Transcript Using a driving simulator to identify older drivers at

Using a driving simulator
to identify older drivers at
inflated risk of motor
vehicle crashes
Professor: Liu
Student: Ruby
Motive & Purpose
• MotiveThere is no published research documenting the
correlation between simulators and crashes
among older adults.
• PurposeTo develop appropriate evaluation methods to
identify older drivers at high risk of crash and
to provide as early as possible.
References
1.About 20% of the population in developed
nations are over 60 years old, but one out of
three persons will over 60 years old by 2050
(United Nations, 1999).
2.It has been discovered that age-related
decrease in cognitive, perceptual, and
physical abilities are associated with an
increased accident risk (Brayne et al., 2000).
References
3.The attributes associated with vehicle crashes
include:
• Decrease in memory and visual attention.
• Deficit in visual perceptual skills.
• Impairment in visual acuity.
• Difficulty in judging and responding to traffic flow.
(Bedard, Molloy, & Lever, 1998; Cooper, Tall,
Tukko, & Beatties, 1993; Wallace, 1997; Owsley
et al.,1998; Duchek, Hunt, Ball,Buckles, & Morris,
1998)
Methods
• Participants and procedure
1. 129 drivers and over 60 years old.
29F, 100M
2. No visual sickness such as cataract and glaucoma.
3. 30min interviews. Including crash history and
other information from each participant.
4. 45min simulate driving session.
Methods
• Driving simulator
1. PC-based STISIM Driving Simulator
• Driving tasks
Methods
Methods
Results
• Population statistics and driving information
1. The main medical conditions:
a. high blood pressure (38%)
b. visual problem (36%)
c. arthritis (26%)
d. hearing problem (25%)
e. heart diseases (15%)
f. diabetes(10%).
Results
2. All participants are retired and they drive per
week from 1 to 35h.
3. Around 12% of the participants’ job required
driving regularly before retirement.
4. 9% of participants have soft dizziness during
the simulated driving.
Results
Reliability analysis:
• There is significant
negative correlation
between each rule and
the age of participants.
Results
• Participants’
performance in driving
tasks involving
Working Memory,
Decision and Judgment,
and Speed Compliance
was found a negatively
associated with the
occurrence of a crash.
Discussion
1. The negative correlation between
individual assessment score and age
provided evidence.
2. The inability to make rapid decision and
judgment was found highly significant in
older drivers.
Discussion
3. The logistic regression analysis showed
that working memory, ability to make rapid
decisions, judgment under time pressure,
and confidence in driving at high speed
were associated with the crash event.