🚗 Path Tracking Control System

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📖 Overview & Methodology

This project implements a path tracking control system that ensures an autonomous vehicle follows a predefined trajectory. The work is structured in two main stages:

🔹 Kinematic Model Extraction

• The vehicle is modeled using a bicycle kinematic model, valid for:
  • Low-speed motion
  • Large curvature paths
  • Negligible bank and inclination angles
• The bicycle abstraction represents each axle (front and rear) by a single wheel located at its midpoint.

🔹 Control Strategy

The proposed control scheme combines two methods:

1. Orientation Error Handling

   • A geometric procedure relates steering angle to orientation error.
   • Aligns the velocity vector with the tangent of the reference path.

2. Cross-Track Error (CTE) Handling

   • A PID controller adjusts the steering angle based on the lateral deviation (CTE).
   • Ensures the velocity vector rotates toward the path centerline.

👉 By combining both, the system avoids the limitations of each method individually (parallel tracking, divergence, or wrong direction).

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🖥️ Simulation Environment

The system is implemented and tested in MATLAB & Simulink.

The simulation includes the following blocks:

• Road Block: Defines the mathematical expression of the path.
• Sensors Block: Computes orientation error and cross-track error.
• Controller Block: Combines PID (for CTE) + geometric approach (for orientation).
• Kinematic Model Block: Updates vehicle pose using lateral kinematic equations.

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📊 Simulation Results

The combined controller demonstrates robust path tracking on different reference paths:

Key findings:

• The orientation-only controller may cause parallel tracking without convergence.
• The CTE-only controller can lead to divergence if the vehicle starts far from the path.
• The combined method ensures convergence and prevents opposite-direction tracking.
• Both orientation error and cross-track error converge and remain small over time.

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🚀 Quick Start

🔧 Prerequisites

• MATLAB 2014a or newer (with Simulink)

📂 Installation & Usage

# Clone the repository
git clone https://github.com/A-S-Control-Systems/Path-Tracking-Control-System

from the src , run play_me_first.m to initialize the car parameters and define the path to be tracked (you can edit it as you want), then run the code main.m which automatically run the Kinematic_Model_Delta_Psi_Control.slx to calculate the traversed path, then it simulates it using drawnow.

📂 Project Structure

├ src  #contains MATLAB codes
│   ├── play_me_first.m           # Initializes car parameters & defines path
│   ├── Kinematic_Model_Delta_Psi_Control.slx       # Simulink model with control scheme
│   ├── main.m          # Runs the simulation & visualization
├ Documentation       # Documentation file (PDF)
├ README.md

📖 Citation

@software{myproject2025,
  author    = {Ali Deeb and Saleh Rabea},
  title     = {Path-Tracking-Control-System},
  year      = {2023},
  publisher = {GitHub},
  note      = {Supervised by Dr. Hasan Alahmad, Dr. Samer Suleiman, Eng. Wassim Ahmad},
  url       = {https://github.com/A-S-Control-Systems/Path-Tracking-Control-System}
}