System for visibility distance estimation in fog conditions based on light sources and visual acuity

Silea, Ioan; Miclea, Razvan-Catalin; Alexa, Florin

doi:10.1109/aqtr.2016.7501323

Cited by 5 publications

(6 citation statements)

References 9 publications

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“…The authors in [ 8 ] present laboratory measurements where fog is generated in a chamber and using a laser and an optical receiver, the fog influence (attenuation and absorption) on the optical laser beam is analyzed. The distance between the transmitter and the receiver is one meter, the fog environment is assured using a fog generator, the quantity of fog being controlled by the level of liquid used to generate it.…”

Section: Fog Detection and Visibility Estimation Methodsmentioning

confidence: 99%

“…The results presented there (see Section 4.2 ) confirm the theory that the decrease, in contrast, is the main fog effect on visual perception. The authors in [ 8 ] present a system that approaches the link between light intensity decrease and visibility decrease in fog conditions. First, they create a concordance between the input power of the light sources (led and laser—most used on modern vehicles) and the output optical power.…”

Section: Reaction Of Human Subjectsmentioning

confidence: 99%

“…There were approaches based on image processing by detecting lane marking, traffic signs, or hazards such as obstacles [ 4 ], image dehazing and deblurring [ 5 ], image segmentation, or machine learning methods [ 6 , 7 ]. Other methods are based on evaluating the optical power of a light source in direct transmission or backscattering, by analyzing the scattering and dispersion of the beam [ 8 , 9 ]. There are approaches that are using systems already installed on the vehicle such as ADAS (Advanced Driver Assistant Systems), LIDAR (LIght Detection And Ranging), radar, cameras, or different sensors [ 10 , 11 , 12 ] and even geostationary satellite approaches [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

Miclea

Ungureanu

Sandru

et al. 2021

Sensors

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In mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers. In addition to the visibility problem, the driver must face also the choice of speed while driving. The main effects of fog are a decrease in contrast and a fade of color. Rain and snow cause also high perturbation for the driver while glare caused by the sun or by other traffic participants can be very dangerous even for a short period. In the field of autonomous vehicles, visibility is of the utmost importance. To solve this problem, different researchers have approached and offered varied solutions and methods. It is useful to focus on what has been presented in the scientific literature over the past ten years relative to these concerns. This synthesis and technological evolution in the field of sensors, in the field of communications, in data processing, can be the basis of new possibilities for approaching the problems. This paper summarizes the methods and systems found and considered relevant, which estimate or even improve visibility in adverse weather conditions. Searching in the scientific literature, in the last few years, for the preoccupations of the researchers for avoiding the problems of the mobile systems caused by the environmental factors, we found that the fog phenomenon is the most dangerous. Our focus is on the fog phenomenon, and here, we present published research about methods based on image processing, optical power measurement, systems of sensors, etc.

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Section: Fog Detection and Visibility Estimation Methodsmentioning

confidence: 99%

Section: Reaction Of Human Subjectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

Miclea

Ungureanu

Sandru

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Finally, merge the multiple visibility indicators by MNLR analysis. The obtained visibility results are calibrated to span the range [10,10000], where the lower limit corresponds to the worst visibility possibly, and the upper limit corresponds to the visibility which has no adverse effects on people's travel.…”

Section: Proposed Visibility Estimation Methodologymentioning

confidence: 99%

“…The camera captures the laser images during the launch and estimates the visibility distance by image characteristics such as the contrast. Silea Ioan et al have presented some principles which can lead to the development of a system capable of estimating the visibility distance in foggy weather conditions by using the light scattering property [10]. The effect of fog concentration on the light source and the relationship between fog concentration and visual acuity are used as the input data.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Dedicated Methods of Night Traffic Visibility Estimation

Qin

2020

Applied Sciences

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Traffic visibility is an essential reference for safe driving. Nighttime conditions add to the difficulty of estimating traffic visibility. To estimate the visibility in nighttime traffic images, we propose a Traffic Sensibility Visibility Estimation (TSVE) algorithm that combines laser transmission and image processing and needs no reference to the corresponding fog-free images and camera calibration. The information required is first obtained via the roadside equipment which collects environmental data and captures road images and then analyzed locally or remotely. The proposed analysis includes calculating the current atmospheric transmissivity with the laser atmospheric transmission theory and acquiring image features by using the cameras and the adjustable brightness target. Image analysis is performed using two image processing algorithms, namely, dark channel prior (DCP) and image brightness contrast. Finally, to improve the accuracy of visibility estimation, multiple nonlinear regression (MNLR) is performed on the various visibility indicators obtained by the two methods. Extensive on-site measurements analysis confirms the advantages of TSVE. Compared with other visibility estimation methods, such as the laser atmospheric transmission theory and image analysis method, TSVE significantly decreases the estimation errors.

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