Automated Driving

This repository showcases a collection of projects in the field of automated driving. It serves as a hub for various models, algorithms, and applications demonstrating core concepts and practical implementations in vehicle dynamics, control, and perception.

Contents

1. Lane Keeping Assist System
   Description: Implementation of a Lane Keeping Assist (LKA) system using Model Predictive Control (MPC).
   Key Features:

   • State-space modeling of lateral vehicle dynamics.
   • Integration of road curvature preview and sensor dynamics for enhanced control.
   • MPC-based steering control for lane tracking with smooth control inputs.
   • Visualization of lateral deviation, yaw angle, and steering inputs.
     Folder: Lane-Keeping-Assist-System
     Reference: Based on MathWorks' example.

2. Adaptive Cruise Control (ACC) Using Model Predictive Control (MPC)
   Description: Implementation of an ACC system using Model Predictive Control (MPC).
   Key Features:

   • Dynamic lead vehicle simulation with sinusoidal acceleration profile.
   • MPC-based control for maintaining safe distance and desired velocity.
   • Nonlinear constraints for velocity and distance safety.
   • Visualization of acceleration, velocity, and relative distance over time.
     Folder: Adaptive-Cruise-Contro-MPC
     Reference: Inspired by MathWorks' example.

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Usage

Clone the repository:

git clone https://github.com/your-username/Automated-Driving.git
cd Automated-Driving

Explore individual project folders for instructions on running the implementations.

Acknowledgments

This repository brings together concepts from vehicle dynamics, control theory, and automated driving.