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The service performance for colored asphalt pavement is inevitably affected by the addition of different colorants, especially the challenge of low temperature environment in cold regions. Therefore, the purpose of study is to explore the effects of different colorants on the service performance for colored asphalt pavement and to provide a foundation for improving the applicability of colored asphalt pavement in cold regions.

In the study, three kinds of colorants (iron oxide red, iron oxide yellow, iron oxide green) were used to compare the influence of different colorants amounts and different colorants kinds on the service performance for colored asphalt pavement in cold regions. According to the characteristics of low temperature in cold regions, the effects of different colorants on the low temperature performance for colored asphalt pavement were studied.

The study shows that different colorants have different effects on the service performance of colored asphalt pavement. The high temperature performance increases with the increase of the colorants amount, but the low temperature performance is opposite. Additionally, the yellow colored asphalt pavement has more advantages of low temperature adaptation than the red and green colored asphalt pavement.

The study results provide a certain theoretical foundation for the application of colored asphalt pavement in cold regions and have certain value and significance for the further development of colored asphalt pavement.

Pavement is one of the main elements of the roads network. It is extremely essential to study and understand the factors affecting its performance and highlight the most important ones for decision-makers and pavement experts to consider during the design, construction and maintenance stages. The purpose of this paper was to identify the factors affecting pavement performance and rank them according to their importance using Analytic Hierarchy Process (AHP) for decision-makers and pavement experts to consider during the design, construction and maintenance stages.

A survey was developed considering 29 factors found in the literature that affect pavement performance. The survey was sent to pavement professionals in Qatar to rate their perception of factors affecting pavement performance to enhance roads' sustainability. 205 responses were collected and analyzed using AHP.

The findings indicate that the factor “unconsidered heavy vehicles volume” is the most critical factor that affects pavement performance. The second most critical factor affecting the pavement performance is the “low asphalt content” due to escalating binder aging, reducing fatigue life of the pavement and decreasing the durability of roads. The third and fourth factors are “poor mechanical and thermal properties” and “unexpected high traffic volume,” respectively. These two factors are strongly attached to the first and second factors since the traffic volume affects the pavement performance less but similar to the heavy vehicles and a mix with poor mechanical and thermal properties is related indirectly to the asphalt content in the mix.

The research provides help for decision-makers in the construction industry to improve the performance of pavements using a multi-criteria decision-making tool. This paper's outcome would help the pavement management professionals in the construction industry to improve pavement performance and management, increase the pavement's life cycle and reduce maintenance costs.

The present study aims to demonstrate the performance assessment of flexible pavement structure in probabilistic framework with due consideration of spatial variability modeling of input parameter.

The analysis incorporates mechanistic–empirical approach in which numerical analysis with spatial variability modeling of input parameters, Monte Carlo simulations (MCS) and First Order Reliability Method (FORM) are combined together for the reliability analysis of the flexible pavement. Random field concept along with Cholesky decomposition technique is used for the spatial variability modeling of the input parameter and implemented in commercially available finite difference code FLAC for the numerical analysis of pavement structure.

Results of the reliability analysis, with spatial variability modeling of input parameter, are compared with the corresponding results obtained without considering spatial variability of parameters. Analyzing a particular three-layered flexible pavement structure, it is demonstrated that spatial variability modeling of input parameter provides more realistic treatment to property variations in space and influences the response of the pavement structure, as well as its performance assessment.

Research is based on reliability analysis approach, which can also be used in decision-making for quality control and flexible pavement design in a given environment of uncertainty and extent of spatially varying input parameters in a space.

With the majority of highway projects in China having entered their operational phases, the maintenance and repair of the pavement is receiving increasing attention. One problem that needs to be addressed urgently is that of how to raise the proper funds for highway maintenance to ensure the sustainable operation of the project. To this end, the aim of this study is to investigate the capital demand for operation and maintenance of a project by means of a refinancing scheme, in order to reduce the possibility of project bankruptcy and to enhance the economic value of the project.

Based on an analysis of the dynamic complexity of the highway pavement maintenance system, a Markov model is used to predict pavement performance, and an optimal capital structure decision model is proposed for highway public–private partnership (PPP) project refinancing, using the method of system dynamics (SD). The proposed model is then applied to a real case study.

Results show that the proposed model can be used to predict accurately the dynamic changes in the demand for road maintenance funds and refinancing during the period of operation, before making the optimal decision for the refinancing capital structure.

Although many scholars have studied the optimal refinancing capital structure of PPP projects, the dynamic changes inherent in the demand for maintenance funds for highway PPP projects are seldom considered. Therefore, in the approach used here the influence of the dynamic change of road maintenance capital demand on refinancing is investigated, and SD is used for the optimal capital structure decision-making model of highway PPP project refinancing, to make the decision-making process more reasonable and scientific.

This study aims to investigate the influence of surface texture distribution in respect to the procedure of pavement surface wear on friction performance.

The Weierstrass–Mandelbrot (W-M) equation is used to appropriate pavement surface profile. Through this approximation, artificial rough profiles by combining fractal parameters and conventional statistical parameters for different macro-texture are created to simulate the procedure of pavement surface wear. Those artificial profiles are then imported into discrete element model to calculate the interaction forces and friction coefficient between rolling tire and road. Furthermore, wavelet theory is used to decompose the profiles into different scales and explore the correlation between the profiles of each scale and pavement friction.

The influence of tire vertical displacement (TVD) on friction coefficient is greater than fractal dimension of road surface texture. When TVD decreases, the profiles can provide higher friction, but the rolling stability of tire is poor. The optimal fractal dimension of road surface is about 1.5 when considering friction performance. The pavement friction performance improves with wavelength from 0.4 to 6.4mm and decreases with wavelength from 12.8 to 51.2mm.

Artificial fractal curves are generated and analyzed by combining W-M function with traditional parameter, which can also be used to analyze the influence of texture distribution on other pavement performance. The preliminary research provides a potential approach for the evaluation of pavement friction performance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0499/

The purpose of this study is the development of an objective approach to prioritize and rank airfield pavement sections based on their condition and justify their funding requirements using a soft-computing technique.

The airfield pavement condition is evaluated by collecting data through field tests and visual surveys. The performance indicators are selected as deflection, structural index, subgrade modulus and pavement condition index, by taking the help of field experts. The condition of pavement sections is analyzed by obtaining scores for each sections using Buckley’s fuzzy analytic hierarchy process. The sections are finally ranked for performing their maintenance and repair activities.

The condition of pavements is represented using a single score that takes an account of cumulative impact of various parameters as well as any subjectivity associated with human perceptions.

The developed methodology is very useful for its practical implications, and it is explained using a case study of an international airport.

Decision-making for maintenance and repair practices is often based on subjective decisions and lacks a robust and judicious approach. Thus, obtaining sufficient budget for repair and maintenance becomes one of the primary challenges. This study adds a value to prevailing practices by developing an objective decision-making methodology. Additionally, the use of non-destructive testing techniques, which pose little or no necessity to destructive coring and boring, eases this task.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

Proper identification, allocation, and pricing of risks are critical to effective procurement and project delivery, particularly when contracts specify the intended performance instead of how the work is to be performed. This paper presents an overview of the sources of project risks when performance specifications are used for highway infrastructure procurement. The findings are based on a comprehensive literature review and interviews with subject-matter experts involved in developing performance specifications for highway infrastructure. The authors conclude that wider use of performance specifications in U.S. highway infrastructure construction requires a fundamental reassessment of risk allocation and pricing. Highway agencies and the contractors need to realign their respective organizational capabilities with the goal of using performance specifications as a facilitator of innovation, a goal that remains elusive after decades of applied research.

Proper identification, allocation, and pricing of risks are critical to effective procurement and project delivery, particularly when contracts specify the intended performance instead of how the work is to be performed. This paper presents an overview of the sources of project risks when performance specifications are used for highway infrastructure procurement. The findings are based on a comprehensive literature review and interviews with subject-matter experts involved in developing performance specifications for highway infrastructure. The authors conclude that wider use of performance specifications in U.S. highway infrastructure construction requires a fundamental reassessment of risk allocation and pricing. Highway agencies and the contractors need to realign their respective organizational capabilities with the goal of using performance specifications as a facilitator of innovation, a goal that remains elusive after decades of applied research.

Porous asphalt has been used for than 50 years, but it was originally developed in 1970 at Franklin institute in Philadelphia, Pennsylvania. By 1974 the first formalized procedure was created by the federal highway administration to design mixtures. Many researches on porous asphalt mixture have been conducted for the past two decades. However, there remains some concern about the potential adverse impacts of infiltrated surface water on the underlying groundwater. The purpose of this paper is to presents a short review on the application of porous asphalt pavement stormwater treatment.

In this paper, a critical review on history and benefits is presented followed by review of general studies of using porous asphalt pavement, and some recent scientific studies that examine potential contamination of soil and groundwater because of infiltration systems.

This paper indicates that porous asphalt pavement is more efficient than conventional pavements in terms of retaining pollutants, improving the quality of water and runoff while maintaining infiltration.

This paper may also help reduce land consumption by reducing the need for traditional storm-water management structures. However, on the other hand, the priority objectives which is minimizing increased flooding and pollution risks while increasing performance efficiency and enhancing local environmental quality-of-life is achieved.