英文标题：
《Forecasting the Impact of Connected and Automated Vehicles on Energy Use
  A Microeconomic Study of Induced Travel and Energy Rebound》
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作者：
Morteza Taiebat, Samuel Stolper, Ming Xu
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最新提交年份：
2019
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英文摘要：
  Connected and automated vehicles (CAVs) are expected to yield significant improvements in safety, energy efficiency, and time utilization. However, their net effect on energy and environmental outcomes is unclear. Higher fuel economy reduces the energy required per mile of travel, but it also reduces the fuel cost of travel, incentivizing more travel and causing an energy \"rebound effect.\" Moreover, CAVs are predicted to vastly reduce the time cost of travel, inducing further increases in travel and energy use. In this paper, we forecast the induced travel and rebound from CAVs using data on existing travel behavior. We develop a microeconomic model of vehicle miles traveled (VMT) choice under income and time constraints; then we use it to estimate elasticities of VMT demand with respect to fuel and time costs, with fuel cost data from the 2017 United States National Household Travel Survey (NHTS) and wage-derived predictions of travel time cost. Our central estimate of the combined price elasticity of VMT demand is -0.4, which differs substantially from previous estimates. We also find evidence that wealthier households have more elastic demand, and that households at all income levels are more sensitive to time costs than to fuel costs. We use our estimated elasticities to simulate VMT and energy use impacts of full, private CAV adoption under a range of possible changes to the fuel and time costs of travel. We forecast a 2-47% increase in travel demand for an average household. Our results indicate that backfire - i.e., a net rise in energy use - is a possibility, especially in higher income groups. This presents a stiff challenge to policy goals for reductions in not only energy use but also traffic congestion and local and global air pollution, as CAV use increases.
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中文摘要：
互联和自动化车辆（CAV）有望在安全性、能效和时间利用率方面取得显著改善。然而，它们对能源和环境结果的净影响尚不清楚。更高的燃油经济性降低了每英里旅行所需的能源，但也降低了旅行的燃油成本，刺激了更多的旅行，并产生了能源“反弹效应”此外，预计CAV将大大减少旅行的时间成本，从而进一步增加旅行和能源使用。在本文中，我们使用现有行程行为的数据预测CAV的诱导行程和反弹。我们建立了收入和时间约束下车辆行驶里程（VMT）选择的微观经济模型；然后，我们利用2017年美国全国家庭旅行调查（NHTS）的燃料成本数据和基于工资的旅行时间成本预测，用它来估计VMT需求相对于燃料和时间成本的弹性。我们对VMT需求的综合价格弹性的中央估计为-0.4，这与之前的估计有很大不同。我们还发现有证据表明，富裕家庭的需求更具弹性，所有收入水平的家庭对时间成本比燃料成本更敏感。我们使用我们估计的弹性来模拟在一系列可能的旅行燃料和时间成本变化下，完全、私人采用CAV对VMT和能源使用的影响。我们预测，普通家庭的旅游需求将增长2-47%。我们的结果表明，适得其反——即能源使用的净增长——是一种可能性，尤其是在高收入群体。随着CAV使用量的增加，这对政策目标提出了严峻挑战，即不仅要减少能源使用，还要减少交通拥堵和当地及全球空气污染。
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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