🚗 Pedestrian Detection for Autonomous Vehicles

This repository contains a project aimed at developing algorithms that allow autonomous vehicles to detect pedestrians in various real-world scenarios. This project was conducted as a course assignment for 20242R0136COSE41600 SELF-DRIVING CARS at Korea University. The dataset includes pedestrians walking, crawling, moving in zigzag patterns, and more—designed to reflect diverse, unpredictable behaviors.

📌 Project Overview

• Goal: Develop a robust pedestrian detection algorithm that performs well across diverse movement scenarios.
• Dataset: Contains simulated or real-world footage featuring pedestrians exhibiting different types of movement.
• Applications: Autonomous driving safety systems, intelligent transportation systems, and urban mobility solutions.

🧠 Key Features

• Design and training of pedestrian detection machine learning models
• Performance evaluation under multiple movement scenarios
• Visualization for detection results

📂 Project Structure

📁 pedestrian-detection/
├── data/              # Pedestrian data under various scenarios
├── models/            # Detection algorithms
├── utils/             # Preprocessing scripts
└── README.md          # Project documentation