How safe is tuning a radio?: using the radio tuning task as a benchmark for distracted driving
Journal article, 2018

Drivers engage in non-driving tasks while driving, such as interactions entertainment systems. Studies have dentified glance patterns related to such interactions, and manual radio tuning has been used as a reference task to set an upper bound on the acceptable demand of interactions. Consequently, some view the risk associated with radio tuning as defining the upper limit of glance measures associated with visual-manual in-vehicle activities. However, we have little knowledge about the actual degree of crash risk that radio tuning poses and, by extension, the risk of tasks that have similar glance patterns as the radio tuning task. In the current study, we use counterfactual simulation to take the glance patterns for manual radio tuning tasks from an on-road experiment and apply these patterns to lead-vehicle events observed in naturalistic driving studies. We then quantify how often the glance patterns from radio tuning are associated with rear-end crashes, compared to driving only situations. We used the pre-crash kinematics from 34 crash events from the SHRP2 naturalistic driving study to investigate the effect of radio tuning in crash-imminent situations, and we also investigated the effect of radio tuning on 2,475 routine braking events from the Safety Pilot project. The counterfactual simulation showed that off-road glances transform some near-crashes that could have been avoided into crashes, and glance patterns observed in on-road radio tuning experiment produced 2.85–5.00 times more crashes than baseline driving.

Naturalistic driving data

Driver distraction

Crash risk

Radio tuning

Author

Ja Young Lee

University of Wisconsin Madison

John D Lee

University of Wisconsin Madison

Jonas Bärgman

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Chalmers, Vehicle and Traffic Safety Centre at Chalmers (SAFER)

J. Lee

University of Cambridge

Battelle

B. Reimer

University of Cambridge

Accident Analysis and Prevention

0001-4575 (ISSN)

Vol. 110 29-37

Subject Categories

Mechanical Engineering

Psychology (excluding Applied Psychology)

Electrical Engineering, Electronic Engineering, Information Engineering

Areas of Advance

Transport

DOI

10.1016/j.aap.2017.10.009

More information

Latest update

3/11/2019