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India Deploys Artificial Intelligence for Road Safety

The Minister of Road Transport and Highways, Nitin Gadkari, recently announced that he plans to put artificial intelligence (AI)-based technology in the government system to improve mobility. He identified several priority areas for AI applications, including forensic post-crash investigations, the pattern of accidents due to black spots, fatigue indicators, sleep detectors, and advanced vehicle collision avoidance systems. AI reduces the need for human interference in road safety systems, making them more efficient and effective.

In a recent statement, the Minister said that AI integration in road safety is the “need of the hour” for the country. Road safety is a major challenge for India, roads fall witness to several road rule violations and negligence, that can cause minor and major accidents. A strong surveillance policy is significant in maintaining road safety. India records about 500,000 road accidents every year, with over 150,000 deaths. These statistics are one of the highest across the world. According to government data, 35% of all road accidents and 84% of total road accidents occur to citizens between the ages of 18 to 60.

Gadkari asked Indian entrepreneurs to develop indigenous AI-based solutions for the monitoring and enforcement of motor vehicle legislation. The highway monitoring system currently uses imported hardware and software. Gadkari stated that the Ministry has commenced an initial project with AI-based technology in Nagpur. The technology in Nagpur will be used to identify black spots on roads, and the project will integrate machine learning and AI in national highway safety systems. Authorities also plan to use digital construction, which enables machines to translate design drawings on the field using sensors.

The government has also initiated a system for Advanced Traffic Monitoring (ATMS) in the Delhi Meerut Eastern Peripheral expressway and plans to apply the technology in all national highways. The system can be used to capture number plates, identify discrepancies in vehicle documentation, and monitor traffic rule violations.

The country’s top research institutes have been developing and deploying tech-based solutions to reduce road accidents. Early last year, the Indian Institute of Technology, Ropar (IIT-Ropar) developed an algorithm for driver drowsiness detection using machine learning and computer vision. The research team said they used computer vision algorithms to extract facial features such as eye closure and yawning as well as machine learning techniques to effectively detect driver’s alertness.

Further, the Karnataka State Road Transport Corporation (KSRTC) said it would implement AI-based technologies to limit road accidents and improve passenger safety in buses last June. The corporation floated a tender for the implementation of an AI-powered Collision Warning System (CWS) and Driver Drowsiness System (DDS) for 1,044 buses. CWS will provide features like forward-looking collision warnings (FLCW), lane departure warnings (LDW), and virtual bumper. It will also generate real-time alerts. This is probably for the first time in the country a state-run bus corporation is using technology on a large scale to reduce accidents. Other state-run bus corporations are also waiting to adopt this system.

In August last year, the Indian Institute of Technology in Mandi (IIT-Mandi) developed a smart road monitoring system to prevent accidents caused by sharp or blind turns. The system works through sensors that detect the speed, direction, gradient of the slope, and type of vehicle and signals the driver about the oncoming turn, as reported by OpenGov Asia.

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