Simulating Autonomous Vehicles Using MATLAB and Simulink for Student Competitions


Overview

With advancements in the automotive industry, various student competitions have introduced the driverless category, where the goal of the teams is to design and build an autonomous vehicle that can compete in different disciplines. In this technical session, you will learn how MATLAB and Simulink can be used to design automated driving system functionality including sensing, path planning, sensor fusion, and control systems.

We will demonstrate an approach to drive an autonomous vehicle in a closed-loop circuit and will conclude the session with a demo where the task is to drive the vehicle on a track avoiding collision with the cones.

Highlights

  • Overview of MathWorks tools for designing autonomous driving systems
  • Demonstration of examples relevant to student competition teams
  • Getting started technical resources

Who Should Attend

  • Automotive teams
  • Students
  • Academics

Why you should attend?

  • Getting started with Simscape
  • Learn more about physical modeling

Pre-requisites

About the Presenters

Veer Alakshendra

Veer is a technical evangelist at MathWorks India. He focuses on working with student teams in the adoption of MATLAB® and Simulink® in automotive and robotics competitions. While pursuing his Ph.D. from VNIT Nagpur in robotics, he primarily focused on kinematics, dynamics, control design, vibration, and optimization. Veer holds a bachelor's degree in aeronautical engineering from Aeronautical Society of India and a master's degree in mechatronics from NITK Surathkal

Akshra Narasimhan Ramakrishnan

I work as a technical evangelist for automotive ADAS competitions at MathWorks, currently working on the SAE AutoDrive competition. I did my Masters in Electrical and Computer Engineering at Ohio State.  I was the ADAS tech lead for 2 years for a collegiate student competition called the EcoCAR mobility challenge where I worked on the following areas - sensor suite selection and evaluation, sensor data acquisition and visualization, perception algorithm development, and perception system integration and testing.

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