Bengaluru is preparing to introduce an advanced Mobility Digital Twin (MDT), an AI-based virtual model of the city’s roads that can learn, predict, and adapt to real-time conditions. The project, aimed at transforming the way traffic is managed, will use live data from vehicles, weather updates, accidents, events, and citizen feedback to anticipate congestion and prevent jams before they occur.
The Bengaluru Traffic Police have floated a tender worth ₹1 crore to kick-start the initiative, marking a major shift from reactive traffic control to predictive and planned management. The MDT will function as a live digital version of the city’s mobility ecosystem, continuously updated with real-time information.
Unlike regular navigation apps, the MDT will integrate every detail of the transport network — from metro routes and potholes to processions and roadblocks — to offer a complete picture of city movement. It will use predictive AI and behavioural data to understand how people actually drive and move across Bengaluru.
While tools like ASTraM and traffic simulation systems are already in use, the MDT’s real-time, AI-driven model will help the police manage traffic more efficiently without relying on static data. Once operational, the system is expected to ease daily commutes, reduce congestion, and elevate Bengaluru to the ranks of global cities that use digital twins for smarter urban mobility.
