|Project Name:||Increased Understanding of Driver Visibility Requirements|
Office of Safety Research and Development |
|Project Description:||This research project will develop a hybrid human/computer model of the quantity and quality of visual information needed to navigate certain curves in the roadway safely and effectively at night. This project is part of the Federal Highway Administration Exploratory Advanced Research Program.|
|Start Date:||October 1, 2007|
|End Date:||April 30, 2012|
(1) Develop knowledge regarding human visual requirements for nighttime driving.
(2) Initiate development of a model of driver visual requirements and performance that can be used to evaluate the adequacy of a roadway scene.
|Test Methodology:||The following test methodologies/approaches will be used: literature review, hypothesis development, and onroad human factors study.|
|Other Information:||This project includes the following fact sheet: Exploratory Advanced Research Program, (2009). Seeing In The Dark: Improving Understanding of Driver Visibility Requirements at Night, FHWA-HRT-09-024, Federal Highway Administration, Washington, DC.|
|Fieldtest:||Texas Transportation Institute, Riverside Campus, June 2010.|
|Expected Benefits:||Develop an understanding of the minimum requirements for visual information required by drivers for guidance. Begin development of a predictive model that may be used to evaluate the available visual information on a given facility (existing or simulated), and determine if that level of information is adequate.|
|Deliverables:||Name: Final report on:
(1) Evaluation of driver performance in curves under varying levels of guidance.
(2) Algorithms for control of autonomous vehicle based on visual input.
(3) Results from comparison between driver performance and autonomous vehicle during "drive-off."|
Product Type(s): Research report, Techbrief
Description: The products include a technical report on development, conduct, and results of human factors study, and a description of algorithms used to control autonomous vehicle using visual information.
Safety and Human Factors