Proactive Safety Improvement via crowdsourcing Live Curve Safety Assessment

通过众包实时曲线安全评估主动改进安全

基本信息

  • 批准号:
    2306684
  • 负责人:
  • 金额:
    $ 49.19万
  • 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
  • 起止时间:
    2023-05-01 至 2026-10-31
  • 项目状态:
    未结题

项目摘要

This project will create novel methodologies for assessing, managing, and improving the safety conditions of horizontal curves on roadway networks. In the US, a disproportionately high number of serious vehicle crashes occur on horizontal curves (25 percent of all fatal crashes), despite curves accounting for only 5 percent of total highway mileage. The advisory speed of curves can change due to pavement condition changes caused by pavement aging and distress, and curve geometry change can be caused by resurfacing and maintenance. This can lead to a higher risk of crashes if the curve advisory speed has not been assessed, monitored, and adjusted in a timely manner. However, the current network-level curve safety assessment practices are labor-intensive, time-consuming, and costly for engineers, resulting in problematic curves often being identified only after crashes occur. To address this issue, this project aims to develop new methodologies that leverage low-cost mobile devices, intra-agency crowdsourcing, advanced and scalable algorithms, and a novel confidence-driven, decision-making method that will make cost-effective and frequent curve safety assessments technically and economically feasible. The methodologies that will be developed in this project will result in significant savings in terms of cost and labor for transportation agencies and will promote transportation safety equity, especially for agencies with limited resources. The research outcomes will lay a solid foundation for advancing the development of future technologies and tools, and, most importantly, they will take a big step towards development of a safe system that saves lives by transforming the reactive safety management practices into proactive roadway safety management practices. The objectives of this project are to develop and validate two methodologies for network-level curve safety assessment by taking a multidisciplinary approach. The first methodology is a crowdsourced multi-run curve safety assessment methodology that will address the technical challenges in the state-of-art technologies related to different vehicle types, suspension properties and driver behaviors when scaling up from individual curve safety assessment to network-wide assessment with a crowdsourcing framework. This methodology will use a novel seed-propagation model and an iterative convergence feedback model combined with the curve-driving kinematics relationship and spatial-temporal analysis for simultaneous estimation of vehicle suspension and curve geometric properties. The second methodology is a trajectory and roadway geometry-dependent confidence level methodology that will enable informed, data-driven decision-making by quantitatively evaluating the confidence level of the computed decision-making outcomes, such as advisory speed, based on a vehicle’s trajectory and roadway geometry. The outcomes of this project will also be integrated into a wide range of classroom and research activities to train the next generation of scientists, engineers, and policymakers on innovative technologies that will promote proactive safety management practices and transportation safety equity.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.
该项目将为评估、管理和改善道路网络水平弯道的安全状况创造新的方法。在美国,尽管弯道只占高速公路总里程的5%,但发生在水平弯道上的严重车祸的数量却高得不成比例(占所有致命车祸的25%)。由于路面老化和破损引起的路面状况变化会改变弯道的建议速度,而由于路面改道和养护会改变弯道的几何形状。如果没有及时评估、监控和调整曲线咨询速度,这可能会导致更高的崩溃风险。然而,目前的网络级曲线安全评估实践对工程师来说是劳动密集型的、耗时的、昂贵的,导致有问题的曲线往往只有在事故发生后才能被识别出来。为了解决这个问题,该项目旨在开发新的方法,利用低成本的移动设备、机构内部众包、先进和可扩展的算法,以及一种新的信心驱动的决策方法,使成本效益高、频繁的曲线安全评估在技术上和经济上都是可行的。本项目将开发的方法将大大节省运输机构的成本和人力,并将促进运输安全的公平性,特别是对于资源有限的机构。研究成果将为推进未来技术和工具的发展奠定坚实的基础,最重要的是,它们将朝着开发安全系统迈出一大步,通过将被动的安全管理实践转变为主动的道路安全管理实践,从而挽救生命。该项目的目标是通过采用多学科方法开发和验证两种网络级曲线安全评估方法。第一种方法是众包多弯道安全评估方法,该方法将在众包框架下从单个弯道安全评估扩展到网络范围评估时,解决与不同车型、悬架特性和驾驶员行为相关的最新技术挑战。该方法将采用一种新颖的种子传播模型和迭代收敛反馈模型,结合曲线-驾驶运动学关系和时空分析,同时估计车辆悬架和曲线的几何特性。第二种方法是基于轨迹和道路几何形状的置信度方法,通过定量评估计算出的决策结果的置信度,例如基于车辆轨迹和道路几何形状的咨询速度,从而实现明智的、数据驱动的决策。该项目的成果还将被纳入广泛的课堂和研究活动,以培训下一代科学家、工程师和政策制定者掌握创新技术,促进主动安全管理实践和运输安全公平。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Yichang Tsai其他文献

Yichang Tsai的其他文献

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{{ truncateString('Yichang Tsai', 18)}}的其他基金

I-Corps: Curve safety assessment solution to help transportation agencies with road curve safety management
I-Corps:弯道安全评估解决方案,帮助运输机构进行道路弯道安全管理
  • 批准号:
    2309336
  • 财政年份:
    2023
  • 资助金额:
    $ 49.19万
  • 项目类别:
    Standard Grant

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