Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic

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 to 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.
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Raphael Stern, Yuche Chen, Miles Churchill, Fangyu Wu, Maria Laura Delle Monache, et al.. Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic. Transportation Research Part D: Transport and Environment, Elsevier, 2019, 67, pp.351-365. ⟨10.1016/j.trd.2018.12.008⟩. ⟨hal-02022692⟩

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