Literature DB >> 17710716

Measurement of driving patterns of older adults using data logging devices with and without global positioning system capability.

Shawn C Marshall1, Keith G Wilson, Frank J Molnar, Malcolm Man-Son-Hing, Ian Stiell, Michelle M Porter.   

Abstract

BACKGROUND: Methods to study driving patterns and exposure of older drivers have typically relied on surveys or driving diaries. Electronic data logging devices may offer a reliable, alternative method of measuring driving exposure, and global positioning system (GPS) technology may be able to provide further information about driving patterns.
OBJECTIVES: The aim of this study was to compare a driving diary with two electronic data logging devices, one of which had GPS capability, in order to identify which method best assesses the driving exposure and habits of older drivers as well as the method most acceptable to study participants.
METHOD: In this prospective cohort study we recruited 20 participants aged 70 years or more (mean 78; range 70-85) (15 men and 5 women). The participants' driving patterns were recorded for one week with an electronic data logging device with GPS (FleetPulse), followed by recording for a further week with an electronic data logging device without GPS (CarChip). During both time periods the subjects also completed a standard driving diary.
RESULTS: More comprehensive information, including braking and acceleration patterns, duration of driving time, time of day, and maximum speeds, was collected with the electronic devices than with the driving diary. There was excellent correlation between the driving diary data and those obtained with the CarChip (r = 0.9; p < 0.01). The correlation between the driving diary data and the FleetPulse data was moderate (r = 0.56; p = 0.02). The subjects clearly preferred the electronic monitoring devices over the driving diary. GPS data were able to demonstrate driving routes.
CONCLUSIONS: Electronic data logging devices are a valid method for recording the driving patterns of older adults. These devices also reduce burden and improve the completeness of data.

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Year:  2007        PMID: 17710716     DOI: 10.1080/15389580701281792

Source DB:  PubMed          Journal:  Traffic Inj Prev        ISSN: 1538-9588            Impact factor:   1.491


  3 in total

1.  Patterns of level and change in self-reported driving behaviors among older adults: who self-regulates?

Authors:  Melissa L O'Connor; Jerri D Edwards; Brent J Small; Ross Andel
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2011-12-01       Impact factor: 4.077

2.  The effects of demographics, functioning, and perceptions on the relationship between self-reported and objective measures of driving exposure and patterns among older adults.

Authors:  L J Molnar; D W Eby; J M Vivoda; S E Bogard; J S Zakraksek; R M St Louis; N Zanier; L H Ryan; D LeBlanc; J Smith; R Yung; L Nyquist; C DiGuiseppi; G Li; T J Mielenz; D Strogatz
Journal:  Transp Res Part F Traffic Psychol Behav       Date:  2018-03-15

3.  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
  3 in total

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