The development of a naturalistic data collection system to perform critical incident analysis: An investigation of safety and fatigue issues in long-haul trucking

被引:56
作者
Dingus, Thomas A.
Neale, Vicki L.
Klauer, Sheila G.
Petersen, Andrew D.
Carroll, Robert J.
机构
[1] Virginia Tech, Transportat Inst, Blacksburg, VA 24061 USA
[2] Fed Motor Carrier Safety Adm, Washington, DC 20024 USA
关键词
driver fatigue; naturalistic truck driving study; critical incident analysis;
D O I
10.1016/j.aap.2006.05.001
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
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. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1127 / 1136
页数:10
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