Mitigating driver distraction with retrospective and concurrent feedback.
OBJECTIVE
An experiment was conducted to assess the effects of retrospective and combined retrospective and concurrent feedback on driver performance and engagement in distracting activities.


BACKGROUND
A previous study conducted by the authors showed that concurrent (or real time) feedback can help drivers better modulate their distracting activities. However, research also shows that concurrent feedback can pose additional distractions due to the limited time and resources available during driving. Retrospective feedback, which is presented at the end of a trip (i.e., post-drive), can include additional information on safety critical situations during a trip and help the driver learn safe driving habits.


METHODS
A driving simulator study was conducted with 48 participants and 3 conditions: retrospective feedback, combined feedback (both retrospective and concurrent), and no feedback (baseline case).


RESULTS
The feedback conditions (retrospective and combined) resulted in faster response to lead vehicle braking events as depicted by shorter accelerator release times. Moreover, combined feedback also resulted in longer glances to the road.


CONCLUSIONS
The results suggest that both feedback types have potential to improve immediate driving performance and driver engagement in distractions.


CONCLUSIONS
Combined feedback holds the most promise for mitigating the effects of distraction from in-vehicle information systems.
Donmez
Birsen
B
Department of Mechanical and Industrial Engineering, University of Iowa, 3131 Seamans Center, Iowa City, IA 52242, United States.
Boyle
Linda Ng
LN
Lee
John D
JD
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001288:Attention / Q000502:physiology*; D001334:Automobile Driving / Q000523:psychology*; D003198:Computer Simulation; D005133:Eye Movements / Q000502:physiology*; D030141:Feedback, Psychological; D005260:Female; D006801:Humans; D008297:Male; D012189:Retrospective Studies; D013647:Task Performance and Analysis; D014796:Visual Perception; D016526:Workload