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The measurement of atmospheric visibility is an important element for road and air transportation safety. We propose in this paper a novel estimator of the atmospheric visibility by already existing conventional highway cameras, with a technique based on the gradient magnitude selected by applying Lambert's law with respect to changes in lighting conditions. The response of this estimator is calibrated by non-linear regression with data from a visibility meter installed in a test site which has been instrumented with a camera. Through our technique, atmospheric visibility estimates are obtained with an average error of 30% for images taken in the day, with sky luminance between 10 to 8,000 cd.m −2 and visibility distances up to 15 km. Our results allow us to envision practical implementation on roadsides in the near future to determine local visibility for the benefit of road safety, meteorological observation and air quality monitoring.

This paper presents an on-board road condition monitoring system. The road condition is continuously evaluated in terms of slipperiness and coarseness and is classified into four grades, normal (m max 5 0.5), slippery (0.3 4 m max , 0.5), very slippery (m max , 0.3), and rough surface (gravel). A non-linear curve fitting technique is adopted to estimate the maximum tyre -road friction coefficient using the so-called 'magic formula'. The characteristic of the relationship between friction coefficient and slip, i.e. the value of maximum friction coefficient m max varies significantly with different surfaces, but its corresponding slip value l max does not vary much, is exploited in the road condition classification algorithm. For surface coarseness analysis, a separate classifier based on the variance of filtered wheel speed signal is implemented. Experimental results demonstrate the feasibility of the road condition monitoring system for detecting slippery and rough road surfaces in close to real-time. In addition, the proposed slip-based friction estimation algorithm has the merits of robustness to vehicletyre variance and easy calibration as opposed to past slip-based friction estimation approaches in the literature.

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