Journal of Transportation Engineering, Part B: Pavements

Pavement monitoring involves periodic damage detection and condition assessment of pavements for efficient pavement management. Unmanned aerial vehicle (UAV)-based pavement monitoring requires multidisciplinary knowledge of pavement distress, drone type, payload, flight parameters, drone deployment, and image processing. Owing to the availability of various UAVs, data sensing devices, operating ecosystems, and post-processing tools, selecting an appropriate combination of these systems is crucial. Therefore, the primary objective of this study is to provide essential knowledge on the prevalent challenges of existing monitoring techniques and discuss the potential advantages of UAVs over conventional pavement monitoring practice. A state-of-the-art review emphasizing UAV technicalities in the context of image-based pavement monitoring is presented. A detailed workflow and checklist for drone deployment is drafted for novice users to ensure safe and high-quality data acquisition. Finally, the present challenges and future scope of UAV-based pavement monitoring is discussed. Overall, this study aims to provide inclusive and comprehensive information on UAV-based pavement monitoring to beginner researchers.

Cracking is a common failure mode in asphalt concrete (AC) pavements. Many tests have been developed to characterize the fracture behavior of AC. Accurate crack detection during testing is crucial to describe AC fracture behavior. This paper proposes a framework to detect surface cracks in AC specimens using two-dimensional digital image correlation (DIC). Two significant drawbacks in previous research in this field were addressed. First, a multiseed incremental reliability-guided DIC was proposed to solve the decorrelation issue due to large deformation and discontinuities. The method was validated using synthetic deformed images. A correctly implemented analysis could accurately measure strains up to 450%, even with significant discontinuities (cracks) present in the deformed image. Second, a robust method was developed to detect cracks based on displacement fields. The proposed method uses critical crack tip opening displacement (${\delta }_c$) to define the onset of cleavage fracture. The proposed method relies on well-developed fracture mechanics theory. The proposed threshold ${\delta }_c$ has a physical meaning and can be easily determined from DIC measurement. The method was validated using an extended finite-element model. The framework was implemented to measure the crack-propagation rate while conducting the Illinois-flexibility index test on two AC mixes. The calculated rates could distinguish mixes based on their cracking potential. The proposed framework could be applied to characterize AC cracking phenomenon, evaluate its fracture properties, assess asphalt mixture testing protocols, and develop theoretical models.

Abstract

Road markings are used on pavement surfaces to provide guidance and information for drivers and pedestrians. When navigating road networks, awareness of upcoming hazards and critical information is essential for safe and comfortable driving. However, once the road markings get damaged from traffic application and environmental conditions, it becomes less efficient due to the removal of surface markings. Hence, it is crucial to determine road marking deterioration and propose appropriate rehabilitation methods. With the advancement of deep learning (DL) methods, as a branch of machine learning (ML), there is high potential for developing an automatic road marking detection algorithm with high accuracy and significantly shorter computational and analysis time. In this study, an automated algorithm for segmenting the road markings using mask region-based convolutional neural networks (mask R-CNNs) and determining their deterioration by image processing using the Otsu algorithm was developed. The developed mask R-CNN model used 6,500 and 3,500 images for training and validation, respectively. As a result, the mask R-CNN model could detect and segment road markings with an average accuracy of 97.10% for road marking object detection and 91.0% for road marking segmentation. Furthermore, the image processing algorithm obtained high precision of 92.0%. Therefore, the proposed method was found to be a promising approach to detecting and segmenting road markings together with determining their severity.

Practical Applications

Road markings play a vital role in traffic safety, so their evaluation and immediate rehabilitation are necessary. Recently, studies determining road marking defects have been conducted; however, they are time-consuming and require a retroreflectivity device. These methods, moreover, can only be applied for image classification and not damage evaluation, especially in extreme conditions. This research provides an automated process of determining the deterioration of road markings with high accuracy, addressing the previous issues discussed. In this study, segmenting road markings as new areas using mask R-CNN under extreme environmental and severely damaged conditions is presented. Using the segmented road marking, the damaged area whose pixel value is less than the threshold is calculated and compared with the whole area. The Otsu algorithm then was used to automatically collect the threshold value through the road marking image histogram. The proposed method can be used in different road networks, as applied to a 502-km road in Seoul. This study has great potential to replace manual visual assessments conducted by humans and retroreflectivity devices with higher precision and reliability. Furthermore, this study can aid pavement agencies in easily setting the deterioration criteria of road markings suitable for self-conditions.

Cracking is a typical defect of cement concrete pavements. This paper investigates the fracture behavior of cement mortar and concrete materials based on experimental observations using acoustic emission (AE) and embedded SmartRock sensor techniques. Examining the AE signals (e.g., AE counts, events, and energy), the bulk displacement responses using LVDT sensors, and the localized responses using the embedded SmartRock sensor during three-point bending (TPB) tests, the correlation between different types of intelligent sensing parameters and the evolution of macroscopic mechanical properties of cement mixtures was analyzed. In addition, a four-stage development process is proposed to describe the fracturing behaviors of the mortar and concrete, as well as the underlying mechanisms. The results show that the four-stage model proposed in this paper can describe the entire fracture process of concrete or mortar materials, especially the transition from Stage 3 to Stage 4. In addition, the SmartRock sensor can effectively monitor the mechanical degradation of the host matrix during the fracture process, and the AE energy and AE events can be used to predict efficiently the degree of material damage: the material stiffness decreases slowly in the early stages of loading and suddenly in the later stages of loading, which can be characterized by the change in AE energy. The rise time/AE amplitude values are an effective way to characterize the crack propagation of cement mixtures in different stages of fracture and help to conduct a comprehensive evaluation of the health of the material.

In Costa Rica, weigh stations for trucks and commercial vehicles were reinstated in 2008. Since then, a stabilizing trend in the percentage of heavy vehicles with excess loading was observed. For pavement design purposes, this resulted in reduced variability in truck equivalency factors. These were statistically validated by processing all the weight data collected at different stations located throughout the national road network between 2008 and 2011. Using linear regressions, it was verified that given a constant noncompliance percentage, the truck equivalency factor for C2, C3, and T3-S2 vehicles tended to stabilize at 0.20, 0.66, 1.19, respectively. These results were consistent with additional power regression performed on the data. Higher weight enforcement on the T3-S3 vehicles’ tandem axle would result in a 0.17 decrease in the truck equivalency factor. The findings presented herein should aid countries that have yet to implement weigh stations, considering the benefits of exploring the evolution of truck factors if weigh stations were installed. This weigh station implementation case study exhibits the reality and development of pavement loading over time. Therefore, government authorities should be encouraged to control truck traffic with weigh stations to reduce pavement damage.

Axle load limits for single axles, 89 kN ($\approx 20\mathrm{kips}$), and tandem axles, 151 kN ($\approx 34\mathrm{kips}$), are set to control potential pavement damage. These axles, at their corresponding weight limits, are considered equivalent. Because pavement layers are more complicated than a linear elastic material, using linear elastic theory would result in erroneous loading response prediction and, hence, potential pavement damage. Thus, actual tandem- and single-axle loading, along with flexible pavement structure, were modeled using an advanced finite-element model. The influences of a 1.2-m-spaced tandem axle and a single axle on flexible pavement responses were assessed qualitatively. Transfer functions from AASHTOWare were used to compute pavement distresses. Tandem and single axles were found to be inequivalent, confirming that the distresses due to the tandem axle were greater than those of the single. Load equivalency was calculated for different parameters, such as tire type, pavement material, and structure. The load equivalency was found to be dependent on various parameters. Wide-base tires (tire type) had the highest influence on the weight limits [135 kN ($\approx 30\mathrm{kips}$)]. Because 72% of national goods are moved on highways, accurate weight limits should be applied using an established equivalency factor.

Abstract

With the huge production of natural rubber (NR), it is feasible to produce natural rubber–modified asphalt binder (NRMB) to achieve carbon neutrality and environmental sustainability in asphalt pavement construction. As a solid thermoplastic elastomer, the dispersion and compatibility of NR in the asphalt binder are poor, which is the main obstacle to using these solid thermoplastic elastomers as modifiers. Accordingly, a high-performance vulcanized natural rubber–modified asphalt binder (VNRMB) was prepared by rotational shearing to disperse NR into the asphalt binder, providing the modification scheme of NR and optimizing the performance of the modified binder to be conducive the better durability. First, the best vulcanization scheme was determined by the consistency tests. Then the rheological and low-temperature properties of the asphalt binders were tested by the dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests, respectively. It was found that in high and low temperatures, VNRMB performed significantly better than virgin asphalt binder (VB) and NRMB. The high-temperature deformation resistance and low-temperature cracking resistance for 2.5/10VNRMB were significantly better than those of 2.5NRMB and VB, apart from the lower thermal sensitivity, the better elastic recovery, and storage stability. Fluorescence microscopy (FM) and Fourier transform infrared spectroscopy (FT-IR) tests indicated that NR dispersed in the binder was cross-linked by the sulfur to form a network structure in VNRMB.

Practical Applications

In general, the novel VNRMB prepared in this paper exhibits preferable performance. Compared with VB and NRMB, VNRMB has better elastic recovery, rutting resistance, and low-temperature cracking resistance. Using VNRMB on the top layer is suggested because of the preferable rutting resistance, but the thermal cracking caused by extreme temperature gradients should be further studied and pursued. Additionally, for cold areas, using VNRMB on the intermediate or bottom layers is suggested to improve low-temperature cracking resistance. However, these results were only from preliminary tests of asphalt binders. In the future, the pavement performances of the modified asphalt mixture, including rutting and fatigue cracking, should be studied with different states of vulcanization of VNRMB considered. Moreover, in the process of study, it was found that the mild cross-linking state could maximize the ductility of modified asphalt binders. But the low-temperature performance of the asphalt mixture was not proved as the best. It is also necessary to conduct further study on the pavement performance of the modified asphalt mixture with different states of vulcanization.

The main objective of this study was to perform survival life analysis and life-cycle cost analysis of different patching methods and materials commonly used for winter pothole maintenance. To this end, a comprehensive testing matrix was developed that included the installation of 356 pothole patches on different types of roads using four different patching techniques with five commonly used patching materials. The patching techniques included spray injection and three types of throw and roll methods using a tamper, a truck tire, or a vibratory roller. The results of the field-testing program indicated that throw and roll with a tamper had the highest productivity, followed by throw and roll with a truck tire and throw and roll with a roller. Spray injection had the lowest productivity. The result of the classification tree model indicated that patching method is the most significant factor affecting the patching performance, followed by patching materials, traffic volume level, pothole size, and number of days to experience first snowfall after installation. In addition, the results of hazard risk analysis indicated that the patching method, materials, size of the pothole, and traffic volume level were statistically significant for the survival life of pothole patches. Survival analysis results indicated that patches installed with throw and roll with a roller and spray injection had a relatively longer survival life than that of throw and roll with a tamper or a truck tire. However, the results also depicted that the survival life of the patches installed with the latter two methods can be satisfactorily longer if a cold mix of good quality is used. The level of compaction was found to be significantly important in the survival life of hot-mix asphalt. In general, throw and roll with a tamper or a truck tire were found to be the most cost effective in both the short and long term, especially on streets with low traffic volumes. However, in the case of heavy/medium traffic volumes, spray injection and throw and roll with a roller could be more cost-effective, especially if the agencies are looking for long-lasting solutions.

Semiflexible pavement (SFP) includes asphalt mixture skeleton, cement mortar, asphalt mortar, and residual voids. The heat conduction behaviors in the SFP become very complicated. To understand the heat conduction behaviors in the SFP, the discrete element model (DEM) of SFP was first established. Then the heat conduction behaviors, temperature field distribution, and effects of residual pores on heat conduction were investigated. Results indicate that the temperature field distribution at the same pavement depth is relatively uniform, and the heat conduction mainly happens in the vertical direction. The aggregate requires more heat to rise temperature, successively followed by asphalt mortar and cement mortar. The aggregate requires longer heat conduction time, but which does not affect the whole heat transfer. Also, when there are residual pores in the SFP, the temperature at the pore top is higher and the temperature at the pore bottom is lower than that at the same pavement depth without pores due to the thermal resistance of pores, respectively. Furthermore, the larger the pore size is, the higher the temperature difference is. Finally, when the pore is closer to pavement surface, the temperature difference between pore bottom temperature and other temperature at the same pavement depth without pores becomes higher. It is proposed that the large residual pore should be avoided or decreased to reduce the distresses of SFP.

Porous asphalt concrete (PAC) has excellent performance in managing rainwater, improving groundwater quality, mitigating the heat island effect, and reducing traffic noise. However, PAC often becomes clogged with soil, sand, and other clogging materials, which attenuates its permeability performance. This paper investigated the anticlogging performance of PAC. Firstly, a clogging test of PAC was carried out, and the clogging material was aeolian sand. Then the PAC specimens were cleaned by manual brushing, vacuum pump suction, and high-pressure water cleaning after each clogging. The permeability coefficients ($k_R$) after clogging and cleaning were measured by a variable head seepage device. Next, the influence of porosity, nominal maximum grain size and cleaning method on the permeability performance of PAC under cyclic clogging–cleaning were investigated in terms of the change law of the permeability coefficient. The effect of different clogging materials on the PAC’s permeability performance also was investigated. The influence of PAC gradation parameters on the permeability performance of PAC pavement was investigated using statistical methods. The results showed that with the increase of loading times, the permeability coefficient’s values after clogging and cleaning first decreased rapidly and then stabilized gradually. The larger the porosity and nominal maximum grain size, the better was the PAC’s anti-clogging performance and the better was its effect on the permeability coefficient’s recovery. The residual rate of permeability coefficient ($\gamma$) of PAC specimens with different porosities and nominal maximum grain sizes differed significantly. The value of $\gamma$ was large for large-porosity and nominal maximum grain size PAC specimens after each cycle. The order of ranking of the cleaning effect from best to worst was high-pressure water cleaning, vacuum pump suction, and manual brushing. The order of ranking of the clogging effect was sandy soil mixture, aeolian sand, and silty soil. Among the PAC gradation parameters, the effect of porosity on PAC’s anticlogging performance was greater than that of nominal maximum grain size.