Introduction to Self-Driving Car Technology
Do you want to learn a technology that has been dubbed the 21st century gold rush? Are you ready to catch a business wave that is expected to add $7 trillion to the global economy each year? Do you want to master engineering skills that are sought after by the tech giants like Google, Apple, Intel, and IBM, as well as every significant automaker like Toyota, GM, Ford, Tesla, Uber, Lyft, not to mention countless startups?
If the answers are yes, this new course at Santa Clara University School of Engineering is for you.
Term: Winter 2019
Course Title: Introduction to Self-Driving Car Technology
Course Number: ELEN 239 (Special Topics)
Course Description:
The main goal of this course is to introduce students to self-driving cars systems. The course will use an open source initiative software for self-driving cars systems to teach you everything you need to know in order to understand, operate, maintain, and enhance this newly emerging technology. Students will gain hands-on experience on the major modules of the system including localization, sensor fusion, perception, detection, segmentation, scene understanding, tracking, prediction, path planning, control, routing, and decision making. You will also learn the in-vehicle robotic operating system, and the datacenter offline operations needed to enable an autonomous vehicle. The lectures, the labs, and the assignments are all designed to work in the overall integrated real-world system to give you teamwork experience with large scale software development.
Course Objectives:
At the end of the quarter, students are expected to:
- Understand the technologies used in autonomous vehicle systems.
- Understand the challenges involved in building an autonomous system.
- Understand the open source initiative for self-driving cars systems as a tool to teach how to understand, operate, maintain, and enhance this newly emerging technology.
- Know how to operate, maintain, and modify the important modules in the self-driving car systems.
Prerequisite: First year ELEN, COEN, MECH graduate standing and knowledge of programming
Number of Units: 4 units
Required Textbook: Creating Autonomous Vehicle Systems, by Shaoshan Liu et al., M&C Publishers, 2018
Course Outline:
The course is designed for a quarter term of 10 weeks and 20 lectures of 2 hours each.
Lecture 1: Autonomous Vehicle Systems Overview: Hardware, Software, Technologies, Algorithms, Architecture.
Lectures 2-5: Localization Techniques in Self-Driving Cars: GNNS, INS, GPS, LiDAR, Odometry, Sensor Fusion.
Lectures 6-7: Perception Methods in Self-Driving Cars: Detection, segmentation, scene understanding, tracking.
Lectures 8-9: Machine and Deep Learning in Self-Driving Cars: CNN for Perception and Localization.
Lectures 10-12: Prediction Technologies in Self-Driving Cars: Path Planning, Control, Routing.
Lectures 13-16: Decision Making Methods in Self-Driving Cars: Motion Planning, Feedback Control Systems.
Lecture 17: Learned Decisions in Self-Driving Cars: Learning based planning and control.
Lectures 18-19: In-Vehicle OS and Computing in Self-Driving Cars: ROS environment, Computing Platform.
Lecture 20: Datacenter and Offline Operations in Self-Driving Cars: Cloud, Simulations, Training, HD map.
Questions? Contact Prof. Tokunbo Ogunfunmi (Email: TOgunfunmi@scu.edu)