This report summarizes work on Honeywell's Driver Adaptive Warning System project funded by a TRB-IDEA grant. The goal was to explore the application of learning algorithms to developing individualized models of a human driver's 'style'--and then using these models to tailor warnings to be more appropriate and useful to the individual. We call this approach a Driver-Adaptive Warning System (DAWS). Such tailored warnings hold promise for reducing the number of false alarms in collision warning and thus enhancing the acceptance and use of such systems by drivers.
Driver-Adaptive Warning System. March 31, 1995. IDEA Project Final Report
1995
20 pages
Report
No indication
English
Transportation Safety , Road Transportation , Transportation & Traffic Planning , Transportation , Human Factors Engineering , Warning systems , Adaptive control systems , Traffic safety , Innovations , Accident prevention , Surface transportation , Implementation , Human factors engineering , Models , Monitoring , Research projects , Collision avoidance , IDEA(Innovations Deserving Exploratory Analysis) , Innovations Deserving Exploratory Analysis
Driver-Adaptive Warning System
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