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Author :
T. Veda Reddy, B. Krishna Sree, K. Ridhi Reddy, D. Kalyan Yadav
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Page No: 1 - 12
Abstract : Vehicle-related violations, including over-speeding, contribute to nearly 25% of urban traffic incidents, leading to escalating enforcement costs globally. Traditional vehicle detection and speed estimation methods face challenges such as low-light conditions, occlusions, and high-speed motion, resulting in reduced accuracy. The project presents a Vehicle Detection and Speed Estimation System utilizing YOLOv8 for real-time vehicle recognition and a centroid-based tracking algorithm for speed estimation. The system achieves over 95% detection accuracy and processes frames within seconds, ensuring efficient traffic monitoring. By automating vehicle detection and speed estimation, the system minimizes manual intervention, enhances enforcement efficiency, and improves road safety. The system’s implementation contributes to smart traffic management, law enforcement, and fleet monitoring, making it a valuable tool for modern transportation infrastructure.
Keyword Vehicle detection, speed estimation, YOLOv8, centroid-based tracking, real-time processing, traffic monitoring, law enforcement, smart traffic management, accuracy evaluation, enforcement efficiency.
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Abstract

Vehicle-related violations like over-speeding contribute to around 25% of urban traffic accidents. These incidents increase global enforcement costs. Traditional detection systems often fail under low light, heavy traffic, or fast-moving vehicles. To solve this, we introduce a vehicle speed detection system. It uses YOLOv8 for real-time vehicle recognition and a centroid-based tracker for speed calculation. This system offers over 95% detection accuracy and processes images within seconds. As a result, it improves monitoring, reduces manual effort, and supports smarter enforcement. It benefits law enforcement, fleet managers, and smart city projects.Vehicle Detection and Speed Estimation System

Keywords: Vehicle detection, speed estimation, YOLOv8, centroid tracking, traffic monitoring, real-time processing, smart traffic systems.

Introduction

The vehicle speed detection system is a next-generation, computer vision-powered solution developed to monitor vehicle movements and detect traffic violations in real time. As road safety concerns and urban congestion intensify, the need for automated and accurate traffic enforcement tools has grown significantly. This system leverages the powerful YOLOv8 deep learning model for precise vehicle detection and pairs it with a centroid-based tracking algorithm to estimate vehicle speed with high accuracy.Vehicle Detection and Speed Estimation System

Designed for dynamic environments, the system performs reliably in high-speed traffic zones, congested urban settings, and low-visibility conditions. By calculating vehicle speed using frame-by-frame tracking and known physical distances, it delivers precise speed data without relying on traditional radar or LIDAR systems. Unlike expensive, hardware-dependent radar systems, this vehicle speed detection system can operate with existing CCTV or surveillance infrastructure, making it a highly scalable and cost-effective solution for smart city initiatives.

With capabilities that extend to multi-lane tracking, erratic driving detection, and violation flagging, this solution empowers traffic authorities with real-time, actionable insights, improving road safety and reducing traffic-related incidents.

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