Top 7 Mistakes Found During Road Marking Audits as per IRC SP 55

Road markings play a critical role in regulating traffic, enhancing road safety, and guiding driver behavior. The Indian Roads Congress (IRC) has laid out strict guidelines in IRC SP:55 for road marking materials, visibility, placement, and maintenance. However, audits frequently reveal non-compliance and poor execution. These lapses compromise traffic safety and cause confusion, especially on high-speed corridors.

With the rise of AI road asset management systems, detecting and rectifying these mistakes has become more precise, efficient, and scalable. In this blog, we detail the top 7 mistakes found during road marking audits as per IRC SP 55 and explain how modern pavement condition monitoring tools powered by AI help ensure standards compliance.

Explore how your agency or firm can avoid costly oversights and make road safety truly data-driven.

1. Poor Retro-Reflectivity

IRC SP:55 specifies minimum retro-reflectivity levels for road markings to ensure they remain visible at night and during rain. However, audits often find:

• Use of substandard reflective beads
• Loss of reflectivity due to wear and weather
• Absence of retro-reflectivity testing

Why it matters: Low visibility increases crash risk, especially in low-light rural or high-speed highway conditions.

How AI helps: Platforms like RoadVision AI use computer vision to continuously assess retro-reflectivity from imagery, automatically flagging fading or ineffective markings.

‍

2. Incorrect Line Width and Placement

According to IRC SP:55, longitudinal lines should generally be 150 mm wide. In practice, auditors frequently report:

• Line widths deviating from standards
• Inaccurate lane placement
• Skewed or inconsistent gaps in broken lines

Why it matters: Even slight deviations confuse drivers and lead to erratic lane discipline.

Solution with AI: Using AI-based road inventory inspection, authorities can map all pavement markings in georeferenced format, highlighting misalignments for targeted correction.

‍

3. Absence of Transverse Markings at Intersections

Transverse markings like stop lines, yield lines, and pedestrian crossings are often missing or faded at intersections.

Findings include:

• Stop lines not placed before pedestrian crossings
• Lack of hatching or boxed markings at junctions
• Use of incorrect materials or colors

AI-based audit insight: With AI road safety audits, intersections can be classified and assessed in bulk. The system flags intersections with missing or faded markings using intersection geometry detection.

‍

4. Use of Non-Durable or Non-Compliant Paint

IRC SP:55 recommends thermoplastic paint or reflective waterborne paint with specified material compositions and drying times. Yet audits reveal:

• Use of low-quality paint that fades within weeks
• Incomplete surface preparation before application
• No adhesion to thermoplastic specs

Consequences: Short paint life cycles, poor night visibility, and increased maintenance costs.

AI-powered remedy: Through pavement condition surveys, AI systems log deterioration patterns and paint types, helping agencies select better materials based on performance data.

‍

5. Inadequate Marking on Curves and Gradients

Sharp curves and gradients demand supplementary markings like chevrons, arrows, or edge lines, as per IRC SP:55. But inspections show:

• Inconsistent edge line markings
• Missing or misplaced directional arrows
• Hazardous fading on approach curves

AI-Based Monitoring Advantage: AI can scan curvature and gradient from roadway imagery, automatically checking for the presence and correctness of directional markings. This strengthens compliance verification with national standards.

‍

6. Skipped Repainting and Maintenance Cycles

Even compliant markings can fail if not repainted on schedule. IRC SP:55 suggests frequent inspection and repainting based on wear and traffic load.

Audit issues often include:

• No record of repainting frequency
• Failure to inspect post-monsoon wear
• Reactive rather than preventive maintenance

Fix with Predictive Insights: AI road asset management systems use pavement lifecycle data to forecast maintenance needs, preventing oversights and optimizing resource allocation.

‍

7. Lack of Standardized Markings Across Zones

One of the most systemic issues is the lack of consistency in markings across different regions or agencies. These include:

• Variations in colors used
• Irregular application of hazard symbols
• Non-standard hatching patterns

Why it matters: Inconsistent markings confuse inter-state drivers and reduce national compliance coherence.

How RoadVision Helps: With a national-scale digital map of road assets, powered by automated road inventory tools, agencies can benchmark markings against national norms and identify anomalies across geographies.

‍

Conclusion

Road marking audits are not just bureaucratic exercises. They are essential for saving lives, improving mobility, and maintaining trust in road infrastructure. IRC SP:55 provides a robust guideline, but compliance still lags in the field.

This is where AI-based pavement condition monitoring and road asset management can make a transformative impact. From automated audits to predictive repainting schedules, tools like RoadVision AI make it easy for authorities to monitor, inspect, and enforce compliance at scale.

RoadVision AI is transforming infrastructure development and maintenance by harnessing artificial intelligence and computer vision AI to revolutionize road safety and management. By leveraging advanced computer vision artificial intelligence and digital twin technology, the platform enables the early detection of potholes, cracks, and other road surface issues, ensuring timely repairs and better road conditions. With a mission to build smarter, safer, and more sustainable roads, RoadVision AI tackles challenges like traffic congestion and ensures full compliance with IRC Codes. By empowering engineers and stakeholders with data-driven insights, the platform reduces costs, minimizes risks, and enhances the overall transportation experience.

To learn how your agency can digitize its road marking audits and ensure IRC compliance through automation, book a demo with us.

‍

FAQs

‍

Q1. What is the main objective of IRC SP:55?

‍
IRC SP:55 outlines technical guidelines for road markings in India to enhance visibility, safety, and consistency across national and state highways.

‍

Q2. How often should road markings be repainted as per IRC guidelines?

‍
Repainting frequency depends on traffic load and weather conditions, but post-monsoon repainting is generally mandatory.

‍

Q3. Can AI detect faded or non-compliant road markings?

‍
Yes, platforms like RoadVision AI use computer vision to automatically detect and report road marking issues during surveys.

‍