Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection

Abstract

This research proposes an intelligent traffic management system (ITMS) leveraging advanced technologies to alleviate traffic congestion, prioritize emergency vehicle passage (specifically ambulances), and detect stolen vehicles. The system integrates real-time traffic data acquisition, predictive modeling for congestion forecasting, and computer vision for vehicle identification. Results demonstrate significant improvements in average travel times, emergency response times, and stolen vehicle recovery rates compared to traditional methods. The system's modular design facilitates scalability and adaptability to various urban environments. This work contributes to enhanced road safety, efficient traffic flow, and improved law enforcement capabilities.

Introduction

Urban traffic congestion poses significant economic and social challenges, leading to wasted time, fuel consumption, and increased pollution. Simultaneously, the timely arrival of emergency vehicles is crucial for saving lives, while the efficient detection and recovery of stolen vehicles are essential for public safety. Current traffic management systems often lack the intelligence and integration needed to address these interconnected issues effectively. This research aims to bridge this gap by developing an intelligent system that combines real-time data analysis, predictive modeling, and advanced vehicle detection techniques to optimize traffic flow, prioritize emergency vehicles, and detect stolen vehicles.

Objectives

• Reduce urban traffic congestion using intelligent light control systems.
• Automatically detect and clear routes for emergency vehicles (ambulance clearance).
• Integrate stolen vehicle detection using number plate recognition and real-time alerts.
• Implement a modular and scalable system adaptable to various cities.

Technical Details

• Microcontroller: Raspberry Pi or ESP32 for processing and connectivity.
• Camera module for license plate recognition using OpenCV.
• RFID or GPS module on ambulances for priority signal override.
• Traffic lights controlled via relay based on congestion logic.
• Stolen vehicle database integrated with alert system.