Autonomous Lane Change Modeling and Control Using MATLAB Simulink | Autonomous Vehicle Simulation
Autonomous lane change control is one of the most important functions in modern intelligent transportation systems and self-driving vehicle technology. This project presents an advanced MATLAB Simulink model for autonomous lane change planning, vehicle dynamics analysis, and closed-loop controller design.
The simulation demonstrates how an autonomous vehicle can detect lane change requirements, generate a smooth trajectory, and track the desired path while maintaining lateral stability and ride safety. The project is useful for research in autonomous driving, advanced driver assistance systems (ADAS), intelligent vehicle control, and automated mobility applications.
Key Features
- Autonomous lane change modeling in MATLAB Simulink
- Vehicle lateral and longitudinal dynamics simulation
- Trajectory planning and path tracking control
- Closed-loop controller design for lane change execution
- Performance analysis for stability, tracking, and safety
Methodology
The proposed autonomous lane change system is implemented in MATLAB Simulink using a vehicle dynamics model, trajectory generation block, and control algorithm for steering and motion regulation. The system evaluates the desired lane transition path and applies a suitable control action to ensure accurate path tracking under different driving conditions.
- Vehicle dynamic model development
- Reference lane change trajectory generation
- Lateral control and steering angle computation
- Tracking error minimization during lane transition
Applications
- Autonomous Vehicles
- Advanced Driver Assistance Systems (ADAS)
- Lane Keeping and Lane Change Control Research
- Intelligent Transportation Systems
- Automotive Control System Development
MATLAB Simulink Autonomous Vehicle Project
This MATLAB Simulink project demonstrates autonomous lane change modeling and control for self-driving vehicle applications. The simulation model can be used for research in autonomous navigation, automotive control, intelligent mobility systems, and advanced trajectory tracking studies.
Keywords: MATLAB projects, Simulink projects, autonomous vehicle simulation, lane change control, trajectory planning, path tracking control, vehicle dynamics modeling, ADAS MATLAB project.
Download MATLAB Simulink Autonomous Vehicle Project
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OUTPUT - Autonomous Lane Change Modeling and Control Using MATLAB Simulink
This project is suitable for PhD research, master's thesis, and final year engineering projects related to autonomous vehicles, automotive control systems, intelligent transportation, ADAS development, and trajectory planning in MATLAB Simulink.
Related MATLAB Projects
- Autonomous Vehicle MATLAB Simulink
- ADAS Simulation MATLAB
- Vehicle Dynamics Control MATLAB
- Trajectory Planning and Path Tracking MATLAB
MATLAB Code and Simulation Files
This project includes complete MATLAB source code, Simulink models, controller implementation files, and detailed documentation to help researchers understand autonomous lane change modeling and control.
Frequently Asked Questions
What is autonomous lane change control in MATLAB Simulink?
Autonomous lane change control in MATLAB Simulink refers to the simulation of a self-driving vehicle that can detect, plan, and perform safe lane transitions using vehicle dynamics and control algorithms.
Which software is used for this simulation?
This project is implemented using MATLAB Simulink for autonomous vehicle modeling, trajectory generation, and controller development.
What are the applications of this project?
This project is useful in autonomous driving research, ADAS system development, intelligent transportation studies, and automated vehicle controller design.
MATLAB Projects for PhD Research
Matlab Projects CODE provides advanced MATLAB and Simulink based research projects for PhD scholars, postgraduate students, and engineering researchers working in power electronics, renewable energy systems, electric vehicles, battery management systems, control systems, autonomous vehicles, and artificial intelligence applications.