The increasing availability and implementation of in-vehicle data recorder (IVDR) technologies has resulted in an increased number of safety applications based on the behavior of drivers during actual driving. The objective of this study is to formulate a flexible framework for IVDR data analysis that has the capability to include roadway geometric attributes, driver characteristics, environmental factors and time-dependencies. This research uses the concept of a homogeneous trip segment (HTS), applied with a survival model to estimate the risk of an event occurrence (e.g. crash or warning from on-board monitoring system). The University of Michigan Transportation Research Institute (UMTRI) provided data from the Road Departure Crash Warning System Field Operational Test. The survival-based model allowed the assessment of event hazard for individual drivers on specific routes as well as individual drivers compared to their peers, while controlling for travel in different routes and under different conditions. The authors believe this capability offers opportunities to safety researchers that were not available from existing methods.

车载数据记录器（IVDR）技术的可用性不断提高和实现方式的增多，导致基于实际驾驶过程中驾驶员行为的安全应用程序数量有所增加。这项研究的目的是为IVDR数据分析制定一个灵活的框架，该框架能够包含巷道几何属性，驾驶员特征，环境因素和时间依赖性。这项研究使用了均质行程段（HTS）的概念，并结合了生存模型来估计事件发生的风险（例如，机载监控系统的崩溃或警告）。密歇根大学交通研究所（UMTRI）提供了“道路偏离碰撞警告系统现场运行测试”中的数据。基于生存的模型允许评估特定路线上的单个驾驶员以及与同伴相比单个驾驶员的事件危险，同时控制在不同路线和不同条件下的行驶。作者认为，这种能力为安全研究人员提供了现有方法无法获得的机会。