International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 13 Issue: 03 | Mar 2026
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p-ISSN: 2395-0072
Integrated Traffic Management System Mohammed Jaorawala 1, Khan Siraj 2, Momin Yusuf 3, Patait Aynan 4, Zeba Syed 5 1 Mohammed Jaorawala ,Web Dev 2 Khan Siraj , Backend (Team Leader) 3 Momin Yusuf ,Alpha Beta Tester 4 Patait Aynan ,Mobile Dev 5Zeba Syed, Professor, Dept. of Computer Engineering, Abdul Razzak Kalsekar Polytechnic , Maharashtra, India ---------------------------------------------------------------------***-------------------------------------------------------------------------Abstract - Urban traffic congestion remains one of the most critical challenges faced by rapidly growing cities worldwide. Conventional traffic signal systems rely on fixed time intervals that are incapable of adapting to realtime traffic conditions, resulting in excessive waiting times, fuel waste, increased air pollution, and delayed emergency vehicle response. This paper presents the design and conceptual implementation of an Integrated Traffic Management System (ITMS), a comprehensive intelligent framework that addresses these challenges through four tightly integrated subsystems. First, an intersection camera module employs computer vision to perform direction-wise vehicle counting, pedestrian detection, and anomaly identification in real time. Second, a novel Grid-Based Detection System divides each traffic lane into a 10×6 occupancy grid of 60 cells covering a 100meter range, assigning hierarchical density grades (S, A, B, C, D) using a weighted averaging formula. This gridbased approach serves as a robust fallback mechanism when object detection fails due to adverse weather. Third, a Priority Scoring System assigns calibrated weights to six vehicle categories, with emergency vehicles receiving an absolute override score of 1000, and calculates a per-lane Composite Score using a fusion of grid grades and proximity-based priority weights. Lane opening combinations are classified into three states: Safe, Less Congestion, and Lesser Congestion, enabling simultaneous non-conflicting lane service. Fourth, a Gamified Reward Mechanism incentivizes road compliance by awarding driver behavior points across three priority tiers, converting them into digital credits and classifying drivers into bronze, silver, and gold tiers with compounding bonus multipliers. All subsystems are coordinated through a Centralized Management System (CMS). Simulation results and design validation demonstrate that the proposed ITMS reduces unnecessary red-light waiting,
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enables dynamic green time allocation, prioritizes emergency vehicles with zero manual intervention, and motivates safe driving behavior through measurable incentives. The system is designed for scalability within smart city infrastructure. Key words - Intelligent Traffic Management System; Occupancy Grid Map; Priority-Based Signal Control; Computer Vision; Emergency Vehicle Prioritization; Reward-Based Compliance; Smart City; Adaptive Traffic Signals; Vehicle Detection; Centralized Management System.
1 INTRODUCTION In recent decades, rapid urbanization has intensified vehicular density in cities across the developing and developed world. The United Nations projects that approximately two-thirds of the global population will inhabit urban areas by 2050, placing unprecedented demand on road infrastructure [1]. Traffic congestion, road accidents, and air pollution are direct consequences of inadequate traffic management systems that fail to adapt dynamically to real-time conditions [2]. Traditional traffic signal systems operate on preprogrammed, fixed-time cycles that distribute green time uniformly across all lanes regardless of actual traffic demand [3]. This static approach generates several well-documented inefficiencies: unnecessary waiting at empty or low-traffic junctions, inability to detect and respond to emergency vehicles, no mechanism to prioritize high-occupancy public transport, and the complete absence of any driver incentivization for compliance [4]. These limitations have a measurable impact on urban productivity, public health, and emergency response effectiveness [5].
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