Determining critical skill deficits that predict novice driver crashes: A prospective study using a novel virtual driving test at point of licensure, state licensing data and crash outcomes

项目摘要 车祸是青少年死亡的主要原因，使其成为美国面临的主要健康威胁 青少年。鉴于95.6%的新手驾驶事故是由于驾驶员失误造成的，提高驾驶技能应该会减少 坠机事件。研究支持这一点：新手司机的撞车率在获得驾照后立即达到峰值 并随着获得执照后几个月积累的经验而急剧下降。然而，目前尚不清楚 驾照预测撞车的关键驾驶技能缺陷。这项研究的长期目标是 在获得执照之前制定干预措施，以获得最安全的独立驾驶后执照。 通过这个R21项目，我们将确定驾驶技能方面的缺陷，这些缺陷(A)与主要预测因素有关 早期撞车风险(获得执照的年龄和性别)和(B)可以预测第一次撞车风险的差异 独立发证之年。我们将利用我们对创新的新数据的独家访问 年轻司机研究的来源。为了能够研究新手司机的安全关键驾驶技能缺陷， 一项新的(截至2017年7月)虚拟驾驶考试(VDT)的结果--由PI开发，由国家通过 并在道路许可考试之前交付-将与俄亥俄州许可挂钩 和崩溃数据。我们提出了这些目标：目标1：使用多变量聚类识别技能簇， 回归和机器学习技术，以检验这些集群与年龄相关的假设 驾照、性别和在学习期间花费的时间；目标2a：使用与报告的驾驶技能相关的数据 俄亥俄州的撞车数据，以确定AIM 1中确定的技能集群是否与撞车风险相关； 目标2b：确定Aim1中的这些技能群是否预示着农村青少年司机发生撞车事故。使用一个 大样本的新司机申请者(&gt；25000)，这项研究将第一次检查不同的 技能，从撞车风险高的年龄(青春期)和时间(获得执照的第一年内)开始。 我们将创建新手驾驶技能的标准数据集；按年龄、性别和时间对技能缺陷进行分类 初学者阶段；并量化前2个月技能缺陷与撞车率之间的关系 驾照(年轻司机的撞车率最高)和接下来的10个月作为经验 积累起来。如果VDT的使用被证明在预测碰撞风险方面是成功的，我们将能够确定 在发放驾照之前，车祸风险较高的新手司机。这款R21将支持以下系列 研究：(1)开发新的干预措施，通过培训解决技能缺陷，并针对 新手司机的需求(与俄亥俄州合作)。(2)开发或调整先进的驾驶员辅助系统 系统(ADAS)或自动驾驶车辆技术，以减少已确定的技能缺陷(作为Dr。 温斯顿国家科学基金产业/大学合作研究中心)。(3)开展 驾驶技能习得与认知发展相互作用轨迹的前瞻性研究(R01) 这导致了获得执照时的个人技能差异，以及随之而来的撞车风险。

Project Summary Motor vehicle crashes lead causes of adolescent mortality, making this a major health threat facing US adolescents. Given that 95.6% of novice driver crashes are due to driver error, improved skill should reduce crash incidence. Research supports this: novice driver crash rates peak immediately following licensure and decline steeply with experience gained over the months following licensure. However, it is not known which critical driving skill deficits present at licensure predict crashes. The long-term goal of this research is to develop interventions prior to licensure that can lead to the safest independent driving post licensure. With this R21 project, we will identify deficits in driving skills that are (a) associated with major predictors of early crash risk (age at licensure and sex) and that (b) can predict differences in crash rates within the first year of independent licensure. We will leverage our exclusive access to an innovative, newly available data source for young driver research. To enable study of safety critical driving skill deficits in novice drivers, results from a new (as of July 2017) virtual driving test (VDT) - developed by the PI, adopted by the State of Ohio and delivered immediately prior to the on-road licensing examination - will be linked to Ohio licensing and crash data. We propose these aims: Aim 1: identify skill clusters using multivariate clustering, regression and machine learning techniques to test the hypothesis that these clusters are related to age at licensure, sex, and time spent in the learner period; Aim 2a: use data on driving skills linked with reported crash data in Ohio to determine whether the skill clusters identified in Aim 1 are associated with crash risk; and Aim 2b: determine if those skill clusters from Aim1 are predictive of crashes in rural teen drivers. With a large sample of new driver applicants (>25,000), this study will examine, for the first time, differences in skill, starting at an age (adolescence) and a time (within the first year of licensure) when crash risk is high. We will create a normative dataset of novice driver skills; classify skill deficits by age, sex and time in learner period; and quantify the relationship between skill deficits and crash rates during the first 2 months of licensure (when crash rates are highest for young drivers) and the following 10 months as experience accumulates. If the use of the VDT proves successful in predicting crash risk, we will be able to identify novice drivers with elevated crash risk before granting a license. This R21 will enable the following lines of research: (1) Develop new interventions that address skill deficits through training, individualized to the needs of the novice driver (in partnership with Ohio). (2) Develop or adapt advanced driver assistance systems (ADAS) or self-driving vehicle technology to mitigate identified skill deficits (as part of Dr. Winston’s National Science Foundation Industry/University Cooperative Research Center). (3) Conduct a prospective study (R01) of the interacting trajectories of driving skill acquisition and cognitive development that lead to individual differences in skills at the time of licensure and the ensuing crash risk.