Literature DB >> 16806028

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

Thomas A Dingus1, Vicki L Neale, Sheila G Klauer, Andrew D Petersen, Robert J Carroll.   

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.

Entities:  

Mesh:

Year:  2006        PMID: 16806028     DOI: 10.1016/j.aap.2006.05.001

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  8 in total

1.  Cues of fatigue: effects of sleep deprivation on facial appearance.

Authors:  Tina Sundelin; Mats Lekander; Göran Kecklund; Eus J W Van Someren; Andreas Olsson; John Axelsson
Journal:  Sleep       Date:  2013-09-01       Impact factor: 5.849

2.  Keep your eyes on the road: young driver crash risk increases according to duration of distraction.

Authors:  Bruce G Simons-Morton; Feng Guo; Sheila G Klauer; Johnathon P Ehsani; Anuj K Pradhan
Journal:  J Adolesc Health       Date:  2014-05       Impact factor: 5.012

3.  Ridesharing and Motor Vehicle Crashes in 4 US Cities: An Interrupted Time-Series Analysis.

Authors:  Christopher N Morrison; Sara F Jacoby; Beidi Dong; M Kit Delgado; Douglas J Wiebe
Journal:  Am J Epidemiol       Date:  2018-02-01       Impact factor: 4.897

4.  The characteristics of sleepiness during real driving at night--a study of driving performance, physiology and subjective experience.

Authors:  David Sandberg; Anna Anund; Carina Fors; Göran Kecklund; Johan G Karlsson; Mattias Wahde; Torbjörn Åkerstedt
Journal:  Sleep       Date:  2011-10-01       Impact factor: 5.849

5.  The Language of Driving: Advantages and Applications of Symbolic Data Reduction for Analysis of Naturalistic Driving Data.

Authors:  Anthony D McDonald; John D Lee; Nazan S Aksan; Jeffrey D Dawson; Jon Tippin; Matthew Rizzo
Journal:  Transp Res Rec       Date:  2013       Impact factor: 1.560

6.  CAN INTERMITTENT VIDEO SAMPLING CAPTURE INDIVIDUAL DIFFERENCES IN NATURALISTIC DRIVING?

Authors:  Nazan Aksan; Mark Schall; Steven Anderson; Jeffery Dawson; Jon Tippin; Matthew Rizzo
Journal:  Proc Int Driv Symp Hum Factors Driv Assess Train Veh Des       Date:  2013

7.  Ridesharing and motor vehicle crashes: a spatial ecological case-crossover study of trip-level data.

Authors:  Christopher N Morrison; Christina Mehranbod; Muhire Kwizera; Andrew G Rundle; Katherine M Keyes; David K Humphreys
Journal:  Inj Prev       Date:  2020-04-06       Impact factor: 2.399

Review 8.  Driver Distraction Using Visual-Based Sensors and Algorithms.

Authors:  Alberto Fernández; Rubén Usamentiaga; Juan Luis Carús; Rubén Casado
Journal:  Sensors (Basel)       Date:  2016-10-28       Impact factor: 3.576

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.