NEW DELHI: The National Highways Authority of India (NHAI) has identified more than 600 stretches covering nearly 40,000 km of the national highway and expressway network for assessment of road conditions and street furniture using advanced AI-powered Dashcam Analytics Services (DAS).
As part of the exercise, Route Patrol Vehicles (RPVs) fitted with dashboard cameras will conduct comprehensive weekly surveys.
Advanced artificial intelligence and machine learning models have been deployed to automatically identify over 30 types of defects and anomalies. The initiative is seen as a significant step towards transforming the operations and maintenance of highways.
For smooth implementation of the project, states and union territories have been divided into five zones: north, central, east, west and south.
The Authority has also issued a standard operating procedure (SoP) detailing the roles and responsibilities of stakeholders, including road maintenance divisions and survey agencies, for the implementation of dashcam surveys and highway monitoring.
According to officials, the primary focus of the exercise will be pavement conditions, including detection of potholes, rutting and severe cracking. The survey will also cover road furniture, with real-time identification of damaged or faded lane markings, crash barriers and non-functional streetlights.
“Special emphasis will be put on safety of users and encroachments through monitoring for illegal median openings, unauthorised signboards, and illegal parking or encroachments…”
To ensure road safety, at least one weekly survey will also be conducted at night every month to evaluate the performance of road signages, pavement markings, road studs and highway lighting. Other critical maintenance issues such as missing drainage covers, water stagnation, vegetation growth and the condition of bus bays will also be monitored, officials said.
This newspaper had recently reported that after focusing on improving the quality of highway construction, the Ministry of Road Transport and Highways (MoRTH) has now shifted attention towards long-term maintenance and protection of highways.
In a first-of-its-kind initiative, the Ministry has launched a nationwide programme to monitor the health of national highways, under which regular state-wise reviews of road infrastructure are being undertaken.
Further, as part of the exercise, the Ministry is set to procure advanced Intelligent Pavement Assessment Vehicles (iPAVe), survey vehicles capable of collecting both structural and functional pavement condition data. According to sources, trial runs of these fully integrated high-tech vehicles are currently underway.
Road Transport and Highways Minister Nitin Gadkari recently reviewed the quality and maintenance of highways in Maharashtra, Uttar Pradesh, Tripura, Assam and Goa based on inputs received through media and social media.
On Tuesday, he also reviewed the quality and maintenance progress of highway projects covering 4,335 km in Punjab and 3,332 km in Delhi and Haryana.
During the review, the Ministry emphasised the need to accelerate on-ground execution of highway projects and ensure timely completion of works. He directed officials and contractors to strengthen coordination and maintain strict adherence to project timelines.
The Minister also underlined the need to improve riding quality and ensure seamless connectivity across key highway corridors in Punjab, Delhi and Haryana. He directed officials to prioritise high standards in construction and maintenance to provide a safer, smoother and more efficient travel experience for commuters.
Officials were also directed to undertake advance monsoon preparedness measures across all project stretches. He stressed the importance of effective drainage management, slope protection measures and swift response mechanisms to minimise disruptions during the monsoon season and ensure commuter safety.
Mr Gadkari instructed concerned agencies to remain vigilant and ensure uninterrupted traffic movement by addressing waterlogging, erosion and other weather-related challenges proactively.