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A prediction model for atmospheric pollution reduction from urban traffic

Author

Listed:
  • Abdelfettah Laouzai

    (University of Science and Technology Houari-Boumediene, Algeria
    SONATRACH-Direction Centrale Recherche et Développement, Algérie)

  • Rachid Ouafi

    (University of Science and Technology Houari-Boumediene, Algeria)

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.

Suggested Citation

  • Abdelfettah Laouzai & Rachid Ouafi, 2022. "A prediction model for atmospheric pollution reduction from urban traffic," Environment and Planning B, , vol. 49(2), pages 566-584, February.
    • Handle: RePEc:sae:envirb:v:49:y:2022:i:2:p:566-584
    DOI: 10.1177/23998083211005776
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    References listed on IDEAS

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