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Distracted driving impairs police patrol officer driving performance
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Purpose
– Most US states exempt police officers from restrictive distracted laws, and most agencies require officers to use mobile data computers while driving. The purpose of this paper is to examine the impact of a text-based distraction task on officer driving performance.
Design/methodology/approach
– Experienced police patrol officers (n=80) participated in controlled laboratory experiments during which they drove a high-fidelity driving simulator on four separate occasions; twice immediately following five consecutive 10:40 hour patrol shifts (fatigued condition) and again 72 hours after completing the last shift in a cycle (rested condition). In each condition, officers drove identical, counterbalanced 15-minute courses with and without distraction tasks. The research used a within- and between-subjects design.
Findings
– A generalized linear mixed-model analysis of driving performance showed that officers’ distracted driving performance had significantly greater lane deviation (F=88.58, df=1,308, p
<
0.001), instances of unintentionally leaving assigned driving lane (F=64.76, df=1,308, p
<
0.001), and braking latency (F=200.82, df=1,308, p
<
0.001) than during non-distracted drives. These measures are leading indicators for collision risk.
Research limitations/implications
– Simulated driving tasks presented were generally less challenging than patrol driving and likely underestimate the impact of distraction on police driving.
Originality/value
– Police officers appear to drive significantly worse while distracted, and their routine experience with using text-based communication devices while driving does not mitigate the risks associated with doing so. Study results suggest that policing organizations should modify policies, practices, training, and technologies to reduce the impact of distraction on officers’ driving. Failing to do so exposes officers and the communities they serve to unnecessary hazards and legal liabilities.
Title: Distracted driving impairs police patrol officer driving performance
Description:
Purpose
– Most US states exempt police officers from restrictive distracted laws, and most agencies require officers to use mobile data computers while driving.
The purpose of this paper is to examine the impact of a text-based distraction task on officer driving performance.
Design/methodology/approach
– Experienced police patrol officers (n=80) participated in controlled laboratory experiments during which they drove a high-fidelity driving simulator on four separate occasions; twice immediately following five consecutive 10:40 hour patrol shifts (fatigued condition) and again 72 hours after completing the last shift in a cycle (rested condition).
In each condition, officers drove identical, counterbalanced 15-minute courses with and without distraction tasks.
The research used a within- and between-subjects design.
Findings
– A generalized linear mixed-model analysis of driving performance showed that officers’ distracted driving performance had significantly greater lane deviation (F=88.
58, df=1,308, p
<
0.
001), instances of unintentionally leaving assigned driving lane (F=64.
76, df=1,308, p
<
0.
001), and braking latency (F=200.
82, df=1,308, p
<
0.
001) than during non-distracted drives.
These measures are leading indicators for collision risk.
Research limitations/implications
– Simulated driving tasks presented were generally less challenging than patrol driving and likely underestimate the impact of distraction on police driving.
Originality/value
– Police officers appear to drive significantly worse while distracted, and their routine experience with using text-based communication devices while driving does not mitigate the risks associated with doing so.
Study results suggest that policing organizations should modify policies, practices, training, and technologies to reduce the impact of distraction on officers’ driving.
Failing to do so exposes officers and the communities they serve to unnecessary hazards and legal liabilities.
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