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Cyclomedia's Road Surface Analysis: Fast and accurate analysis of every roadway lane

Cyclomedia's Road Surface Analysis: Fast and accurate analysis of every roadway lane

Imagine Transportation and Public Works departments no longer needing to complete cumbersome, lengthy, and confusing PCI studies to register road and pavement defects. 

Instead, visualize these inspections being completed with artificial intelligence using high resolution street level imagery and LiDAR that provides the severity, extent, and classification of each individual defect a rapid ASTM based PCI and OCI score – all automated from a workstation. This has a major impact on the efficiency of road inspection.

Benefits of Cyclomedia's Road Surface Analysis technology

  • Provides public critical data to prioritize which streets will receive pavement
  • Accurate determination of size and position
  • Training by experienced road inspectors
  • Uniform, objective and constant

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An Objective Analysis of Road Conditions

It makes perfect sense to have a computer inspect road surface damages, as 'on-site' inspections are completely subjective and take an incredible amount of time and money to perform. By training AI to detect road damages and their severity, we can move from a subjective scoring to an objective one, free from human error- this is exactly what Cyclomedia has accomplished with our RSA product.

To do this, we added the knowledge and years of experience belonging to the Arcadis road inspectors to our RSA algorithm. The algorithm was trained with the RSA data collected by the inspectors, resulting in an AI driven, single set of eyes which looks objectively at each individual road defect, year after year. The AI technology will be used to create a road inspection that is in line with the most common methodologies, such as ASTM 6433 –07 (Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys - American Society for Testing and Materials) and PASER (Pavement Surface Evaluation and Rating system ) in the US.

Accountability in respect to your pavement preservation plan

To build a successful multi-year pavement preservation plan, high-quality, multi-year datasets are needed. The RSA product can be produced after every capture done by Cyclomedia. And because the same algorithms will be scanning the same type of imagery from year to year, the data can be compared over time, providing the needed output to prove the pavement strategy is resulting in an overall improved pavement quality.The data will be transparent and can be shared with citizens to assure them that budgets are being spent in the most optimal way. 

By fixing roads that are just beginning to degrade, total pavement life is extended, thus maximizing the value of each dollar spent on the roads. Another important benefit of the pavement preservation approach is that it enables the preservation of four to ten times more streets than if resources were used to fixing the ‘bad' roads first, since the treatment cost to preserve ‘good' roads is substantially less. An overall increased PCI scoring based on high-quality data will prove the strategy is working.

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Automatic detection of road defects with road analysis

With the power of machine learning, road inspections become faster and more accurate. By using historical data, the system learns to identify different types of road defects. This makes automated inspections possible, saving time and resources. Data analysis helps to understand the current road conditions and predict future issues, which is crucial for maintaining road safety.

Road safety is a top priority for every community

ith advanced image recognition technology, every defect on the road surface can be detected accurately. This technology ensures that no defect is missed, improving the overall quality of road inspections. Digital technologies like these transform how we manage local roads.

One of the biggest advantages of using AI for road inspections is the ability to collect and analyze real-time data. This means that the condition of the roads is always up-to-date, allowing for immediate action when needed. Data collection from high-resolution images provides detailed information about each defect. This makes the process of maintaining roads more efficient and effective.

Artificial intelligence automated systems also help in reducing costs

Traditional road inspections require significant manpower and time. With AI, these processes are streamlined, resulting in lower expenses for the community. Reducing costs allows for better allocation of resources, ensuring that the most critical areas receive attention first.

Improving road safety is the ultimate goal. By using AI and machine learning, road inspections become more reliable. Historical data combined with real-time data provides a comprehensive view of road conditions. This ensures that local roads are kept in the best possible state, preventing accidents and enhancing safety for all users.

Data analysis and pavement defects

The integration of digital technologies in road inspections revolutionizes the way we maintain our roads. Automated inspections using image recognition and data analysis lead to better road safety and more efficient use of resources. By focusing on road defects, severity, and extent, we can ensure that our road surfaces are always in top condition. This improves the quality of the roads and reduces the costs associated with traditional inspection methods. With AI, we move towards a future where road conditions are monitored and maintained seamlessly.

Past Webinars: "Road Surface Analysis for Smart Cities"

Watch the recordings of our RSA Webinars to:

  • Get a high-level introduction to Cyclomedia's Road Surface Analysis product
  • Learn how our unique collaboration between industry leaders results in a transformational product for our clients
  • Learn how our RSA product can help a Smart City move towards a long term pavement preservation approach

Cyclomedia Webinars

Arcadis and Cyclomedia

Unique collaborations result in unique products. CycloMedia and Arcadis have combined their knowledge and automated the work of a road inspector through artificial intelligence. CycloMedia is responsible for the annual capturing of high resolution panoramic imagery and LiDAR point clouds. As a leading an expert in road analysis, Arcadis developed an algorithm that allows road defects to be automatically detected.

Size and position

The LiDAR point cloud of Cyclomedia is an very detailed, 3D representation of public space. With this photorealistic data source, the size and position of a road-defect can be determined exactly.

Experienced road inspectors to improve road safety

The algorithm is trained and validated by Arcadis' experienced road inspectors. These road inspectors contributed their in-depth knowledge of the common methods for classifying road defects inserted into the algorithm. This ensures a constant quality of detection of road defects.

Uniform, objective and constant

An algorithm doesn't know good days or bad days. The results of the analysis are always objective and completely uniform. Differences in interpretation of road defects do no longer occur. In addition, the analysis can be repeated annually, making a year to year comparison possible.

Budget efficiently spent in the right place

With the algorithm, road segments of 100 ft and 1000 ft can be selected and classified according to the guidelines of ASTM and PASER. This provides direct insight into which road segments should be maintained first. The available budget for road improvement will be spent where it has the biggest impact for road users.