Literature DB >> 22163101

DIFFERENCES IN SIMULATED CAR FOLLOWING BEHAVIOR OF YOUNGER AND OLDER DRIVERS.

Elizabeth Dastrup1, Monica N Lees, Jeffrey D Dawson, John D Lee, Matthew Rizzo.   

Abstract

Older drivers are at risk for vehicle crashes due to impairments of visual processing and attention, placing these drivers at greater risk in driving tasks that require continuous attention to neighboring traffic, especially lead vehicles (LVs). We investigated car following behavior in 42 younger drivers (ages 18 to 44 years) and 58 older drivers (ages 65 to 86 years) in a driving simulator. The drivers were instructed to maintain two car lengths from a virtual LV. The LV varied its velocity according to a sum of three sine waves, making the velocity changes unpredictable to the drivers. A Fourier analysis was performed using the vehicle trajectory data to derive measures of coherence, gain, and delay as indices of car following behavior. These measures as well as headway distance were compared between the two groups. Older drivers were less able to match changes in the LV velocity indicated by lower coherence (0.76 v. 0.84, p=0.019) and larger gain (2.24 v. 1.74, p=0.031). However, these drivers followed further behind the LV than younger drivers, a potential compensatory strategy that may reduce collision risk for older drivers.

Entities:  

Year:  2009        PMID: 22163101      PMCID: PMC3233354     

Source DB:  PubMed          Journal:  Proc Int Driv Symp Hum Factors Driv Assess Train Veh Des


  5 in total

1.  Drug effects on driving performance.

Authors:  D de Waard; K A Brookhuis
Journal:  Ann Intern Med       Date:  2000-10-17       Impact factor: 25.391

2.  Risky car following in abstinent users of MDMA.

Authors:  Elizabeth Dastrup; Monica N Lees; Antoine Bechara; Jeffrey D Dawson; Matthew Rizzo
Journal:  Accid Anal Prev       Date:  2010-05

3.  Optical information for car following: the driving by visual angle (DVA) model.

Authors:  George J Andersen; Craig W Sauer
Journal:  Hum Factors       Date:  2007-10       Impact factor: 2.888

4.  Using eye movements to evaluate effects of driver age on risk perception in a driving simulator.

Authors:  Anuj Kumar Pradhan; Kim R Hammel; Rosa DeRamus; Alexander Pollatsek; David A Noyce; Donald L Fisher
Journal:  Hum Factors       Date:  2005       Impact factor: 2.888

5.  Human factors field evaluation of automotive headway maintenance/collision warning devices.

Authors:  T A Dingus; D V McGehee; N Manakkal; S K Jahns; C Carney; J M Hankey
Journal:  Hum Factors       Date:  1997-06       Impact factor: 2.888

  5 in total
  1 in total

1.  The STEP model: Characterizing simultaneous time effects on practice for flight simulator performance among middle-aged and older pilots.

Authors:  Quinn Kennedy; Joy Taylor; Art Noda; Jerome Yesavage; Laura C Lazzeroni
Journal:  Psychol Aging       Date:  2015-08-17
  1 in total

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