Advanced Research on the Empirical Mode Decomposition (EMD) Algorithm - This project is designed to further refine this advanced mathematical concept and explore its potential applications in highway safety, infrastructure, and environment. The research consists of two broad fronts of studies: to improve the presently available EMD algorithms and to establish a rigorous mathematical foundation for the generalized adaptive data analysis methodology. The success of the first will enhance immediate improvement of information management in a complex or significantly rich signal data system, such as the Integrated Safety System (ISS) being considered by FHWA or for full scale traffic control systems. The success of the second research area would enable drastic improvement of robustness and reliability of the algorithm and guarantees its further applications. The project is managed by the Office of Safety R&D.
Fact sheet here.

Princeton University, NASA Goddard Space Flight Center, and Center for Ocean Land Atmospheric Studies

Underway with completion anticipated in 2012

Development of Methodologies to Evaluate the Nighttime Safety Implications of the Roadway Visual Scene Under Varying Cognitive Task Loads - This cooperative agreement aims to integrate new technology and identify a dynamic driver visual model to improve nighttime driving safety. The research is designed to develop a model framework of human visual perception in the driving environment that is comprehensive yet simple enough to derive probabilistic forecasts of driver performance under given visual conditions. An important aspect of the research is development of a combined driver/roadway monitoring system, which combines two existing systems, an infrared eye tracker and a dynamic photometer, into a unified system which also links to in-vehicle instrumentation. The project is managed by the Office of Safety R&D.

Virginia Tech Transportation Institute with Texas Transportation Institute and Franklin & Marshall College

Underway with completion anticipated in March 2010

Human Factors for Limited-Ability Autonomous Driving Systems - This project proposes to study the human factors aspects of limited automated driving systems. The research will address a number of concerns pertaining to these systems including drivers becoming over-reliant upon the systems, drivers evoking such systems outside of design parameters and drivers not being aware when the systems are not operating as intended. Expected outcomes are the impact of human factors on performance of automated systems and better definition of roles of drivers using such systems in a variety of scenarios. The project is managed by the Office of Safety R&D.
Fact sheet here.

General Motors Corporation and Delphi Corporation

Underway with completion anticipated in September 2011

Making Driving Simulators More Useful for Behavioral Research - Under this contract, the researchers will evaluate issues related to the use of interactive driving simulators in highway safety and operations research. Driving behavior in simulators will be correlated to driving behavior in the real world. The influences of visual, auditory, and haptic fidelity will be investigated. The proposed research will develop a theoretical model of the relationship between driver performance in interactive driving simulators and driving performance in real vehicles on real roads. [More]
Fact sheet here.

University of Iowa with Western Transportation Institute, Montana State University, Battelle Memorial Institute, Entropy Control, Inc., and William H. Levison Associates

Underway with completion anticipated in August 2011.

Layered Object Recognition System for Pedestrian Collision Sensing - Research will develop a real-time, in-vehicle, vision-only system that detects moving or stationary pedestrians on sidewalks and along roadways with high accuracy and a very low false alarm rate.
Fact sheet here.

Sarnoff Corporation with AutoLiv Electronics America

Project Completed

Increased Understanding of Driver Visibility Requirements - Research will develop a rational theoretical framework for determining the quantity and quality of visual information needed by drivers to navigate the roadway safely and effectively.
Fact sheet here.

SAIC with NIST and Texas Transportation Institute

Underway with completion anticipated in April 2011