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Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles

机译:帮助还是阻碍?高度自动化的车辆对旅行,能源和碳的影响

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Experts predict that new automobiles will be capable of driving themselves under limited conditions within 5-10 years, and under most conditions within 10-20 years. Automation may affect road vehicle energy consumption and greenhouse gas (GHG) emissions in a host of ways, positive and negative, by causing changes in travel demand, vehicle design, vehicle operating profiles, and choices of fuels. In this paper, we identify specific mechanisms through which automation may affect travel and energy demand and resulting GHG emissions and bring them together using a coherent energy decomposition framework. We review the literature for estimates of the energy impacts of each mechanism and, where the literature is lacking, develop our own estimates using engineering and economic analysis. We consider how widely applicable each mechanism is, and quantify the potential impact of each mechanism on a common basis: the percentage change it is expected to cause in total GHG emissions from light-duty or heavy-duty vehicles in the U.S. Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half - or nearly double them - depending on which effects come to dominate. We also find that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. We close by presenting some implications for policymakers and identifying priority areas for further research. (C) 2016 The Authors. Published by Elsevier Ltd.
机译:专家预测,新汽车将能够在5-10年内的有限条件下以及在10-20年内的大多数条件下自我驾驶。自动化可能通过引起出行需求,车辆设计,车辆运行状况和燃料选择的变化,以正反两种方式影响道路车辆的能源消耗和温室气体(GHG)排放。在本文中,我们确定了自动化可能会影响出行和能源需求以及由此产生的温室气体排放的具体机制,并使用相干的能量分解框架将它们结合在一起。我们回顾了文献中对每种机制的能量影响的估计,并在缺乏文献的情况下,使用工程和经济分析得出了自己的估计。我们考虑每种机制的适用范围,并在一个共同的基础上量化每种机制的潜在影响:在美国,轻型或重型车辆在温室气体总排放量中所预期造成的百分比变化。我们的主要重点是与旅行相关的能源消耗和排放,因为潜在的生命周期影响通常较小。我们通过几种示例性方案探索了自动化对排放的净影响,发现自动化可能会根据占主导地位的影响,将道路运输的温室气体排放量和能源消耗合理地减少近一半(或近两倍)。我们还发现,通过部分自动化可以实现许多潜在的节能收益,而在完全自动化的情况下,主要的能源/排放下行风险似乎更大。最后,我们向决策者提出一些建议,并确定需要进一步研究的优先领域。 (C)2016作者。由Elsevier Ltd.发布

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