Odisha train accident: Could the KAVACH system have prevented it?
Friday was a traumatising day for Indians. Three trains collided one after another in Odisha’s Balasore district, leading to the deaths of at least 261 people. The crash involved the Bengaluru-Howrah Superfast Express, the Shalimar-Chennai Central Coromandel Express, and a goods train.
After the accident, some are saying that the KAVACH could have prevented the accident. What is the KAVACH? What is its deployment strategy? Could it have actually prevented the Odisha train accident?
In this podcast, Nabodita Ganguly speaks to Abhishek Law, Special Correspondent, to decode the meaning of KAVACH.
KAVACH, also known as the Train Collision Avoidance System, was announced by the Indian Railways Minister in March 2022. It is an indigenous system designed to prevent head-on collisions between trains by employing a warning system and an auto-braking mechanism. This system garnered attention as a potential solution to avert train accidents and save lives.
Now, in the wake of the devastating accident in Odisha, the discussion on coverage has resurfaced. People are questioning whether the installation of such a system could have prevented this massive loss of lives. While the railways confirmed that the Odisha route did not have KAAVACH installed, there is ongoing speculation about its potential effectiveness in a side-on collision scenario.
Law highlights that the successful testing of coverage took place in March 2022, with Railway Minister Ashwini Vaishnaw himself participating in the demonstration. The system demonstrated features such as an auto-braking mechanism to prevent collisions between trains. Additionally, it included features like SMS alerts and gate whistling to enhance safety measures.
However, the nationwide rollout of coverage faces practical challenges, as acknowledged by the Railway Minister in a parliamentary response. Factors such as track conditions, rolling stock compatibility, migration to LTE networks, and evaluations by safety assessors contribute to the timeline uncertainty. Listen in. Read the full story here.
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