Pavement Damage Research Articles

Analysis of micromechanical response to viscoelastic and plastic behaviors of asphalt mixture using a smart sensing technology

The damage evolution of asphalt pavement is intrinsically related to mechanical behaviors of asphalt mixture. Knowing the micromechanical responses of asphalt mixture is of great significance for essentially revealing the pavement damage evolution. This study aims to measure the inter-particle contact force among aggregates in laboratory tests by utilizing a Smart Aggregate, and investigate the micromechanical responses to viscoelastic and plastic behaviors of asphalt mixture in real time. Various uniaxial loading tests, including compression-recovery test, dynamic loading test, penetration test and creep test, were conducted on the asphalt mixture with Smart Aggregate inside. After that, the evolution of inter-particle contact force was comprehensively analyzed for the macroscopic mechanical behaviors in view of particle level. Results indicates that the Smart Aggregate performs well in sensing the evolution of micromechanical behaviors for asphalt mixture under external loads. The measured force along with loading direction (i.e. FSA_Z) follows well with the strain variation of asphalt mixture during the stress-controlled loading tests. The FSA_Z has a significant linear relation to the strain of asphalt mixture, and the correlation coefficients of FSA_Z amplitude with compressive strain and recoverable strain are 0.994 and 0.986, respectively. As the maximum strain amplitude of asphalt mixture is less than 0.006% under dynamic load, the FSA_Z exhibits in lower level even though the stress amplitudes are larger at lower temperature. After the local strain is more than 0.4%, FSA_Z varies with a same trend to the stress evolution of asphalt mixture when it takes a plastic deformation. Strain, which is associated to micro displacements of aggregates and change of their interactions, plays the fundamental role in transmitting the loading stress to the Smart Aggregate.

Characterization of 3D-Radar images of pavement devoid damage based on FDTD

Accurate judgement of devoid damage information by 3D-Radar is an effective way of repairing damage in nondestructive pavements. In order to systematically analyse the characteristics of devoid damage under nondestructive pavements in 3D-Radar response. In this study, the 3D-Radar response to devoid damage of different sizes, locations and moisture contents was quantified by FDTD orthorectified simulations. Data acquisition of the pre-buried devoid damage on site was carried out using 3D-Radar, compared with the orthorectified simulation results and numerical analysis. The detection effect was also verified by relying on the project. The results show that the radar wave characteristics of the devoid damage are obvious. Different colour and waveform image characteristics in B-Scan in the presence and absence of water at the location; the size of the devoid also has an impact on the image characteristics. It depends on the footprints and size of the devoid. It creates “upward-convex”, “down-concave” and straight features; the presence of the devoid characteristics in the 3D-Radar mapping will enhance the confidence of the devoid identification through field tests and engineering verification.

Physical modelling of climate-soil-infrastructure interactions of paved roadways constructed in expansive soil

Roadways founded on expansive soils are notorious for incurring damage in the months and years after construction. Soil swelling and shrinking manifest at the road surface as differential displacements of the pavement and eventually lead to linear cracks developing parallel with the direction of traffic flow. This climate-soil-infrastructure interaction occurs over daily, seasonal, and annual cycles that cause variations in moisture, temperature, relative humidity, and precipitation. Design recommendations often call for expansive soil to be compacted 1–2% wet of optimum to limit pavement damage regardless of the local climatic conditions or soil swell potential. Despite the prevalence of expansive soils found worldwide and the significant damage they cause to overlying infrastructure, very few studies appear in the literature that include field monitoring. To overcome this lack of physical data and examine the traditional design specification centrifuge modelling was undertaken to reproduce a stress-appropriate environment and control the moisture boundary conditions. These centrifuge experiments examine the effect of as-placed moisture content on the response of a two-lane paved road profile subjected to wetting–drying cycles. The centrifuge model results provide high temporal and spatial resolution displacement measurements using Digital Image Correlation. Cumulative subsurface strains are reflected at the road surface and cause detectable differential displacements of the model paved road. The relatively minor variation of initial moisture content in the three tests examined (varied from 29 to 34%) was found to have a significant impact on the hydraulic-mechanical response expressed in the isolated ground located beyond the influence of the road as well as the pavement-ground interface. The experimental results provide new insight into climate-soil-infrastructure interaction under a paved road, which would otherwise be unobservable using traditional discrete measurement techniques in the field. Interpretation of the high-density displacement measurements allowed for calculation of unique curvature / bending envelopes for the pavement under the different as-placed moisture conditions. The wet of optimum model displayed 5-times greater curvature / bending compared to the optimum and dry of optimum tests. Compacting wet of optimum may not be uniformly beneficial to limit pavement damage and construction specifications should consider local climate and swelling potential.

Investigation of the Fatigue Performance of Sustainable Asphalt Pavement

Selecting suitable materials for sustainable asphalt pavement construction can be a challenging task, particularly due to the significant issue of fatigue damage in flexible pavement. The fatigue performance of gap-graded asphalt mixes (GGCP) was assessed through four-point bending beam fatigue testing, examining the impact of incorporating 6% Calcium carbonate (CaCO3) and 2% treated palm oil fuel ash (TPOFA) on fatigue cracking. The testing was conducted at various stress levels (800, 1000, and 1200 kPa) and a temperature of 5°C. Additionally, the asphalt mixtures underwent acceleration ageing and moisture conditions, which varied during the study. The experimental findings indicated that higher stress levels resulted in a decrease in the fatigue life of asphalt mixtures due to ageing effects. Moreover, moisture conditioning was found to diminish the fatigue life of the asphalt mixture. Comparatively, the fatigue model incorporating a plateau value and fatigue life demonstrated greater accuracy when compared to previous regression models.

Settlement Characteristics of Urban Underground Comprehensive Pipe Gallery under Different Backfill Conditions

In order to solve the problem of differential settlement of pavement after the backfilling of urban underground comprehensive pipe corridors based on a pipe gallery project in Xiong’an New Area, the mechanical calculation model of the pipe gallery foundation pit backfilling process was simulated by ABAQUS, and the pavement settlement and the change of the pipe gallery model under different construction conditions were simulated and verified. The results show that many external environmental factors have an impact on pavement settlement, and methods such as increasing the compaction degree of backfill soil and the slope of the foundation pit, reducing the width of the pit floor, and controlling the vehicle load after work can avoid the pavement damage caused by uneven settlement.

Use of geothermal energy to prevent road pavement icing and damage in cold climate areas

In cold climate or alpine regions, freezing temperatures and snow can result into road icing, with consequent threat of the circulation security (Figure 1(a)). When the road surface temperature goes below zero, not only the road surface ices, but also the soil below the pavement can undergo freezing. The phenomenon of soil freezing is complex due to the multi-phase and porous nature of the soil itself. Generally speaking, as ice expands in the soil pores, the soil volume increases (of about 9%, depending on the soil porosity and water saturation). This can induce frost heaving, with consequent damage of the road pavement. In this framework, the possibility to use geothermal energy systems embedded in tunnel linings for road pavement de-icing has rarely been investigated. In such systems, the concrete tunnel lining is equipped with a circuit of pipes, in which a heat carrier fluid circulates and exchanges heat with the ground. As the rock or soil around the tunnel is generally hotter than the external air temperature, heat is extracted from the rock or soil to the fluid, transported through the pipes circuit outside the tunnel, and used to de-ice the pavement road.
 The objective of this study is to go a step forward in the investigation of this innovative application, for both road de-icing and prevention of frost heave. A portion of a geothermally activated tunnel and its connection to a road pipe circuit was simulated numerically (Figure 1 (b)). Appropriate climatic conditions were considered as boundary conditions at the surface level and inside the tunnel, according to available data. The efficiency of the technology was investigated under different climatic and exploitation scenarios. Figure 1 (c) shows as an example the thermal field obtained after the activation of the geothermal plant. The evolution of temperature on the road pavement surface and at the road pipes depth (30 cm from the road pavement surface) are presented on Figure 2 (a), together with the evolution of the external air and tunnel temperature, imposed as boundary conditions according to the monitored climatic conditions in the city of Oslo [1].
 The geothermal system was activated after two years of simulation, by changing the fluid pipes velocity from 0 (non active system) to 0.9 m/s (purple curve on the right axis on Figure 2 (a)). The results show that the road temperature increases thanks to the activation of the system (i.e. when the fluid pipes velocity is imposed to 0.9 m/s).
 Furthermore, a recently developed thermo-hydro-mechanical constitutive model for frozen soils [2] was used to quantify the soil heave due to freezing, with and without the activation of the geothermal system. For this purpose, a similar numerical model has been developped where a column of saturated soil below the road and the tunnel were modelled. The phreatic water table is at the ground surface level and gravity as well as the geostatic stress conditions are considered. The soil is a clay with a low hydraulic conductivity of Kw=4.1×10-10 m/s and a thermal conductivity of Γ=2.35 W/m/K. The other soil properties are: soil stiffness E=100 MPa, Poisson’s ratio ν=0.3, porosity n=0.25, solid grain thermal volumetric expansion coefficient αs=3.4×10-4 K-1. The same soil surface climatic conditions used in the first part were applied. The temperature evolution obtained in the road from the previously mentioned analyses (Figure 2 (a)) was imposed to reproduce the effect of the geothermal activation on the road behaviour. Furthermore, the soil surface is free of stress to study the soil swelling and settlement. The bottom limit of the soil column is hydraulically drained and allows heat flux (at constant liquid pressure and temperature). The lateral far field boundaries are thermally adiabatic, hydraulically impervious, and with oedometric conditions. The results were firstly compared with the case without geothermal activation to quantify the effects in terms of road heave and settlement (Figure 2 (b)). Swelling and settlement are due to thermal expansion and compression of the soil under positive temperature (T>0°C) and to frost heave and thaw settlement under negative temperature (T<0°C). The liquid pressure at the road surface is also depicted (Figure 2 (b)). These results and comparisions allowed understanding the performance of the technology in reducing road mechanical damage induced by freezing.

Vehicle-Mounted Pavement Health Monitoring System Based on a Spring-Guide-Assisted Triboelectric Sensor.

The present pavement health monitoring is limited by a professional staff patrol. Herein, a vehicle-mounted pavement health monitoring system (VPHMS) based on a spring-guide-assisted triboelectric sensor (S-TES) is proposed, which uses the vibration generated by vehicles passing through uneven pavements to monitor the pavement damage. The VPHMS consists of S-TES, the integration module, and the terminal display module. The designed S-TES has high stability and can achieve a high linear vibration amplitude measurement within 90 mm. Moreover, the integration module is used to process signals and transmit wireless data transmission. The terminal display module is used to receive signals and display the measurement results on the screen. When a vehicle equipped with VPHMS is driven over uneven pavements, the system can accurately monitor the potholes and upheavals on the pavement in real time. This work has significant application value in fields such as pavement health monitoring and intelligent transportation.

Improved YOLOv5-Based Real-Time Road Pavement Damage Detection in Road Infrastructure Management

Deep learning has enabled a straightforward, convenient method of road pavement infrastructure management that facilitates a secure, cost-effective, and efficient transportation network. Manual road pavement inspection is time-consuming and dangerous, making timely road repair difficult. This research showcases You Only Look Once version 5 (YOLOv5), the most commonly employed object detection model trained on the latest benchmark Road Damage Dataset, Road Damage Detection 2022 (RDD 2022). The RDD 2022 dataset includes four common types of road pavement damage, namely vertical cracks, horizontal cracks, alligator cracks, and potholes. This paper presents an improved deep neural network model based on YOLOv5 for real-time road pavement damage detection in photographic representations of outdoor road surfaces, making it an indispensable tool for efficient, real-time, and cost-effective road infrastructure management. The YOLOv5 model has been modified to incorporate several techniques that improve its accuracy and generalization performance. These techniques include the Efficient Channel Attention module (ECA-Net), label smoothing, the K-means++ algorithm, Focal Loss, and an additional prediction layer. In addition, a 1.9% improvement in mean average precision (mAP) and a 1.29% increase in F1-Score were attained by the model in comparison to YOLOv5s, with an increment of 1.1 million parameters. Moreover, a 0.11% improvement in mAP and 0.05% improvement in F1 score was achieved by the proposed model compared to YOLOv8s while having 3 million fewer parameters and 12 gigabytes fewer Giga Floating Point Operation per Second (GFlops).

Pavement damage identification and evaluation in UAV-captured images using gray level co-occurrence matrix and cloud model

In the road structure, the pavement is in direct contact with the wheel, and its daily maintenance is very important. Traditional pavement damage detection relies heavily on manual work, which is inefficient and unsafe. In this paper, the unmanned aerial vehicle (UAV) is used to pick up the pavement damage image, and then combine the gray level co-occurrence matrix (GLCM) algorithm and the cloud model theory to construct a damage identification and evaluation model. In the experimental stage, a road in Chongqing, China is selected to verify the model. The results show that the accuracy of the proposed theoretical model in pavement damage identification exceeds 82.5%, and the performance is good. In addition, in the evaluation case, the lightest damage is the crack, and the most serious is the rut. For the hollow and block repair, the texture feature cloud droplet membership ratio of the two is mostly between 0.5 and 0.6, indicating that the damage state of the pavement is evolving from slight to moderate.

Influence of Deicer on Water Stability of Asphalt Mixture under Freeze–Thaw Cycle

In seasonal frozen soil areas, the repeated freeze–thaw cycle of internal moisture in asphalt mixture in winter and spring will accelerate the peeling of asphalt film and aggravate the water damage of asphalt pavement. It is of great significance to carry out the attenuation law of mechanical properties of asphalt mixture under freeze–thaw cycles to prevent and reduce the economic losses caused by water damage to asphalt pavement. This study will investigate the impact of deicer application on the water stability of asphalt mixtures within the climatic conditions prevalent in Northwest China. Specifically, freeze–thaw cycle tests were administered to two types of dense-graded asphalt mixtures under three distinct deicer solutions and three disparate low-temperature environments. The Marshall water immersion test and freeze–thaw splitting test were employed to evaluate the water stability of asphalt mixtures subject to multiple factors, and the relative importance of each factor was statistically analyzed using the acquired data. Results demonstrated that AC-13 and AC-16 asphalt mixtures (AC is asphalt-concrete, which is asphalt concrete, and 13 or 16 represents the maximum particle size of aggregate (13 mm or 16 mm)), saturated in 15% CH4N2O, 20% NaCl, and 20% CH2CH3OH solutions, underwent a varying number of freezing–thawing cycles (0, 5, 10, 15, 20, 25, and 30) at temperatures of −5 °C, −15 °C, and −25 °C, respectively, displayed a discernible decline in their residual stability MS0 and freeze–thaw splitting tensile strength ratio TSR. This decline was particularly marked when temperatures dropped below the solution’s freezing point. Disregarding the fixed factors of weather variation (different low-temperature environments) and road service duration (number of freezing–thawing cycles), the aggregate grading imposed a more pronounced influence on asphalt mixture water stability than the presence of deicers.

Automated detection of airfield pavement damages: an efficient light-weight algorithm

ABSTRACT Fast and accurate detection of airfield pavement damage is crucial to airport flight safety and airfield pavement maintenance. An efficient and lightweight detection algorithm that can be embedded into the mobile detection device has been in urgent demand. However, traditional Convolutional Neural Networks (CNNs) usually generate redundant feature maps during feature extraction or use extra operations during feature fusion to gain better performance, which greatly challenges the efficiency of the algorithm. We approached this issue by proposing an accurate and efficient detection algorithm, the YOLOv5-APD. The algorithm improves the model performance in two ways: Speeding up training and inferencing by using cheaper operations during feature extraction; Reducing the model complexity by removing redundant nodes during feature fusion. We verified the detection performance of YOLOv5-APD on a self-made dataset and compared it with the other state-of-the-art (SOTA) models. Then ablation experiments were carried out to investigate the effects of the proposed model design and the impact of image augmentation. Results showed that the proposed YOLOv5-APD model outperformed the SOTA algorithms in model performance and efficiency, which attained the optimal performance mean average precision (mAP) of 0.924. The proposed model also achieved the fastest inference speed of 142 frame-per-second (FPS), with a model footprint of 8.3 G FLOPs and 8 MB Parameters.

Modeling roadway temperatures for wildfire evacuation and assessment of pavement damage

Wildfires can cause enormous loss of assets and human lives, and thus, timely evacuation from the wildfire zone is critical to saving lives. Understanding evacuation route conditions, including traffic and temperature data, is imperative for safe evacuation. This study modeled the temperature conditions of an evacuation roadway within a wildfire zone, using the 2018 Camp Fire in Butte County, California as an experiment. The numerical modeling program, FlamMap, was used in this study to analyze the temperature conditions of an evacuation route. The results show that the temperature of the evacuation roadway increased quickly in a matter of a few hours. The change of roadways temperatures ranged from 3°C to 297°C within five hours after ignition, depending on the specific location along the roadway and other conditions. The results from this study can be used to understand temperature conditions for effective evacuation and to estimate roadway damage as well.

A step toward improving management practices for airfield pavement infrastructures: a mechanistic-based analysis approach

Conventional performance indicators commonly used to evaluate airfield pavement infrastructures focus on surface condition assessment. However, the structural soundness of pavements remains a key element in determining the best intervention measures. Methods used worldwide to design and evaluate flexible airfield pavements are often based on the Multi-Layered Elastic Theory (MLET). The Federal Aviation Administration (FAA) also applies MLET to analyse data collected primarily with on-site Non-Destructive Testing (NDT). However, material behaviour is not always aligned with MLET assumptions. In this study, pavement analysis results are investigated from a mechanistic view considering, in particular, the viscoelastic properties of Asphalt Concrete (AC). The analysis is performed using NDT and coring data collected in-situ from a runway considering variable aircraft loading and moving speeds. Based on the response status at both critical locations of a flexible pavement plus its surface, it is observed that MLET appears to be less conservative at normal operating speeds, where higher pavement damage is expected. In addition, an integration potential of viscoelastic strains and NDT data is shown, which can accelerate the pavement evaluation process. It is expected that the presented approach can provide a framework for improving airfield pavement management practices.

Real-time identification of asphalt mixture segregation during paving process using digital imaging technique and Four-side static moment

The uniformity of the asphalt mixture is severely affected by aggregate segregation during the paving process, and there are many studies that indicate that segregation may lead to early pavement damage. This study aims to develop a real-time asphalt mixture segregation identification algorithm during paving process based on digital imaging technique and the static moment method. Static moments of the aggregate particles relative to the four boundaries of the image were calculated as an evaluation parameter, and the dispersion coefficient between the static moment of segregated asphalt mixture and the value of uniform asphalt mixture was calculated to quantify the degree of segregation. The algorithm was applied in a filed construction project in Yunnan, China. Comparing the result from the proposed algorithm with the sand patch test shows that the proposed algorithm is capable of detecting the segregation of an asphalt mixture in real-time and that it is accurate in identifying the degree of segregation. In addition, the proposed algorithm is more accurate than the sand patch test for areas where the gradation meets the standard but the distribution of the aggregate particles is not uniform.

Assessment of the Effect of Different Loading Combinations Due to Truck Platooning and Autonomous Vehicles on the Performance of Asphalt Pavement

Autonomous vehicles and truck platooning have become the future in the transportation field. This new strategy has many benefits because it lowers fuel consumption and CO2 emissions, improves safety, optimizes transport by using roads more effectively, and reduces traffic congestion. In this research, the effect of the controlled positioning of autonomous and non-autonomous truck loadings on the long-term performance of pavement was estimated using different variables such as climate, uniform wandering values of distance between trucks, and percentage of autonomous trucks by using MEPDG/AASHTOWare Pavement ME Design software. This was achieved by first computing the strain and stress of the different loading combinations, resulting in the computation of the failures in the pavement infrastructure and the pavement thickness needed to support each combination. The second part of the research consisted of designing a platoon strategy that was developed for a series of autonomous and connected trucks such that the lateral position of the trucks and the spacing between them could be explicitly optimized to minimize flexible pavement damage. The findings revealed that a small percentage of autonomous trucks can be beneficial to pavement life and that truck platooning following a well-studied skeleton can open a whole new world of pavement design. This can be revolutionary in changing roads around the world to improve traffic and infrastructure.

Simulating floodwater movement in pavements for developing post-flooding time-depth-damage functions

Flooding has caused severe damage to civil infrastructure worldwide. Roadway pavements are one of the infrastructures most affected by flooding, however, quantification of post-flooding pavement damage has not received attention until recently. There remains a gap to advance knowledge on how floodwater moves inside pavements and, consequently, how it will impact post-flooding pavement damage. This study adopted finite element seepage modeling to observe floodwater movement in three different pavements, each under three flood scenarios. Laboratory testing is conducted to validate the accuracy of the model. It is concluded that both the finite element seepage modeling and laboratory testing show similar post-flooding weakening and recovery behavior in pavements. The recovery phase is much longer than the weakening phase, due to the hysteretic nature of soil moisture related to suction. The base layer loses stiffness drastically during the weakening phase, more than any studied subgrade materials. The improved understanding reported here can enhance the development of time-depth-damage functions for post-flooding pavements. It will enable the quantification of post-flooding damage and thus facilitate estimation of flood induced economic losses in practices.

Preparation and characterization of phase change capsules containing waste cooking oil for asphalt binder thermoregulation

The green utilization of waste is of great significance to the sustainable development of human society. In this work, a new kind of capsule with the phase change heat storage function was prepared using waxy components extracted from waste cooking oil (WCO) as core material for the thermoregulation of asphalt binder. The differences in waxy components before and after hydrolysis treatment were studied including functional groups, phase transition temperature, and phase transition enthalpy. Meanwhile, the surface morphology, thermodynamic properties, and mechanical properties of the phase change capsules (PCCs) were also characterized comprehensively. Additionally, the effect of PCCs on asphalt thermoregulation was also examined in the laboratory. The results indicate that the waxy components after hydrolysis treatment are more suitable for asphalt binder thermoregulation in terms of the phase transition temperature, phase transition enthalpy, and thermal stability. According to the results of differential scanning calorimeter and thermogravimetric experiments, it can be calculated that the ratio of wall material and core material in PCCs is about 1:1, which endows the capsule with excellent heat storage properties (125 J/g), mechanical properties (>13 N), and thermal stability (>190 ℃). With the help of the temperature sensor, it is found that PCCs can delay the change rate of asphalt temperature with the environment by undergoing a phase transition to mitigate the damage of asphalt pavement in extremely hot climates. However, the performance of PCCs in asphalt mixtures still needs to be further explored. Overall, the findings of this research can further promote the green utilization of WCO and the functionalization of construction and building materials.

Effects of Liquid Polymers on the Strength and Freezing-Thawing Properties of Bentonite and Kaolin Clays: A Comparative Study for Cold Climates

Clay soils can exhibit swelling and settlement behaviour when interacted with water. The clays located in road infrastructure can damage the road pavement and cause cracks because of swelling and/or settlement of clays. The freezing-thawing processes of clay soils can increase the damages of pavement. Additionally, the strength losses can occur. Weak soils can be improved using various soil improvement techniques with or without additives. In this study, liquid polymers (polyurethane, epoxy resin, and styrene acrylic) were combined with clays in various amounts (5 wt.%, 10 wt.%, 15 wt.%, and 20 wt.%) to improve the strength and investigate the freezing-thawing behaviour of high-plasticity bentonite and low-plasticity kaolin clay. Unconfined compression tests and freezing-thawing cycles were performed on the samples with additives that were cured for 1 and 7 days. As a result, it was observed that polyurethane, epoxy resin, and styrene acrylic additives had positive effects on both the unconfined compressive and the post freezing-thawing unconfined compressive strengths of low and high plasticity clays in cold climates.

The ecosystem disservices of trees on sidewalks: A study based on a municipality urban tree inventory in Central Italy

Urban green infrastructure, including street trees, plays a key role in providing ecosystem services to urban residents. However, to fully understand the effective role of trees in the urban context, it is also necessary to evaluate the disservices that they can produce in the development of their functions if not managed in an adequate and integrated way. This contribution aims to demonstrate an approach to assess three disservices (pavement damage, aesthetic damage, likelihood of tree failure) of street trees at the municipal level, starting from the existing municipal tree inventory. In this case study, from the street tree population, a sample of approximately 5% of the trees was drawn by stratified random sampling, where the strata were composed of groups of tree species. In particular, a sampling scheme is adapted in which the probability to select a tree in the sample is greater for bigger trees, under the assumption that the bigger the trees the greater are the disservices caused. In this way, a greater precision of the estimates of the considered disservices for the population of urban trees is expected. The results show a high variability of disservices provision among species groups. The results also confirmed a positive correlation between the considered disservices and tree diameter at breast height, while other tree attributes such as total height and crown diameter were found to be positively related only to pavement damages. Finally, severe pruning can lead to a high level of the aesthetic and functional disservices even for shorter and younger street trees.

Road potholes detection from MLS point clouds

The extraction of pavement damage information is one of the major difficulties in the application research of mobile laser scanning point cloud data. To address the problem of inaccurate detection results by using only relative distance to detect potholes, this paper proposes a novel pothole detection method that combines directed distance and skewed distribution. Firstly, the rapid positioning of the pothole is realized by the directed distance, which is calculated from the points and the local fitted plane. And monomerization and denoising of potential potholes are achieved by density clustering. Then, the new accurate plane is fitted by the surrounding pavement points of the potential pothole to obtain accurate directed distances. The negative skewed distribution of the directed distance histogram and the skewness coefficient are used for the accurate determination of the pothole. Finally, the three-dimensional geometric features of the pothole are extracted. Experiments were carried out on a road with poor road conditions. The experimental results validated the effectiveness and practicality of the proposed method. It can achieve automatic detection of potholes with different shapes and deformation degrees, and has effectively improved the efficiency of automatic road inspection.