Effects of controlling aggressive driving behavior on network-wide traffic flow and emissions

The scope of this paper is to assess the impact of adopting smooth driving habits on traffic and emissions in large scale urban networks. A methodological approach combining data driven and simulation models is proposed, which, first tries to reveal the prevailing driving profiles using real world driving data gathered from smartphones, and second, to simulate the effect of controlling the observed profiles on traffic and emissions using microscopic simulation. The available database contains a total of 4156 urban trips originating from 100 distinct drivers, for whom detailed driving analytics exist. A k-means clustering algorithm is implemented to extract the driving profiles based on speed and acceleration data. The simulation results show that smooth driving leads to a statistically significant reduction in the emissions of the most important air pollutants. Moreover, limiting the variability of the acceleration to a narrower range, as it occurs in the eco profile, leads to an increase in the output of vehicles in comparison to the other profiles.

Language

  • English

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Filing Info

  • Accession Number: 01746521
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 26 2020 3:04PM