Individualized Fatigue Management Program Technology for Trucking Operations

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: DTRT5709C10038
Agency Tracking Number: DTRT5709C10038
Amount: $99,998.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solitcitation Year: 2009
Solitcitation Topic Code: 091FM1
Solitcitation Number: DTRT5709RSBIR1
Small Business Information
Pulsar Informatics Inc.
3624 Market Street, PHILADELPHIA, PA, 19104
Duns: 158273743
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Daniel Mollicone
 President
 (215) 520-2630
 Daniel@pulsarinformatics.com
Business Contact
 Matthew Van Wollen
Title: Business Administrator
Phone: (215) 550-2630
Email: Matthew@pulsarinformatics.com
Research Institution
N/A
Abstract

Individual differences in vulnerability to sleep loss and fatigue from extended work hours and night work are a substantial problem in transportation work schedule development, fatigue risk management strategies, and prediction of performance impairment in real-world operations.  This project will deliver an individualized Fatigue Management Program (FMP) technology for trucking operations that incorporates information about sleep/wake history (from actigraphy) and cognitive performance (PERCLOS, a device measuring percent eye closure as a validated correlate of performance impairment due to fatigue) to produce physiology-based individualized predictions of future performance capability (e.g. 2h, 6h, 12h, 24h, 48h ahead, etc.).  This technology will be accomplished by building on our extensive peer-reviewed pioneering work in this area investigating trait individual differences in vulnerability to sleep loss and developing closed-loop, Bayesian and Kalman filter-basedadaptive algorithms to individually tailor mathematical models of performance.  By the end of Phase II, the individualized alertness model and FMP technology will be ready for Field Operational Testing (FOT) and commercialization in the motor carrier industry to predict future performance of a given individual, which can be used to improve CMV drivers schedule development, inform an in-truck drowsiness detection and warning system or be uplinked for telemonitoring and dynamic resource management.

* information listed above is at the time of submission.

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