The multi-lane free flow (MLFF) toll system and AI-driven highway management will be completed across the country by 2026-end, and after implementation, these technologies will eliminate wait time at toll plazas for commuters, Union Minister Nitin Gadkari informed the Rajya Sabha on Wednesday.
Responding to supplementaries during the question hour, the road transport minister said the new technology will be AI-based. Commuters will not have to wait any longer at toll plazas, and this will help save fuel worth Rs 1,500 crore and add Rs 6,000 to the government revenue.
"The multi-lane free flow toll (MLFF) is a very good facility. Earlier, we had to pay at the toll, and it would take 3 to 10 minutes; then, due to FastTag, the time has come down to 60 seconds or less. Our income has increased by at least Rs 5,000 crore. After MLFF came, replacing FastTag, cars can now cross the toll at a maximum of 80 km per hour, and no one will be stopped at the toll," he said in the House.
"Our attempt is to make it to zero minutes, and this would involve number plate recognition through satellite with AI and FastTag," he added.
"By 2026, we will complete this work 100 per cent, and once this task is complete, our income will help save Rs 1,500 crore, and our income will further rise by another Rs 6,000 crore, and toll theft will end. There will be no problems, and people will not have to stop at the toll plaza," Gadkari told the members.
He said the new technology will certainly help people, and travel time will certainly be reduced.
The minister said the government was, however, only responsible for national highways and not state highways or city roads. But, many times on social media, there are problems on state and city roads and are dubbed as if they happened on national highways, he said.
"We are trying to make the system transparent and corruption-free," the minister told members.
(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
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