Proactive Safety Improvement via crowdsourcing Live Curve Safety Assessment

该项目将为评估、管理和改善道路网络上水平曲线的安全条件创造新的方法。在美国，严重的车辆碰撞事故发生在水平弯道上（占所有致命事故的25%），尽管弯道仅占公路总里程的5%。 由于路面老化和破损引起的路面状况变化，曲线的咨询速度会发生变化，而重铺和养护会引起曲线几何形状的变化。如果没有及时评估、监测和调整曲线建议速度，这可能导致更高的撞车风险。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，并且成本高昂，导致有问题的曲线通常仅在发生碰撞后才被识别。为了解决这个问题，该项目旨在开发新的方法，利用低成本的移动的设备，机构内众包，先进的和可扩展的算法，以及一种新的信心驱动的决策方法，这将使成本效益和频繁的曲线安全评估在技术和经济上是可行的。本项目将开发的方法将大大节省运输机构的成本和劳动力，并将促进运输安全公平，特别是对资源有限的机构。研究成果将为推动未来技术和工具的发展奠定坚实的基础，最重要的是，他们将朝着开发一个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来拯救生命。该项目的目标是通过多学科方法开发和验证两种网络级曲线安全评估方法。第一种方法是众包的多运行曲线安全评估方法，该方法将解决与不同车辆类型、悬架特性和驾驶员行为相关的最新技术中的技术挑战，当从单个曲线安全评估扩展到具有众包框架的网络范围评估时。该方法将使用一种新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几何特性。第二种方法是依赖于轨迹和道路几何形状的置信水平方法，其将通过基于车辆的轨迹和道路几何形状定量地评估所计算的决策结果（诸如咨询速度）的置信水平来实现知情的、数据驱动的决策。该项目的成果也将纳入广泛的课堂和研究活动，以培养下一代科学家，工程师，该奖项反映了NSF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进行评估，被认为值得支持的搜索.

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.