An automated visibility detection algorithm utilizing camera imagery
January 14, 2007
The Federal Highway Administration (FHWA) has had a focused program to improve the integration of weather decision support systems into surface transportation operations since 1999. Clarus (Latin for clear) is the FHWA's most recent surface transportation weather initiative. The Clarus concept is to develop and demonstrate an integrated surface transportation weather observing, forecasting and data management system (Pisano, 2006a). As part of this effort, the FHWA is also promoting research into methods for applying new and existing sensor or probe data. These efforts include utilizing new in-vehicle sensor data that will be part of the vehicle infrastructure initiative (VII) (Pisano, 2006b), and finding innovative ways to use existing camera imagery. MIT Lincoln Laboratory (MIT/LL) was tasked to evaluate the usefulness of camera imagery for sensing ambient and road weather conditions and the feasibility for creating a portable visibility estimation algorithm. This paper gives a general background on the current utilization of camera imagery, including past and ongoing research of automated weather/condition algorithms. This is followed by a description of the MIT/LL camera test site, the analyses performed and the resultant prototype visibility estimation algorithm. In addition, the paper details application of the prototype algorithm to existing state DOT cameras in Utah. The final section discusses the future possibilities of camera-based weather and road condition algorithms.