes passenger and freight vehicle flows on major UK roads and predicts future demand in the form of an inter-zonal origin-destination matrix, using and elasticity-based simulation approach. An important part of the model is the network assignment step during which predicted flows are assigned to the road network. This allows for the assessment of road capacity utilisation and facilitates the identification of "pinch points" where future infrastructure investments might be targeted. Several policy interventions are studied in the paper, including road expansion with additional lanes, new road development and vehicle electrification. The model also explicitly considers cross-sectoral interdependencies with other infrastructure networks, primarily with the energy sector where the transport sector is the largest consumer, the digital communications sector, water supply and waste management. In future extensions, the model will also be able to estimate the environmental footprint and assess the risk and resilience of the transport network. This model has the potential to inform policy makers about the long-term performance of UK road infrastructure, considering a range of possible future scenarios for population growth, technological innovation and climate change.
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Accepted/In Press date: 22 August 2017
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International Symposia for Next Generation Infrastructure, One Great George Street, London, United Kingdom, 2017-09-11 - 2017-09-13
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Local EPrints ID: 414981
URI: http://eprints.soton.ac.uk/id/eprint/414981
PURE UUID: a240f364-193f-4d51-8d65-533a6c41cc43
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Date deposited: 19 Oct 2017 16:30
Last modified: 16 Mar 2024 03:59
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