Vision-Based Safety-Related Sensors in Low Visibility by Fog

Kim, Bong Keun; Sumi, Y.

doi:10.3390/s20102812

Cited by 8 publications

(15 citation statements)

References 12 publications

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“…9, it always detected a wall-like object in the entire field of view under fog conditions, without parameter tuning. This is like the behavior observed with the TOF sensors in our previous report [15]. So, the MODT values of Sensor F are meaningless because they are consistent with the transmittance of the thickest fog with the simulator.…”

Section: Measurement Results and Discussionsupporting

confidence: 82%

“…We have developed artificial sunlight lampheads for a light interference test method [13] and a simulated-snow chamber to reproduce the visibility reduction due to snowfall at room temperature [14]. To investigate the sensor effects of visibility reduction due to fog, basic experiments were conducted, and the results were published [15].…”

Section: Our Previous Workmentioning

confidence: 99%

“…For example, a TOF sensor may detect a group of fog particles in space as a single wall-like object because of scattering. Such sensor does not become "undetectable" no matter how much the spatial transmittance decreases [15]. In principle, it does not fall into failure to danger against low visibility due to fog, although they do not provide normal operation.…”

Section: (4)mentioning

confidence: 99%

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Evaluation of Detection Performance for Safety-Related Sensors in Low-Visibility Environments

Sumi

Kim

Kodama³

2021

IEEE Sensors J.

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This paper addresses the evaluation of object detection performance for non-contact safety-related sensors in low-visibility environments due to adverse weather conditions. An evaluation metric, MOT (Minimum Object-detectable Transmittance), is proposed to quantitatively evaluate the influence of the low-visibility environments on the object detection performance. Traditionally, the Meteorological Optical Range (MOR) has been used for this purpose. However, MOR is not appropriate for the sensor evaluation because it is a meteorological metric which is optimized for human eyes to estimate the distance at which a person can see clearly through an atmosphere. On the other hand, MOT is a physical and optical measure that quantifies the relationship between the spatial transmittance and the distance at which a sensor can detect a specified object. It is specialized for the sensor evaluation and can express the sensor characteristics in the low-visibility environments at each measurement distance. The usefulness of MOT will be demonstrated by presenting the experimental results of MOT measurements for various sensor devices in a fog space reproduced with environmental simulator equipment.

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Section: Measurement Results and Discussionsupporting

confidence: 82%

Section: Our Previous Workmentioning

confidence: 99%

Section: (4)mentioning

confidence: 99%

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Evaluation of Detection Performance for Safety-Related Sensors in Low-Visibility Environments

Sumi

Kim

Kodama³

2021

IEEE Sensors J.

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“…Such a study is very helpful to understand how fog can affect an autonomous vehicle or other safety features based on cameras. On the same topic, we can mention [ 102 ], where the performances of vision-based safety-related sensors (SRS) are analyzed. The fog was created in a special chamber, and experiments were conducted to determine how the environment is affecting the safety functions.…”

Section: Sensors and Systems For Fog Detection And Visibility Enhancementioning

confidence: 99%

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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“…The necessity and the importance of dealing with these questions for vision-based safety-related sensors were extensively discussed recently by Kim and Sumi [ 3 ]. However, although their work aimed to explore the fog as the environmental condition for a robot, they did not use a self-navigation platform with active illumination, and their imitation of an actual fog with nozzles produced much larger water droplets than those that actually exist in a real fog.…”

Section: Introductionmentioning

confidence: 99%

Sensing with Polarized LIDAR in Degraded Visibility Conditions Due to Fog and Low Clouds

Ronen

Agassi

Yaron

2021

Sensors

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LIDAR (Light Detection and Ranging) sensors are one of the leading technologies that are widely considered for autonomous navigation. However, foggy and cloudy conditions might pose a serious problem for a wide adoption of their use. Polarization is a well-known mechanism often applied to improve sensors’ performance in a dense atmosphere, but is still not commonly applied, to the best of our knowledge, in self-navigated devices. This article explores this issue, both theoretically and experimentally, and focuses on the dependence of the expected performance on the atmospheric interference type. We introduce a model which combines the well-known LIDAR equation with Stocks vectors and the Mueller matrix formulations in order to assess the magnitudes of the true target signal loss as well as the excess signal that arises from the scattering medium radiance, by considering the polarization state of the E–M (Electro-Magnetic) waves. Our analysis shows that using the polarization state may recover some of the poor performance of such systems for autonomous platforms in low visibility conditions, but it depends on the atmospheric medium type. This conclusion is supported by measurements held inside an aerosol chamber within a well-controlled and monitored artificial degraded visibility atmospheric environment. The presented analysis tool can be used for the optimization of design and trade-off analysis of LIDAR systems, which allow us to achieve the best performance for self-navigation in all weather conditions.

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Vision-Based Safety-Related Sensors in Low Visibility by Fog

Cited by 8 publications

References 12 publications

Evaluation of Detection Performance for Safety-Related Sensors in Low-Visibility Environments

Evaluation of Detection Performance for Safety-Related Sensors in Low-Visibility Environments

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

Sensing with Polarized LIDAR in Degraded Visibility Conditions Due to Fog and Low Clouds

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