Traffic Flow Optimization Using Automated Highway Systems: A Case Study on Urban Intersections in India

Urban road networks in India face severe traffic congestion due to rapid urbanization, heterogeneous vehicle composition, and inadequate traffic management. This paper presents a comprehensive study on traffic flow optimization for a selected urban arterial signalized intersection using traffic engineering principles, classical flow models, and Webster's signal optimization method. Field data including classified traffic volume, speed, and delay were collected and analyzed. The peak hour traffic volume was measured at 2850 PCU/hr with a volume-to-capacity (V/C) ratio of 0.46, corresponding to Level of Service (LOS) E under existing conditions. Using Webster's method, the signal cycle length was optimized from 240 seconds to 193 seconds, achieving a 32% reduction in average delay (from 85 sec/veh to 58 sec/veh), a 38% reduction in queue length (from 451 m to 278 m), and improvement of LOS from E to C. Three classical traffic flow models—Greenshields, Greenberg, and Underwood—were applied to characterize the speed-density relationship. Fuel savings of approximately 330 liters/day and significant reductions in vehicular emissions (CO: 28%, NOx: 22%, PM: 18%) were estimated. The study demonstrates that intelligent signal optimization and Intelligent Transportation Systems (ITS) can substantially mitigate urban traffic congestion without major infrastructure expansion.