Key Takeaways
- Bengaluru Traffic Police issues a ₹1 crore tender for an AI-powered Mobility Digital Twin to improve traffic management.
- The system will utilize real-time data and predictive simulations to enhance road safety and manage congestion.
- Global cities have successfully implemented similar technologies, showcasing their effectiveness in urban mobility enhancement.
AI-Powered Traffic Control Initiative
Bengaluru is set to introduce an AI-driven Mobility Digital Twin (MDT)—a virtual representation of the city aimed at transforming traffic management and public engagement. This initiative, sanctioned by the Bengaluru Traffic Police under the Bengaluru City Road Safety and Traffic Management Programme, is expected to cost around ₹1 crore, symbolizing a shift from reactive to predictive traffic control.
Joint Commissioner of Police (Traffic) Karthik Reddy emphasized that the Mobility Digital Twin marks a pivotal advancement in urban mobility. It will function as a data-driven command center, facilitating real-time simulations, predictions, and proactive measures to alleviate congestion and enhance road safety.
Currently, Bengaluru employs systems like ASTraM (Actionable Intelligence for Sustainable Traffic Management). However, these systems have been underutilized. The MDT seeks to bridge this gap by creating an adaptive digital model of the city’s mobility ecosystem that evolves based on real-world changes.
The MDT will integrate behavioral modeling of commuters and drivers with live vehicle tracking and dynamic mapping of critical infrastructures, including junctions and roadworks. It will also incorporate real-time data streams like weather updates and accident alerts, enabling traffic police to pre-plan diversions for events and assess the impacts of external factors such as rain or construction.
Furthermore, the system will enhance enforcement capabilities by identifying repeat offenders and high-risk drivers. Officials anticipate a 30 percent improvement in violation detection accuracy, a reduction in peak-hour congestion, and enhanced safety near schools—aiming to foster public trust through transparent operations.
The platform will be hosted on a government-approved cloud infrastructure, adhering to strict data protection and privacy regulations. Training sessions are mandated for traffic officers and engineers to ensure proper implementation and usage. Additionally, data retention for three years will support audits and long-term traffic planning.
Globally, cities like New York and Los Angeles have adopted similar digital twin frameworks, leading to reductions in commute times and improvements in emergency response simulations. In Bengaluru, traffic authorities have already mapped around 3,200 kilometers of its 14,000-kilometer road network, focusing primarily on key routes. The Mobility Digital Twin will build on this groundwork, creating a comprehensive traffic model.
A senior officer encapsulated the initiative: “This program transitions us from merely managing disruptions to predicting them, aiming to create safer and more efficient roads in Bengaluru.”
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