SAI: Large-scale Planning for Electric Vehicle Public Charging Infrastructure

加强美国基础设施(SAI)是一项NSF计划，旨在刺激以人类为中心的基础性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创新，增长经济，创造就业机会，提高公共部门服务提供效率，加强社区力量，促进机会均等，保护自然环境，增强国家安全，推动美国的领导地位。要实现这些目标，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能够建立和维护有效的基础设施，以改善生活和社会，并建立在技术和工程进步的基础上。美国正在对其电动汽车基础设施进行大量投资。公共充电站是这一基础设施的重要组成部分。要实现国家目标，到2030年将需要增加50万个新的公共充电站。这一扩展预计将产生显著的经济效益，并促进电动汽车的采用。它还将重塑美国人旅行和获得机会的方式。要充分利用这一投资，需要注意人的和社会的考虑，并预见到意想不到的负面后果。这个SAI项目为公共充电站开发了一个以人为中心的规划框架。它将人类认知过程和社会影响整合到工程模型中，目的是确保社区的长期利益。这项研究通过更好地了解人们如何选择公共充电站的使用，并考虑这些充电站在全国范围内的公平分布，为可持续和公平的全国公共充电站网络做出贡献。该项目融合了心理学、社会学和工程学的专业知识，创建了一个综合的公共充电站框架。利用调查数据和实验室实验，开发了一个认知框架来解释公共充电站的使用选择。对电动汽车和非电动汽车用户的公平性和社区影响进行了调查。对公共充电站的部署决策进行了建模，并使用具有真实社会认知动态和真实世界数据的基于代理的模拟器对结果进行了验证。本课题运用综合、跨学科的研究方法，建立了公共充电站选择的社会决策新理论和新模型。它倡导以人为本的新思维，部署公共充电基础设施，支持实现国家电动汽车目标。该奖项得到了社会、行为和经济(SBE)科学局、工程局和数学和物理科学局的支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.The United States is investing heavily in its electric vehicle infrastructure. Public charging stations represent an important part of that infrastructure. Achieving national goals will require the addition of 500,000 new public charging stations by 2030. This expansion is expected to yield significant economic benefits and to promote the adoption of electric vehicles. It will also reshape the way Americans travel and access opportunities. To fully leverage this investment requires attention to human and social considerations, and to anticipate unintended negative consequences. This SAI project develops a human-centered planning framework for public charging stations. It integrates human cognitive processes and social impacts into engineering models, with the goal of ensuring long-term community benefits. The research contributes to sustainable and fair nationwide public charging networks by gaining a better understanding of how people make choices about public charging station use and by considering the equitable distribution of those stations across the country.Bringing a convergence of expertise from psychology, sociology, and engineering, this project creates an integrated public charging station framework. Using survey data and laboratory experiments, a cognitive framework is developed to account for choices in the use of public charging stations. Equity and community impacts are investigated for both electric vehicle and non-electric vehicle users. Public charging station deployment decisions are modeled, and the outcomes are validated using an agent-based simulator with realistic social cognition dynamics and real-world data. By using an integrative and interdisciplinary research approach, this project establishes new theories and models of social decision-making for public charging station choices. It promotes new human-centered thinking of deploying public charging infrastructure, supporting the achievement of national electric vehicle goals.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences, the Directorate for Engineering, and the Directorate for Mathematical and Physical 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.