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

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。美国正在大力投资其电动汽车基础设施。公共充电站是该基础设施的重要组成部分。要实现国家目标，到2030年需要新增50万个公共充电站。这一扩张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，就需要注意人和社会方面的考虑，并预见到意想不到的负面后果。该项目为公共充电站制定了以人为本的规划框架。它将人类认知过程和社会影响整合到工程模型中，目标是确保长期的社区利益。通过更好地了解人们如何选择公共充电站的使用，并考虑到这些充电站在全国范围内的公平分配，该研究有助于建立可持续和公平的全国公共充电网络。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使用公共充电站的选择。对电动汽车和非电动汽车用户的公平和社区影响进行了调查。建立了公共充电站部署决策模型，并利用基于智能体的仿真器，结合现实社会认知动态和真实世界数据对决策结果进行了验证。本项目采用融合、跨学科的研究方法，建立公共充电站选择的社会决策新理论和新模型。它促进了以人为本的新思维，部署公共充电基础设施，支持实现国家电动汽车目标。该奖项由社会、行为和经济（SBE）科学理事会、工程理事会和数学和物理科学理事会支持。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。

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.