Assessing Eco-driving Behaviors Using Driving Simulator

Eco-driving is a technology that can reduce fuel consumption and emissions at signalized intersections by using Infrastructure-to-Vehicle (I2V) communication system. In this research, eco-driving behaviors of human drivers and automated vehicle were evaluated based on a driving simulator. To minimize the deceleration or avoid the complete stop at the traffic signals, and to ultimately eliminate unnecessary fuel consumptions, the eco-driving guidance provided drivers with speed profile derived from current velocity, distance to the intersection, and remaining green or red time. A total of 43 drivers participated in the driving simulator-based experiments by following the base case and the eco-driving case. At the first experiment, the results showed that the performance of the eco-driving varied a lot by the individual participants. This was because the participants did not closely follow the eco-guidance. At the second experiment, randomly selected 8 drivers from the first experiment were given more time to become comfortable with the interface before the experiments, as well as incentives to motivate them to follow the eco-guidance interface. The second experiment results showed statistically significant about 5% improvements in fuel consumption and emissions over the base case. When the eco-driving case was compared with an automated vehicle case, the automated vehicle improved fuel consumption and emissions between 18-20% over the human-driven eco-driving case.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Cui, Lian
    • Park, Byungkyu Brian
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Photos; References; Tables;
  • Pagination: 16p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01626667
  • Record Type: Publication
  • Report/Paper Numbers: 17-06132
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 27 2017 9:25AM