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The focus of this research is to develop a systematic method for ascertaining the level of service (LOS) of gravel roads in the US. To date, such a method does not exist in the highway capacity manual (HCM). In this research, a methodology comprising eight criteria that affect gravel road traffic operations is developed. For each criterion, a rating is assigned. It is either "Good", "Fair" or "Poor". The results of each individual criterion rating are combined to develop an overall LOS rating. Furthermore, a non-parametric machine learning technique, namely the classification and regression tree (CART) modeling structure, is employed to quantify the contribution of each criterion to the overall gravel roads' LOS. As a case study, the developed methodology is implemented to assess traffic operations of gravel roads in Laramie County, Wyoming. The studied gravel road network is compiled and managed in a Geographic information system (GIS) shapefile prepared for the purpose of this research. That is to provide decision-makers in local agencies a computerized tool to efficiently track the performance of their gravel road network. Roughly 63.5% of the gravel road segments are operating at an LOS "Fair", while 19% are operating at an LOS "Poor" and unexpectedly 17.5% are operating at an LOS "Good". All gravel roads assessed are low-volume roads with 400 vpd or less. The developed methodology is intended to benefit traffic engineers, decision-makers, and any other stakeholders. The gravel road LOS methodology was developed and applied to Wyoming's conditions. Minor adjustments might be needed for implementation in other jurisdictions. [ABSTRACT FROM AUTHOR]

Mechanistic-empirical pavement design guide (MEPDG) or Pavement ME Design requires traffic inputs in three levels based on the availability of data and the importance of the project. The availability of site-specific (Level 1) traffic data is generally limited due to expensive cost and the accuracy of Level 3 average is unsatisfactory, and therefore the intermedium level (Level 2) traffic data need to be developed. Using multiple years of weigh-in-motion (WIM) and vehicle classification data from Oklahoma, this paper starts with a comprehensive check of the traffic data quality, and generates site-specific traffic inputs that are required in Pavement ME Design. Cluster analysis is then applied to develop homogeneous groups for each traffic input. Subsequently, decision tree model and multinomial regression model are developed for the selection of appropriate traffic clusters under given site design conditions. In addition, a case study is included to evaluate the variations of pavement performance at various levels of traffic inputs. [ABSTRACT FROM AUTHOR]

Pavement resurfacing is a maintenance activity that is undertaken to enhance the service life of pavement. This pavement resurfacing activity involves laying a new layer of asphalt concrete over existing pavement after certain time. Due to engineering factors, economic variables and uncertainty in forecasting, the pavement resurfacing decision process is a complicated activity. Various optimization approaches currently used are simplified models for finding optimal frequency and resurfacing intensity within pavement maintenance framework. In this research, artificial bee colony algorithm is proposed to solve this pavement resurfacing optimization problem. This algorithm mimics the collective behaviour of bees while searching for nectar. In this approach, various scenarios are generated, optimality of each case is evaluated, and the information thus generated is used in subsequent evaluation until global optimality is reached. The effectiveness of proposed method is demonstrated through a numerical example. The solution obtained is similar to the exact solution reported in literature. The results indicate optimal resurfacing values can be obtained with little computational effort with proposed approach. The main advantage of proposed algorithm is removal of specification of trigger values for maintenance decision. [ABSTRACT FROM AUTHOR]

The mechanical performance of epoxy asphalt concrete has been well reported in existing studies. This study investigated the surface characteristics of asphalt concrete, including the permeability, friction coefficient, moisture damage resistance and surface texture. The permeability test, dynamic friction test, Cantabro test, Hamburg test and laser texture scanning test were carried out for such investigations. Test results show that the permeability of the epoxy asphalt concrete was very low, which is desirable for protecting the steel deck. The friction coefficient can satisfy the requirement for steel deck bridge according to the Pendulum Number. However, it was found that the skid resistance could be a concern when the vehicle speed is higher than a certain level according to the dynamic friction test. The results suggested to control the traffic speed when epoxy asphalt concrete is applied as steel bridge pavement. In terms of the raveling and stripping, it was found that the epoxy asphalt mixture has an excellent anti-stripping performance based on the Cantabro test and Hamburg wheel tracking test results. The yield point was not reached after 20,000 loading cycles at 60 °C in the immersed Hamburg wheel tracking test. The mean profile depth of the epoxy asphalt concrete is 0.305 mm, much lower than conventional asphalt concrete indicating a very fine surface texture. [ABSTRACT FROM AUTHOR]

The objective of this research is to investigate the pavement response of road-bridge transition section without slab under impact load caused by vehicle bumping. The three-dimensional (3D) finite element models (FEM) of road-bridge transition section without slab were developed to simulate the response under impact load. The influence of different parameters (damping ratio, step height, vehicle speed as well as axle load) on the pavement response was investigated. Results indicated that an obvious increase of pavement response was observed with the step height and axle load rising. On the contrary, the rise of vehicle speed and damping ratio led to the decrease of pavement response. In addition, the pavement under impact load exhibited larger response as compared to under static load. Therefore, the phenomenon that static load was considered only in the traditional pavement structure is defective. Finally, the correction coefficients of design index for highway asphalt pavement were proposed to consider the influence of impact load. [ABSTRACT FROM AUTHOR]

In China, the research on asphalt pavement deterioration was hindered by a lack of comprehensive investigations on field data collection of pavement performance within its service life. The problem of traditional methods that yield inadequate data can be addressed using a combination of the Pavement Mechanistic-Empirical (PME) system and matter-element analysis (MEA). Measured data for the rutting of a road section in the Shaanxi province was employed as the validation data in this study. The input parameter for PME was localized, and a decay model based on the predicted results of PME was established by the MEA method. The results from PME indicate that the predicted results of rutting show a ''lagging" characteristic when compared with the measured data. Some optimization measures are employed to process the predicted results of PME so as to better fit the measured data. The predicted data for rutting resistance can be considered essential data for the MEA method to investigate the decay tendency of the rutting of asphalt pavement in its design life. A case study indicates that the rutting resistance of asphalt pavement will deteriorate from excellent to good, good to medium, medium to inferior, and inferior to bad in 13.8 months, 32.5 months, 43.8 months, and 55.2 months, respectively. The combination of PME and MEA proves to be appropriate to evaluate rutting potential in project level pavements. Follow-up research can be carried out on the developing trend of pavement damage, so as to better determine the maintenance time for a chosen road section. [ABSTRACT FROM AUTHOR]

The recent preparation of the Operation and Maintenance (O&M) Manual for Palestinian municipalities is an important step to guide them towards preparing and implementing their O&M priority-based plans, considering scare resources. During the course of preparation of the Manual, the proposed procedures were applied at ten pilot municipalities. This study aims to explore the outcome of the implementation of the 2014 O&M road maintenance plans at these municipalities. To achieve this, analysis of the outcome of a questionnaire designed to collect relevant information from these municipalities was conducted. The results show that seven of the targeted municipalities used the prioritization criteria proposed in the O&M Manual. Despite that the remaining municipalities had the liberty to slightly change the relative weight of the indicators, sensitivity analysis was conducted and indicated robustness of the indicators. The average percentage of roads' lengths of the actually maintained to the planned was 35%, suggesting that the plans were ambitious and need to be more rational. Most of the allocated funds for road maintenance came from the municipalities own budgets, indicating need to have more financing by the government to ensure the integrity of the municipal road infrastructure assets. The results also indicated that 95% of the maintenance works were executed through external contracts, and that the municipalities need to be supported and equipped to conduct the basic road maintenance works. [ABSTRACT FROM AUTHOR]

The traffic input parameters in the Mechanistic Empirical Pavement Design Guide (MEPDG) are: (a) general traffic inputs, (b) traffic volume adjustment factors, and (c) axle load spectra (ALS). Of these three traffic inputs, the traffic volume adjustment factors specifically monthly adjustment factor (MAF) and the ALS are widely considered to be important and sensitive factors, which can significantly affect design of and prediction of distress in flexible pavements. Therefore, the present study was undertaken to assess the sensitivity of ALS and MAF traffic inputs on rutting distress of a flexible pavement. The traffic data of four years (from 2008 to 2012) were collected from an instrumented test section on I-35 in Oklahoma. Site specific traffic input parameters were developed. It was observed that significant differences exist between the MEPDG default and developed site-specific traffic input values. However, the differences in the yearly ALS and MAF data, developed for these four years, were not found to be as significant when compared to one another. In addition, quarterly field rut data were measured on the test section and compared with the MEPDG predicted rut values using the default and developed traffic input values for different years. It was found that significant differences exist between the measured rut and the MEPDG (AASHTOWare-ME) predicted rut when default values were used. [ABSTRACT FROM AUTHOR]