India’s road network—spanning national highways, state highways, urban corridors, and rural connectivity routes—is the backbone of the country’s economic and social mobility. However, bituminous pavements face constant stress from heavy traffic, monsoon cycles, oxidation, and environmental wear. Without a structured maintenance framework, even high-quality roads can deteriorate rapidly, leading to safety hazards and higher rehabilitation costs.
To address this challenge, engineers rely on IRC 67 maintenance guidelines that provide scientific procedures for maintaining bituminous roads effectively. As infrastructure experts often say, “A road ignored today becomes a repair bill tomorrow.” Modern digital solutions such as RoadVision AI further support these practices by enabling AI-powered road condition monitoring systems.
Road maintenance is not simply a routine engineering activity—it is a strategic investment that protects infrastructure assets and public safety.
Consistent maintenance practices help to:
Slow pavement deterioration
Extend the functional service life of roads
Reduce vehicle operating costs (VOC)
Improve road safety by preventing potholes and skidding surfaces
Minimise long-term rehabilitation expenditure
Modern AI-driven pavement condition intelligence tools help agencies detect early signs of deterioration so maintenance actions can be scheduled according to IRC recommendations.
IRC 67—commonly referenced through IRC 82-2015 guidelines—defines structured maintenance practices for bituminous pavements. These practices are organised into three major maintenance categories.
Routine maintenance activities ensure that roads remain safe and operational on a daily basis.
Typical activities include:
Crack sealing
Pothole patching
Cleaning drainage and pavement surfaces
Repainting road markings
Automated AI-based road damage detection systems allow engineers to identify these defects quickly across long road corridors.
Preventive maintenance slows down pavement deterioration before structural damage occurs.
Common treatments include:
Fog sealing
Slurry sealing
Microsurfacing
Rejuvenation sprays
These treatments restore surface quality while delaying the need for costly overlays or reconstruction.
Periodic maintenance is scheduled based on pavement age, traffic loading, and surface condition.
Typical treatments include:
Renewal coats
Thin bituminous overlays
Mill-and-replace resurfacing operations
Traffic insights obtained from AI-enabled roadside asset monitoring systems help infrastructure agencies prioritise high-traffic corridors for periodic maintenance.
IRC 67 categorises pavement distress types and recommends specific treatments for each.
Hairline cracks – Fog seal or rejuvenator
Alligator cracking – Full-depth repair and overlay
Longitudinal cracks – Rubberised bitumen sealing
Reflection cracks – Stress-absorbing membrane layers (SAM/SAMI)
Bleeding – Sand blotting or surface milling
Slippery surfaces – Microsurfacing or anti-skid treatments
Hungry surfaces – Fog seal or slurry treatment
Rutting – Premix patching followed by compaction
Shoving or corrugation – Scarification and resurfacing
Depressions – Open-graded patching and leveling
Ravelling – Slurry sealing or surface dressing
Potholes – Cold mix or hot mix patching with proper edge sealing
Advanced AI-powered road safety inspection platforms help detect such pavement defects early, improving maintenance accuracy.
IRC 67 recommends specific materials and equipment for effective maintenance.
Common materials include:
Bituminous emulsions
VG-30 or VG-40 grade binders
Cold patch mixtures
Reclaimed asphalt pavement (RAP) blends
Typical equipment includes:
Pavement cutters
Portable premix plants
Rollers and compactors
Sprayers for sealing operations
Safety protocols must also be followed during maintenance operations, including traffic cones, barricades, warning signage, and reflective safety markings.
Modern road maintenance increasingly relies on intelligent technologies to improve inspection speed and accuracy.
Computer vision systems automatically detect:
Longitudinal cracks
Alligator cracks
Rutting and depressions
Potholes with severity classification
These insights allow agencies to align maintenance plans with IRC-defined distress categories.
RoadVision AI generates condition analytics such as:
Pavement Condition Index (PCI)
Severity mapping of defects
Treatment recommendations aligned with IRC maintenance strategies
Traffic analysis helps identify roads exposed to heavy axle loads, allowing preventive treatments to be scheduled before structural deterioration occurs.
RoadVision AI builds digital twins of road corridors, enabling engineers to monitor pavement deterioration patterns and plan long-term maintenance strategies using AI-powered road monitoring platforms.
Although IRC 67 provides clear guidelines, implementation across large road networks still faces several challenges.
Manual inspection techniques vary widely between agencies and contractors.
Funding often prioritises reactive repairs instead of proactive treatments.
Heavy rainfall accelerates cracking, potholes, and surface disintegration.
Maintenance records from different agencies may lack standardisation.
Precision maintenance operations require trained technicians and engineers.
Digital platforms like AI-driven pavement analytics systems help standardise inspections and improve decision-making.
IRC 67 provides the scientific framework for maintaining India’s bituminous pavements effectively. However, guidelines alone cannot guarantee results—consistent implementation and accurate condition data are equally important.
As traffic volumes increase and infrastructure ages, the need for proactive, data-driven maintenance becomes more critical than ever. By integrating AI-powered inspections, digital twins, and automated condition analysis through RoadVision AI, road agencies can shift from reactive repairs to predictive maintenance strategies.
The outcome is simple: longer-lasting roads, lower maintenance costs, and safer journeys for millions of road users across the country.
IRC Code 67 sets the guidelines for maintaining bituminous road surfaces through visual and technical methods. It is widely used by engineers and platforms like RoadVision AI for road inspection.
RoadVision AI enables automated crack detection, surface analysis, and distress classification in line with IRC 67 guidelines, helping road agencies make informed decisions.
IRC Code 67 recommends cold/hot mix patching, cleaning, and sealing edges. RoadVision AI helps pre-identify potholes with severity ratings for prioritization.
The Autonomous Road Engineer
AI-powered road condition monitoring, asset management, & infrastructure intelligence helping agencies move from reactive maintenance to predictive road management.
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