Impacts of Eco Driving on Traffic Flow and Emissions in Large Scale Urban Networks

Eco-driving has been gaining increasing interest the last decade not only as means to reduce fuel consumption, but also as a global strategy to reduce emissions and improve air quality. The scope of this paper is to assess the impact of eco driving on traffic flow and emissions in large scale urban networks. To this end, a methodological approach based on data science and simulation is proposed, which, first targets 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 to traffic and emission using a microscopically simulated scenarios of different driving profiles of the road network of the city of Luxembourg. The available database contains a total of 4156 urban trips originating from 100 distinct drivers, for whom detailed driving analytics exist. A k-means algorithm is implemented to extract the driving profiles based on speed and acceleration data. Results show that eco driving leads to a statistically significant reduction in the emissions of the most important air pollutants. Moreover, limiting the acceleration to a narrower range, as it occurs in the eco profile, lead to an increase in the output of vehicles in comparison to the other profiles. This finding may prove particularly important in the future as autonomous, interconnected vehicles through a c-ITS may be able to adjust to one another’s kinematic characteristics and increase the capacity of existing roads, although with limitations concerning the application of this principle in different traffic conditions.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABJ70 Standing Committee on Artificial Intelligence and Advanced Computing Applications.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Adamidis, Filippos K
    • Mantouka, Eleni G
    • Barmpounakis, Emmanouil N
    • Vlahogianni, Eleni I
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01697461
  • Record Type: Publication
  • Report/Paper Numbers: 19-04158
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:28AM