CoolPath 工具：面向城市出行的热舒适路径规划工具
CoolPath Tool: A Thermal Comfort Path Planning Tool for Urban Mobility
AI总结：
CoolPath 工具通过热舒适指数规划步行和骑行路线，减少高温对行人的影响，提升城市出行安全性和健康效益。
摘要：
极端高温对城市中的主动出行构成了日益严峻的挑战，传统天气报告（如对整个城市的有限空气温度测量）无法捕捉行人和骑行者所经历的大幅微气候变化。我们提出了一种新的步行和骑行路线规划工具（“CoolPath 工具”），该工具基于通用热气候指数（UTCI）而非仅距离或旅行时间来选择路径。该系统结合了高分辨率热建模与实时路线映射。我们使用GPU版本的Solar和LongWave Environmental Irradiance Geometry（SOLWEIG）模型生成城市级UTCI地图，以考虑城市特征（建筑物、树木）和天气条件。城市特征通过卫星数据产品预先映射，路线为道路。对于任意给定的起点和终点，我们的工具计算每条可能路线的平均UTCI，并推荐“最凉爽”的路线，即热应力最低的路径（通常是遮荫或其它热舒适路径），同时仍保持合理直接。我们在德克萨斯州奥斯汀进行了案例研究。该方法识别出显著减少行人热暴露的路线（通常推荐具有更大比例遮荫的路线）。这种基于热的路线规划具有重要的公共健康和经济影响：通过帮助人们避免危险的高温热点和阳光暴露区域，可以降低中暑风险，使步行或骑行在炎热天气中成为更安全的选择。该工具是奥斯汀数字孪生项目的一部分，该项目是UT-City CoLab需求的一部分。尽管该方法已在德克萨斯州奥斯汀展示，但其方法具有可扩展性，并可在全球其他城市中推广。
英文摘要：
Extreme heat poses a growing challenge for active transportation in cities where conventional weather reporting (e.g. limited air temperature measurement for the whole city) fails to capture the large microclimate variations that pedestrians and cyclists experience. We present a novel walking and biking route planning tool (''CoolPath Tool'') that selects paths based on thermal comfort using the Universal Thermal Climate Index (UTCI) rather than just distance or travel time. This system combines high-resolution thermal modeling with real-time route mapping. We generate city-scale UTCI maps using GPU version of Solar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, to account for urban features (buildings, trees,) and weather conditions. The urban features are pre-mapped using satellite data products and the routes are the roadways. For any given origin and destination, our tool calculates the average UTCI along each possible route and recommends the ''coolest'' route, i.e. the path with the lowest heat stress (often the most shaded or otherwise thermally comfortable), while still being reasonably direct. We demonstrate this in a case study for Austin, Texas. The approach identifies routes that significantly reduce pedestrians' heat exposure (often recommending routes with a much larger proportion of shade). Such thermally-informed route planning has important public well-being, and economic implications: by helping people avoid dangerous heat hotspots and sun-exposed areas, it can reduce the risk of heat-related illness and make walking or biking a safer choice even on hot days. This tool is part of the Austin Digital Twin efforts developed as part the UT-City CoLab needs. The work while demonstrated for Austin, TX is scalable, and transferrable to other cities globally.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
