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SAI-R: Uncovering Barriers to Low-Carbon Travel to Strengthen Transportation Infrastructure in Rural Communities

SAI-R: Uncovering Barriers to Low-Carbon Travel to Strengthen Transportation Infrastructure in Rural Communities
SAI-R:消除低碳出行障碍,加强农村社区的交通基础设施
批准号:
2228667
负责人:
Dana Rowangould
金额:
$75.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-15 至 2025-08-31

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中文摘要
翻译
加强美国基础设施(SAI)是美国国家科学基金会的一个项目,旨在促进以人为本的基础研究和潜在的变革性研究,以加强美国的基础设施。有效的基础设施为社会经济活力和广泛的生活质量改善提供了坚实的基础。强大、可靠和有效的基础设施刺激私营部门的创新,发展经济,创造就业机会,使公共部门提供的服务更有效率,加强社区,促进机会平等,保护自然环境,加强国家安全,并推动美国的领导地位。为了实现这些目标,需要来自科学和工程学科的专业知识。SAI侧重于人类推理和决策、治理以及社会和文化过程的知识如何使有效的基础设施的建设和维护能够改善生活和社会,并以技术和工程的进步为基础。为了实现美国的气候目标,减少小型和农村社区旅行对环境的影响是必要的。交通运输是美国最大的温室气体排放来源,交通运输的温室气体在小型和农村社区尤为重要,美国30%的汽车出行发生在这些社区,人均出行距离比城市居民高出40%。然而,尽管农村社区的自然和社会环境存在重大差异,但大多数侧重于减少交通运输温室气体的研究都是在城市地区进行的。要设计出适用于农村环境的温室气体减排战略,就需要清楚地了解这些差异。农村旅行行为研究的缺乏,部分原因在于缺乏关于农村居民在哪里、为什么以及如何旅行的可靠信息。这个SAI研究项目首先建立了一个强大的新的农村旅行数据集,然后用它来揭示影响人们在农村社区旅行的因素,从而加强了对小社区和农村社区旅行行为的理解。本项目还评估了基础设施投资和政策对小型和农村社区居民出行决策和交通温室气体排放的影响。小型和农村社区的旅行是交通部门温室气体排放总量的重要驱动因素。该项目创建了一个新的面板数据集,该数据集融合了来自三个来源的空间详细数据:车辆观测数据、交通基础设施数据和个人层面的调查数据,填补了关于农村出行行为知识方面的一个关键空白。这些数据是使用从交通规划和工程、经济学和行为科学领域提取的人类行为框架来评估的。重要的是,该数据集跟踪了旅行行为随时间的变化,支持分析人们对能源价格变化、电动汽车(EV)购买激励措施、宽带互联网可用性、土地利用变化和电动汽车充电基础设施位置等干预措施的反应。这项研究将为如何利用交通基础设施投资、技术和政策减少温室气体排放提供见解,同时支持经济活力、流动性和公平性,从而帮助小型和农村社区实现温室气体排放的大幅减少。该奖项由社会、行为和经济科学理事会(SBE)支持。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.Reducing the environmental impact of travel in small and rural communities will be necessary to meet U.S. climate goals. Transportation is the largest source of greenhouse gas (GHG) emissions in the U.S., and transportation GHGs are particularly significant in small and rural communities where 30% of U.S. auto-travel occurs and the average person travels 40% farther than their urban counterparts. However, most research that focuses on reducing transportation GHGs has been conducted in urban areas despite important differences in the physical and social contexts of rural communities. A clear understanding of those differences is needed to design GHG reduction strategies that work in rural contexts. The lack of rural travel behavior research stems in part from a lack of robust information about where, why and how people who live in rural places travel. This SAI research project strengthens understanding of travel behavior in small and rural communities by first building a powerful new rural travel dataset and then using it to uncover the factors that influence how people travel in rural communities. This project also evaluates the effects of infrastructure investments and policies on the travel decisions and transportation GHGs of people in small and rural communities.Travel in small and rural communities is a significant driver of overall GHG emissions from the transportation sector. This project fills a critical gap in knowledge about rural travel behavior by creating a novel panel dataset that fuses spatially detailed data from three sources: vehicle observations, transportation infrastructure data, and individual-level survey data. The data are evaluated using a convergent human behavioral framework drawn from the fields of transportation planning and engineering, economics, and behavioral sciences. Importantly, the dataset tracks changes in travel behavior over time, supporting an analysis of peoples’ responses to interventions such as changes in energy prices, electric vehicle (EV) purchase incentives, the availability of broadband internet, changes in land use, and the location of EV charging infrastructure. This research will help small and rural communities achieve deep reductions in GHG emissions by providing insights into how to leverage transportation infrastructure investments, technology, and policies to reduce GHGs while supporting economic vitality, mobility, and equity.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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