Browse Learn C1896

LIDAR and Infrared Cameras for ADAS and Autonomous Sensing C1896


This two-day seminar examines ADAS and autonomous vehicle technologies that have disrupted the traditional automotive industry with their challenges and potential to increase safety while attempting to optimize the cost of car ownership. LIDAR and Infrared camera sensing are seeing a rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve almost every six months. This course will provide the foundation to build on for these two technologies in automotive applications. It will include a demonstration model for LIDAR and Infrared camera.

The seminar will begin with a review of Infrared basics - electromagnetic spectrum, spectral irradiance, night vision and eye safety. We will then dive into LIDAR – flash, scanning, wavelengths, lasers, detectors, scanners, range and resolution calculations, optics, thermal design, challenges to automotive qualification and sensor fusion. The second half will cover Infrared camera topics with focus on driver monitoring for interior and machine vision for exterior. We will review rolling and global shutter imagers, wavelength selection, use of secondary optics, continuous vs pulsed IRED operation, thermal design, power consumption, eye safety certification and HMI considerations. A brief review of iris recognition, cabin monitoring and face recognition. We will end with a short discussion on trends and challenges facing optical sensing in autonomous vehicles.


Learning Objectives
Upon completion of this course the participants will be able to:
  • Comprehend electromagnetic spectrum, spectral irradiance, night vision and eye safety
  • Describe various LIDAR architectures based on key design parameters
  • Formulate LIDAR requirements based on an understanding of system edge use cases
  • Prescribe Infrared camera requirements with a comprehension of key variables
  • Calculate IRED and Laser power requirements to meet system needs
  • Gain an overview of challenges and opportunities for sensing trends in ADAS and AV

Who Should Attend
Audience can be comprised in all types of engineers, specifically Mechanical, Lead, Application, Electronical Engineers along with Head of Innovation and BOM Family Owner. Anyone involved in active safety, LIDAR, driver monitoring, machine vision and automated driving would benefit from attending.

Prerequisites
An undergraduate engineering degree or a strong technical background is highly recommended. A basic knowledge of college algebra, college physics, and a basic awareness of LIDAR and Infrared camera applications in ADAS and autonomous vehicles will be beneficial.
DAY ONE
  • ADAS and Autonomous Sensing
    • Market Forces shaping Industry
    • Regulation landscape
    • From Guidelines to Regulation – Typical path
    • ADAS – NCAP & IIHS rating
    • NHTSA Autonomous Driving Guideline
    • NHTSA Autonomous Levels
    • Human Vs Autonomous Driver
    • LIDAR, Camera, RADAR - Overview
    • Sensor Fusion – Need for Holistic View
    • The Importance of HMI for Level 3
  • Infrared Basics
    • Electromagnetic spectrum
    • Infrared Energy, wavelength and temperature
    • Photometric and Radiometric units
    • Eye sensitivity to light – Visible and Infrared
    • Photopic, Scotopic and night vision
    • Eye Safety Basics
    • Near Infrared Classifications
    • Spectral irradiance on earth – day and Night (Ambient noise)
    • Photon energy calculation
  • LIDAR Topics
    • LIDAR basics – Laser, Detector, Range calculation
    • Laser Basics
    • Laser types – Edge Emitter, VCSEL, Multimode, Single Mode, stacked, Fiber, single channel, Arrays
    • Detector Basics
    • Detector options – PIN Photodiode, APD, SIPM, Arrays, NIR Enhanced CMOS
    • Wavelength Selection – 905nm, 1550nm, others
    • Laser & Detector Considerations
      • Laser Packages - Bare die, Through Hole, Surface Mount
      • Detector Packages – Through Hole, Arrays
      • Matched Sensitivity of Laser and Detector
      • Wavelength Shifts
      • Temperature and efficiency
      • Heat dissipation
      • EMC and ESD considerations
      • Reduction in Performance due to rain, Fog, Snow
    • Types of LIDAR – Flash, Scanning, Time-of-Flight, FMCW
    • Scanner Types – Mechanical Mirrors, MEMS Mirror, Optical phase Arrays, Liquid Crystal scanning
    • Developing requirements for LIDAR
      • System Latency and Range
      • Field of view and resolution
      • Frame Rate, Power Consumption
      • Form factor and Packaging Considerations
    • Signal to Noise ratio – Ambient noise considerations
    • Eye Safety
      • Laser Class
      • IEC and ANSI standards for Laser Safety
      • Example of limit calculation (AEL, MPE)
      • Certification
    • Optical challenges for LIDAR
    • Laser drivers – need, challenges for high current and low pulse width
    • Cost reduction – opportunities and challenges
    • Automotive Qualification and ASIL D standard
DAY TWO
  • Camera and Image Processing Basics
    • Image Sensor Array
    • Aperture Size
    • Thin Lens Optics
    • FOV, Range, Image Size, Resolution
    • Frame Rate, Shutter Speed and image Accuracy
    • Rolling and Global shutter Camera
    • NIR sensitivity of CMOS cameras
  • Infrared Camera Topics
    • IR illumination sources and efficiency
    • IR Illumination calculations (# of infrared LED)
    • Eye Safety for LED (60 mins)
      • IEC and ANSI standards
      • Example of limit calculation (AEL, MPE)
      • Certification
      • Hazard Zone intrusion – Design Strategies
    • Driver Monitoring with NIR
      • System requirements
      • Wavelength Selection
      • Image sensor selection
      • Use of secondary optics
      • Continuous vs Pulsed operation of IRED
      • Thermal design
      • Power consumption
      • Wavelength Shift
      • Eye Safety – certification
      • Human Machine Interface considerations
    • Exterior Camera with NIR
      • Need for application – Sensor fusion gaps
      • System requirements
      • Power consumption challenges
      • Illumination concepts
      • Integration to Vehicle Headlamps and Tail lamps
      • Use of simulation Software
  • Other Infrared camera applications and Trends
    • Iris Recognition
    • Face Recognition
    • Cabin Monitoring
    • Mood Lighting
    • Gesture Recognition
  • Autonomous Vehicles and Optical Sensors
    • Trends and challenges
    • Artificial Intelligence
    • New Sensing Technologies on Horizon
    • Working with startups, Tier1, Tier2, OEM and other Eco system partners
Rajeev Thakur

Rajeev Thakur is currently Regional Marketing Manager at OSRAM Opto Semiconductors - responsible for infrared product management and business development in the NAFTA automotive market. His current focus is on LIDAR, driver monitoring, night vision, blind spot detection and other ADAS applications.
 
Thakur joined OSRAM Opto Semiconductor in 2014. He has prior experience in the Detroit automotive industry since 1990 – working for companies such as Bosch, Johnson Controls and Chrysler. He has concept-to-launch experience in occupant sensing, seating and power train sensors. He holds a masters degree in Manufacturing engineering from the University of Massachusetts, Amherst and a bachelors degree in Mechanical engineering from Guindy engineering college in Chennai, India. He is a licensed professional engineer and holds a number of patents on occupant sensing. He is also a member of the SAE Active Safety Standards development committee and a reviewer for IEEE Intelligent Transportation Systems Transactions.

Hotel & Travel Information

Fees: $1415.00
SAE Members: $1415.00 - $1415.00

1.3 CEUs
You must complete all course contact hours and successfully pass the learning assessment to obtain CEUs.

To register, click the Register button above or contact SAE Customer Service 1-877-606-7323 (724-776-4970 outside the U.S. and Canada) or at CustomerService@sae.org.

Duration: 2 Days
March 5-6, 2019 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
August 6-7, 2019 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
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