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The data fusion task was a collection of studies that were necessary to bridge the gaps between the component tasks (1-10) and the final system integration (Task 13), in preparation for the Task 14 evaluations.
The objective of Task 9 (Adaptive Safety Warning Countermeasures) is to improve safety-warning systems by designing these systems to adaptively respond to real-time measures of driver distraction.
The objective of Task 7 was to investigate how visual distraction impacts driving performance.
The objective of Task 6C (Telematics Demand) is to develop a means to identify cognitive demand resulting from in-vehicle device use while driving. This information will complement measures of driver state as an input to moderate information interaction with the IVIS and mitigate distraction.
The objective of Task 5 (Cognitive Distraction) is to develop an algorithm that uses driver state information to predict decrements in driving performance due to cognitive distraction.
The objective of Task 4 (Distraction Mitigation) is to develop countermeasures that mitigate distraction in a way that drivers find acceptable.
The objective of Task 3c (Performance) is to infer from driving performance in real time when the driver appears to be distracted, and then regulate secondary tasks (by locking them out, warning the driver, etc.) based on that information.
The objectives of Task 2c (develop and validate equations) were to determine (1) how various vehicle parameters that are measurable by technologies in the SAVE-IT program can be combined to predict drivers’ subjective ratings of driving task demand (especially as a function of road geometry and...
SAVE-IT Reports and Articles
This presentation provides a summary of the results of the SAVE-IT program. It was delivered during the “Human Factors at the Interface Session,” G19, at the 2008 SAE Government/Industry Meeting in Washington, D.C., on May 13, 2008.