In a first for the city, Bengaluru is set to roll out an AI-powered Mobility Digital Twin (MDT)—a virtual replica of the city designed to enhance traffic operations and public engagement.
The Bengaluru Traffic Police has floated a tender for this initiative, estimated to cost around ₹1 crore, under the Bengaluru City Road Safety and Traffic Management Programme. Authorities believe the project will mark a significant shift from reactive policing towards predictive, AI-enabled traffic control.
Joint Commissioner of Police (Traffic) Karthik Reddy said the Mobility Digital Twin represents a major step into the future of urban mobility. It will act as a data-driven command centre, enabling simulations, predictions, and proactive interventions to manage congestion and road safety issues in real time.
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He added that this is not merely a technological upgrade but a commitment to smarter, safer, and more sustainable mobility for the city’s citizens.
Currently, Bengaluru Traffic Police operates systems such as ASTraM (Actionable Intelligence for Sustainable Traffic Management) and advanced traffic simulation tools to forecast congestion. However, a senior officer noted that these systems remain underutilised unless integrated with behavioural models and responsive frameworks. The proposed MDT aims to bridge this gap by creating a living digital model of the city’s mobility ecosystem that continuously evolves with real-world changes.
How the Digital Twin Will Function
The MDT will combine behavioural modelling of commuters and drivers with vehicle tracking, dynamic mapping of infrastructure—such as junctions, metro stations, parking zones, and roadworks—and real-time data integration.
These data streams will include weather updates, accident alerts, public event schedules, citizen apps, and law enforcement databases.
Through predictive simulations and interactive dashboards, the system will enable the traffic police to pre-plan diversions for protests or road closures, assess the impact of rainfall or construction works, and issue real-time alerts in sensitive zones like schools and pedestrian areas.
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It will also enhance enforcement by flagging repeat violators, high-risk drivers, and non-compliant vehicles. Officials expect the system to improve violation detection accuracy by up to 30 per cent, ease peak-hour congestion, strengthen safety near schools, and build greater public trust through transparent operations.
Deployment, Adoption & Security
The platform will be hosted on MeitY-approved cloud infrastructure, ensuring strict adherence to data protection and privacy norms. It will include real-time analytics and Service Level Agreement (SLA)-based technical support.
The tender also mandates training sessions for traffic officers and engineers to ensure effective adoption. Additionally, all data must be retained for at least three years to support audits, research, and long-term traffic planning.
Global Comparisons & Local Foundations
Globally, cities such as New York, Los Angeles, Moscow, and Barcelona have already implemented digital twin frameworks as part of their smart mobility strategies. These systems have helped reduce commute times, simulate emergency responses, and suggest optimal routes using AI, machine learning, and real-time traffic data.
In Bengaluru, traffic authorities have already mapped approximately 3,200 kilometres of the city’s 14,000-kilometre road network, focusing primarily on arterial and sub-arterial roads. The Mobility Digital Twin will expand upon this foundation to create a fully adaptive, city-wide traffic model.
As one senior officer remarked, “This initiative moves us from firefighting on the roads to foresight-driven management. We aim to anticipate disruptions and make Bengaluru’s roads safer, smoother, and more efficient.”
