How AI Enhances Road Safety Audits Conducted Under IRC-SP:72

Road safety audits have become a critical requirement in India as road networks expand and traffic complexity increases. The Indian Roads Congress introduced IRC-SP:72 to provide structured guidance on conducting road safety audits at different project stages, from planning and design to operation and maintenance.

Today, road asset management India is evolving beyond manual checklists. With increasing expectations for accuracy, speed, and consistency, AI road safety audits are emerging as a practical enhancement to audits conducted under IRC-SP:72, without replacing the engineering judgement that the code strongly emphasises.

What IRC-SP:72 Requires from a Road Safety Audit?

IRC-SP:72 defines a road safety audit as a formal examination of a road project by an independent team to identify potential safety issues for all road users. It focuses on alignment, cross section, signage, markings, roadside features, junctions, and vulnerable road users.

While the standard outlines what must be reviewed, it does not prescribe how data should be collected at scale. This gap is where AI-based road safety assessment tools are increasingly supporting auditors in real world conditions.

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Limitations of Conventional Audit Practices

Traditional audits rely heavily on site visits, visual observation, drawings, and manual documentation. These approaches face several challenges in modern highway projects.

1. Large project lengths make repeated site visits time consuming
2. Human observation can vary between audit teams
3. Temporary safety risks may be missed between inspections

As road networks grow, these limitations directly impact the effectiveness of IRC SP 72 road safety audit implementation.

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How AI Strengthens Road Safety Audits Under IRC-SP:72?

AI does not replace auditors. Instead, it enhances their ability to observe, measure, and prioritise safety risks with greater confidence.

1. Continuous and Objective Data Collection

Using vehicle mounted cameras and sensors, Digital road safety audit tools powered by AI collect continuous visual data along the corridor. This ensures that no section is skipped due to access constraints or time limitations.

AI automatically extracts safety relevant elements such as lane widths, shoulder conditions, sight distance constraints, roadside hazards, and pedestrian facilities, directly supporting IRC-SP:72 checklist requirements.

2. Faster Identification of Safety Hazards

Through AI hazard detection on roads, issues like missing signs, faded markings, unsafe median openings, inadequate barriers, and encroachments are flagged automatically. This allows audit teams to focus on interpretation and corrective recommendations rather than manual spotting.

This capability aligns well with operational stage audits defined under IRC-SP:72.

3. Better Coverage for Vulnerable Road Users

IRC-SP:72 places strong emphasis on pedestrians, cyclists, and non motorised traffic. AI systems can detect footpaths, crossings, bus stops, and roadside activity patterns, supporting a more inclusive safety review.

When combined with traffic survey insights, auditors gain a clearer picture of how different users interact with road geometry in real conditions.

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Integration with Road Asset and Safety Workflows?

AI driven audits become even more effective when connected to broader asset data.

Through road inventory inspection, auditors can correlate safety risks with asset condition such as guardrails, lighting, and signage inventory. Similarly, pavement related risks identified during audits can be validated using pavement condition survey outputs.

This integrated approach improves decision making under road asset management India, ensuring safety improvements are prioritised alongside maintenance planning.

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Supporting Consistency Across Audit Stages

IRC-SP:72 requires audits at multiple stages including feasibility, design, construction, and operation. AI ensures consistency by applying the same detection logic across all stages.

For example, hazards identified during design stage audits can be revalidated during operational audits using fresh AI collected data, creating a closed loop safety review process.

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Role of RoadVision AI in Enhancing IRC-SP:72 Audits

RoadVision AI enables scalable, repeatable, and data rich safety audits aligned with Indian standards. Its AI driven platforms support road safety audit workflows by providing structured insights that auditors can validate and interpret.

Authorities and consultants can explore practical implementations through RoadVision AI case study examples and stay updated on best practices via the RoadVision AI blog.

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Long Term Impact on Road Safety Outcomes

When AI is systematically applied to audits conducted under IRC-SP:72, the benefits extend beyond compliance.

1. Improved detection of latent safety risks
2. Reduced dependency on subjective judgement alone
3. Better documentation for corrective action tracking

Over time, this leads to safer roads, fewer crashes, and more accountable infrastructure delivery.

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Conclusion

IRC-SP:72 provides a strong framework for road safety audits in India. By integrating AI road safety audits and Digital road safety audit tools into this framework, authorities can significantly enhance accuracy, coverage, and efficiency.

RoadVision AI is revolutionizing road infrastructure development and maintenance by leveraging cutting-edge AI in road safety and computer vision technology. Through advanced digital twin technology, the platform performs comprehensive road safety audits, enabling early detection of potholes, cracks, and other surface issues, ensuring timely repairs and improved road conditions. It also enhances traffic surveys by providing data-driven insights to address challenges like traffic congestion and optimize road usage. With a focus on building smart roads, RoadVision AI ensures full compliance with IRC Codes, empowering engineers and stakeholders to reduce costs, minimize risks, and improve the overall road safety and transportation experience.

If you are looking to modernise road safety audits while staying aligned with Indian standards, book a demo with RoadVision AI to see how intelligent safety analytics can support your audit process. Visit the contact us page to get started.

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FAQs

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Q1. Does AI replace road safety auditors under IRC-SP:72?
No. AI supports auditors by improving data collection and hazard detection while decisions remain engineer led.

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Q2. Can AI based audits be used for existing highways?
Yes. AI is particularly effective for operational stage audits where continuous monitoring is valuable.

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Q3. How does AI improve compliance with IRC-SP:72?
AI ensures consistent coverage of safety elements and helps auditors document risks more systematically.

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