POSE: Phase II: CONNECT: Consortium of Open-source plaNNing models for Next-generation Equitable and efficient Communities and Transportation

POSE：第二阶段：CONNECT：下一代公平高效社区和交通的开源规划模型联盟

• 批准号: 2303748
• 负责人: Xuesong Zhou
• 金额: $ 150万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2303748&HistoricalAwards=false
• 关键词: POSE; Phase; II; CONNECT; Consortium

This project, funded by Pathways to Enable Open-Source Ecosystems (POSE), aims to promote a healthy and equitable society with diverse mobility options by addressing traffic congestion, air quality, and sustainability issues through efficient and effective multimodal transportation planning. The project will achieve this by extending the General Modeling Network Specification (GMNS) to GMNS+ through the Consortium of Open-Source Multimodal PlaNNing for Equitable and Sustainable Communities and Transportation Systems (CONNECT). The project's novel features include integrating a multimodal network modeling approach, ensuring equity among diverse communities, employing cross-resolution strategies, offering personalized mobility options, and utilizing time-sensitive network data. Additionally, the project will establish an extensive open-source ecosystem for a wide range of transportation solutions. Its impacts encompass fostering efficient, sustainable, safe, accessible, and inclusive transportation systems and facilitating informed decision-making at national, state, and city levels. With numerous Metropolitan Planning Organizations and Regional Councils in the United States, the project's streamlined process and open-source ecosystem will support informed decision-making at various governance levels. The research team adopts a technical approach that capitalizes on existing data formats to create seamlessly integrated multimodal networks, fostering offline and real-time data sharing among agencies and software packages. This strategy empowers the execution of dynamic multimodal analysis, heralding a new age of standardized data in transportation science, and making the examination of extensive multimodal datasets more approachable through a versatile and adaptable tool—potentially transforming data science within transportation. The team aims to integrate open data specifications with system optimization tools to optimize efficiency and equity within the urban transportation infrastructure community. By implementing sustainability governance, the project will strengthen the connection between real-world challenges faced by practitioners and the research community, ensuring product competitiveness and overall sustainability. The GMNS+ ecosystem holds the potential to significantly impact data science by facilitating the study of large multimodal datasets using innovative, highly flexible, and scalable computational and educational tools.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.

该项目以实现开源生态系统（POSE）的途径资助，旨在通过解决交通拥堵，空气质量和可持续性问题，通过高效有效的多模式运输计划来促进具有潜水员出行选择的健康和公平社会。该项目将通过将一般建模网络规范（GMN）扩展到GMNS+通过开源多模式计划，以公平和可持续的社区和运输系统（Connect）将一般建模网络规范（GMN）扩展到GMNS+。该项目的新颖特征包括整合多模式网络建模方法，确保潜水员社区之间的公平性，采用跨分辨率策略，提供个性化的移动性选项以及使用时间敏感的网络数据。此外，该项目将为广泛的运输解决方案建立广泛的开源生态系统。它的影响包括促进高效，可持续，安全，可及的运输系统，并在国家，州和城市层面支持明智的决策。在美国的众多大都市规划组织和区域委员会中，该项目简化的过程和开源生态系统将支持各种治理水平的知情决策。研究团队采用了一种技术方法，该方法利用了现有的数据格式，以创建无缝集成的多模式网络，促进离线和实时数据共享之间的机构和软件包。该策略赋予了动态多模式分析的执行，预示了运输科学中标准化数据的新时代，并通过一种通过多功能且适应性的工具更容易地对广泛的多模式数据集进行了检查，这可以在运输中转换传输中的数据科学。该团队旨在将开放数据规格与系统优化工具集成，以优化城市运输基础设施社区内的效率和权益。通过实施可持续性治理，该项目将加强从业者和研究界面临的现实世界挑战之间的联系，从而确保产品竞争力和整体可持续性。 GMNS+生态系统具有通过使用创新，高度灵活且可扩展的计算和教育工具来支持大型多模式数据集的研究的潜力。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子和更广泛的影响来评估NSF的法定任务，并被视为珍贵的支持。