Modeling sea level rise scenarios and their effects on smart mobility infrastructure using GIS

IF 3.8 Q2 TRANSPORTATION
Khaula Alkaabi , Justine Sarrau
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引用次数: 0

Abstract

As climate change progresses, monitoring the impact of rising sea levels has become a critical issue for coastal communities. This is particularly relevant for autonomous vehicles (AVs), which depend on favorable weather conditions to function optimally. This challenge is significant in the Middle East, where events like the flash floods in 2023 in the UAE have occurred. In response, TXAI launched an AV taxi service operating in a specific touristic area of Abu Dhabi. In this study, a storm surge model is applied to four sea level rise scenarios in ArcGIS Pro to assess their potential future impact on the TXAI deployment area. Two elevation data at 11 and 30 m of spatial resolutions are compared, using the same methodology, to observe the impact of the data accuracy on the results. By comparing them, the study explores the necessity of using higher resolution data for this type of analysis. Statistics are then computed to evaluate the significance of the results and assess the potential impact of sea level rise scenarios on the road network and drop off stations. Findings indicate that the transportation network would be moderately impacted under the first three scenarios, while a 4-meter sea level rise scenario would severely affect key areas, including drop-off stations. These findings highlight the importance of conducting such studies to develop effective adaptive strategies by stakeholders and policymakers. They also contribute to the broader scientific community’s understanding of the complex interplay between climate change, urban infrastructure, and autonomous vehicle systems.
利用GIS模拟海平面上升情景及其对智能交通基础设施的影响
随着气候变化的进展,监测海平面上升的影响已成为沿海社区的一个关键问题。这对于自动驾驶汽车(AVs)来说尤其重要,因为自动驾驶汽车依赖于有利的天气条件才能发挥最佳功能。这一挑战在中东地区意义重大,像2023年在阿联酋发生的山洪暴发这样的事件就发生在中东。作为回应,TXAI在阿布扎比的一个特定旅游区推出了自动驾驶出租车服务。在本研究中,在ArcGIS Pro中应用风暴潮模型对四种海平面上升情景进行了评估,以评估它们对TXAI部署区域的潜在影响。采用相同的方法,比较了11 m和30 m空间分辨率下的两个高程数据,观察数据精度对结果的影响。通过比较,本研究探讨了使用更高分辨率数据进行这类分析的必要性。然后计算统计数据以评估结果的重要性,并评估海平面上升情景对道路网络和下落站的潜在影响。结果表明,在前3种情景下,交通网络将受到中度影响,而海平面上升4米情景将严重影响包括落客站在内的关键区域。这些发现强调了开展此类研究对利益相关者和决策者制定有效适应性战略的重要性。它们还有助于更广泛的科学界对气候变化、城市基础设施和自动驾驶汽车系统之间复杂相互作用的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
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