To provide innovative, practical, fast, and reliable detection of driver fatigue and distraction under a wide variety of operating conditions.
Fatigue and distraction are among the major risk factors associated with commercial motor vehicle (CMV) crashes. The effects of fatigue on drivers include impaired performance, loss of attentiveness, slower reaction times, impaired judgment, and increased probability of falling asleep. Excessive driver fatigue leads to drowsiness, a major cause of crashes, and can lead to severe physical injuries, deaths, and significant economic losses. A distracted driver (e.g., a driver who is texting, talking on a phone, eating while driving, etc.) may not be paying attention even when looking toward the road. Head pose and gaze estimations are the critical measurement of driver distraction for most cases. This Phase II Small Business Innovation Research (SBIR) project will develop a driver fatigue and distraction monitoring and warning system for CMV drivers.
The research team will develop an innovative, low-cost, practical, and non-contact concept called the Multi-Modal Driver Distraction and Fatigue Detection/Warning System (MDF). The MDF consists of four major modules:
- The Vision Module, for measuring driver pose and psychophysiological measures of alertness (PERCLOS) and for detecting hand gestures and yawning;
- The Driving Style Module, for detecting erratic inter/intra-lane driving and erratic speed variations based on yaw rate sensor and/or controller area network (CAN) bus signals;
- The Non-contact Physiological Sensing Module, which leverages recent advances in physiological sensing (like heart rate monitoring) from a distance using a simple camera system; and
- The Sensor Fusion, Recording, Warning and Individualization Module, which manages the inputs from the other modules, takes appropriate action, and issues a warning when necessary.
By fusing different modalities of sensor information, the MDF will work for various drivers with different physiological features and will provide unique and customized feedback.
A driver fatigue and distraction monitoring and warning system that provides reliable detection and warning of driver fatigue and distraction.
|October 2016: Kick-off meeting.||☑|
|July 2017: Evaluate fatigue and distraction estimation algorithms.||☑|
|October 2017: Annual progress review completed.||☑|
|March 2019: Final briefing and report.||☑|
FY16 Funding: $375,000
FY17 Funding: $375,000
FY17 Funding: $375,000
For more information, contact Terri Hallquist of the Research Division at (202) 366-1064 or email@example.com.
Intelligent Automation, Inc.
Updated: Tuesday, May 28, 2019