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Indigenous train collision prevention system 'Kavach' to be exported: Vaishnaw

Vaishnaw, who travelled in a locomotive and inspected the working of 'Kavach', including an on-site demonstration of a head-on collision, said it is a significant milestone in the history of Indian Railways.

Indigenous train collision prevention system 'Kavach' to be exported: Vaishnaw Image for representation

Terming the indigenously developed Automatic Train Protection (ATP) system--'Kavach' as a phenomenal improvement in safety and a great contribution to accident prevention, Railway Minister Ashwini Vaishnaw on Friday said the technology will be implemented over the entire rail network in the country and will also be exported to the world in the next coming years, even as he had a first-hand experience of the collision aversion mechanism by being part of a live demo here.

Vaishnaw, who travelled in a locomotive and inspected the working of 'Kavach', including an on-site demonstration of a head-on collision, said it is a significant milestone in the history of Indian Railways. The highlight of the demonstration was the avoidance of the head-on collision by 'Kavach' without manual intervention.

This was demonstrated between Gullaguda, Chitgidda railway stations on Lingampalli, Vikarabad section of Secunderabad Division in South Central Railway (SCR), with Vaishnaw travelling in a locomotive in one direction, while Vinay Kumar Tripathi, Chairman and CEO, Railway Board was travelling in another on the opposite direction on the same track and 'Kavach' worked as desired to stop the trains and avert a collision.

Also read: Watch: With Railway Minister on board, speeding trains successfully tests anti-collision system 'Kavach'- Video

The Minister witnessed how the technology avoids trains passing Signal at Danger, how their speed is automatically regulated while passing through loop lines, and how to rear-end collision is how to rear-end collision is automatically avoided.

Kavach, which literally means armour, is being promoted by the Railways as the world's cheapest automatic train collision protection system.

Announced in the 2022 Union Budget as a part of the Atmanirbhar Bharat initiative, 2,000 km of the rail network is planned to be brought under 'Kavach' for safety and capacity augmentation in 2022-23.

"In the budget, 2,000 km has been approved, and in subsequent years, 'Kavach' will be deployed in 4,000-5,000 km every year," Vaishnaw told reporters.

"Kavach is a very important Automatic Train Protection technology. This is a great technological development and a major step taken by Indian Railways in taking forward Prime Minister Narendra Modi's initiative of Atmanirbhar Bharat," he said.

It increases passenger safety. It is designed, developed and manufactured in India and will be deployed in India and exported to the world in the coming years.

"If we bring such a technology from Europe, it will cost between Rs 1.5 crore to Rs 2 crore per kilometre to operate while 'Kavach', which is indigenously developed Automatic Train Protection system, will cost between Rs 40 lakh to Rs 50 lakh per km and is a step ahead when compared to the technology offered by another similar system," he said.

The target is to install Kavach in 2,000 km, and it will be deployed on Delhi-Mumbai and Delhi-Howrah corridors initially. And in subsequent years, 'Kavach' will be deployed in 4,000 km to 5,000 km every year, he added.

Vaishnaw further said 4G spectrum had been allocated to the Railways, which will further improve the reliability of train operations.

He said 'Kavach' technology has been tested at SIL-4 (Safety Integrity Level- 4), which is the highest level of safety and integrity. "It means during 11,600 years of operation, there is a probability of only one error, and that is the level of safety and integrity of this system. It has already been tested on high speed at 180 km per hour, and subsequent testing beyond 200 km is also going on," he said.

To a query on when the Railways will achieve the goal of "zero accidents", the Minister said there are so many factors on which we have to continuously work on.

"We have to make sure that our passengers are safe. We have to make sure that every needed technology has to be developed and deployed on the railway network. That is the target with which we have to work. This (Kavach) is a great contribution to accident prevention. There are many more things that we have to do in terms of improving the track quality, in terms of improving the coaches and the trains that we travel in", he said.

Kavach is designed to bring a train to a halt automatically when it notices another train on the same line within a prescribed distance. Trains will also stop on their own when digital system notices any manual error like "jumping" of the red signal or any other malfunction.

The 'On-Board Display of Signal Aspect' (OBDSA) is to help loco pilots check signals onboard consoles. RFID tags are provided on the tracks and at the station yard for each track and signals for track identification, location of trains and identification of train direction.

Once the system is activated, all trains within a 5-km range will halt to provide protection for trains on adjacent tracks. Currently, loco-pilots or assistant loco-pilots usually crane their necks out of the window to look for caution signs and signals, said officials.

It also includes stationary equipment to gather signalling and loco inputs and relay them to a central system for seamless communication with the train crew and stations.

Kavach is developed by Research Design and Standards Organisation (RDSO) in collaboration with the Indian industry.

During the development phase, Kavach was implemented for 264 km covering 25 stations across Wadi, Vikarabad, Sanath Nagar and Vikarabad, Bidar sections over South Central Railway. Later, the system has been further extended by an additional 936 km, taking the cumulative deployment of Kavach to 1,200 km, an SCR release said.

SCR General Manager Sanjeev Kishore, other senior officials from Railway Board and South Central Railway were present. 

With inputs from PTI

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