In this article, we propose a new way to estimate fog extinction at night with a camera. We also propose a method for the classification of fog depending on the forward scattering. We show that a characterization of fog based on the atmospheric extinction parameter only is not sufficient, specifically in the perspective of adaptive lighting for road safety. This method has been validated on synthetic images generated with a semi Monte-Carlo ray tracing software dedicated to fog simulation as well as with experiments in a fog chamber, we present the results and discuss the method, its potential applications and its limits.

An atmospheric visibility measurement system capable of quantifying the most common operating range of onboard exteroceptive sensors is a key parameter in the creation of driving assistance systems. This information is then utilized to adapt sensor operations and processing or to alert the driver that the onboard assistance system is momentarily inoperative. Moreover, a system capable of either detecting the presence of fog or estimating visibility distances constitutes in itself a driving aid. In this paper, we first present a review of different optical sensors likely to measure the visibility distance. We then present our stereovision based technique to estimate what we call the "mobilized visibility distance". This is the distance to the most distant object on the road surface having a contrast above 5%. In fact, this definition is very close to the definition of the meteorological visibility distance proposed by the International Commission on Illumination (CIE). The method combines the computation of both a depth map of the vehicle environment using the "v-disparity" approach and of local contrasts above 5%. Both methods are described separately. Then, their combination is detailed. A qualitative evaluation is done using different video sequences. Finally, a static quantitative evaluation is also performed thanks to reference targets installed on a dedicated test site.