Paint-Line Retroreflectivity over Time

Scheuer, Michael; Maleck, Thomas L.; Lighthizer, Dale R

doi:10.3141/1585-08

Cited by 10 publications

(6 citation statements)

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“…The age of markings variables is present in all such models. It is also the only variable used on the exponential model proposed by Lu [14], linear models proposed by Scheuer et al [15], Taek et al [16], Sarasua et al [17] and Thamizharasan et al [18], and the inverted quadratic equation model proposed by Bahar et al [19]. Abboud and Bowman [20], Lindly and Wijesundera [1], and Lee et al proposed independently the Vehicle Exposure ( ) variable defined as a weighted product of the Annual Average Daily Traffic (…”

Section: State Of the Art Of Current Degradation Model Of Retroreflecmentioning

confidence: 99%

A Clustering-based Approach to Segment a Pavement Markings Line

Redondin¹,

Bouillaut²,

Daucher³

2020

Int J Performability Eng

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The maintenance of road infrastructure is a classic social challenge, especially in the context of a decreasing maintenance budget and the advent of autonomous vehicle traffic. Road markings need an accurate replacement strategy to guarantee that the markings remain perceptible. The retroreflective luminance of markings is currently dynamically quantifiable only by using a retroreflectometer such as the Ecodyn from MLPC. The main objective of this research is to construct a performance-based approach for retroreflective marking replacement adapted to a given road network. This approach involves three main tasks: localize the strategic area based on past inspections, determine an adapted decay model for a given area, and evaluate the economic impact of replacing markings. This paper focuses on the first task. We apply the Agglomerative Hierarchical Clustering (AHC) method to a given dataset to obtain a suitable markings line segmentation. Markings whose retroreflective luminance exhibits similar evolution over time are interpreted to belong to a specific area of the road network. When no follow-up replacement has occurred, a replacement detector deduces the date at which markings were laid from the clusters. The broken center line of the French National Road 4 illustrates the proposed approach; the road is divided into 5 clusters and 34 lifecycles. A study of markings laid in 2008 and replaced in 2012 shows important variations in the decay of the retroreflective luminance as identified by the clustering approach. Even for a single road, an optimal replacement strategy for retroreflective road markings is necessary and is composed of several local maintenance strategies.

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Section: State Of the Art Of Current Degradation Model Of Retroreflecmentioning

confidence: 99%

A Clustering-based Approach to Segment a Pavement Markings Line

Redondin¹,

Bouillaut²,

Daucher³

2020

Int J Performability Eng

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“…Much research effort has gone in to estimating the service life of pavement markings in the United States based on statistical models (Abboud & Bowman, 2002;Andrady, 1997;Bahar, Masliah, Erwin, Tan, & Hauer, 2006;Kopf, 2004;Lee et al, 1999;Lindly & Wijesundera, 2003;Lu & Barter, 1998;Martin, Perrin, Jitprasithsiri, & Hansen, 1996;Migletz et al, 2000;Migletz, Graham, Harwood, & Bauer, 2001;Sarasua, Clarke, & Davis, 2003;Sathyanarayanan, Shankar, & Donnell, 2008;Scheuer, Maleck, & Lighthizer, 1997;Zhang & Wu, 2006). However, several of the studies used retroreflectivity data collected from retroreflectometers with a measurement geometry of 15 meters (Bowman & Abboud, 2001).…”

Section: Literature Reviewmentioning

confidence: 99%

Use of Pavement Marking Degradation Models to Develop a Pavement Marking Management System

Sasidharan

Karwa

Donnell

2009

Public Works Management & Policy

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The Pennsylvania Department of Transportation collected periodic pavement marking retroreflectivity data on 88 roadway segments over a 1-year period from May 2007 through May 2008. The purpose of this effort was to use the data collected to develop a series of pavement marking degradation models that could be used to implement a management system. In this study, panel data models were used to estimate the service life of both waterborne and epoxy pavement markings because of the repeated retroreflectivity measurements recorded over time. It was found that pavement marking retroreflectivity decreases as the age of both epoxy and waterborne-paint pavement markings increase. White pavement markings were shown to have higher estimated service lives than yellow pavement markings. Traffic exposure was found to be negatively correlated with pavement marking retroreflectivity in the waterborne-paint analysis, but traffic exposure was not statistically significant in the epoxy pavement marking retroreflectivity model. A life cycle cost analysis showed that waterborne paints are more cost-effective than epoxy pavement markings if applied on a statewide basis.

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“…Various research efforts have been undertaken to address the objective of modeling degradation of pavement marking retroreflectivity (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26). The majority of studies used ordinary least-squares techniques to model degradation of retroreflectivity over time.…”

Section: Modeling Degradation Of Pavement Marking Retroflectivitymentioning

confidence: 99%

Pavement Marking Retroreflectivity Inspection Data

Sathyanarayanan

Shankar

Donnell

2008

Transportation Research Record: Journal of the Transportation R

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Quantifiable life-cycle models of the service life of pavement markings are essential for a cost-efficient pavement marking management system. A study was conducted to develop an analysis procedure for typical pavement marking retroreflectivity inspection data. Retroreflectivity data collected by the National Transportation Product Evaluation Program on water-based paints in 2002 on a Pennsylvania test deck were used. Those data were considered interval-level duration data, and a Weibull analysis was performed. A Weibull analysis is a typical method in reliability engineering in which Weibull scale and shape parameters are estimated from failure data for making objective maintenance decisions. Results of the Weibull analysis indicated that the water-based paints had shape and scale parameters of 1.42 (±0.05), and 601.67 (±17.73) days, respectively, for skip line areas and 2.38 (±0.08) and 227.41 (±4.48) days, respectively, for left wheelpath areas. It was also determined that the probability of 2-year water-based paints lasting above 100 mcd/m2/lx varied from 0% to 27%. The lower limit corresponds to the left wheelpath, and the upper limit corresponds to the skip line area. The left wheelpath markings failed to stay above 100 mcd/m2/lx after approximately a year, while skip line markings could maintain 100 mcd/m2/lx ratings or higher for more than 1,000 days. White markings were found to last longer than yellow markings for the same exposure. This study used data from a single site in Pennsylvania. A multisite analysis accounting for time and space variations is recommended before adopting this method for minimum pavement marking retroreflectivity standard assessment.

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Paint-Line Retroreflectivity over Time

Cited by 10 publications

References 0 publications

A Clustering-based Approach to Segment a Pavement Markings Line

A Clustering-based Approach to Segment a Pavement Markings Line

Use of Pavement Marking Degradation Models to Develop a Pavement Marking Management System

Pavement Marking Retroreflectivity Inspection Data

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