A prediction model for atmospheric pollution reduction from urban traffic

Abdelfettah Laouzai and Rachid Ouafi ()
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Abdelfettah Laouzai: University of Science and Technology Houari-Boumediene, Algeria

Environment and Planning B, 2022, vol. 49, issue 2, 566-584

Abstract: In order to reduce the atmospheric pollution in urban areas, an enhanced approach is proposed in this paper for the traffic congestion analysis. The approach is formulated as bi-level optimization program considering additional constraints in the traffic assignment problem. To respect the required eco-friendly threshold constraint, the travel demand between several origin–destination pairs was categorized in two classes: old polluting cars and modern (less) nonpolluting cars. The validity of the formulation was verified by optimality conditions. Two network examples are discussed to explain the properties and advantages of the suggested technique. It is found that for the both examples, the proposed optimal solution displays better results as compared to the common user equilibrium route choice policies. As a result, the enhanced approach leads to traffic network congestion relief with minimum air pollution and maximum use of routes network.

Keywords: Traffic congestion; mathematical model; travel decisions; equilibrium; traffic network; atmospheric pollution (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:49:y:2022:i:2:p:566-584

DOI: 10.1177/23998083211005776

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