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Training Center Classroom

Welcome to this installment of EE Classroom on ADAS!

Whether or not you want a self-driving car, there’s no arguing that most drivers need “assistance”, which makes ADAS a formidable technology. But it is also a tricky one involving a unique blend of sensors, microcontrollers, cameras — and a fair amount of regulation, not surprisingly given drivers are being asked to have faith in almost one-and-a-half tons of steel in which are buried hundreds of automotive MCUs.

It’s a new learning curve for many, and this classroom is here to help. Neural network software (and the memory to accommodate it), ADAS sensors, LiDAR, are just some of the technologies that allow a car to “see”. How and why? Start with tutorials here. And while there may never be a final word on safety and security, we’ve got enough words in our basics and beyond to understand the discussions further.

Note: There is no grading here — and no grading on the curve…

Aimee Kalnoskas

Editor in Chief, EE World Online

ADAS Classroom Sponsored by

 Sensors  •  Microcontrollers

What is LiDAR and Time of Flight?

Automous vehicle sees with LiDAR eyes

The tricky business of teaching cars to see

The role of ADAS sensors in automotive design

ADAS is designed to prevent deaths and injuries and also seen as a stepping stone toward fully automated vehicles.

There are a lot of vision technologies and sensors available, but fine-tuning them has proved to be challenging.

Neural network software functions only vaguely in the way it has been explained to the general public.

LiDAR systems and ToF techniques are critical to providing self-driving cars with a detailed picture of the surroundings.

Related Resources

The Drive Towards the Software-Defined Vehicle Built on Ethernet

Current Trends in Autonomous Vehicle Adoption

INICnet™ Technology for Automotive Multimedia Networking – Part 1

INICnet™ Technology for Automotive Multimedia Networking – Part 2

Safety  •  Security  

What does automotive qualification mean?

Navigating in-vehicle network communications securely

Technical challenges of automated vehicles

What are ASILs and how do they work?

Features and technologies needed for automated driving are being developed incrementally, with some already in use.

ASIL risk classification system including how ASILs work, challenges when using ASILs and how ASILs are evolving.

Automotive qualification is not a static landscape in a world of the emergence of new technologies.

Connections via Bluetooth, USB, LTE, 5G, Wi-Fi, and more have dramatically increased a vehicle's attack surface.

Memory  •  Software   

Memory and functional safety in autonomous vehicles

Flash memory keeps cars connected

Open standards for driverless cars

How to improve ADAS with hardware

Learn why unsafe autonomous vehicle systems are passing undetected during development.

The demand for NAND is growing with the rise of ADAS technology and autonomous piloting functions.

Designers need a deeper understanding of DRAM and its impact as software expands in vehicles.

Deep learning for autonomous vehicle systems requires a blended software and hardware strategy.

Microchip Technology Inc. is a leading provider of smart connected and secure embedded control solutions. Its easy-to-use development tools and comprehensive product portfolio enable customers to create optimal designs which reduce risk while lowering total system cost and time to market. The company’s solutions serve more than 120,000 customers across the industrial, automotive, consumer, aerospace and defense, communications and computing markets. Headquartered in Chandler, Arizona, Microchip offers outstanding technical support along with dependable delivery and quality.

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