This repository contains the code for an AI-based Autonomous Vehicle System that focuses on self-driving capabilities, scene understanding, and intelligent navigation. The project integrates multiple sensors, computer vision techniques, and machine learning algorithms to allow the vehicle to understand its environment, make real-time decisions, and navigate autonomously.
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Perception Module (/perception)
This module includes code for sensor integration, data collection, and computer vision tasks, such as object detection, lane detection, and environmental perception.
Scene Understanding Module (/scene_understanding)
This folder contains AI models and algorithms used for scene understanding, which helps the vehicle recognize objects, interpret the driving environment, and make decisions based on visual inputs.
Decision-Making Module (/decision_making)
Contains the FSM logic and decision-making algorithms for handling various driving scenarios, such as lane following, overtaking, and obstacle avoidance.
Path Planning Module (/path_planning)
This folder includes code for dynamic path planning using the Google Maps API, as well as local path adjustments to avoid obstacles.
Control Module (/control)
The control module translates the decisions from the FSM into vehicle actions such as steering, accelerating, or braking.
The goal of this project is to develop an autonomous vehicle system capable of scene understanding, path planning, and real-time decision-making. The system uses several modules to process environmental data, analyze scenes using AI, and control the vehicle's movement.
Key Features:
Sensor Integration: Uses cameras, LiDAR (if applicable), and ultrasonic sensors to gather environmental data.
Scene Understanding: AI-based scene analysis to detect objects, lanes, and other vehicles, allowing the system to understand the driving environment.
Computer Vision: Object detection, lane detection, and other image processing tasks using state-of-the-art computer vision algorithms.
Decision Making: A Finite State Machine (FSM) is used to manage real-time decisions, including lane following, obstacle avoidance, and overtaking.
Path Planning: Integration with Google Maps API for dynamic route planning and local path planning to avoid obstacles.
Control System: Real-time control of the vehicle's steering, acceleration, and braking based on input from decision and planning modules.
