Executive Programs

Workshops

Projects

Blogs

Careers

Student Reviews

For Business

Academic Training

Informative Articles

Find Jobs

We are Hiring!

All Courses

Choose a category

All Courses

Autonomous Vehicle Controls using MATLAB and Simulink

Pursue the 3-month autonomous car course curated by industry experts and gain in-demand skills. Our mentor-led course will take you through the advanced concepts essential for developing ADAS control systems using MATLAB and Simulink.

Approved Training Partner

RELATED RECENT PLACEMENTS

Rohit Mali

William O'Neil India

NMIMS MUMBAI

Dhiraj Satghare

RD Civil Solution

Acharya Shrimannarayan Polytechnic

Namrata Rao

Piaggio & C. S.p.A.

Rajeev Gandhi College of Engg and Research Institute

Siddhi Parab

C.C Engineers

lokmanya tilak college of engineering

Anil Katarkar

3D engineering

NATIONAL INSTITUTE OF TECHNOLOGY

Bhavesh Kumbhare

Dar Al-Handasah Engineering company

Rashtrasant Tukadoji Maharaj Nagpur University

Akash Bhadkumbe

XS CAD

Dr. D Y Patil College of Engineering & Innovation, Varale

Madhura Joshi

NEILSOFT LIMITED

Government Polytechnic Ratnagiri

& 1200+ more

Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

The students will learn and develop model-based control strategies for driver-assistant systems.
During the coursework, the students will learn the following concepts:
- Various control strategies used to develop automotive systems
- Hands-on experience in developing algorithms and interfaces for driver-assistant technologies
- Model-based system engineering
Also, they will be able to build their own model for level 2 autonomous vehicle features and add modifications to improve the system capabilities
The course will give an overview of the software tools such as MATLAB and Simulink which are widely used in the industry.
The students are exposed to the modern trends and standard practices being followed in the industry right now.
This course forms the foundation for anyone wanting to pursue a career in this domain.

Course Syllabus

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week 1 - Course Overview and Classical control

Course overview:
- Introduction
- Overview of Automotive Systems Engineering
- Program Management – Systems Engineering
Classical Controls Theory Overview
- Stability Pole Zeros
- Transient Performance
- Disturbance and Tracking
- PID Systems
- Gain Selection and Tuning
- Examples Comparing P, PI, PD, PID

Week 2 - Longitudinal Controller Design

Longitudinal Dynamic Model
Aero Drag and Rolling Resistance
Linearizing Longitudinal Model
Controller Design in Simulink
Normal Cruise Control Project
Performance Analysis Using Step Response

Week 3 - Adaptive cruise control model

Design and Develop ACC Control Algorithm and Model in Simulink
- Feature Overview: Implementation, Sensor Sets, etc.
- Headway Control Model
- Speed Control Model
- Switching Logic in State Flow Techniques
- Controller Design and Tuning
- Performance Tuning using Feed-Forward Method

Week 4 - Advanced ACC - ACC Feature Modification

Add Additional Functionality to the Model to Improve ACC Performance.
- CACC overview: Cooperative ACC Model
- Logic Implementation
- A Complete Model with Ego Vehicle and Target Vehicle in Simulink
- Simulation Scenarios and MIL

Week 5 - Lateral Control for Vehicles - Geometric Method

Geometric Control Methods
Pure Pursuit Controller
Lane Keep System Using Pure Pursuit
Stanley Controller
LKS Using Stanley

Week 6 - Lateral Controller Model for Vehicles- Dynamic Modeling

Lateral Control Model Elements and Overview
Bicycle Model
Tire Model
State Equation for Lateral Control Model
Introduction to MPC
Controller Design using MPC
Integration and Modelling in MATLAB

Week 7 - Lane Centering Assist

Develop a Level 2 Model for Lane Centering Assist
- Lane Center Assist Logic
- Feature Boundary Diagram and Functions
- Steering Path Polynomial
- Mode Manager and Fault Manager Design
- Switching Logic for Scenarios
- Model in Simulink

Week 8 - Complete Level 2 Feature Model - Autopilot

Combine the Models Developed Previously into a Single-vehicle Model and Simulate Scenarios with all Active Features
- Introduction to System Architecture
- Introduction to Electronic Horizon, HD Maps

Week 9 - LCA Modification: Assisted Lane Biasing and Assisted Lane Change

Assisted Lane Biasing Logic and Implementation
Assisted Lane Change Logic
Path Planning for ALC
Path Planning Function with LCA Model

Week 10 - Combined Controller - 5 DOF

Combined Model of Lateral and Longitudinal Control
Vehicle Dynamic Derivation for State Matrices
State-Space Mathematics for 5 DOF System
Implement a Single Controller System in Simulink

Week 11 - Advanced Topics in Controls for Autonomous Driving- Part 1

Predictive Speed Assist
- Introduction to Predictive Speed Assist and Intelligent Speed Assist
- Curve Speed Control Derivation
- Pseudo Code for PSA and ISA
- Integration of PSA with Velocity Control Logic
Control for Roundabout Scenarios
Minimum Risk Manuevers

Week 12 - Advanced Topics in Controls for Autonomous Driving- Part 2

AV Special Applications
- Off-road Mining
- Logistics and Supply Chain
- Agricultural Activities
- Smart Mobility
AV Special ODs
- Toll Gates
- U-turns in Dead-end
Other Control Techniques
- Cascade Control
- Nonlinear MPC
- Sliding Mode Control
Future Topics for Research
- Deep Reinforcement Learning
- Machine Learning Applications in AVs

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Design and Develop Adaptive Cruise Control Model in Simulink

In this project, the students will create a green wave traffic assist feature that recommends vehicle speeds such that the vehicle can be driven in the green wave and minimise stop time in traffic. The students will design and develop an ACC control algorithm and model in Simulink.

Develop an Integrated Automated Driving Model

In this project, the students will develop a level 2 model for lane centering assist and analyze the performance of different controller designs at different road/vehicle scenarios. They will gain hands on experience to develop an integrated automated driving model.

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

4.8

Learn how to design self-driving cars with our Autonomous Vehicle Controls using MATLAB and Simulink course.

The primary goal of this 3-month autonomous vehicle course is designed to give students a hands-on approach to learning and developing model-based control strategies for driver-assist systems.

There was an increase of 163% in the number of Electric Vehicles that were registered in India during the FY 2021 constituting 1.7% of the total petrol vehicles sold in the same year. This increase in EV sales has directly contributed to an increase in the number of ADAS-trained engineers in the ecosystem.

Who Should Take This Course?

This certification course in autonomous vehicles forms the foundation for anyone wanting to pursue a career in this domain.

Students who want to Design and Develop Adaptive Cruise Control Model in Simulink and students who want to Develop an Integrated Automated Driving Model can ernoll in Skill-Lync’s autonomous vehicle course.

What Will You Learn in This Course?

This 12-week course on autonomous vehicle controls will train you in learning and developing model-based control strategies for driver-assistant systems. During this autonomous vehicle course, students will learn about,

Various control strategies are used to develop automotive systems,
Hands-on experience in developing algorithms and interfaces for driver-assistant technologies
Model-based system engineering

Students will also be able to will be able to build their own model for level 2 autonomous vehicle features and add modifications to improve the system's capabilities. The course will give an overview of the software tools such as MATLAB and Simulink which are widely used in the industry.

Towards the end of the autonomous car course, you will be equipped with cutting-edge technologies like MATLAB and Simulink. MATLAB and Simulink are used to develop path-planning control algorithms and vehicle control systems. Using these powerful tools, you can test, generate or debug codes of different sub-systems of autonomous cars.

This autonomous course will give you an overview of automotive and program management system engineering. Our experts will teach industry-standard techniques and methodologies for designing intelligent driver assistant systems.

Skills You Will Gain

You will design and develop an ACC control algorithm and model in Simulink.
You will learn how to develop a level 2 model for lane centring assist and analyze the performance of different controller designs in different road/vehicle scenarios
By working on real-time projects, you will become industry-ready.
You will gain industry experience in Simulink.

Key Highlights of the Program

The duration of the course is 12 weeks.
Besides the course completion certificate for all participants, the top 5% of learners get a merit certificate.
You will get Individual Video Support, Group Video Support, Email Support, and Forum Support to clear your queries and doubts.
Real-time industry-relevant projects will make your learning purposeful.

Why Should You Pursue the Autonomous Vehicle Dynamics and Control Control Course?

Skill-Lync's automobile sensors course is focused on imparting the key technical skills that are required by the industry. We constantly revise our car control course curriculum to make it aligned with the new trends and techniques that are being discovered.
We are the pioneer in providing advanced autonomous vehicle courses in India for engineers like you and are on a mission to level up the engineering workforce. This self-driving car course delves deep into the essential technicalities and teaches the most in-demand software tools as per industry standards.
Combined with our unique pedagogy, the autonomous vehicle dynamics and control course can help you either kick-start or advance your career if you are a professional.

Career Opportunities after Taking This Course

Senior software engineer
ADAS test engineer
Engineering technical writer
Architect ADAS
ADAS EE feature owner

FAQs on Autonomous Vehicle Controls using MATLAB and Simulink

Who can take up these autonomous vehicle certification courses?

Students and graduates with a technical background in electrical engineering and mechanical engineering can opt for this course.

Is this an online autonomous vehicle course?

Yes, this is a 100% online course.

What is an autonomous vehicle?

A conventional vehicle that has automated its driving parameters. Autonomous driving does not just include self-driving cars, it includes proximity sensors that warn the user when a vehicle is approaching your vehicle or cruise controls that ensure a static speed while driving on the highway.

What is the fee for this autonomous vehicle online course?

The fee structure is flexible, and you can choose a plan that suits you. The basic plan would give you two months of access, the pro plan would give you four months of access, and the premium plan would give you lifetime access.

How much can a machine learning engineer earn?

According to Glassdoor, the average salary of a machine learning engineer is INR 8 LPA. After completing this course, you can also earn this average pay, and you can expect more once you become an experienced professional.

Is there any certificate for completing this Autonomous Vehicle Controls using MATLAB and Simulink course?

Yes, After completing this Autonomous Vehicle Controls using MATLAB and Simulink course, you shall be given a course completion certificate. The top 5% of the scorers will be given a merit certificate alongside the course completion certificate.