This paper discusses the permanent deformation behavior of unbound aggregates used in accelerated pavement test (APT) sections. A traffic simulator loaded two test pavements consisting of surface treatment, dense crushed rock bases, and macadam subbases. The dependence of rutting evolution on stress state was verified, and a model relating rut depth to load repetition was derived. A laboratory study was carried out to verify if pavement rutting could be estimated by permanent-strain laboratory testing. The first stage of the investigation focused on the strain behavior of the dense graded crushed rock used in bases. Specimens were tested in a triaxial chamber in which repeated loadings were applied. Laboratory results and APT showed similar trends even if some of the results were unexpected. Rut depths in the APT test sections were noticeably more than expected from the permanent deformation in specimens in the triaxial apparatus. Although it seems clear that the investigation must be extended to the macadam aggregate and to the subgrade soil, the approach presented seems suitable to predict rutting of thin asphalt pavements.

Pavement deterioration models are important inputs for pavement management systems (PMS). These models are based on the study of performance data, and they provide the evolution law of pavement deterioration. Performance data consist of observations of pavement section conditions, and are collected through several follow-up campaigns on road networks. To characterize the pavement deterioration process, several statistical methods have been developed at the Laboratoire Central des Ponts et Chaussées (LCPC). However, these methods are suboptimal for modeling the evolution of pavement deterioration, as they ignore unit-specific random effects and potential correlation among repeated measurements. This paper presents a nonlinear mixed-effects model enabling accounting for the correlation between observations on the same pavement section. On the basis of this nonlinear mixed-effects modeling, we investigate and identify structural and climatic factors that explain differences in the parameters between pavement sections, and quantify the impact of these factors on pavement evolution. The proposed model provides a good fit for describing the evolution law of different pavement sections. The performance of this model is assessed using simulated and real data.

In this study, combinations of layer, stiffness, and thickness that produce an optimal perpetual pavement are determined for implementation on New Mexico State highways. Using a number of trial designs in the Mechanistic-Empirical Pavement Design Guide (MEPDG), pavement performances are determined and analyzed for a 50-year design life. The required thickness of a perpetual pavement varies from 10 to 15 in. (0.254 to 0.381 m) for moderate to high truck traffic roads. One example is a pavement that has a 3 in. (76.2 mm) surface layer containing a fine asphalt mix and a 7 in. (177.8 mm) intermediate layer that uses a coarse asphalt mix. This perpetual pavement carries up to 180 million equivalent single axle loads (ESALs) over its 50-year design life. Low bottom-up fatigue cracking ($<12\%$) and little or no top-down cracking [$<0.2\mathrm{ft}/\mathrm{mi}$ (37.88 $\mathrm{mm}/\mathrm{km}$)] are observed at the end of 50 years. Rutting in the intermediate layer is also low [$<0.05\mathrm{in}$. (1.27 mm)] at the end of the 10-year maintenance cycle. Overall, fatigue cracking is not a major concern in the design of perpetual pavements for New Mexico’s conditions, rather rutting is more of a concern. For implementation of the perpetual pavements, a resurfacing plan is recommended to remove rutting [$\mathrm{\text{if}}>0.1\mathrm{in}$. (2.54 mm)] in the top surface every 10 years. Additionally, perpetual pavements with and without rich-binder layers (RBLs) are examined in this study. Recommendations are made for using a perpetual pavement that does not include a RBL on the basis of life-cycle cost analysis. Another factor that is investigated in this study is debonding of hot mix asphalt (HMA) layers. Analysis shows that 88% of the perpetual pavements may fail by top-down cracking if debonding occurs between two HMA layers. Bottom-up cracking also increases significantly in a debonded environment.

This study compares the results of two measurement methods for pavement surface macrotexture: the ASTM E965 sand patch volumetric method and the Digital Surface Roughness Meter (DSRM, laser technique) conducted at a total of 13 different paved road sites in metropolitan Clark County, Nevada. Least-squares regression of DSRM-measured mean profile depth (MPD) on sand patch mean texture depth (MTD) was statistically significant ($r^2=0.95$, $p<0.05$), with DSRM estimates within 0.1 mm of sand patch in 58 of 61 cases. The magnitude of the DSRM coefficient of determination was similar to that reported by previous writers for the laser Circular Track Meter.

The need to manage construction and demolition waste (CDW) has led to environmentally-friendly actions that promote the reuse and recycling of this type of waste and other forms of waste valorization. The main priority is to foment sustainable construction work, which has the advantage of avoiding the deposit of large quantities of construction waste at landfills and greatly reducing the use of borrow material in construction projects. In this sense, the reuse of CDW materials significantly lessens the impact of construction work on the surrounding environment. The aim of this research study is to verify the technical viability of using construction waste as material for the base pavement layers of road surfaces. For this purpose, a field study was carried out, which included testing the performance of pavement composed of concrete, asphalt mix, and ceramic waste aggregate. This was done by analyzing the characteristics of the recycled material on a section of an actual road under real vehicle traffic conditions. It was observed that the load-bearing capacity of the recycled artificial CDW aggregate was satisfactory.

Dynamic vehicle dispatching at the transfer station can improve the transit service quality by optimizing the transfer coordination of routes. In this paper, a dynamic vehicle dispatching model is proposed that aims to minimize the total waiting time of passengers at the transfer station and the downstream stops. A prediction model based on support vector machines (SVM) is also developed to forecast the arrival time of the next vehicles at the transfer station. To reduce the disconnected cases between the transfer routes, an SVM-based model is introduced to forecast the elastic time for the estimated arrival time at the transfer station. According to the estimated arrival time and elastic time, vehicles are dispatched in a dynamic way to reduce the total waiting time of passengers. The dynamic vehicle dispatching approach at the transfer station is examined with the data of three transfer routes in the city of Dalian, China. Results show that the approach proposed in this paper can reduce the total waiting time of passengers at the transfer station and the downstream stops.

The development of new fuel consumption and emission models creates the need to characterize traffic conditions by using vehicle-specific power (VSP) distribution. However, in existing transportation engineering, there has been a lack of knowledge of relationships between the VSP distribution and commonly used traffic parameters and a lack of models to develop the VSP distribution from traffic parameters. To examine how traffic conditions affect VSP distributions, this study uses large samples of floating car data collected from expressways in Beijing to associate VSP distributions with various average travel speeds. After a comprehensive analysis, regular patterns are found between the VSP distribution and the average travel speed. Specifically, when the average travel speed is more than $20\mathrm{km}/\mathrm{h}$, the VSP distribution comes close to a normal distribution. The mean of the VSP distribution is the VSP value when cruising at the average travel speed, and the standard deviation could be expressed as a power function of the average travel speed. On the basis of these findings, a mathematical model for developing VSP distributions is then derived by using the average travel speed. Finally, an analysis between estimated and actual fuel consumption demonstrates that the VSP distributions developed by the proposed model are applicable for the estimation of fuel consumptions. This study indicates a possibility of developing VSP distributions mathematically for dynamic traffic conditions, which can be integrated practically with traffic models or data for the real-time estimation of fuel consumption and emissions.

Lane use distribution is a useful factor in understanding the lane-by-lane variations of speed and volume on freeways. The most common lane distribution measure has been traffic volume. However, because travel speed from two conditions—congested and uncongested—corresponds to one traffic volume, this measure may provide a misleading or inaccurate assessment. This study used density measures to uniquely match traffic conditions (e.g., congestion level) and investigated lane use distributions in 2-, 3-, and 4-lane basic segments of freeways. In addition to the lane use distributions under uncongested to transition conditions, which has been addressed by previous research efforts, this study investigated lane use distributions under transition to congested conditions. A series of regression models was developed to predict lane use distributions of individual lanes that could provide information for monitoring traffic conditions and possibly predict when and how traffic breakdown would occur from a given condition. Statistical tests showed that the developed regression models from one site could be applicable to other sites that have similar roadway conditions, operational characteristics, and traffic regulations (e.g., posted speed limit).

Estimates of planning-level treatment costs are vital inputs for preservation project budgeting, prioritization, and programming in highway asset management. However, with the paucity of analytical research on highway asset preservation costing, agencies have resorted to the use of average costs. However, average cost values fail to adequately accommodate the influence of cost factors such as project size and asset condition at the time of the preservation treatment. In addressing this issue, this paper explores the efficacy of different mathematical specifications, including the Cobb-Douglas form and a variety of other nonlinear forms, for developing treatment cost functions. The paper shows how flexible formulations could be used to specify the response variable in order to avoid unduly restricting the models and to yield cost estimates that are more reliable compared to average costs. The paper shows how to investigate the direction and strengths of scale economies and condition economies in highway asset preservation costs using mathematical forms that allow for determining the partial derivatives of treatment cost with respect to asset dimensions and pretreatment condition. The paper demonstrates its concepts by using data on flexible pavement preservation treatments at a midwestern state highway agency.

On-street parking is an important component of the parking system. Because of its occupancy of roadway resources, it can significantly impact traffic performance and safety. The aim of this paper is to give a quantitative analysis of the influence of on-street parking on travel time. The travel time data of the motor vehicles moving in the road sections with on-street parking are gathered by observers. A proportional hazard-based duration model is proposed to analyze the influential factors related to on-street parking, including effective lane width, the number of parking maneuvers, and occupancy. The results show that on-street parking has a significant impact on the travel time of vehicles. In addition, various factors can modify travel time in different degrees, and the model can be used to estimate the travel time under assumed conditions. It is hoped that this paper will help to improve the planning and management of on-street parking.

Heavy vehicles can considerably affect traffic flow particularly during heavy-traffic conditions. Large numbers of heavy-vehicle lane-changing maneuvers can contribute to increase the number of traffic accidents and hence to reduce the freeway safety. The increase in the number of heavy vehicles on freeways has been the motivation to establish strategies to reduce the interaction between heavy vehicles and passenger cars. Previous studies have examined different lane-restriction strategies for heavy vehicles using microscopic traffic-simulation packages. Those packages mostly use a general lane-changing model to estimate the lane-changing behavior of heavy-vehicle and passenger-car drivers. The general lane-changing models ignore the fundamental differences in the lane-changing behavior of passenger cars and heavy vehicles. However, an exclusive lane-changing model for heavy vehicles can increase the accuracy of simulation models. The application of such a model can result in a more reliable evaluation of lane restriction strategies. In this paper, different lane restriction strategies are defined for heavy vehicles. For each strategy, the macroscopic and microscopic traffic measurements of two freeway sections in California are analyzed, using the VISSIM default lane-changing model and an exclusive heavy- vehicle lane-changing model. The results show that the VISSIM default model unrealistically overestimates the observed number of heavy-vehicle lane-changing maneuvers and potentially overestimates the number of traffic accidents. Using the exclusive lane-changing model for heavy vehicles enhances the accuracy of the VISSIM traffic simulation model in microscopically estimating the lane-changing maneuvers of heavy vehicles.

The presented study compares three alternative straight-line approximations of the longitudinal road-profile power spectral density (PSD). The one straight line and two and three split straight-line approximations were analyzed. The minimizing of the root-mean-squared error (RMSE) was used as criteria of goodness of fit for the approximation models. The statistics of the PSD approximation model parameters, i.e., unevenness index, waviness, break angular spatial frequency, and the standard error of the regression for 145 test sections from the long-term pavement performance program (SPS-6) were calculated. The approximations were compared with connected versus unconnected lines. The approximation with two connected lines seems to be a reasonable substitution of a raw spectrum. A mean improvement of approximately 35% compared to the one straight-line approximation was identified.