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Coupling traffic and emission models: dynamic driving speed for emissions assessment
Delphine Lejri, Ludovic Leclercq, Arnaud Can

Coupling traffic and emission models: dynamic driving speed for emissions assessment

Science & Mathematics Published 2016 Verification Pending

Overview & Synopsis

Emission models can provide an estimation of the environmental impact of road traffic. However, decision makers need to be confident in these assessments in order to implement reduction strategies. The key issue at stake, especially in dense urban zone, is to describe accurately the traffic dynamic and particularly the congestion periods. The proper definition of the link mean speed is the ratio of total travelled distance and total time spent during a given period. This spatial speed description can be easily obtained from a dynamic traffic simulation. However, in operational conditions, it is often deduced from observed speeds on loop detectors or speed limit, which inevitably implies a bias on related emissions to be quantified. For this study we focused on vehicle trajectories in the morning peak for a typical weekday in a 3km2 urban network. These detailed traffic data represent a considerable amount of data, but allows us to operate any spatiotemporal aggregation used for emission assessment sake. The emission calculations were made at link level each 6 minutes, combining the various traffic indicators and either the Copert emission factors database or Phem model. The related fuel consumption and NOx emissions are compared.

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Document Information

Document Title Coupling traffic and emission models: dynamic driving speed for emissions assessment
Author / Organization Delphine Lejri, Ludovic Leclercq, Arnaud Can
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2016
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-12222
Original Source Link Visit Source Page on hal.science »