1. Distraction
Comparing its effects with the
frequency of exposure in different
road user groups
Matt Staton

2. Introduction
This presentation will cover the following:
Aim of the study
Self-reporting survey
Findings from the survey
Suggested reasons for findings
Application

3. Aim
Compare distraction in different road user
groups
Wallace (2003)
Age and experience

4. Self-Reporting Survey
200 responses
Age range 17-70
67% female
1-7 Likert Scale for frequency
Most distracting and most dangerous
Accident or near-miss involvement

5. Findings
Most frequently reported distractions
Other vehicles
Adult passengers
In-car entertainment
Child passengers
Other people

6. Distracters perceived to be most distracting
Mobile phone – combined
In-car entertainment
Other vehicles
Child passengers
Adult passengers
Advertising

7. Distracters perceived to be most dangerous
Writing text message
Hand-held mobile phone
Mobile phone (not specific)
In-car entertainment
Child passengers

8. Accident or Near-Miss
2%
21%
1%
76%
accident
near miss
both
no accident/near miss

9. Accident or Near-Miss by Age
0%
5%
10%
15%
20%
25%
30%
35%
17-24 25-34 35-44 45-54 55-64
Age Group

10. Accident or Near-Miss by Experience
0%
5%
10%
15%
20%
25%
30%
35%
0-10 11-20 21-30 31-40 41-50
Length licence held (years)

11. Different Distracters According to Age
17-24 – text messaging
25-44 – child passengers
44+ – advertising

12. Groups at Higher Risk
17-24 years old
25-34 years old
0-10 years experience

13. Why is this the case?
Attention
Filtering
Arousal
Sensation seeking

14. Skill acquisition
Decreasing demand with repetition
Automaticity
Process environment and control vehicle

15. Prefrontal cortex development
Late adolescence
Voluntary recall
Managing social behaviour

16. How do we reduce risk?
Improve simultaneous task performance
Adequate control measures?
Acceptable performance levels?
Avoid/minimise through conscious action
Remove completely
Socially unacceptable
Legislation – heterogeneous?

17. Matt Staton
Matt.staton@cambridgeshire.gov.uk
Twitter: @StatonMatt