An Operations Research Framework for Sustainable Urban Mobility in Bengaluru: A Phased Strategy for Congestion Mitigation and System Optimization

Executive SummaryThis framework addresses the critical structural failure of Bengaluru’s urban transport system, which currently imposes an estimated economic loss of USD 5.92 billion annually. Moving beyond traditional supply-side infrastructure, this paper proposes a phased Operations Research (OR) strategy designed to maximize human throughput (Passenger-Kilometers per Hour) while minimizing total societal costs.Key Findings:•Systemic Friction: Private vehicles in major corridors average only 11 kmph, while BMTC buses operate at a significantly slower 8 kmph, actively discouraging modal shifts.•Supply-Demand Mismatch: While the city population grew by 32% between 2011 and 2019, the bus fleet increased by only 7.89%, leading to a dramatic drop in public transit ridership.•Infrastructure Deficit: Only 7.3% of the city area is allocated to transportation, far below the global norm of 20%.The Three-Phased Roadmap:1.Phase I: Tactical Optimization (0–2 Years): Immediate deployment of Deep Reinforcement Learning (DRL)for adaptive traffic signal control at 136 high-volume intersections.2.Phase II: Strategic Capacity (2–5 Years): Accelerated completion of the Metro/Suburban rail network and the introduction of Bus Rapid Transit (BRT) corridors.3.Phase III: Structural Redesign (5+ Years): Long-term implementation of Transit-Oriented Development (TOD) and Electronic Road Pricing (ERP). Keywords: Urban Mobility, Bengaluru, Operations Research, Traffic Congestion, Deep Reinforcement Learning, Public Transit Optimization, Sustainable Transport.