Course

Unit 1

Autonomous vehicle sensor categories – Visible light imaging sensors Intrinsic and Extrinsic camera parameters in Machine vision Stereo vision vs Monocular vision cameras: Wide angle, HD Lens distortion and correction Image correspondence and Stitching (Surround 360 Camera) Camera based object detection -AI-Based Computer Vision.

Unit 2

Automotive RADAR types – Radio frequency bands and standards 2D, 3D and 4D Radars – RADAR frequencies, Wave shapes, detection, False positives and signal processing. LIDAR: Conventional and Imaging: Solid State vs Rotating type LIDARS – Reconstruction of point – cloud data LIDAR/ RADAR based object detection-Scenario generation for safety testing.

Unit 3

GPS, GNSS and IMU sensors and sensing systems, Differential GPS, Ultrasonic sensors, Sensors for V2X Communication (DSRC / CV2X), Object tracking using RADAR, LiDAR and Camera based sensors, Case Studies: Pedestrian detection and tracking, Sign board detection, Trajectory prediction using AI.

Text Books / References

References:

1. Hanky Sjafrie, Introduction to Self-Driving Vehicle Technology, First Edition, Chapman & Hall/CRC, 2019.
2. Winner et al. (Eds.), Handbook of Driver Assistance Systems, Springer Cham, 2016.
3. Luca Venturi and Krishtof Korda, Hands-on Vision and Behavior for Self-Driving Cars, Packt Publishing Limited, 2020.
4. S. Thyagarajan, Introduction to Digital Signal Processing Using MATLAB with Application to Digital Communications, First Edition, Springer International Publishing, 2019.
5. Byron, Radar – Principles, Technology, Applications, Third Indian Reprint, Pearson Education LPE, 2005.
6. Yoshida (Ed.), Guide to Sensors in Automotive: Making Cars See and Think Ahead, Aspencore Media, 2020.

Course Objectives

• To provide insight into the principles of 2-D and 3-D digital signal processing
• To impart understanding the role of RF sensors in self-driving vehicular platform operations
• To enable the realization in functionality of various other ADAS sensor systems

Course Outcomes

• CO01: Ability to understand various sensors in automotive systems
• CO02: Ability to understand the principles of image and video signal processing
• CO03: Ability to apply RADAR sensors and operations in self-driving vehicular platforms
• CO04: Ability to analyze the functioning of various other sensor systems as part of ADAS

CO-PO Mapping

Skills Acquired: Vehicle sensors, Automotive sensor integration and fusion, Scenario extraction