SBIR Phase I: Testing computational feasibility and effectiveness of real time traffic nearcast for wildfire evacuation at the wildland urban interface
SBIR Phase I: Testing computational feasibility and effectiveness of real time traffic nearcast for wildfire evacuation at the wildland urban interface
批准号:
2322210
负责人:
Sarah Lindbergh
金额:
$27.5万
依托单位:
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
项目状态:
已结题
起止时间:
2023-12-15 至 2024-09-30
中文摘要
这个小型企业创新研究(SBIR)第一阶段项目的更广泛/商业影响是,通过提供个性化的疏散指导,减少居民疏散到安全目的地的时间,从而在野火期间降低生命风险和更顺畅的政府运作。野火是一种日益普遍的灾难;目前有5000万美国家庭位于荒地-城市交界处(WUI)地区。该项目旨在通过开发在野火期间提供实时信息和个性化疏散指导的服务来增强WUI社区居民的能力。这种服务还补充了应急机构的行动,这些机构在野火期间往往因资源和劳动力限制而超负荷工作。从这个项目中吸取的经验教训可以应用于其他自然灾害或人为灾害,使更多的美国公民受益。这项技术将创造高技能的就业机会,并增加学术界、工业界、政府和荒地-城市交界处社区之间的伙伴关系。这项技术创新使用动态和自适应的实时交通近距离模拟,在荒野城市界面(WUI)的数字副本上搜索最佳疏散策略。这些策略随后被提供给撤离者,作为通往安全目的地的实时、个性化的路线指导。该技术还将为应急机构提供通信能力、态势感知和优化平台。该项目采用最新的数字孪生(DT)技术,以革命性的静态规划方法和以传单形式分发的疏散计划信息。具体地说,对于野火疏散,DT框架涉及对火灾、通信和交通流的多功能模拟;旨在纳入基础设施参数,如道路网络、环境参数以及疏散人员和应急管理机构的行为参数。该项目的技术范围集中在基于DT模拟技术的实时解决方案的开发和演示上,该解决方案改进了一系列紧急疏散指标,包括总疏散时间、火灾暴露时间和交通拥堵。将根据观测数据进行数值验证和计算速度测试,以量化有效性和计算效率,以便建立对解决方案性能的基线理解,并随后建立对现实生活实施的信心。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to reduce the time for residents to evacuate to safe destinations by providing personalized evacuation guidance, resulting in lower risk to life and smoother government operations during a wildfire. Wildfires are an increasingly prevalent disaster; 50 million U.S. homes are currently in the Wildland-Urban Interface (WUI) areas. This project aims to empower residents in WUI communities by developing services that provide real-time information and personalized evacuation guidance during wildfires. Such services also supplement the actions of emergency response agencies that are often overloaded during wildfires due to resource and workforce constraints. The lessons learned through this project can be applied to other natural or man-made disasters, benefiting many more U.S. citizens. This technology will create highly skilled jobs and increase partnerships between academia, industry, government, and wildland-urban interface communities. This technology innovation searches for the best evacuation strategies on digital replicates of the Wildland Urban Interface (WUI) using real-time traffic nearcast simulations that are dynamic and adaptive. These strategies are then be provided to evacuees as real-time, individualized routing guidance to safe destinations. The technology will also provide communications abilities, situational awareness, and an optimization platform for emergency response agencies. The project adopts the latest digital twin (DT) technology to revolutionize static planning methods and evacuation plan information distributed in leaflets. Specifically, for wildfire evacuation, the DT framework involves versatile simulations of the fire, communications, and traffic flow; Is designed to incorporate infrastructural parameters such as the road network, environmental parameters, as well as behavioral parameters of both the evacuees and the emergency managing agencies. The technical scope of this project focuses on the development and demonstration of a real-time solution based on DT simulation technology that improves a series of emergency evacuation metrics, including the total evacuation times, fire exposure times, and traffic congestion. Numerical validation against observed data and computational speed testing will be carried out to quantify the effectiveness and computational efficiency in order to build a baseline understanding of the performance of the solution, and subsequently establish confidence in real-life implementation.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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