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Modelling Externalities using Dynamic Traffic Assignment Models: A Review

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  • Luc Wismans
  • Eric Van Berkum
  • Michiel Bliemer

Abstract

Recently, there has been a growing interest in externalities in our society, mainly in the context of climate and air quality, which are of importance when policy decisions are made. For the assessment of externalities in transport, often the output of static traffic assignment models is used in combination with so-called effect models. Due to the rapidly increasing possibilities of using dynamic traffic assignment (DTA) models for large-scale transportation networks and the application of traffic measures, already several models have been developed to assess the externalities using DTA models more precisely. Different research projects have shown that there is a proven relation between the traffic dynamics and externalities, such as emissions of pollutants and traffic safety. This means that the assessment of external effects can be improved by using temporal information about flow, speed and density, which is the output of DTA models. In this paper, the modelling of traffic safety, emissions and noise in conjunction with DTA models is reviewed based on an extensive literature survey. This review shows that there are still gaps in knowledge in assessing traffic safety, much research is available concerning emissions, and although little research has been conducted concerning the assessment of noise using DTA models, the methods available can be used to assess the effects. Most research so far has focused on the use of microscopic models, while mesoscopic or macroscopic models may have a high potential for improving the assessment of these effects for larger networks.

Suggested Citation

  • Luc Wismans & Eric Van Berkum & Michiel Bliemer, 2011. "Modelling Externalities using Dynamic Traffic Assignment Models: A Review," Transport Reviews, Taylor & Francis Journals, vol. 31(4), pages 521-545.
  • Handle: RePEc:taf:transr:v:31:y:2011:i:4:p:521-545
    DOI: 10.1080/01441647.2010.544856
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    Cited by:

    1. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    2. Andrea Gemma & Orlando Giannattasio & Livia Mannini, 2023. "Motorway Traffic Emissions Estimation through Stochastic Fundamental Diagram," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    3. Arwa S. Sayegh & Richard D. Connors & James E. Tate, 2018. "Uncertainty Propagation from the Cell Transmission Traffic Flow Model to Emission Predictions: A Data-Driven Approach," Service Science, INFORMS, vol. 52(6), pages 1327-1346, December.

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