Bengaluru to get AI-powered mobility digital twin soon, traffic police floats tender

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In a first, Bengaluru is set to get an AI-powered mobility digital twin (MDT) - a virtual model of the city designed to enhance traffic management and improve communication with citizens.

The Bengaluru Traffic Police has floated a tender for the project, estimated to cost around Rs 1 crore, under the Bengaluru City Road Safety and Traffic Management initiative. Officials said the MDT is a major step towards shifting from reactive policing to predictive, AI-driven traffic management.

Moneycontrol reported on January 30, 2025, that Bengaluru is set to soon join the ranks of global cities with a 'digital twin' for traffic management.

Joint commissioner of police (Bengaluru traffic) Karthik Reddy told Moneycontrol: "The Mobility Digital Twin is our leap into the future - a data-driven command centre for Bengaluru’s traffic. It enables us to simulate, predict, and solve congestion and safety challenges in real time. This is not just a tech investment, it’s a commitment to smarter, safer, and more sustainable mobility for our citizens"

The city police have already deployed tools such as ASTraM (Actionable Intelligence for Sustainable Traffic Management) and advanced traffic simulation systems for congestion forecasting and planning. However, these platforms remain “underutilised unless integrated with dynamic and behaviour-responsive models,” a senior officer said.

Also read: Bengaluru to soon join ranks of global cities with 'digital twin' for traffic management

“The proposed MDT seeks to bridge this gap by creating a virtual replica of the city’s mobility ecosystem that continuously adapts to changing conditions,” the officer added.

What the digital twin will do

The MDT will combine behavioural modelling of commuters and drivers with vehicle tracking and dynamic mapping of infrastructure such as junctions, metro access points, parking areas, and roadworks. It will also integrate real-time feeds from weather services, accident reports, public events, citizen apps, and enforcement databases.

Also read: AI-powered signals reduce travel time by 20-33% across three road sections: Bengaluru Traffic Police

Through predictive simulations and dashboards, traffic police will be able to pre-plan diversions for protests or road closures, assess the impact of rain or construction on traffic, and issue dynamic alerts for school zones and pedestrian-heavy areas. It will also enable targeted enforcement by identifying repeat violators, high-risk drivers, and non-compliant vehicles.

According to officials, the system is expected to improve violation targeting by up to 30%, reduce congestion during peak hours and VIP movements, enhance safety in school zones, and build greater public trust through transparent traffic management.

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Deployment and adoption

The platform will be hosted on MeitY-approved cloud infrastructure with stringent data protection norms, real-time analytics, and SLA-backed operational support.

“Training sessions for officers and embedded traffic engineers will ensure smooth adoption. Data will be retained for at least three years to support audits and long-term planning,” the tender document states.

Global benchmarks

Globally, cities such as New York, Los Angeles, Moscow, and Barcelona are using digital twins as part of their urban mobility strategies. These systems help reduce commuting times, simulate accident responses, and recommend routes for emergency vehicles by fusing AI and machine learning with real-time traffic data.

Also read: Bengaluru gets ‘Traffic Police Museum & Experience Centre’, ASTraM mobile app

In Bengaluru, traffic police have already simulated about 3,200 km of the city’s 14,000 km road network, covering high-density corridors, arterial, and sub-arterial roads. The MDT is expected to build on this foundation to deliver a comprehensive, adaptive mobility model.

“This is about moving from firefighting on the roads to foresight-driven traffic management,” the senior officer said. “It will allow us to prepare for disruptions before they occur and make Bengaluru’s roads safer and more efficient.”

Also, read: Bengaluru traffic police launches AI-powered ASTraM; to provide congestion alerts