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

Arvind Prabu

No sqmfa_v1, SocArXiv from Center for Open Science

Abstract: Executive Summary This 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.

Date: 2026-01-25
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:sqmfa_v1

DOI: 10.31219/osf.io/sqmfa_v1

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