This paper focuses on modeling of the distribution of shrinkage strain in early-age concrete pavements. In the modeling, an integrative model for autogenous and drying shrinkage predictions of concrete at an early age is introduced first. Second, a model taking both cement hydration and moisture diffusion into account synchronously is used to calculate the distribution of the interior humidity in concrete. The previous two models are experimentally verified independently by a series of shrinkage and interior humidity tests on three types of concretes with different compressive strengths. Using the models, the distribution of shrinkage strain in early-age concrete pavement (with respect to drying of the pavement surface) is calculated. The model results show the development of interior humidity inside of the pavement because the concrete cast obeys a two-stage mode, i.e., a vapor-saturated stage with 100% relative humidity (Stage 1) and a stage with the relative humidity gradually decreasing (Stage 2). The duration of Stage 1 increases with respect to the location, i.e., from the slab top to bottom. Within Stage 1, a uniform shrinkage strain is expected throughout the slab. By contrast, the shrinkage gradient along the slab depth is obvious in Stage 2. The maximum and minimum shrinkages occur at the slab top and bottom, respectively. The distribution of the shrinkage strain along the pavement depth is nonlinear and the nonlinearity is strong where it is close to the drying face. Concrete strength can significantly influence the magnitude of the shrinkage strain within the slab. For a given age and location, an increased concrete strength corresponds with an increased shrinkage strain and shrinkage gradient.

This paper focuses on modeling of the shrinkage stress in concrete pavements that experience nonlinear shrinkage strain through the depth of the slab. A closed form of an analytical solution of shrinkage stress is developed. In the modeling, the nonlinear shrinkage strain through the depth of the slab is divided into three components, as follows: (1) uniform, (2) linear, and (3) nonlinear shrinkage. Afterwards, the shrinkage stress resulting from each component is calculated separately. The total shrinkage stress is then obtained by summing the three stress components together. Using the model, the distribution of the shrinkage stress in concrete pavements at an early age from concrete casting is calculated and analyzed. The model results show that the developed law of shrinkage stress in pavement is consistent with the development of shrinkage strain. Within the stage of the shrinkage strain uniformly developed, a uniform shrinkage stress is expected throughout the slab. In the stage with a shrinkage strain gradient, a stress gradient is also expected. With respect to the condition that the slab top experiences drying, the distribution of the shrinkage stress along the pavement depth is apparently nonlinear and the nonlinearity is stronger in the area close to the drying surface. The maximum and minimum tensile shrinkage stresses occur at the top and bottom, respectively, of the middle section of the slab in this case. Concrete strength can significantly influence the magnitude of the shrinkage stress and its distribution in the slab. For a given age and location, a higher concrete strength corresponds with a larger shrinkage stress and stress gradient.

Local calibration of the mechanistic-empirical pavement design guide (MEPDG) is performed by determining the pavement-performance model coefficients to minimize the difference between the measured and predicted distresses of New Mexico department of transportation (NMDOT) pavements. A total of 24 New Mexico pavement sections, which have all the MEPDG inputs and quantitative-distress values required for MEPDG calibration, were used for calibration. Pavement-performance models such as rutting, alligator cracking, longitudinal cracking, and roughness models were calibrated by an error-minimization algorithm. In the calibration methodology, the target was fixed to reduce the sum of squared errors, defined by the square of the difference between predicted and measured distress, so that any bias was eliminated and precision was increased. The optimized calibration coefficients are: ${\beta }_{r1}=1.1$, ${\beta }_{r2}=1.1$, ${\beta }_{r3}=0.8$, ${\beta }_{\mathrm{GB}}=0.8$, and ${\beta }_{\mathrm{SG}}=1.2$ for the rutting model; $C_1=0.625$, $C_2=0.25$, and $C_3=\mathrm{6,000}$ for alligator cracking; $C_1=3$, $C_2=0.3$, and $C_3=\mathrm{1,000}$ for longitudinal cracking; and site factor = 0.015 for roughness. The results show that these calibration coefficients reduce error in the MEPDG prediction and assist better design of flexible pavements using MEPDG in New Mexico.

In this paper, the mechanism of near-surface cracking under critical loading conditions was investigated using mechanistic modeling approaches. These loading conditions were represented by a combination of nonuniform tire contact stresses in three directions generated during vehicle maneuvers (free rolling, acceleration/braking, and cornering) that were predicted from a tire-pavement interaction model. Three-dimensional finite element models of uncracked and cracked pavements were developed to evaluate the critical factors that are responsible for crack initiation and propagation at the near-surface of a typical full-depth pavement structure. It was found that the near-surface cracks in the proximity of tire edges showed strong mixed-mode (tension and shear) fracture potential. The pavement responses from both uncracked and cracked pavement models indicated that shear mode of fracture in the presence of compression appeared to be the dominant mode of damage for near-surface cracking. Compared to the free rolling condition, tire braking/acceleration and cornering induced high tangential contact stresses on the pavement surface, which could significantly accelerate the development of cracks at the pavement near-surface. The near-surface cracking potential was dependent on the variations of localized tire contact stress distributions. The findings presented in this study shed light on the experimental characterization of the near-surface cracking phenomenon, which appears to be driven by different stress conditions than the classical bottom-up fatigue cracking. This study also highlights the impact of vehicle maneuvering on premature pavement damage that is often neglected in the current pavement design process.

The uncertainty in material properties and traffic characterization in the design of flexible pavements has led to significant efforts in recent years to incorporate reliability methods and probabilistic design procedures for the design, rehabilitation, and maintenance of pavements. In the mechanistic-empirical (ME) design of pavements, despite the fact that there are multiple failure modes, the design criteria applied in the majority of analytical pavement design methods guard only against fatigue cracking and subgrade rutting, which are usually considered as independent failure events. This study carries out the reliability analysis for a flexible pavement section for these failure criteria based on the first-order reliability method (FORM) and the second-order reliability method (SORM) techniques and the crude Monte Carlo simulation. Through a sensitivity analysis, the most critical parameter affecting the design reliability for both fatigue and rutting failure criteria was identified as the surface layer thickness. However, reliability analysis in pavement design is most useful if it can be efficiently and accurately applied to components of pavement design and the combination of these components in an overall system analysis. The study shows that for the pavement section considered, there is a high degree of dependence between the two failure modes, and demonstrates that the probability of simultaneous occurrence of failures can be almost as high as the probability of component failures. Thus, the need to consider the system reliability in the pavement analysis is highlighted, and the study indicates that the improvement of pavement performance should be tackled in the light of reducing this undesirable event of simultaneous failure and not merely the consideration of the more critical failure mode. Furthermore, this probability of simultaneous occurrence of failures is seen to increase considerably with small increments in the mean traffic loads, which also results in wider system reliability bounds. The study also advocates the use of narrow bounds to the probability of failure, which provides a better estimate of the probability of failure, as validated from the results obtained from Monte Carlo simulation (MCS).

This paper introduces an Empirical Bayesian (EB) before-after analysis method for assessing the effects of highway shoulder paving on safety performance. In the first step, multi-year data on field-observed crash frequencies for highway segments with pavement resurfacing and shoulder paving (Type I treatment) and highway segments with pavement resurfacing only (Type II treatment), as well as untreated highway segments, on the Illinois state–maintained rural and urban interstate, multilane, and two-lane highways are collected. Next, data on untreated highway segments are used to calibrate safety performance functions (SPFs) and to predict crash frequencies for Type I and II treated highway segments, in the cases where respective treatments not been implemented. After computing the EB-adjusted crash frequency as a weighted sum of field-observed and SPF-predicted crash frequencies, the EB crash frequency for the after-treatment period is established by adjusting the EB crash frequency for the before-treatment period according to changes in traffic volumes and segment lengths between before- and after-treatment periods. The safety effects of shoulder paving are determined as the difference in the EB-adjusted Type I and II crash frequencies for the after-treatment period. It is revealed that reductions in shoulder-related fatal, injury, and property damage only (PDO) crashes from shoulder paving varies greatly by highway functional classification; and adding a new paved shoulder tends to be more effective in terms of crash reductions than paving the same width of the existing paved shoulder that has deteriorated over time or widening the paved shoulder.

This paper presents a cumulative travel-time responsive (CTR) real-time intersection control algorithm that takes full advantage of connected vehicles (CVs). The potential benefits of the proposed CTR algorithm under varying imperfect CV market penetration rates and traffic congestion conditions were investigated. The core of the CTR algorithm is based on a stochastic state estimation technique utilizing Kalman filtering that is used in estimating the cumulative travel times under imperfect market penetration rates at every update interval. Comprehensive simulation experiments covering varying volume-to-capacity ratios and imperfect market penetration rates were performed at a hypothetical isolated intersection with two through lanes and a single left-turn lane at each approach. At 100% market penetration, the CTR algorithm improved the total delay time and average speed of the intersection by 34 and 36%, respectively, compared to an optimized actuated control. It was found that at least 30% market penetration rates are needed to realize the benefits of the CTR algorithm.

Proper traffic control and guidance are imperative to reduce fatalities and property damage. When resources are scarce during emergency evacuation for any natural or artificial disasters, it is crucial to identify the most critical traffic control locations or intersections to deploy temporary control devices or to arrange manual traffic guidance so that the best system performance can be achieved. To answer the urgent theoretical and practical deployment problems, this study has proposed mixed integer nonlinear programming (MINLP) models for both static and dynamic situations. The proposed models aim to find the most crucial intersections, the optimal traffic control strategies for those intersections, and the best destination choices for evacuees to minimize the total system cost. The proposed models assume that evacuees will follow their past travel experience to safe zones unless they encounter the critical intersections. At those fully controlled critical intersections, evacuees will completely comply with the evacuation guidance to help achieve the minimum total system cost. The proposed MINLP models have also been expanded to include cell-based modules to capture the dynamic nature of evacuation flows, which is essential for real-time operation. Numerical tests on a large network with multiple origins and destinations have shown that the proposed models perform reasonably well.

Provision of bicycle facilities at intersections is often inadequate and can lead to unsafe interactions between motorists and bicyclists. The bicycle box is a tool intended to improve the predictability of bicyclist stopping position at an intersection by allowing bicyclists utilizing a bicycle lane to position themselves in front of motorists during a red phase. The bicycle box in this application is meant to reduce the possibility of a right-hook collision, where a right-turning motorist collides with a through-moving bicyclist departing the intersection. The primary goal of this study was to determine what effect, if any, bicycle boxes have on bicyclist and motorist behavior. In 2009, 950 bicyclists were observed at two sites in three phases: existing conditions, after bicycle box markings were installed, and after a green colored pavement marking was added to the bicycle box and approaching bicycle lane. The predictability of bicyclists’ behavior improved based on the increased percentage of bicyclists who used the bicycle lane to approach the intersection, departed the intersection before motorists, and stopped in front of the motor vehicle queue. While only 20–26% of bicyclists stopped in the bicycle box area after installation of the bicycle box markings, over 90% of bicyclists stopped in front of motorists and were therefore more visible to motorists. The addition of the green pavement markings led to significant improvements in bicyclist behavior, but at a considerably higher material cost. Motorist encroachment on the bicycle box was common at both sites as well as illegal right turns on red at one site. No bicycle-motorist collisions were observed during any stage of the study.