Coordinated, progressive vehicular headlight glare reduction for driver safety using wireless sensor networks

Devassy, Alin; Gopinath, N.; Narayanan, V. Anantha; Ramachandran, Anand

doi:10.1109/iccve.2014.7297531

Cited by 4 publications

(13 citation statements)

References 3 publications

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“…A very common occurrence during navigation is the presence of overly intense light that can overwhelm the driver or the visual sensors of an autonomous ground vehicle, and thereby reduce visibility. When dazzled by a light source, typical reactions by the drivers are (1) flipping down the sunshades, which is not always effective, especially when the glare is caused by a low-positioned external light source, e.g., low sun or direct light from the headlights of an oncoming vehicle; [1] (2) using one hand to occlude the strong light source from the eyes of the driver, which is not safe and can block the view of some important obstacles on the road; and (3) wearing sunglasses, which has comfort issues. [2] For autonomous vehicles, which depend on onboard cameras for navigation, none of these reactions is possible, thus resulting in the partial or full loss of environment perception and subsequent failures.…”

Section: Introductionmentioning

confidence: 99%

An algorithm for glare detection via photometric, colorimetric, and global positioning features

Andalibi

Kawai²,

Chandler

2020

AIR

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Biological and automated vision systems which use digital video for navigation depend on the video to be of sufficient quality in order to extract reliable information that can inform the guidance and/or other decision-making processes. Although systems are available for detection and mitigation of digital distortions (e.g., compression, packet loss), detection and mitigation of natural distortions such as glare, rain, and fog have received much less attention. In this paper, we address the issue of glare detection in a single captured frame. We propose an algorithm which uses a combination of simple and efficient photometric, colorimetric, and GPS features to detect the location and spatial extent of glare within captured images. Specifically, feature maps using lightness, saturation, contrast, and color distance are computed, combined, and then, refined based on the sun's predicted location from the GPS information. In addition, we present a new ground-truth database for glare detection, in which the location, extent, and severity of glare was rated by human subjects for a collection of images. Testing on our ground-truth database revealed that the proposed algorithm can reliably detect the locations and spatial extents of glare sources in a variety of images based on subjective ratings and well-known quantitative measures.

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Section: Introductionmentioning

confidence: 99%

An algorithm for glare detection via photometric, colorimetric, and global positioning features

Andalibi

Kawai²,

Chandler

2020

AIR

View full text Add to dashboard Cite

show abstract

“…To see and be seen is considered a basic prerequisite for safe driving in road transport [6]. In order for a person to recognize the obstacle, the approaching vehicle or the roadside failure, they must be sufficiently illuminated [6]. This requirement is particularly important in terms of reduced visibility.…”

Section: Introductionmentioning

confidence: 99%

“…Their light can meet the requirement of lighting the surroundings [3]. The problem arises once another vehicle is approaching the opposite direction [6]. Vehicle's headlights transmit beams to illuminate the roadway, while some of which diverge and fall into the field of the driver's field of view [6].…”

Section: Introductionmentioning

confidence: 99%

“…The problem arises once another vehicle is approaching the opposite direction [6]. Vehicle's headlights transmit beams to illuminate the roadway, while some of which diverge and fall into the field of the driver's field of view [6]. In his eye, they dissipate (disperse) and a glare process occurs [6].…”

Section: Introductionmentioning

confidence: 99%

“…Vehicle's headlights transmit beams to illuminate the roadway, while some of which diverge and fall into the field of the driver's field of view [6]. In his eye, they dissipate (disperse) and a glare process occurs [6]. This causes the driver to have a brighter and stronger illumination to detect obstacles [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Examination of the vehicle light intensity in terms of road traffic safety: a case study

Vrábel¹,

Rievaj²,

Synák³

et al. 2018

The Archives of Automotive Engineering – Archiwum Motoryzacji

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Road transport is an essential part of modern life. It brings with itself, besides the desired effects, negative aspects as well. Negative aspect is not only the emissions production but also the traffic accidents occurrence even with tragic consequences. In proportion to traffic intensity, accidents during decreased visibility represent a significant share. A driver has a limited source of information at this time, since only vehicle headlights illuminate the runway and its surroundings. However, these do not only illuminate the roadway ahead of the vehicle, but part of the emitted light also falls into the drivers’ eyes of vehicles in the opposite direction. Thus, the eyes of such glared drivers worse recognize details, or lose the ability to see at all, i.e. vision ability. The level of vision loss depends on the light intensity that falls into the drivers’ eyes in the opposite direction. This light intensity is related not only to the correct headlights alignment (setting) but also to their design. In this paper, three generations of headlights in terms of the light intensity falling into the driver’s eyes of the vehicle in the opposite direction are compared. The headlights alignment of the examined vehicles was checked prior to measurements in accordance with the manufacturer's requirements. Given the fact that intensity of the emitted light is also related to the age of the used source, they have been replaced by the new ones. For the reason of objectivity, examination was performed at night at the New Moon phase, thus it did not light up. The starlight also did not affect the measurement results because it was cloudy, but it did not rain. There were no artificial sources of light near the measuring point..

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Development of Glare Recognition for Advanced Driver Assistance System

Madan¹,

Geetha²

2018

Computational Vision and Bio Inspired Computing

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Coordinated, progressive vehicular headlight glare reduction for driver safety using wireless sensor networks

Cited by 4 publications

References 3 publications

An algorithm for glare detection via photometric, colorimetric, and global positioning features

An algorithm for glare detection via photometric, colorimetric, and global positioning features

Examination of the vehicle light intensity in terms of road traffic safety: a case study

Development of Glare Recognition for Advanced Driver Assistance System

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