AI Alliance Pune: Artificial Intelligence can transform cities' transport systems, says Mumbai Metro MD Ashwini Bhide

Mumbai Metro MD Ashwini Bhide

AI has the potential to completely transform the way cities travel and achieve integration in different modes of transport, said Mumbai Metro MD Ashwini Bhide on March 27.

Speaking at the CNBC-TV18 & Moneycontrol AI Alliance Pune on March 27, Bhide said, "Metro is much ahead of the conventional transportation system. However, we are still not making full use of it today. The most important aspect of Metro is its communication-based train control system (CBTC signalling system). It has the potential to operate the train on its own, with multiple grades of automation: ATP (automatic train protection); ATO (automatic train operation); and UTO (unattended train operation)."

"Many countries in the world, even those with Metro rail system, may not have the UTO system that we have, but we are still not using it. The reason is that we are a bit scared of fully relying on digital technology. However, the potential is there, and AI can do much more than what we are testing today," she added.

Bhide emphasised that various AI algorithms and tools, such as machine learning and deep learning can be integrated into different aspects of transport systems. "This can make these systems more reliable, safer, faster, and more comfortable, ultimately focusing more on passengers' needs," she said.

She also highlighted that the transportation sector is transforming due to digital technology and AI.

Bhide pointed out, "Today's urban transport or transit systems are not just physical infrastructures made of cement and steel; they are becoming digital and smarter, evolving into intelligent systems."

Bhide used the example of buses, stating, "Passengers can now get real-time live information, knowing exactly where the buses are. This also provides valuable data and intelligence to operators for scheduling and planning bus routes effectively."

She said that AI could improve the commuter experience, operation, asset management and maintenance, planning and execution, and safety in urban transportation.

"When we have AI chatbots or mobility as a service, where integration of all different modes of transport can happen, and commuters can get the route plan for the whole system. Sometimes, physical integration of different modes becomes a little challenging, but with digital integration, it is much easier and can result in a better commuter experience" she said.

On rolling stock maintenance, Bhide suggested a shift from periodic to predictive maintenance using different sensors and camera feeds, saving time, and effort, and improving maintenance procedures.

"We are currently doing periodic maintenance so that we know when each asset is due for maintenance. However, instead, we can shift to using different kinds of sensors and camera feeds. This would enable predictive maintenance, saving time and human effort, and improving maintenance procedures," she said.

She also emphasised that proper data usage through segregation and analysis could enhance decision-making processes and improve commuter experience and safety.

Bhide stressed that AI tools are crucial for utilising data effectively in real-time to prevent incidents and enhance sustainability and energy efficiency in urban transportation systems.

"Safety is the most important aspect that AI could improve. Although all our stations have CCTV cameras and other safety measures, without AI tools, we cannot effectively utilize the data from these sources. With AI, we can access real-time feeds and prevent incidents proactively," she emphasised.