评估公交出行过程中极端温度累积暴露的框架
A Framework for Assessing Cumulative Exposure to Extreme Temperatures During Transit Trip
AI总结：
本文提出HeatPath Analyzer框架，利用TransitSim 4.0逐秒模拟公交出行轨迹并结合NWS与CDC热应激标准，评估极端温度累积暴露，揭示不同出行路段及缓解与适应策略间的暴露差异。
摘要：
城市热岛、气候变化和极端温度事件的综合影响正日益冲击公交出行者，尤其是老年人、残障人士和慢性病患者等脆弱群体。以往研究通常试图在微观或宏观层面解决这一问题，但每种方法在模拟对公交出行的影响时都存在不同的局限性。其他研究提出了中观层面的方法来填补其中一些空白，但采用加性暴露计算和空间最短路径寻路对中观建模精度构成了制约。本研究引入HeatPath Analyzer框架，利用TransitSim 4.0生成逐秒的时空出行轨迹、出行者活动概况以及整个行程中的热舒适水平，以评估公交乘客对极端温度的暴露。该方法采用热应激指标，结合美国国家气象局（NWS）和美国疾病控制与预防中心（CDC）提出的标准来估计公交乘客的累积暴露，并针对老年人和残障人士设置了特定参数。该框架评估了极端高温和冬季严寒的影响。在佐治亚州亚特兰大开展的一项案例研究表明，2019年夏季普通工作日中有10.2%的出行面临极端高温风险。结果揭示了不同公交出行方式路段之间以及基于缓解策略和基于适应策略之间的暴露差异。基于缓解的策略突出显示了长距离进出站等高暴露路段，而基于适应的策略应优先关注行程中段或后半段，即出行者等待公交或在路线之间换乘时。传统的加性方法与所提出的动态方法之间的比较也显示出显著差异，若忽视这些差异，可能会误导政策决策。
英文摘要：
The combined influence of urban heat islands, climate change, and extreme temperature events are increasingly impacting transit travelers, especially vulnerable populations such as older adults, people with disabilities, and those with chronic diseases. Previous studies have generally attempted to address this issue at either the micro- or macro-level, but each approach presents different limitations in modeling the impacts on transit trips. Other research proposes a meso-level approach to address some of these gaps, but the use of additive exposure calculation and spatial shortest path routing poses constraints meso-modeling accuracy. This study introduces HeatPath Analyzer, a framework to assess the exposure of transit riders to extreme temperatures, using TransitSim 4.0 to generate second-by-second spatio-temporal trip trajectories, the traveler activity profiles, and thermal comfort levels along the entire journey. The approach uses heat stress combines the standards proposed by the NWS and CDC to estimate cumulative exposure for transit riders, with specific parameters tailored to the elderly and people with disabilities. The framework assesses the influence of extreme heat and winter chill. A case study in Atlanta, GA, reveals that 10.2% of trips on an average summer weekday in 2019 were at risk of extreme heat. The results uncover exposure disparities across different transit trip mode segments, and across mitigation-based and adaptation-based strategies. While the mitigation-based strategy highlights high-exposure segments such as long ingress and egress, adaptation should be prioritized toward the middle or second half of the trip when a traveler is waiting for transit or transferring between routes. A comparison between the traditional additive approach and the dynamic approach presented also shows significant disparities, which, if overlooked, can mislead policy decisions.
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。
