Measuring platooning performances of connected and automated vehicles in energy consumption, emission, and efficiency

IF 9 1区 工程技术 Q1 ENERGY & FUELS
Yuan Zheng , Ziyuan Pu , Shen Li , Yu Han , Haoning Xi , Bin Ran
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引用次数: 0

Abstract

Determining the most appropriate connected and automated vehicle (CAV) platoon among alternatives is difficult for the decision-makers while considering multiple conflicting criteria, especially under different spacing policies facing conflicting criteria. The study measures platooning performances of CAVs under different spacing policies, considering energy consumption, emission, and efficiency impacts to determine the ranking order of the alternatives for two distinct groups of decision-makers. A hybrid multi-criteria decision-making approach is developed by integrating three modeling methods and jointly using the simulated and linguistic variables data. An illustrative case is conducted for two alternative CAV platoons from the decision-maker perspectives of enterprise owners and administrators. The results indicate that the CAV platoons with the constant spacing (CS) and constant time gap (CTG) policies exhibit better platooning performance for the enterprise owners and administrators, respectively. Therefore, the proposed approach can effectively serve as a decision-making tool for decision-makers to determine the platooning strategies for CAVs.
测量联网和自动驾驶车辆在能源消耗、排放和效率方面的列队行驶性能
当考虑多个相互冲突的标准时,特别是在不同间距政策下,面对相互冲突的标准,决策者很难在多个备选方案中确定最合适的车联网和自动驾驶车辆(CAV)排。本研究通过对不同间距政策下的自动驾驶汽车的队列行驶性能进行测度,综合考虑能源消耗、排放和效率影响,确定两组不同决策者的备选方案排序。综合三种建模方法,结合模拟变量和语言变量数据,提出了一种混合多准则决策方法。从企业所有者和管理者的决策角度对两个备选CAV排进行了实例分析。结果表明,对于企业所有者和管理者而言,采用等间距和等时间间隔策略的CAV排具有较好的排行性能。因此,该方法可以有效地作为决策者确定自动驾驶汽车队列策略的决策工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Energy
Energy 工程技术-能源与燃料
CiteScore
15.30
自引率
14.40%
发文量
0
审稿时长
14.2 weeks
期刊介绍: Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics. The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management. Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.
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