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Sustainability assessment approaches for intelligent transport systems: The state of the art

Kolosz, Ben; Grant-Muller, Susan

Authors

Profile image of Ben Kolosz

Dr Ben Kolosz B.W.Kolosz@hull.ac.uk
Lecturer in Renewable Energy and Carbon Removal and Director of the MSc Renewable Energy and Low Carbon Solutions Programme

Susan Grant-Muller



Abstract

The appraisal of intelligent transport systems (ITS) has become increasingly important in order to capture their full range of potential impacts. This study aims to assess the appropriateness of conventional transport appraisal models and tools for this task, particularly in reflecting the environmental and socio-economic impacts of ITS. These include the most common environmental systems analysis tools (ESATs), which incorporate international standards and are of considerable importance in indicating sustainability. A review of how emerging methods relate to the goal of a successful transition to a low carbon future is reported, based on the literature. The appraisal of ITS is inherently uncertain due to the decentralised nature of information communication technology; therefore, a range of methods to capture this aspect are reviewed. The models, weights and methods are analysed concerning their ability to estimate sustainability performance, given the numerous configurations of ubiquitous technology that may comprise ITS services. Weighting methods are important in reflecting perceptions of how sustainability should be assessed. These can be incorporated by identifying, classifying and selecting one or more ESAT's based on their suitability for a particular application. Finally, recommendations are given on which tools can be integrated to more comprehensively reflect the performance of ITS.

Citation

Kolosz, B., & Grant-Muller, S. (2016). Sustainability assessment approaches for intelligent transport systems: The state of the art. IET Intelligent Transport Systems, 10(5), 287-297. https://doi.org/10.1049/iet-its.2015.0025

Journal Article Type Article
Acceptance Date Dec 15, 2015
Online Publication Date Jun 1, 2016
Publication Date Jun 1, 2016
Deposit Date Aug 3, 2024
Journal IET Intelligent Transport Systems
Print ISSN 1751-956X
Electronic ISSN 1751-9578
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 10
Issue 5
Pages 287-297
DOI https://doi.org/10.1049/iet-its.2015.0025
Public URL https://hull-repository.worktribe.com/output/4057356