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The Senses Considered As Perceptual Systems

One source of accidents when driving a vehicle is the presence of fog. Fog fades the colors and reduces the contrasts in the scene with respect to their distances from the driver. Various camera-based Advanced Driver Assistance Systems (ADAS) can be improved if efficient algorithms are designed for visibility enhancement in road images. The visibility enhancement algorithm proposed in [1] is not optimized for road images. In this paper, we reformulate the problem as the inference of the local atmospheric veil from constraints. The algorithm in [1] thus becomes a particular case. From this new derivation, we propose to better handle road images by introducing an extra constraint taking into account that a large part of the image can be assumed to be a planar road. The advantages of the proposed local algorithm are the speed, the possibility to handle both color and gray-level images, and the small number of parameters. A new scheme is proposed for rating visibility enhancement algorithms based on the addition of several types of generated fog on synthetic and camera images. A comparative study and quantitative evaluation with other state-of-the-art algorithms is thus proposed. This evaluation demonstrates that the new algorithm produces better results with homogeneous fog and that it is able to deal better with the presence of heterogeneous fog. Finally, we also propose a model allowing to evaluate the potential safety benefit of an ADAS based on the display of defogged images.

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Vision Enhancement in Homogeneous and Heterogeneous Fog

A meta-analysis of the effects of texting on driving

Texting while driving: is speech-based text entry less risky than handheld text entry?

In the present study, we examined whether perceptual learning methods can be used to improve performance of older individuals. Subjects performed a texture discrimination task in the peripheral visual field and a letter discrimination task in central vision. The SOA threshold was derived by presenting a mask following the stimuli. Older subjects (age greater than 65 years) were either trained for 2 days using near threshold stimuli (experimental group) or were trained with the task with supra-threshold stimuli (older control group). The experimental group showed significant improvement in the task as a result of training whereas the older control group showed no significant improvement. The improved performance post-training equaled that of a younger control group and was maintained for at least 3 months. The results of two additional experiments indicate that the improved performance was not due to changes in divided attention, that the effect of perceptual learning was location specific, and that the pattern of learning was similar to that of younger subjects. These results indicate that perceptual learning with near threshold training can be used to improve visual performance among older individuals, that the improvements are not the result of practice with the visual task, and that the improvements do not transfer to non-trained locations.

Perceptual learning, aging, and improved visual performance in early stages of visual processing.

Age-related declines in car following performance under simulated fog conditions

Aging and visual processing: Declines in spatial not temporal integration

A study examined the effects of reduced visibility of scene information because of fog on car-following performance. Drivers were presented with a straight roadway scene in a driving simulator and were asked to maintain a predetermined driving distance in response to speed variations of a lead vehicle. Lead vehicle speed varied according to a sum of three prime sine wave frequencies. Five simulated fog density conditions and three average lead vehicle velocities were examined. Car-following performance was assessed using distance headway, variance of distance headway, root-mean-square (RMS) velocity error, control gain, phase angle, and squared coherence. Distance headway decreased only at the highest fog density condition examined. RMS velocity error increased with an increase in fog density. These results indicate that drivers had greater difficulty responding to changes in lead vehicle speed than to changes in headway. Results for squared coherence indicated that the effects of fog were greatest for th...

Rui Ni

Papers

Texting while driving: is speech-based text entry less risky than handheld text entry?

Perceptual learning, aging, and improved visual performance in early stages of visual processing.

Age-related declines in car following performance under simulated fog conditions

Aging and visual processing: Declines in spatial not temporal integration

Effects of Reduced Visibility from Fog on Car-Following Performance