Dingus Thomas A, Neale Vicki L, Klauer Sheila G, Petersen Andrew D, Carroll Robert J
Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061, USA.
Accid Anal Prev. 2006 Nov;38(6):1127-36. doi: 10.1016/j.aap.2006.05.001. Epub 2006 Jun 27.
Traditionally, both epidemiological and empirical methods have been used to assess driving safety. This paper describes an alternative, hybrid, naturalistic approach to data collection that shares advantages with each traditional approach. Though this naturalistic approach draws on elements of several safety techniques that have been developed in the past, including the Hazard Analysis Technique, instrumented vehicle studies, and fleet studies of driving safety interventions, it has a number of unique elements. Sophisticated instrumented vehicles collected over 400,000 km of commercial vehicle data to address the long-haul trucking application described in this paper. The development of this data collection and analysis method and data collection instrumentation has resulted in a set of valuable tools to advance the current state-of-the-practice in driving safety assessment. An application of this unique approach to a study of long-haul truck driver performance, behavior, and fatigue is described herein.
传统上，流行病学方法和实证方法都被用于评估驾驶安全性。本文描述了一种替代性的、混合的、自然主义的数据收集方法，它兼具每种传统方法的优点。尽管这种自然主义方法借鉴了过去开发的几种安全技术的元素，包括危险分析技术、仪器化车辆研究以及驾驶安全干预措施的车队研究，但它有许多独特的元素。先进的仪器化车辆收集了超过40万公里的商用车数据，以解决本文所述的长途货运应用问题。这种数据收集与分析方法以及数据收集仪器的开发，产生了一套有价值的工具，以推动驾驶安全评估方面的当前实践状态。本文介绍了这种独特方法在长途卡车司机绩效、行为和疲劳研究中的应用。
