Angular spectral response from covered asphalt

Casselgren, Johan; Sjödahl, Mikael; LeBlanc, James

doi:10.1364/ao.46.004277

Cited by 40 publications

(25 citation statements)

References 7 publications

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“…Sample points were collected from each surface type, and then statistics for backscattering intensity were calculated (mean, standard deviation, minimum, and maximum). The mean values for surface types have a similar pattern, with spectral reflectance in the green region (0.5 -0.6 m) of Figure 3 and from a previous study [34]. Mean values were in the following order: vegetation, dry asphalt, wet asphalt, and sidewall of the ice.…”

Section: Backscattering Intensity By Road Surface Conditionssupporting

confidence: 80%

See 1 more Smart Citation

Characteristics of Laser Backscattering Intensity to Detect Frozen and Wet Surfaces on Roads

2019

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A frozen or wet road surface is a cause of skidding and accidents, so road surface condition is important information for driving safety. Some instruments and methods have been developed to investigate road surface conditions based on optical imagery, although an active sensor is needed, regardless of the time of day. Recently, the laser scanner, which acquires backscattering intensity data related to reflectivity, has become popular in various fields. There is a need to investigate road surface conditions (frozen, wet, or dry) using laser backscattering intensity. This study tries to analyze signal characteristics of laser backscattering intensity to detect frozen and wet surfaces on roads. An ice target with a 7 cm thickness was placed on a road surface, and a wet surface was made due to the melting ice. The ice target, wet surface, dry surface, and roadside vegetation were scanned using a laser scanner. As a result, backscattering signals from the top surface of the ice target were missing due to its smoothness. Dry and wet asphalt surfaces showed distinguishable intensity ranges in their signals. The thick sidewall of the ice target and vegetation at the roadside showed overlapping intensity ranges. An ice sheet is only a few millimeters thick on a real road surface, and the roadside vegetation might be easily distinguished by using texture or auxiliary data. Therefore, laser backscattering intensity can be used to detect frozen, wet, and dry road surfaces, regardless of the time of day. The laser scanner can be installed to acquire information about road surface conditions from observation stations and vehicles in an application for transportation.

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Section: Backscattering Intensity By Road Surface Conditionssupporting

confidence: 80%

“…One study reported the directional distribution of reflected energy by various conditions of asphalt surface (dry, water-covered, ice-covered, and snow-covered) using halogen illumination [34]. The strongest reflection backward, in the sensor direction, was when an asphalt surface is dry.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Laser Backscattering Intensity to Detect Frozen and Wet Surfaces on Roads

2019

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“…Casselgren et al [7] have developed the so called RoadEye systems for automotive use. They have performed exhaustive investigations concerning the changes of light intensity with varying incident angle and the spectrum of light.…”

Section: State Of the Artmentioning

confidence: 99%

In-vehicle sensor data fusion for road friction monitoring

Kutila

Pyykönen

Kauvo

et al. 2011

2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing

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This study presents the in-vehicle road friction estimation module to provide information for the driver to adapt his/her driving style. Our main aim is to enable support for saving fuel, minimising ecological impact and improving traffic safety. The module is based on the IcOR camera system developed by VTT which has been combined with inertia unit. Moreover, GPS receiver has been implemented to provide geographical position of the vehicle which is important for the infrastructure side of cooperative traffic services. The test results indicate clear correlation with the lateral accelerations and IcOR road state measures. The most importantoutcome is the chance to reduce number of false alarms of the IcOR system with acceleration based measurement. Moreover, the benefit of the acceleration data is the possibility to maintain the detection reliability of IcOR system in level of 70 % when driving in dark environment such as tunnels or night time.

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“…Anyway, the most promising approach seems the analysis of the different spectral content of the light reflected from the asphalt in dry, wet, icy, or snow conditions [4]. More precisely, the ShortWave InfraRed (SWIR, 0.9-1.7 nm) bandwidth shows different light reflection patterns depending on the road status [5,6,12].…”

Section: Introductionmentioning

confidence: 99%

Adverse Driving Conditions Alert: Investigations on the SWIR Bandwidth for Road Status Monitoring

Bertozzi

Fedriga

D’Ambrosio

2013

Image Analysis and Processing – ICIAP 2013

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Abstract. The 2WIDE SENSE (WIDE spectral band & WIDE dynamics multifunctional imaging SENSor Enabling safer car transportation) EU funded project is aimed at the development of a low-cost camera sensor for automotive applications able to acquire the full visible to Short Wave InfraRed (SWIR) spectrum, from 400 to 1700 nm. This paper presents the results obtained using this extended spectral responsivity sensor for a Road Status Monitoring application to inspect the vehicle's frontal area and detect layers of ice or water on the road surface.

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Angular spectral response from covered asphalt

Cited by 40 publications

References 7 publications

Characteristics of Laser Backscattering Intensity to Detect Frozen and Wet Surfaces on Roads

Characteristics of Laser Backscattering Intensity to Detect Frozen and Wet Surfaces on Roads

In-vehicle sensor data fusion for road friction monitoring

Adverse Driving Conditions Alert: Investigations on the SWIR Bandwidth for Road Status Monitoring

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