气候变化领域集成服务门户(CCPortal): The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study

CCPortal

DOI	10.1016/j.atmosenv.2020.117399
	The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study
	Makridis M.; Mattas K.; Mogno C.; Ciuffo B.; Fontaras G.
发表日期	2020
ISSN	1352-2310
卷号	226
英文摘要	The interest on the impact of vehicle automation and connectivity in the future road transport networks is very high, both from a research and a policy perspective. Results in the literature show that many of the anticipated advantages of connected and automated vehicles or automated vehicles without connectivity (CAVs and AVs respectively) on congestion and energy consumption are questionable. Some studies provide quantitative answers to the above questions through microsimulation but they systematically ignore the realistic simulation of vehicle dynamics, driver behaviour or instantaneous emissions estimates, mostly due to the overall increased complexity of the transport systems and the need for low computational demand on large-scale simulations. However, recent studies question the capability of common car-following models to produce realistic vehicle dynamics or driving behaviour, which directly impacts emissions estimations as well. This work presents a microsimulation study that contributes on the topic, using a scenario-based approach to give insights regarding the impact of CAVs and AVs on the evolution of emissions over a highway network. The motivation here is to answer whether the different driving behaviours produce significant differences in emissions during rush hours, and how significant is the impact of detailed vehicle dynamics simulation and instantaneous emissions in the outcome. The status of the network is assessed in terms of flow and speed. Furthermore, emissions are estimated using both the average-speed EMEP/EEA fuel consumption factors and a generic version of the European Commission's CO2MPAS model that provides instantaneous fuel consumption estimates. The simulation results of this work show that AVs can deteriorate the status of the network, and that connectivity is the key for improved traffic flow. Emissions-wise, the AVs have the highest fuel consumption per km travelled among other types, while CAVs only marginally lower the overall consumption of human-driven vehicles. For the same traffic demand, the total emissions for different vehicle types remain at comparable levels. © 2020 Elsevier Ltd
英文关键词	Car-following; CO2 emissions; Connected and automated vehicles; Emissions estimation; Traffic flow; Traffic microsimulation; Vehicle dynamics
语种	英语
scopus关键词	Automation; Carbon dioxide; Dynamics; Energy utilization; Fuels; Highway traffic control; Traffic congestion; Automated vehicles; Car following; CO2 emissions; Emissions estimation; Traffic flow; Traffic micro simulations; Vehicle dynamics; Road vehicles; carbon dioxide; fuel; automation; carbon dioxide; carbon emission; congestion; European Commission; road transport; simulation; traffic management; acceleration; Article; automation; car; carbon footprint; comparative study; controlled study; deceleration; energy consumption; European; human; molecular dynamics; priority journal; reaction time; simulation; traffic
来源期刊	Atmospheric Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/129582
作者单位	European Commission Joint Research Centre, Ispra, 21027, Italy; Democritus University of Thrace, Xanthi, 67100, Greece
推荐引用方式 GB/T 7714	Makridis M.,Mattas K.,Mogno C.,et al. The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study[J],2020,226.
APA	Makridis M.,Mattas K.,Mogno C.,Ciuffo B.,&Fontaras G..(2020).The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study.Atmospheric Environment,226.
MLA	Makridis M.,et al."The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study".Atmospheric Environment 226(2020).