Model for Predicting Road Markings Service Life

Babić, Dario; Ščukanec, Anđelko; Fiolić, Mario

doi:10.7250/bjrbe.2019-14.447

Cited by 21 publications

(14 citation statements)

References 21 publications

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“…Field evaluation of RM is quite difficult because of a plethora of factors that affect their durability; numerous researchers have struggled to find an appropriate deterioration model for R L that could predict their performance [26]. Hence, fair comparison of results from various test fields is frequently impossible and burdened with high error.…”

Section: Laboratory Testing Of Road Markingsmentioning

confidence: 99%

“…Prediction of the point of failure and, consequently, the service life of RM is difficult, and no universal formula has been found despite numerous attempts [26]. One of the more reliable methods is the fitting of R L decay data to an exponential curve [57].…”

Section: Service Life Predictionmentioning

confidence: 99%

“…While researchers were often analysing various environmental and traffic parameters in an attempt to find the optimum performance model for RM [26,27], only very small part of their attention was given to GB, which appeared to be treated as ingredients of RM so uniform that no particular consideration was needed. Furthermore, the vast majority of reports ignored the possibility of using GB other than those with refractive index (RI) of 1.5 [28,29]; however, other types of GB with higher RI are readily available and can furnish exceptional R L [30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Glass Beads for Road Markings: Surface Damage and Retroreflection Decay Study

Wenzel

Burghardt²,

Pashkevich

et al. 2022

Applied Sciences

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Road markings must be reflectorised with glass beads to be visible to drivers at night, retro-reflecting light from vehicle’s headlights, which is critical for road safety. Four commonly used types of glass beads were evaluated in a laboratory setting for retroreflectivity and their surfaces were analysed using optical and scanning electron microscopy. The glass beads were subjected to abrasion and a visual correlation was sought between the measured retroreflectivity and the surface damage. Scratching the glass bead surface with corundum in a rotary drum resulted in major differences in the rates of damage development, depending on the type of the glass beads, and it could be correlated with the rate of retroreflectivity decay. The relative results from abrasion testing were confirmed under tyre action during a turntable evaluation. Based on the outcomes of these tests, service lives, defined as maintaining appropriately high retroreflectivity, were predicted and used to calculate the consumption of raw materials—the basic sustainability parameter. It was shown that the use of ‘premium’ glass beads, enhanced with TiO2 and made in a proprietary process, provided the road marking system characterised by the lowest long-term consumption of resources.

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Section: Laboratory Testing Of Road Markingsmentioning

confidence: 99%

Section: Service Life Predictionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Glass Beads for Road Markings: Surface Damage and Retroreflection Decay Study

Wenzel

Burghardt²,

Pashkevich

et al. 2022

Applied Sciences

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“…Road marking is a sign located above the road surface that combines either a line or a symbol and provides information as visual guidance to road users [1]. Road markings must be made as clear as possible so that road users can understand and the traffic will be safe.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Template Matching on Detection of Stop Line Violations

Larasati

Setyawan

2021

JNTE

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Road marking is a sign located above the road surface that combines either a line or a symbol and provides information as visual guidance to road users. One example of road marking is the stop line behind the zebra crossing. Many violations of pedestrian rights are committed by motorized vehicles, especially because vehicles do not stop behind the stop line. This paper proposes a system to detect this type of traffic violation using the template matching method. This method is a technique in digital image processing to find small parts of the image that match the image template, so it can detect whether there is a traffic violation or not. This system uses the appropriate template images for each dataset (morning, afternoon, and evening). The system produces accuracy performances for the morning and afternoon dataset of about 100% and 78% respectively, and for the evening dataset is 70%. So, the overall average accuracy rate is 83%. The main factor affecting the overall accuracy performance is the inability to automatically extract the best template for the dataset from the morning and evening datasets.

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“…The explanatory variables for each model depend on experimental planning and data collection. As can be seen, there is no agreement on which explanatory variables best describe the retroreflectivity decrease, indicating that the degradation depends on several aspects of the experimental planning as well as the road characteristics (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20).…”

mentioning

confidence: 99%

Probabilistic Service Life Model of Pavement Marking by Degradation Data

Mazzoni

Vasconcelos

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Pavement markings are important features for improving road safety. As these markings must possess adequate retroreflectivity, road agencies are concerned about retroreflectivity maintenance. Consequently there is an increased focus on modeling the durability of pavement markings. Such models use time-to-failure data from life test experiments. The current study proposes a new method that consists of three steps: (i) designing an accelerated experiment for data collection; (ii) fitting a pavement marking retroreflectivity model using a generalized linear mixed model and the degradation data from the planned experiment, confirming the goodness of fit of the fitted model through the residual analysis; and (iii) conducting Monte Carlo simulation (with at least 10,000 runs of simulated vectors of the fitted model’s coefficients) to obtain the pavement marking service life distribution for a failure retroreflectivity threshold level. The simulation of service life of pavement marking provides relevant information, such as service life expectation and empirical quantities of interest (as median). The proposed method is applied to data on retroreflectivity degradation obtained from an experimental test site, a Brazilian highway with a high traffic volume, with two fixed factors (waterborne paints and glass bead application rates, both with three levels). The model indicates that retroreflectivity decreases at an average rate of 2% per day, and how materials differ from each other. The proposed model is easily implementable and can help management teams to adequately plan the maintenance time for pavement markings.

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Model for Predicting Road Markings Service Life

Cited by 21 publications

References 21 publications

Glass Beads for Road Markings: Surface Damage and Retroreflection Decay Study

Glass Beads for Road Markings: Surface Damage and Retroreflection Decay Study

Implementation of Template Matching on Detection of Stop Line Violations

Probabilistic Service Life Model of Pavement Marking by Degradation Data

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