Highlights We estimated the air quality impact of distributed dynamic control in a CAV-enabled network. Traffic delay, total GHGs, and total NOx decreased by applying the control system. Average NO2 concentration over the entire simulation period was lower with CAV control. The NO2 maxima were higher in the scenario with CAV control. The control system did not necessarily lead to less energy consumption in a full-EV environment.
Abstract Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO2 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NOx) increased with higher CAVs. Besides, a higher frequency and severity of NO2 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.
Quantifying the impacts of dynamic control in connected and automated vehicles on greenhouse gas emissions and urban NO2 concentrations
Transportation Research Part D: Transport and Environment ; 73 ; 142-151
2019-01-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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