Travel time, delay and CO2 impacts of SAE L3 driving automation of passenger cars on the European motorway network

IF 2.1 4区 工程技术 Q3 TRANSPORTATION
Elina Aittoniemi, Teemu Itkonen, Satu Innamaa
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引用次数: 0

Abstract

Impacts of driving automation on traffic flow and emissions are usually studied with traffic simulations using only few speed limits and traffic volumes. Without considering the real-world prevalence of simulated scenarios, it is unknown how the results translate to real-world conditions, such as a regional motorway network. The present study assessed the potential impacts of conditionally automated driving, described by stable vehicle motion control and longer time gaps, on the European motorway network assuming no changes in other influential factors, such as travel demand or vehicle fleet. Traffic simulations provided estimates of the effect magnitude per vehicle kilometre travelled (VKT) in representative conditions, and results were scaled up using map-, traffic- and weather-related data, accounting for the VKT per condition. Overall, the impacts of automated vehicles (AVs) on the European motorway network are likely small. Travel times and delay are estimated to increase by 0.8% and 1.3% respectively at a 100% AV penetration rate among passenger cars, and CO2 emissions to drop by 0.5%. While large reductions of average travel time (up to 8.0–10.4%), delay (up to 17.5–34.8%) and emissions (up to 13.5–15.0%) were found at high traffic volumes, most (86%) of the VKT accumulate at low traffic volumes, with small estimated effects. Thus, although beneficial in some conditions, the AVs considered in this study are not likely to support Europe’s sustainability goals. Findings advocate a comprehensive approach: Whereas impacts are likely greatest in heavy traffic, the prevalence of conditions must be considered in network level assessment.
SAE L3自动驾驶乘用车在欧洲高速公路网上的行驶时间、延迟和二氧化碳影响
驾驶自动化对交通流和排放的影响研究通常只使用少量的限速和交通量进行交通模拟。如果不考虑现实世界中普遍存在的模拟场景,则不知道结果如何转化为现实世界的条件,例如区域高速公路网络。目前的研究评估了有条件自动驾驶的潜在影响,通过稳定的车辆运动控制和更长的时间间隔来描述,假设其他影响因素(如旅行需求或车队)没有变化。交通模拟提供了代表性条件下每车辆行驶公里(VKT)影响程度的估计,并使用地图、交通和天气相关数据对结果进行了缩放,计算了每种条件下的VKT。总体而言,自动驾驶汽车(AVs)对欧洲高速公路网络的影响可能很小。如果自动驾驶汽车在乘用车中的普及率达到100%,预计出行时间和延误时间将分别增加0.8%和1.3%,二氧化碳排放量将下降0.5%。虽然在高交通量时,平均行车时间(高达8.0-10.4%)、延误(高达17.5-34.8%)和排放(高达13.5-15.0%)大幅减少,但大部分(86%)的VKT在低交通量时累积,估计影响很小。因此,尽管在某些条件下是有益的,但本研究中考虑的自动驾驶汽车不太可能支持欧洲的可持续发展目标。研究结果主张采用综合方法:尽管在繁忙的交通中影响可能最大,但在网络级别评估中必须考虑条件的普遍性。
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来源期刊
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
30 weeks
期刊介绍: The European Journal of Transport and Infrastructure Research (EJTIR) is a peer-reviewed scholarly journal, freely accessible through the internet. EJTIR aims to present the results of high-quality scientific research to a readership of academics, practitioners and policy-makers. It is our ambition to be the journal of choice in the field of transport and infrastructure both for readers and authors. To achieve this ambition, EJTIR distinguishes itself from other journals in its field, both through its scope and the way it is published.
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