Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

Discrete optimization models and methods for management systems of pavement maintenance and rehabilitation

With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four discrete optimization models are proposed for different parties involved in the management system： government,highway agent,con- tractor and the common users.These four optimal decision models are formulated as linear integer programming problems with binary decision variables.The objective function and constraints are based on the pavement performance and prediction model using the pavement condition index （PCI）.Numerical experiments are carried out with the data from a highway system in Sichuan Province which show the feasibility and effectiveness of the proposed models.

A comprehensive analysis on the pavement condition indices of freeways and the establishment of a pavement management system

In Taiwan, both the engineers and temporary employees serving in National Freeway Bureau are graduates of civil engineering. The lack of specialization in the pavement domains as students and the increasing financial requirement of pavement maintenance are hindering new engineers from further improving their knowledge on pavement. The present study aimed to improve the comfort index of national freeways. First, the inspection aspects of national freeways, such as road testing items and methods, are analyzed. Subsequently, the lack of previous literature on this subject prompted the researchers to organize relevant information pertaining to the comfort index and inspection processes of national freeways. The inspection and analysis of national freeways are beneficial for maintaining and enhancing the comfort and quality of national freeways. Moreover, the International Roughness Index is adopted to elucidate the differences exhibited at different speeds. In addition, the present study endeavored to determine skid number （SN） degradation equations to improve road traffic safety. First, a correlation analysis between SN and traffic flow, as well as between SN and climate data, was performed. Findings revealed an increased correlation between SN and traffic flow, while the correlation between SN and climate （temperature and rainfall） is less prevalent. Subsequently, traffic flow and climate were adopted as the factors for the SN degradation equations. The present study divided the traffic flow data of the entire national freeway system into five groups, enabling researchers to present individual SN degradation equations for various traffic flow conditions, thereby contributing to maintain and elevate the road traffic safety of national freeways.

Multi-objective optimization in highway pavement maintenance and rehabilitation project selection and scheduling:A state-of-the-art review

The motivation for cost-effective management of highway pavements is evidenced not only by the massive expenditures associated with these activities at a national level but also by the consequences of poor pavement condition on road users.This paper presents a state-of-the-art review of multi-objective optimization(MOO)problems that have been formulated and solution techniques that have been used in selecting and scheduling highway pavement rehabilitation and maintenance activities.First,the paper presents a taxonomy and hierarchy for these activities,the role of funding sources,and levels of jurisdiction.The paper then describes how three different decision mechanisms have been used in past research and practice for project selection and scheduling(historical practices,expert opinion,and explicit mathematical optimization)and identifies the pros and cons of each mechanism.The paper then focuses on the optimization mechanism and presents the types of optimization problems,formulations,and objectives that have been used in the literature.Next,the paper examines various solution algorithms and discusses issues related to their implementation.Finally,the paper identifies some barriers to implementing multi-objective optimization in selecting and scheduling highway pavement rehabilitation and maintenance activities,and makes recommendations to overcome some of these barriers.

Determination and prediction of pavement skid resistance–connecting research and practice

Adequate pavement skid resistance is a key requirement for safe road operations.Unfortunately,the measurement and prediction of the skid resistance property of an in-service road pavement,or pavement mixture specimens in the laboratory,is a highly challenging process from both theoretical and practical points of view.For more than 60 years,owing to the lack of theoretical solutions to the complex tire-fluid-pavement interaction problem,the practice of pavement skid resistance determination and prediction has essentially been derived from experimental and field observed data.The rapid development of efficient numerical computational techniques and high-power computing facilities in the last two decades made it possible for researchers to numerically solve the tire-fluidpavement interaction problem.It enables the numerical evaluation and prediction of high-speed wet skid resistance,and the determination of the tire-pavement kinetic friction coefficient in the evaluation of low-speed skid resistance.This paper presents a state-of-the-art review of the research development of theoretical mechanistic approaches in the determination and prediction of pavement skid resistance.It covers the following main aspects of the subject matter:(i)mechanisms of skid resistance generation in dry,wetted(i.e.,damp),wet and flooded pavements;(ii)theoretical evaluation of pavement skid resistance in dry,wetted,wet and flooded states;(iii)theoretical approaches in pavement skid resistance prediction;and(iv)concepts of representing the skid resistance state of pavement.The capability of finite element simulation approach for wet skid resistance evaluation with good accuracy is explained.Also highlighted is the practical significance of the Concept of Skid Resistance State.Areas of practical applications of the concept,coupled with the simulation model,are introduced.They include applications in driving safety analysis,road safety design and control,design of paving mixtures,safety maintenance and management of pavements,and harmonization of skid resistance measurements and predictions.

CPSO-XGBoost segmented regression model for asphalt pavement deflection basin area prediction

The use of non-destructive testing(NDT) equipment, such as the falling weight deflectometer(FWD), provides important estimates of road health and helps to optimize road management regimes. However, periodic road testing and post-processing of the collected data are cumbersome and require much expertise, a considerable amount of time, money, and other resources. This study attempts to develop a reliable prediction method for estimating the deflection basin area of different asphalt pavements using road temperature, load time, and load pressure as main characteristics. The data are obtained from 19 kinds of asphalt pavements on a 2.038-km-long full-scale fleld accelerated pavement testing track named RIOHTrack(Research Institute of Highway Track) in Tongzhou, Beijing. In addition, a chaotic particle swarm algorithm(CPSO) and a segmented regression strategy are proposed in this paper to optimize the XGBoost model. The experiment results of the proposed method are compared with those of classical machine learning algorithms and achieve an average of mean square error and mean absolute error respectively by 5.80 and 1.59.The experiments demonstrate the superiority of the XGBoost algorithm over classical machine learning methods in dealing with nonlinear problems in road engineering. Signiflcantly, the method can reduce the frequency of deflection tests without affecting its estimation accuracy, which is a promising alternative way to facilitate the rapid assessment of pavement conditions.

A review of top-down cracking in asphalt pavements:Causes, models, experimental tools and future challenges

In the last decades,a new type of distress has been observed more and more frequently on asphalt pavements.This distress,ascribable to fatigue failure,has been named top-down cracking(TDC) because it consists in longitudinal cracks that initiate on the pavement surface and then propagate downwards.A series of surveys recently carried out on Italian motorways highlighted that TDC can affect up to 20%-30% of the slow traffic lane.Therefore,in order to achieve a better understanding of such distress,this paper reviews causes,models and experimental tools and highlights future challenges for TDC.The literature review indicates that TDC can evolve on the pavement surface in three stages(i.e.,single crack,sister cracks,alligator cracking) and,below a certain depth,the cracks can form angles of 20°-40° with respect to the vertical plane.Even though multiple factors contribute to TDC development,thick pavements are more likely to fail due to TDC induced by tire-pavement contact stresses,especially in the presence of open-graded friction courses(OGFCs).Moreover,in literature there are several TDC models based on mechanics(e.g.,fracture mechanics or continuum damage mechanics) which allow a rigorous study of crack initiation and propagation.Future challenges include the identification of a reliable and feasible test method,among those proposed in literature,to study the TDC performance of asphalt mixtures and the implementation of TDC in pavement management systems(PMSs) through the definition of criteria for TDC recognition in the field as well as for the rehabilitation depth evaluation.Finally,more research is needed for open-graded asphalt mixtures,which present critical drawbacks in terms of TDC.

A semi-empirical model for top-down cracking depth evolution in thick asphalt pavements with open-graded friction courses

Thick asphalt pavements with open-graded friction course(OGFC) are exposed to topdown cracking(TDC), a distress consisting of longitudinal cracks that initiate on the pavement surface close to the wheel path and propagate downwards. The main objective of this study is to develop a semi-empirical model for the prediction of TDC depth evolution for such pavements. For this purpose, a series of cores were taken from different Italian motorway pavements affected by TDC and analyzed in the laboratory. Cracked cores taken from the wheel path area were analyzed to determine TDC depth, whereas intact cores taken from the middle of the lane(not affected by traffic loadings) were tested to obtain the volumetric and mechanical properties of the OGFC mixture. The proposed model, developed on the basis of the results already available in literature and on the findings of the laboratory investigation, predicts the evolution of TDC depth as a function of the applied traffic loadings(in terms of 12-ton fatigue equivalent single axle loads, i.e., ESALs). The model is sigmoidal with a maximum TDC depth assumed equal to 150 mm. The shape parameter of the sigmoidal function depends on the indirect tensile strength(ITS) of the OGFC mixtures(which takes into account indirectly also the volumetrics and stiffness of the OGFC), whereas the evolutive translation factor depends on the age of the OGFC mixture. After excluding some outliers, the model was able to predict the measured TDC depth very well. Moreover, in-situ observations allowed a preliminary validation of the proposed model. This model can be used in pavement management systems(PMSs) to plan surface repairs due to TDC in a timely manner, thus minimizing pavement damage and maintenance costs.

Optimising local council's return on investment from annual pavement rehabilitation budgets through targeting of the average pavement condition index

A high quality transportation system is necessary in a modem economy, and a road network is a common and significant, component of the system. Road systems have two major objectives： to enable the movement of passenger vehicles and the movement of freight vehicles at reasonable speeds. An important part of the transportation system and an expensive investment, a functional road network must meet both objectives to main- tain an efficient economy. In Australia, the Department of Infrastructure and Regional Development reported that, in 2011/12, the total road length was approximately 900,000 kin, and the total road expenditure was approximately $19 billion. Good policy requires that infrastructure investments provide a return on investment, thus warranting judicious management to ensure that it is maintained in a cost effective manner. Recent studies in Queensland, Australia, have identified differences between financial and engi- neering professionals in their understanding of infrastructure depreciation, condition deterioration, and future funding needs. Furthermore, the Queensland Asset Sustainability Ratio （ASR） requires clearer definitions to ensure that infrastructure remains meaningful to all users. This study proposes a separate sustainability index for road pavements （SIR） unlike the ASR that combines all type of assets. The justification is our ability to assess road condition, the high value of road assets, relative value to other infrastructure, and advanced knowledge of deterioration relative to other infrastructure. The SIR involves community consultation to target an average pavement condition index （PCI）. This study also provides an alternative method to determine the optimal target PCI for a local