Skip to main content

Research Repository

Advanced Search

A macroscopic forecasting framework for estimating socioeconomic and environmental performance of intelligent transport highways

Kolosz, Ben W.; Grant-Muller, Susan M.; Djemame, Karim

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 M. Grant-Muller

Karim Djemame



Abstract

The anticipated introduction of new forms of intelligent transport systems (ITS) represents a significant opportunity for increased cooperative mobility and sociotechnical changes within the transport system. Although such technologies are currently technically feasible, various socioeconomic and environmental barriers impede their arrival. This paper uses a recently developed ITS performance assessment framework, i.e., Environmental Fusion (EnvFUSION), to perform dynamic forecasting of the performance for three key ITS technologies: active traffic management (ATM), intelligent speed adaptation (ISA), and an automated highway system (AHS) using a mathematical theory of evidence. A consequential lifecycle assessment (c-LCA) is undertaken, which forms part of a data fusion process using data from various sources. The models forecast improvements for the three ITS technologies in line with social acceptability, economic profitability, and major carbon reduction scenarios up to 2050 on one of the U.K.'s most congested highways. An analytical hierarchy process (AHP) and the Dempster-Shafer theory (DST) are used to weight criteria that form part of an intelligent transport sustainability index (ITSI). Overall performance is then synthesized. Results indicate that there will be a substantial increase in socioeconomic and emissions benefits, provided that the policies are in place and targets are reached, which would otherwise delay their realization. © 2013 IEEE.

Citation

Kolosz, B. W., Grant-Muller, S. M., & Djemame, K. (2014). A macroscopic forecasting framework for estimating socioeconomic and environmental performance of intelligent transport highways. IEEE Transactions on Intelligent Transportation Systems, 15(2), 723-736. https://doi.org/10.1109/TITS.2013.2284638

Journal Article Type Article
Online Publication Date Nov 8, 2013
Publication Date Apr 1, 2014
Deposit Date Aug 3, 2024
Journal IEEE Transactions on Intelligent Transportation Systems
Print ISSN 1524-9050
Electronic ISSN 1558-0016
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 15
Issue 2
Pages 723-736
DOI https://doi.org/10.1109/TITS.2013.2284638
Keywords Economics; Environmental factors; Forecasting; Intelligent transport systems (ITSs); Probabilistic model; Social factors
Public URL https://hull-repository.worktribe.com/output/4057383