Literature DB >> 16962059

Car following decisions under three visibility conditions and two speeds tested with a driving simulator.

Kathy L M Broughton1, Fred Switzer, Don Scott.   

Abstract

The National Highway Traffic Safety Administration web site reports that rear-end collisions in the United States exceed 1.5 million per year, or approximately 23% of all vehicle crashes. Car following behavior and the decision-making habits of drivers seem fundamental to understanding how to avoid these rear-end crashes. The present research aimed to reveal factors that govern car following under conditions of reduced visibility. It employed a KQ-Vection high-fidelity driving simulator to measure the behavior of automobile drivers following a lead vehicle at 13.4 m/s (30 MPH) or 22.4 m/s (50 MPH) under three visibility conditions--clear or one of two densities of simulated fog. At the higher speed, fog conditions separated participants into a group that stayed within visible range of the lead car, even though the headway time violated the NHTSA recommendations for the speed involved, and another group that lagged beyond the visible range. Data were compared to the model of Van Winsum for car following (The human element in car following models. Transportation Research Part F 2, 1999). Contrast and image size measurements allowed comparison to a standard contrast sensitivity function and allowed estimation of the JND term in the Van Winsum model.

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Year:  2006        PMID: 16962059     DOI: 10.1016/j.aap.2006.06.009

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


  8 in total

1.  Age-related declines in car following performance under simulated fog conditions.

Authors:  Rui Ni; Julie J Kang; George J Andersen
Journal:  Accid Anal Prev       Date:  2010-05

2.  Measuring listening effort: driving simulator versus simple dual-task paradigm.

Authors:  Yu-Hsiang Wu; Nazan Aksan; Matthew Rizzo; Elizabeth Stangl; Xuyang Zhang; Ruth Bentler
Journal:  Ear Hear       Date:  2014 Nov-Dec       Impact factor: 3.570

3.  Blind haste: As light decreases, speeding increases.

Authors:  Emanuel de Bellis; Michael Schulte-Mecklenbeck; Wernher Brucks; Andreas Herrmann; Ralph Hertwig
Journal:  PLoS One       Date:  2018-01-03       Impact factor: 3.240

4.  Examining the effect of adverse weather on road transportation using weather and traffic sensors.

Authors:  Yichuan Peng; Yuming Jiang; Jian Lu; Yajie Zou
Journal:  PLoS One       Date:  2018-10-16       Impact factor: 3.240

5.  Driving under low-contrast visibility conditions in Parkinson disease.

Authors:  E Y Uc; M Rizzo; S W Anderson; E Dastrup; J D Sparks; J D Dawson
Journal:  Neurology       Date:  2009-10-06       Impact factor: 11.800

6.  Impacts of Fog Characteristics, Forward Illumination, and Warning Beacon Intensity Distribution on Roadway Hazard Visibility.

Authors:  John D Bullough; Mark S Rea
Journal:  ScientificWorldJournal       Date:  2016-05-22

7.  Changes in Drivers' Visual Performance during the Collision Avoidance Process as a Function of Different Field of Views at Intersections.

Authors:  Xuedong Yan; Xinran Zhang; Yuting Zhang; Xiaomeng Li; Zhuo Yang
Journal:  PLoS One       Date:  2016-10-07       Impact factor: 3.240

8.  Effect of Imitation Phenomenon on Two-lane Traffic Safety in Fog Weather.

Authors:  Jinhua Tan; Li Gong; Xuqian Qin
Journal:  Int J Environ Res Public Health       Date:  2019-10-01       Impact factor: 3.390

  8 in total

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