Ensuring Skid Resistance and Riding Quality as per IRC and How AI Can Verify It

Maintaining safe, durable, and comfortable roads is one of the top priorities for modern road asset management in India. According to the Indian Roads Congress (IRC), two of the most critical parameters that directly affect road safety and user comfort are skid resistance and riding quality. Both are central to assessing pavement performance and ensuring compliance with national standards.

Today, technologies like AI roadway inspection systems, and automated skid resistance testing AI are revolutionizing the way engineers and authorities verify these parameters. Backed by predictive analysis and automation, the best digital tools now make it possible to ensure compliance with IRC guidelines while improving efficiency and transparency.

Understanding Skid Resistance as per IRC

Skid resistance is the measure of a pavement’s ability to prevent vehicles from slipping or skidding under wet or dry conditions. IRC specifies that minimum levels of skid resistance must be maintained for highways, expressways, and urban roads to reduce accidents. The IRC recognizes the British Pendulum Number (BPN), sideway force tests, and other modern methods for measuring skid resistance.

Loss of skid resistance often occurs due to polishing of aggregates, surface wear, or contamination. Maintaining it is crucial for braking distance, cornering stability, and overall traffic safety.

AI-driven monitoring solutions can continuously measure and flag sections where skid resistance drops below IRC limits. Through road safety audits powered by AI, agencies can act before these deficiencies lead to crashes.

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Riding Quality Standards as per IRC

The riding quality of a pavement reflects how smooth and comfortable it feels for road users. According to IRC guidelines, this is measured by the International Roughness Index (IRI) or Bump Integrator Tests.

For highways and national roads, IRC prescribes specific maximum roughness values. For example, well-maintained highways should maintain an IRI value below 2.5 to 3.0 m/km depending on the road type. Exceeding these values leads to discomfort, increased vehicle operating costs, and safety concerns.

Digital monitoring with AI roadway inspection systems ensures continuous tracking of riding quality. Instead of periodic manual surveys, agencies can now deploy AI sensors and vision-based technologies for automated IRI measurement, aligned with IRC standards.

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Role of AI in Pavement Testing and Monitoring

Traditional pavement evaluation methods are labor-intensive and sometimes inconsistent. AI-powered technologies now offer:

1. Automated Skid Resistance Testing AI – Using digital vision and machine learning models, skid resistance can be measured across long stretches quickly, ensuring compliance with IRC thresholds.
   
   
2. AI Pavement Testing – Road surface images, LIDAR scans, and accelerometer-based inputs are analyzed in real time for cracks, rutting, roughness, and texture.
   
   
3. Predictive Maintenance – AI can forecast when skid resistance or riding quality may drop below IRC standards, enabling preventive maintenance.
   
   
4. AI for Road Safety Audit – Intelligent systems help conduct accurate, large-scale road safety audits that combine skid resistance and riding quality metrics with traffic data.
   
   

By integrating these methods into national monitoring programs, India can significantly reduce accident risks and extend pavement lifespans.

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Benefits for Road Agencies and Urban Planners

1. Accuracy and Compliance – Automated systems minimize human error in measuring skid resistance and riding quality.
   
   
2. Faster Data Collection – AI-powered traffic surveys and pavement scans cover large networks within a fraction of the time required by manual surveys.
   
   
3. Cost Efficiency – Predictive analysis helps allocate budgets better by addressing issues before they become major failures.
   
   
4. Transparency – Digital records generated by AI monitoring systems make compliance with IRC standards easy to track and verify.
   
   

Why RoadVision AI is Leading the Future?

As the best AI road asset management company in India, RoadVision AI offers a complete suite of intelligent solutions. 

Through proven case studies and industry insights shared via our blog, we showcase how AI transforms roadway safety, quality, and compliance in India.

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Conclusion

Ensuring skid resistance and riding quality as per IRC is not optional. These are vital benchmarks that directly affect road safety, comfort, and cost-effectiveness. With the rise of AI-based pavement testing, AI roadway inspection systems, and automated skid resistance testing AI, agencies in India now have the tools to not only meet but exceed IRC compliance standards.

To transform your road monitoring and safety compliance with AI-powered solutions, book a demo with us today.

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FAQs

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Q1. What is the minimum skid resistance requirement as per IRC?
IRC requires pavements to maintain adequate skid resistance levels using standard tests like BPN to ensure vehicle safety under wet and dry conditions.

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Q2. How does the IRC measure the riding quality of roads?
Riding quality is measured using the International Roughness Index (IRI) or Bump Integrator tests, with defined maximum permissible values depending on road type.

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Q3. Can AI replace traditional skid resistance and riding quality tests?
AI does not replace but enhances traditional methods, offering automated, large-scale, and real-time verification aligned with IRC standards.

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