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[Audio] Ant Colony Optimization for Urban Traffic Light Scheduling A novel multi-objective framework for sustainable traffic management in modern cities By C. Karpagham Assistant professor Department of Management studies St Joseph's institute of technology OMR Chennai.
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[Audio] The Urban Traffic Challenge Environmental Impact Rising Congestion Urbanization drives traffic gridlock, fuel waste, and delays Idling vehicles emit massive CO₂, harming air quality System Limitations Fixed-time controls can't adapt to dynamic traffic patterns Traditional traffic systems struggle to balance efficiency, mobility, and sustainability simultaneously.
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[Audio] ACO-TLS Framework Three Core Objectives Minimize vehicle waiting time Maximize intersection throughput Reduce carbon emissions Decentralized Control Pheromone Trails Multi-Objective Balance Each intersection manages signals autonomously Virtual markers encode optimal signal phases Pareto optimization manages trade-offs.
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[Audio] Breakthrough Performance Results 27.8% 19.6% 14.3% Wait Time Reduction Throughput Increase Emissions Cut Average vehicle delay decreased vs. fixed-time control More vehicles served per intersection cycle CO₂ reduction through optimized signal timing 12.1% Multi-Objective Edge Superior balance vs. adaptive heuristics Tested on benchmark 4-intersection urban network using real traffic data.
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[Audio] Comparative Analysis Wait Time (sec) Throughput (%) Emissions (g/veh/km) Fixed-Time Scheduling Adaptive Heuristic ACO-TLS (Proposed) Rigid cycles unable to respond to traffic changes Local queue-based adjustments, limited coordination Swarm intelligence with multi-objective optimization.
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[Audio] Future of Intelligent Transportation Scalable Solution Real-Time Optimization Decentralized architecture adapts to growing networks Dynamic response to changing traffic conditions Sustainable Mobility Environmental goals integrated into traffic control ACO-TLS demonstrates that bio-inspired swarm intelligence can deliver efficient, flexible, and environmentally responsible traffic management for modern cities.