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Driverless Vehicle Course by Formula Bharat
Rating: 4.2 out of 5(7 ratings)
58 students

Driverless Vehicle Course by Formula Bharat

Explore the world of Autonomous Vehicles
Created byCuriosum Tech
Last updated 9/2024
English
English [Auto],

What you'll learn

  • Advanced data analysis and AI/ML, Radar antenna design and implementation, ADAS, Advanced simulation to assist DV development.
  • Path Planning and trajectory control with visual cone detection, Getting started with ROS.
  • Real-time simulation using Typhoon HIL.
  • Simultaneous Localization and Mapping (SLAM) and Sensor Fusion.
  • Creation of Real-world environment in simulations.
  • Understanding modern time autonomous technology, cybersecurity, functional safety, deep learning and computer vision algorithm.

Course content

7 sections • 51 lectures • 32h 12m total length

  • Introduction to the Speaker0:26

    Discover integrated system of systems simulation that connects od, 1d, and 3d core simulations for driverless vehicles, hosted by Altair and presented by Manish K.V.

  • M1-Integrated system-of-systems simulation connecting 0D, 1D & 3D co-simulations1:00:51

    • Explore the virtual system level modelling connecting multiple physics to build the complex vehicle. Further, build virtual controls systems for various technologies like obstacle detection, cruise control, collision avoidance and emergency braking etc.

    • Utilize the flexibility by connecting with virtual reality engines like Unreal engine, Carla. Validate various scenarios in Carla which is an autonomous driving research engine.

  • Introduction to the Speakers3:12
  • M2 - Advanced data analytics & AI/ML to enable Real time Digital Twins1:24:42

    • Data analytics and machine learning are now an integral part of autonomous vehicles as self-driving cars need the human brain and eye.

    • Explore AI/ML starting from easily prepping the data from any source, developing models to production and process massive data generated over the tests.

  • Introduction to the Speakers1:02
  • M3 - Radar Antenna Design and Integration41:40

    • Apply a wide array of engineering for antennas: from design to placement to communication.

    • Accurately simulate radar antenna design & integration aspects, including radome, bumper effects and a solution for ultrasonic sensors.

    • Explore 5G Antenna design and placement, 5G wave propagation models and ray-tracing for the next generation connectivity.

  • M4 - Virtual Drive Tests for ADAS Radar Sensors and Communication Antennas16:41

    • Apply a full environment including buildings, cars and street objects to get accurate representations of the radio waves impinging on the antennas and the multipath radar channels including reflections, diffractions and scattered contributions.

    • Allow realistic and fully reproducible evaluations of different options for the antennas and sensors including their integration and configuration.

  • Introduction to the Speaker3:03

    Explore embedded system design and open vision for ADAS, focusing on image and video processing for driverless cars within a model-based development framework.

  • M5 - Embedded System Design & Open Vision for ADAS37:53

    • Design, analysis and algorithm development for image and video processing, and real time implementation .

    • Develop OpenVision applications including Lane detection / tracking, object detection, avoidance, lane keep assistance and many others.

    • Automatic Code generation and deployment on Microprocessors like Rasberry Pi and AMD64.

  • Introduction to the Speaker3:33
  • M6 - Advanced Simulations to Assist Development of Autonomous Vehicles1:02:27

    • Electrical and Electromechanical device simulations using Altair Flux.

    • Learn virtual development using CFD for autonomous vehicle design improvement.

    • Advanced structural analysis and optimization.

    • Efficient product development with simulation driven rapid design.

Requirements

  • Basic understanding of Automobile technology, AI/ML, ROS, and Sensors.
  • Interested to learn about autonomous vehicles and technology

Description

Are you struggling to understand the complexities of driverless vehicle? Are you finding it challenging to design a compliant autonomous driving system? Are you finding it difficult to efficiently plan and manage your autonomous vehicle project? This course is here to eliminate those concerns.

What You'll Learn:

  • Advanced data analysis and AI/ML, Radar antenna design and implementation, ADAS, Advanced simulation to assist DV development.

  • Path Planning and trajectory control with visual cone detection, Getting started with ROS.

  • Real-time simulation using Typhoon HIL.

  • Simultaneous Localization and Mapping (SLAM) and Sensor Fusion.

  • Creation of Real-world environment in simulations.

  • Understanding modern time autonomous technology, cybersecurity, functional safety, deep learning and computer vision algorithm.

  • Experience of FS Teams.

  • Various available software for driverless.

Course Highlights:

  • Understanding Autonomous vehicles with the technology used in the current world.

  • Comprehensive coverage of Engineering used in the development of Autonomous Vehicles on software stack, including -
    - Data analysis and Machine learning
    - ADAS Radar sensor and Communication Antenna
    - Simultaneous Localization and Mapping (SLAM)
    - Real-time simulation using Typhoon HIL
    - ROS and Sensor Fusion
    - Modern day autonomous vehicle technology

Program Basis: The course contains sessions from industrial experts working in automobile and autonomous systems. This course does not contain any rule adaptation of the formula student driverless category

Course Outcome: By the end of this course, you will be able to develop your software stack for autonomous vehicle using various tools and software.

Who this course is for:

  • Anyone interested to learn about automobile, autonomous vehicle technology.
  • Anyone who is part for Formula Student DV Cup category.
  • Anyone who will be joining Formula Student DV Cup category.

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