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Papers

Modelling Externalities using Dynamic Traffic Assignment Models: A Review

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Pages 521-545 | Received 09 Feb 2010, Accepted 30 Nov 2010, Published online: 17 May 2011
 

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.

Acknowledgements

The authors would like to thank the ATMA (Advanced Traffic MAnagement) and Pay-As-You-Drive projects of the TRANSUMO programme for their financial contributions. The authors also thank three anonymous referees for their helpful suggestions on improving the original version of the article.

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