title: The development of a naturalistic data collection system to perform critical incident analysis: an investigation of safety and fatigue issues in long-haul trucking.
abstract: 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.
authors.affiliation: Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061, USA. tdingus@vtti.vt.edu
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Dingus
authors.forename: Vicki L
authors.initials: VL
authors.lastname: Neale
authors.forename: Sheila G
authors.initials: SG
authors.lastname: Klauer
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Petersen
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Carroll
mesh_terms: D000328:Adult; D001334:Automobile Driving; D003625:Data Collection; D005260:Female; D006801:Humans; D008297:Male; D005222:Mental Fatigue / Q000453:epidemiology; D008875:Middle Aged; D018986:Motor Vehicles; D012449:Safety; D012894:Sleep Stages; D013647:Task Performance and Analysis