Development of a Visibility Estimation Model Based on Visibility Information from Road Images Captured in Winter.

Author(s)
Minami, M. Kato, R. Hagiwara, T. Araki, K. Nagata, Y. & Takitani, K.
Year
Abstract

This study proposes a visibility estimation model in winter that uses multiple regression analysis. The Road Visibility Information System (RVIS) can provide only visibility information at the present time. Road maintenance offices and drivers need to know road visibility information a few hours in advance. The project used a database of visibility information stored by the RVIS and 1-km-mesh meteorological data recorded during the winter of 2005/2006 to develop the visibility estimation model. Four kinds of multiple regression analysis were established with WIPS values as the dependent variable and 1-km-mesh meteorological data as independent variables. The best of the four models has a 60% hit rate, an 80% extended hit rate and a 2% undetected rate. The study revealed that visibility information based on road images captured in winter can be estimated from 1-km-mesh meteorological data using a multiple regression analysis. Implementation will require increased accuracy under poor visibility conditions, expansion to fog-induced poor visibility adding relative humidity as a factor, and overcoming inaccuracy of 1-km-mesh meteorological data under poor visibility conditions using the advanced method.

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Publication

Library number
C 44050 (In: C 43862 CD-ROM) /72 / ITRD E839913
Source

In: Compendium of papers CD-ROM 87th Annual Meeting of the Transportation Research Board TRB, Washington, D.C., January 13-17, 2008, 16 p.

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