SEMI-PARAMETRIC MODELING OF PAVEMENT MARKING VISIBILITY DEGRADATION

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SEMI-PARAMETRIC MODELING OF PAVEMENT MARKING VISIBILITY DEGRADATION

ABSTRACT

The core objective of this research is to provide a methodology for obtaining guidance based on empirical evidences on pavement marking replacement times. This dissertation investigates the degradation process of pavement marking visibility over time in the United States using semi-parametric family of duration models. Specifically, a methodological framework to analyze typical pavement making visibility inspection data was formulated. The National Transportation Product Evaluation Program datasets pertaining to water based paints from a total of nine testing locations in the states of Alabama, Pennsylvania, Mississippi, Minnesota, Texas, and Wisconsin were used for the purpose of this investigation. From a methodological standpoint this research suggests that mid-point imputation is reasonable to approximate interval level failure data. Furthermore, the elapsed time model seemed to exploit the empirical pattern of event dependence among multiple marking samples on an experimental deck better than the gap-time model. This suggests that event dependence exists and degradation of the pavement marking visibility is more simultaneous than sequential.

 

 

TABLE OF CONTENTS

LIST OF FIGURES ………………………………………………………………………………………..v

LIST OF TABLES………………………………………………………………………………………….vi

ACKNOWLEDGEMENTS……………………………………………………………………………..viii

Chapter 1  Introduction……………………………………………………………………………………1

Motivation for this research……………………………………………………………………….1

Roadway Pavement Markings in the United States—A Status Quo………………..2

Research Inquiry………………………………………………………………………………………8

Chapter 2  Literature Review……………………………………………………………………………10

Introduction……………………………………………………………………………………………..10

Cost of Pavement Markings……………………………………………………………………….10 Determinants of Pavement Marking Service Life …………………………………………16

Previous Research on Pavement Marking Service Life Modeling…………………..19

Lessons Learned ………………………………………………………………………………………31

Chapter 3  Research Plan…………………………………………………………………………………37

Introduction……………………………………………………………………………………………..37

Phase 1: Database Development…………………………………………………………………37

Phase II: Service Life Modeling…………………………………………………………………41 Characteristics of Duration Data ………………………………………………………….43

Duration Modeling Framework……………………………………………………………45

Cox Regression …………………………………………………………………………..48

Summary…………………………………………………………………………………………………52

Chapter 4  Data Analysis and Results………………………………………………………………..53

General……………………………………………………………………………………………………53 Data Summary…………………………………………………………………………………………53

Modeling Results……………………………………………………………………………………..59

Life Cycle Cost Analysis…………………………………………………………………………..73

Chapter 5  Conclusions and Future Research ……………………………………………………..78

Bibliography ………………………………………………………………………………………………….86

Appendix   Pavement Marking Selection Matrices ……………………………………………..94

Chapter 1

 

Introduction

Motivation for this research

Quality management pioneers, such as Deming, Juran, Crosby, Feigenbaum and Ishika have emphasized various quality management principles [1]. After undergoing many conceptualizations of quality principles, the Balridge criteria for excellent quality performance provided by the National Institute of Standards and Technology (NIST) resulted in seven categories in which the core values and quality concepts are embodied [1, 2]. They are: leadership, strategic planning, customer and market focus, measurement analysis-knowledge management, workforce focus, process management, and business results. Though quality-based approaches and methodologies are well embraced by the private sector, quality management continues to progress in the public sector, particularly in transportation agencies [1, 37]. The transportation sector has implemented a continuous improvement strategy, where the philosophy is that there is always room for organizational improvement [1]. In addition, key strategic priorities are set for different dimensions of quality, such as learning and growth, business processes, customer service and financial progression. As the transportation sector is moving towards a quality approach in various facets of administration, design, construction, and maintenance, this research attempts to contribute to that movement through a data-driven focus on quality approaches in infrastructure maintenance and asset management of highway facilities.

This research falls under the measurement-analysis-knowledge management category and fact-based decisions, which address one of the seven Balridge-NIST criteria. Specifically, the research contributes to the development of a data-driven information system for costeffective and efficient decision-making processes in roadway pavement marking management.

Roadway Pavement Markings in the United States—A Status Quo

The Manual on Uniform Traffic Control Devices (MUTCD) for Streets and Highways [8], developed under the auspices of the Federal Highway Administration (FHWA), provides guidance on the use of pavement markings in the United States. It states that roadway delineation through pavement markings is one of the important ways to provide positive driver guidance, particularly for nighttime driving. This assumes the provision of a consistent and reliable standard for pavement marking visibility. Visibility is measured by retroreflectivity which is the material property that redirects light back in the direction of its source. More precisely, according to current pavement marking visibility standards, retroreflectivity is defined as the amount of light traveling in the direction of the source when viewed from 30 meters at an entrance angle of 88.76° and an observation angle of 1.05° [9] (Figure 1-1). In an effort to provide consistent visibility, the U.S. Congress has

mandated that the FHWA establish minimum levels for pavement marking

retroreflectivity [10]. While research efforts are being pursed to address this issue, state transportation agencies are incurring millions of dollars of expenses installing and maintaining road markings. In 1993, the annual expenditure for maintaining pavement marking programs for nearly 795,000 miles of U.S. roadways was estimated to be approximately $ 353 million [16]. In 2000, the annual expenditure in 50 states in the United States and 13 Canadian provinces and territories was estimated to be about $1.5 billion for maintaining a total of 3.8 million centerline miles of roadway [11].

 

Currently, there are many types of pavement marking materials used for roadway delineation by various highway agencies across the United States, ranging from $0.05 to $ 4 per linear foot [11, 12, 14, 16]. A literature review and survey of various state practices across the United States suggests that pavement marking practices is inconsistent [100]. It is, however, evident that some state agencies have made an effort to develop a structured pavement marking management process (Figure 1-2) [100].

Figure 1-2: General Pavement Marking Practice in the United States.

Typically, commercially available products are tested using standard material laboratory tests, and a qualified product list is developed (step 1 in Figure 1-2). Next, markings are selected from the products available in the qualified product list for installation purposes (step 2 in Figure 1-2). Then, the selected product is installed on the roadway by private contractors or state agency maintenance forces according to the specifications provided by the agency (step 3 in Figure 1-2). Subsequently, the installation is examined for quality purposes and specification correctness by state agencies during the installation and quality assurance period (step 4 in Figure 1-2). Steps 1-4 are repeated at every occasion when the pavement marking is re-striped. However, the justification when the re-striping should be done is not clear in the current practice (step 5 in Figure 1-2). The central focus of this research is to develop a framework so that guidance on re-stripe time based on empirical evidences could be provided.

 

The replacement schedule for pavement markings is often a function of traffic, climatic conditions, remaining useful life of the pavement, available funds, blanket replacement, subjective visual inspection, subjective durability ratings, or manufacturers’ durability recommendations. Some states do use quantitative measures such as benefit-cost ratios, traffic accidents, and/or visibility in their decision making process for pavement marking maintenance [27 , 101]. Appendix presents a sample of pavement marking selection matrices that are currently used by various state agencies. Although some maintenance strategies are identified, the maintenance practice adopted by state agencies is not integrated and consistent and often consists of heuristics [13, 27]. An integrated and consistent decision making process could provide cost-effective improvement in pavement marking management. To strike a balance between available resources, system performance, cost, and the promotion of consistent practice, a management system that can integrate all of the aforementioned information is required. While efforts are currently underway to create such a management system [13], this research is essential to build a management system.

 

Since the main component of an effective pavement marking management system is service life prediction, it is imperative that accurate models of pavement marking degradation be developed. Further, such models should be portable across states from the standpoint of simplicity in data collection, model updating, and implementation. Combined, the two characteristics of this research approach enhance the development of a “belief” system among state agencies that quantitative methods such as the one proposed herein, may be beneficial both in the short and long term.

 

The core idea of this research is to focus on making decisions to replace pavement markings based on the likely end of their useful lives. This motivation steers to address the following two main factors:

  1. not replacing the marking long after the expiration of the useful life, and
  2. not replacing the markings when there is remaining useful life.

Since pavement markings are associated with lane guidance for drivers, the first scenario could create traffic safety concerns because of exposing drivers to roadway environments where pavement markings are no longer visible. The second scenario might result in inefficient use of transportation agency resources, unnecessary exposure of the work crew in the traffic environment, and undue increases in traffic delay due to constraints imposed on normal traffic flow for installation purposes. Either way, the replacement decision of the pavement marking not based on likely end of its useful life would incur unnecessary expenses and might result in inefficient management for the agencies.

 

Several researchers have attempted to understand and model the degradation of pavement marking visibility over time [1531] (see Table 1-1). Many have studied the degradation of actual longitudinal lines; however, relatively few have used the National Transportation Product Evaluation Program (NTPEP) data. No explicit criticism of the data is available. On the contrary, the data provide for geographically diverse site locations, pavement types, material types, and varying geo-climatic zones. Furthermore, due to the recent changes in the visibility measurement standards [9], the results of some previous studies are no longer reliable because past retroreflectivity measurements were not recorded to the standard specifications of the current retroreflectometers.

 

From a methodological standpoint, nearly all previous pavement marking degradation evaluations have used the ordinary least squares (OLS) regression model (Table 1-1) to estimate the time when the marking would reach a given threshold retroreflectivity or visibility value [1525, 27, 28]. Some have used trend analysis [29, 30]. Various studies have considered the effects of traffic, marking material type, initial retroreflectivity value, and line configuration (centerline, edgeline, skipline) as a part of the model. Zhang and Wu [26] explained the need for adopting more rigorous modeling techniques and illustrated the use of time series models to understand the service life of pavement markings. Chapter 2 presents details on these studies.

 

Overall, many studies have addressed the objective of modeling pavement marking visibility degradation. However, their results vary widely. This could be attributed to a multitude of reasons including updates in visibility measuring instrument standards, evolution of marking material chemistry, inconsistent state practices, limited consideration of explanatory variables in the modeling, modeling methodology used, and time and space effects.

 

Table 1-1: Previous studies in pavement marking service life modeling

 

Research Inquiry

Based on the aforementioned gaps identified in the current pavement marking management research, there is a need to better understand the degradation process of pavement markings. This research proposes to understand the degradation of pavement markings using duration models and to motivate pavement marking maintenance

decisions on the basis of quantitative reasoning. As such, this research aims to contribute to the existing state of the knowledge in pavement marking management by providing:

  1. an empirical basis for making pavement marking maintenance decisions such as inspection and replacement timing, as opposed to subjective judgments and fixed cycle replacement and other heuristic approaches,
  2. a methodology for comparing durability performance of different pavement marking materials,
  3. a method to utilize typical pavement marking visibility data collected by state transportation agencies,
  4. an exposition of duration models using pavement marking visibility inspection data, and
  5. a motivation to use duration models, which have been under utilized in the field of transportation engineering, where infrastructure degradation, failure, and rehabilitation are emerging as significant issues in the overall infrastructure asset management area.

SEMI-PARAMETRIC MODELING OF PAVEMENT MARKING VISIBILITY DEGRADATION

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