Contrast Ratio of Road Markings in Poland - Evaluation for Machine Vision Applications Based on Naturalistic Driving Study

Burghardt, Tomasz E.; Pashkevich, Anton

doi:10.1007/978-3-030-79801-7_49

Cited by 4 publications

(4 citation statements)

References 47 publications

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“…Te authors of [59] assess the brightness of the road markings and the pavement of the nearby road, to calculate the so-called "Weber" contrast. Te study shows that the average contrast ratio on typical roads is 0.8 during the day and 2.0 at night.…”

Section: Real-time Frame-based Methodologiesmentioning

confidence: 99%

“…Te control component could then use that information to train, for example, the collision avoidance braking function. An approach based on measuring the contrast ratio (CR) is proposed in [59], where the CR is compared with the enhanced CR image under day and night conditions, and the speed was evaluated up to 140km/h. However, no speed-based evaluation was present; CR was evaluated under rainy conditions, drizzle, and glare; however, a limitation is that intensity does not appear to be considered, which could reduce the results of using Weber contrast for machine vision technology in higher intensities of rain [56] estimate the visibility of drivers toward trafc lights during rainy conditions, raindrops, and heavy rain during the day.…”

Section: Custom Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Morden,

Caraffini,

Kypraios

et al. 2023

International Journal of Intelligent Systems

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Rain can significantly impair the driver’s sight and affect his performance when driving in wet conditions. Evaluation of driver visibility in harsh weather, such as rain, has garnered considerable research since the advent of autonomous vehicles and the emergence of intelligent transportation systems. In recent years, advances in computer vision and machine learning led to a significant number of new approaches to address this challenge. However, the literature is fragmented and should be reorganised and analysed to progress in this field. There is still no comprehensive survey article that summarises driver visibility methodologies, including classic and recent data-driven/model-driven approaches on the windshield in rainy conditions, and compares their generalisation performance fairly. Most ADAS and AD systems are based on object detection. Thus, rain visibility plays a key role in the efficiency of ADAS/AD functions used in semi- or fully autonomous driving. This study fills this gap by reviewing current state-of-the-art solutions in rain visibility estimation used to reconstruct the driver’s view for object detection-based autonomous driving. These solutions are classified as rain visibility estimation systems that work on (1) the perception components of the ADAS/AD function, (2) the control and other hardware components of the ADAS/AD function, and (3) the visualisation and other software components of the ADAS/AD function. Limitations and unsolved challenges are also highlighted for further research.

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Section: Real-time Frame-based Methodologiesmentioning

confidence: 99%

Section: Custom Simulationmentioning

confidence: 99%

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Morden,

Caraffini,

Kypraios

et al. 2023

International Journal of Intelligent Systems

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“…This dashed line was painted on the edge of paver blocks, which, under sunny (glare) conditions, makes it look like a continuous line or even blends into such a surface. Because drivers recognize road markings based on the visibility level, which is provided by the contrast against the neighbouring surface [43] and could be estimated by using the contrast ratio (CR) measured through luminance [44], the calculation of the Michelson CR (CR M ) was carried out to confirm this effect here. As shown in Figure 6, three areas were selected: the painted part of the dashed line as a white marking, the road surface between painted parts as a space and road surface of paver blocks near the dashed line as a background.…”

Section: Entrance To the Kandf Zonementioning

confidence: 99%

“…As shown in Figure 6, three areas were selected: the painted part of the dashed line as a white marking, the road surface between painted parts as a space and road surface of paver blocks near the dashed line as a background. Figure 6a presents cloudy weather conditions as a good one and Figure 6b-sunny weather with the presence of sunshine glare, which is considered as critical visibility conditions [44,45]. When calculating the CR between a white marking and a space, the CR M values are 0.05 and 0.00 during good visibility conditions and glare, respectively.…”

Section: Entrance To the Kandf Zonementioning

confidence: 99%

Analysis of Traffic Organisation in the Kiss-and-Fly Zone of Kraków Airport: Eye-Tracking Study

Pashkevich,

Piegza,

Krawiec

et al. 2024

Applied Sciences

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When choosing the way to come to airports, quite a large number of passengers prefer when they are dropped off/picked up at airports using kiss-and-fly (K&F) zones. Such a travel option is associated with a special traffic organisation on the airport ground access. As there are no common regulations or standards when creating such a complex infrastructure object, it could be a challenge for drivers when searching and moving through it. Therefore, the main aim of the presented study was to assess and verify the eye-tracking technique as an objective tool, which can allow one to identify and estimate confusion points met by road users when using such an object. The field tests with 23 drivers were conducted in the K&F zone of Kraków Airport, and the data analysis focused on the traffic organisation and road signage as its key and integral parts. The eye-tracking approach allowed us to clearly find confusing situations for drivers as well as explain their reasons confirming its suitability and usefulness for the declared aim. Also, the perception of standardised and unstandardised signage of the K&F zone as well as the influence of route familiarity for drivers were discussed.

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