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Every day, whether commuting or traveling for leisure, we encounter potholes, cracks, rutting, and other pavement issues. These are all manifestations of pavement distress.
What many people don’t realize is that pavement distress is not only a matter of driving comfort — it is a hidden threat to traffic safety, accelerates road deterioration, and significantly increases maintenance costs.
Today, let’s first take a closer look at what pavement distress really is, and then explore how GreenValley International is addressing the challenges of pavement distress detection with advanced digital technologies.
What Is Pavement Distress?
Pavement distress refers to various forms of damage, deformation, or functional degradation of road surfaces and related structures caused by environmental conditions, traffic loads, and material aging. It is not a single issue, but a collection of different distress types, commonly including:
• Cracking
Typical forms include alligator cracking, longitudinal cracks parallel to the road centerline, transverse cracks perpendicular to traffic flow, and edge cracks along pavement edges — all clear indicators of structural deterioration.
• Deformation
Distresses such as rutting caused by long-term traffic loading, uplift or heaving, waviness, and shoving severely affect ride comfort and vehicle stability.
• Potholes and Depressions
Material loss leading to potholes or ill-defined depressions is a major cause of tire blowouts and vehicle damage.
• Other Distresses
Bleeding, surface weathering, raveling, and failures in repaired areas also fall within the scope of pavement distress, gradually reducing pavement serviceability.
Although these distresses are common, they pose serious risks. Small cracks can expand into potholes due to water infiltration and traffic loading; deep rutting may cause vehicle deviation; potholes increase the likelihood of tire damage and rear-end collisions.
Traditional manual inspections are inefficient (only 5–10 km per day), labor-intensive, and risky. Conventional equipment often lacks sufficient accuracy or requires complex post-processing, making timely and comprehensive detection extremely difficult.
The “Hardware + Software” Golden Combination
To address these challenges, GreenValley introduces a revolutionary solution for pavement distress detection — the powerful combination of LiMobile M2 Ultra mobile mapping system and LiDAR360MLS post-processing software.
LiMobile M2 Ultra
As the core carrier of vehicle-based mobile mapping technology, LiMobile M2 Ultra integrates three key sensors into a fully synchronized, all-in-one data acquisition system:
• High-Precision LiDAR
With million-point-level density and millimeter-level ranging accuracy, LiMobile M2 Ultra precisely captures pavement 3D geometry. Even subtle cracks and deformations are clearly detected, providing a solid data foundation for distress analysis.
• Panoramic Camera
360° panoramic imagery captures surrounding road environments and is spatially linked to pavement distresses, providing intuitive visual evidence to support maintenance decisions.
• Pavement Camera
Optimized specifically for pavement scenarios, the high-resolution pavement camera accurately captures surface textures, cracks, patches, and repair details. Combined with LiDAR data, it enables robust point cloud + imagery dual validation.
The system supports flexible vehicle-mounted deployment and requires no road closure. Data collection can be completed at normal driving speeds, dramatically improving inspection efficiency.
While traditional manual inspections cover only 5–10 km per day, LiMobile M2 Ultra can inspect over 100 km per day, with no need for personnel to leave the vehicle — completely eliminating on-site safety risks.
LiDAR360MLS
LiDAR360MLS has been upgraded with advanced pavement distress detection algorithms based on dual-source data fusion of point clouds and imagery, supporting both automatic extraction and manual annotation for maximum efficiency and accuracy.
Its key advantage lies in the ability to automatically detect common pavement distresses such as rutting, cracking, and potholes without frame-by-frame manual labeling, significantly reducing labor costs.
At the same time, interactive manual editing allows users to refine and supplement detection results, ensuring high-precision outputs for professional applications.
Dual-Source Fusion for Diverse Scenarios
The upgraded algorithms fully leverage the complementary strengths of point clouds and imagery:
Point cloud data ensures high 3D spatial accuracy, capturing distress depth and geometric characteristics.
Image data provides rich texture information, enhancing surface-level distress identification.
Together, they form a complete 3D + 2D closed-loop detection workflow.
Trained on large-scale real-world road datasets, the algorithms demonstrate strong adaptability to varying lighting conditions (strong or weak illumination) and different pavement materials such as asphalt, delivering highly reliable results for downstream maintenance decisions.
Flexible Customization and Efficient Decision Conversion
LiDAR360MLS allows users to train pavement distress extraction models using their own imagery datasets, flexibly adapting to highways, urban roads, and other customized scenarios. Based on detection results, the system automatically calculates key parameters such as distress area, depth, and length, and accurately computes the Pavement Condition Index (PCI) according to industry standards (range 0–100, with 100 representing optimal pavement condition). Manual refinements can be incorporated to further improve accuracy, and standardized inspection reports are generated automatically. These outputs seamlessly integrate with road maintenance management systems, truly enabling “data acquisition to decision-making” in one workflow.
LiDAR360MLS allows users to train pavement distress extraction models using their own imagery datasets, flexibly adapting to highways, urban roads, and other customized scenarios. Based on detection results, the system automatically calculates key parameters such as distress area, depth, and length, and accurately computes the Pavement Condition Index (PCI) according to industry standards (range 0–100, with 100 representing optimal pavement condition). Manual refinements can be incorporated to further improve accuracy, and standardized inspection reports are generated automatically. These outputs seamlessly integrate with road maintenance management systems, truly enabling “data acquisition to decision-making” in one workflow.
Full-Cycle Coverage for Digital Road Maintenance
From urban arterials and local streets to expressways and national, provincial, and county roads, the combination of LiMobile M2 Ultra and LiDAR360MLS supports a wide range of applications:
Routine inspections: Efficient monitoring of pavement health and early-stage distress detection
Maintenance evaluation: Accurate distress data to guide rehabilitation and repair planning
Project acceptance: Objective quality assessment for newly built or reconstructed roads
Emergency inspection: Rapid damage assessment after disasters such as earthquakes or heavy rainfall
By centering on vehicle-based mobile mapping technology and integrating hardware data acquisition with intelligent software analytics, GreenValley International breaks the efficiency and accuracy limitations of traditional pavement distress detection. This solution drives the transition from reactive repairs to proactive prevention, empowering the digital transformation of road infrastructure management.
Looking for a high-efficiency, high-precision pavement distress detection solution?
Contact us to explore more technical details and real-world application cases.