The effects of foamed bitumen contents on the strength and deformational behavior of foamed bitumen mixes used for road pavements is very complex and not fully understood yet. While some writers report an increase in strength using one type of laboratory test, other writers report either only a small increase or even a decrease in strength using other types of tests, thus detracting foamed bitumen from being implemented as a cold-recycling technique for road pavement rehabilitation. This paper presents a laboratory study carried out on a specific granular material from New Zealand containing 1% cement and different foamed bitumen contents using indirect tensile strength (ITS), monotonic load triaxial (MLT), and repeat load triaxial (RLT) tests. The curing procedure, loading regime, and moisture contents were selected to simulate construction practice and suboptimal conditions normally found in New Zealand pavements. The results from these tests showed that an increase in foamed bitumen content up to an “optimum” content, increases the ITS but, at the same time, decreases both the permanent deformation resistance measured in RLT tests and the peak strength in MLT tests. In order to systematically examine the results from these tests, a general stress analysis was conducted, in which the stress paths applied in laboratory tests were plotted in $I_1-J_2^{1/2}$ stress diagrams. The stress analysis showed that adding foamed bitumen results in a reduction of the compressive strength of the mixes and a simultaneous increase in the tensile strength, which explains the apparently “contradictory” effects of foamed bitumen reported in the literature depending on the type of test used.

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high-risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High-risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using property damage only equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large annual average daily traffic (AADTs), whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

While there is an increasing interest in mechanistic-empirical flexible pavement design, this methodology will likely not be implemented by the majority of transportation agencies for several more years. Therefore, there is a need for optimization of the current design methodology, which for many agencies, is the 1993 AASHTO design guide. This approach contains a flexible pavement design equation with inputs of soil modulus, traffic, structural number, reliability, variability, and change in serviceability. A sensitivity analysis conducted on the inputs to this equation showed that the HMA layer coefficient $\left(a_1\right)$ is the most influential on the resulting HMA thickness. A recalibration of $a_1$ was performed using data from the National Center for Asphalt Technology Test Track. A least-squares regression was performed to minimize the error between predicted and actual equivalent single axle loadings applied to the test sections. The resulting average $a_1$ was 0.54 with a standard deviation of 0.08. Using 0.54 instead of the AASHTO recommended coefficient (0.44) results in a HMA thickness savings of approximately 18%.

The bonding condition between pavement layers plays an important role in the performance of pavement structures. In this paper, a three dimensional finite-element (3D-FE) program was used for modeling the mechanistic responses (stresses and strains) in the asphalt concrete (AC) layers by simulating two layer interfacial bonding conditions, namely fully bonded and debonded (i.e., the layer separated but still considering friction). The 3D-FE modeling incorporated actual measured vertical tire-pavement contact pressure (TPCP) and assumed horizontal TPCP, including investigating the effects of vehicle acceleration and deceleration. The results of these computational modeling are presented in this paper and indicated that the layer interfacial bonding condition has a significant effect on some pavement mechanistic responses such as the tensile, compressive, and shear stresses/strains in AC pavement structures. In general, layer interface debonding (or separation) was analytically found to indirectly exacerbate pavement distresses such as slippage cracking, fatigue cracking, shoving, shear deformation, and rutting, which is undesirable.

This paper presents a comparative study of laboratory results of both dynamic modulus testing and field rutting performances of hot-mix asphalt (HMA) in the state of Michigan. Fourteen field-produced mixtures at various traffic levels and aggregate sizes were evaluated and compared to those of field rutting. These mixtures were collected from job sites and compacted with a Superpave gyratory compactor to imitate the common air void level used in Mich., which is 7%. Dynamic modulus $E^{\ast }$ was measured at temperatures ranging from −5 to $39.2°\text{C}$ and frequencies ranging from 0.1 to 25 Hz. The results show that the dynamic modulus values increased when the designed traffic level for HMA mixtures increased. The field rutting performance was evaluated based on theoretical pavement rutting life index. Two parameters, $\left|E^{\ast }\right|$ and $\left|E^{\ast }\right|/\text{sin}\left(\phi \right)$ , were compared to the theoretical pavement rutting index. Based upon the preliminary study, it was found that $E^{\ast }$ was a suitable parameter in comparing the field and laboratory performance. Preliminary $\left|E^{\ast }\right|$ criteria for Mich. were prepared based upon the contractor’s warranty criteria consisting of the theoretical pavement rutting life index, and the collected traffic survey data. In addition, sigmoidal master curves were constructed using all minimum $\left|E^{\ast }\right|$ data in order to meet the practitioners’ needs.

This paper compares the performance of various advanced evolutionary algorithm (EA) techniques to solve the problem of dynamic origin/destination (O/D) estimation. The potential of EA in the dynamic O/D estimation problem lies in their powerful global search and optimization capabilities. This EA-based demand estimation framework is implemented into a model that we call dynamic O/D estimator (DynODE). DynODE is integrated with an existing dynamic traffic assignment (DTA) platform (i.e., Dynasmart-P). The EA-based methods in this research are further augmented with EA parallelization as well as hybridization schemes to further improve the quality and efficiency of the solution. In this paper, we evaluate the performance of the basic EA model, the hybrid EA model, the parallel EA (PEA) model, as well as the parallel hybrid EA model. Additionally, the performance of a local-search method is examined and compared with the EA-based approaches. The comparison is performed on a medium size network. The results from the study show that the PEA model outperforms the other algorithms in terms of speed as well as solution quality. However, all hybrid and PEA runs result in savings in computation resources as well as enhancement in the quality of solution as compared to the basic EA model. Still, the basic EA model outperforms the local-search model.

Even though speed limits of gravel roads are typically set based on statutory guidelines, there are some instances where exceptions are allowed and in place. In the absence of detailed literature on the subject, this study made an effort to evaluate and compare two criteria used in setting speed limits on low-volume gravel roads, with the intention of providing guidelines for future use. Field speed data were collected at a number of straight, level sections of gravel roads in Kansas where there is sufficient sight distance. Several sites located in two adjoining counties that use two different criteria for setting speed limits were also specifically selected for comparison purposes. One of the two counties adopts 35-mph speed limits on gravel roads and posts speed limit signs similar to those on paved roads. Characteristics of gravel roads in the adjoining county are very similar except that the speed limit is governed by the statutory limit (55 mph) and not posted. Collected actual speed data indicated no significant differences between the two speed data sets. In addition to operational speed comparisons, crash experience was also taken into consideration, which showed no major differences in terms of safety. When looking at the findings of this study, it is clear that lowered, posted speed limit values on gravel roads have not necessarily helped in improving either operational conditions or safety. Rather, reduced posted speed limits on gravel roads have increased the percentage of speed limit violators. Accordingly, care should be taken in making such decisions in the future for new situations.

This paper developed new uniform delay models for multiregime oversaturated traffic conditions at signalized intersection. Separate models were developed for each AT and then general models were obtained. The models directly consider the signal coordination (platoon arrival) effects, and thus eliminate the need to apply progression adjustment factors. The models were validated by comparing the control delays obtained from proposed models to the simulated delays from calibrated CORSIM simulation software. The control delays from the proposed delay models were not significantly different from the simulated field data for 93% of the conditions (52 scenarios out of 56). In contrast, when the HCM delay values were compared to the simulated field data, HCM estimates were not significantly different from the simulated field data only for 48% of the conditions (25 scenarios out of 56) Thus, the proposed models yield results that are comparable to field data, and the accuracy gained is worth the additional effort in computing delay.

The objective of this study consists of assessing the application of generalized additive models (GAMs) for estimating accident modification factors (AMFs). GAMs are a new type of models that have been recently introduced by the statistical community for modeling observed data. These models offer more flexible functional forms than traditional generalized linear models and allow for more adaptable variable interactions. As recently documented in the literature, variable interactions should be included in the development of AMFs. To accomplish the study objective, AMFs were derived from GAMs using data collected on rural frontage roads in Texas. The AMFs were then compared to the AMFs produced from a previous study using the same data set. The results of the study show that AMFs produced from GAMs are more flexible to characterize the safety effect of simultaneous changes in geometric and operational features (or variable interactions) than when independent AMFs are applied together. The results also show that GAMs indicated a nonlinear relationship between crash risk and changes in lane and shoulder widths for frontage roads in Texas.

The implementation of the new mechanistic-empirical design guide has led to the need for more accurate inputs. One of the most important inputs that affect the performance of the pavement materials is the climatic data. The importance of accurate climatic data is investigated in this case study. Climatic files available with the design guide and ones developed based on historical information for counties in the state of Iowa through the Iowa Environmental Mesonet were used. The climatic files that were interpolated from the data available within the design guide predicted higher rutting (both total and asphalt cement layer) for the northern part of the state, lower thermal cracking, and lower international roughness index compared to the files developed in this study. Statistical analysis showed that the results calculated using both groups are different.