Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic

Raphael E. Stern, Yuche Chen, Miles Churchill, Fangyu Wu, Maria Laura Delle Monache, Benedetto Piccoli, Banjamin Seibold, Jonathan Sprinkle, Daniel B. Work

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

It is anticipated that in the near future, the penetration rate of vehicles with some autonomous capabilities (e.g., adaptive cruise control, lane following, full automation, etc.) will increase on roadways. This work investigates the potential reduction of vehicular emissions caused by the whole traffic stream, when a small number of autonomous vehicles (e.g., 5% of the vehicle fleet) are designed to stabilize the traffic flow and dampen stop-and-go waves. To demonstrate this, vehicle velocity and acceleration data are collected from a series of field experiments that use a single autonomous-capable vehicle to dampen traffic waves on a circular ring road with 20–21 human-piloted vehicles. From the experimental data, vehicle emissions (hydrocarbons, carbon monoxide, carbon dioxide, and nitrogen oxides) are estimated using the MOVES emissions model. This work finds that vehicle emissions of the entire fleet may be reduced by between 15% (for carbon dioxide) and 73% (for nitrogen oxides) when stop-and-go waves are reduced or eliminated by the dampening action of the autonomous vehicle in the flow of human drivers. This is possible if a small fraction (∼5%) of vehicles are autonomous and designed to actively dampen traffic waves. However, these reductions in emissions apply to driving conditions under which stop-and-go waves are present. Less significant reductions in emissions may be realized from a deployment of AVs in a broader range of traffic conditions.

Original languageEnglish (US)
Pages (from-to)351-365
Number of pages15
JournalTransportation Research Part D: Transport and Environment
Volume67
DOIs
StatePublished - Feb 1 2019

Fingerprint

Air quality
air quality
air
traffic
traffic emission
nitrogen oxides
Nitrogen oxides
carbon dioxide
Carbon dioxide
automation
vehicle
Adaptive cruise control
driver
carbon monoxide
road
penetration
Carbon monoxide
experiment
hydrocarbon
Automation

Keywords

  • Autonomous vehicles
  • Traffic stability
  • Traffic waves
  • Vehicle emissions

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation
  • Environmental Science(all)

Cite this

Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic. / Stern, Raphael E.; Chen, Yuche; Churchill, Miles; Wu, Fangyu; Delle Monache, Maria Laura; Piccoli, Benedetto; Seibold, Banjamin; Sprinkle, Jonathan; Work, Daniel B.

In: Transportation Research Part D: Transport and Environment, Vol. 67, 01.02.2019, p. 351-365.

Research output: Contribution to journalArticle

Stern, Raphael E. ; Chen, Yuche ; Churchill, Miles ; Wu, Fangyu ; Delle Monache, Maria Laura ; Piccoli, Benedetto ; Seibold, Banjamin ; Sprinkle, Jonathan ; Work, Daniel B. / Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic. In: Transportation Research Part D: Transport and Environment. 2019 ; Vol. 67. pp. 351-365.
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