Ph.D. In Computer Engineering

EEE 527 | Course Introduction and Application Information

Course Name

Principles of Autonomous Vehicle Design

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
EEE 527	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	Prof. Dr. Süha Bayındır
Course Lecturer(s)	Prof. Dr. Süha Bayındır
Assistant(s)	-

Course Objectives

This course aims at introducing the concepts of how autonomous cars operate and teaching the state of the art technologies required for localization, sensor fusion, SLAM, avoiding obstructions, recognizing the road lane markings, traffic signs, traffic prediction, lane level routing, reliability and security.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	Will be able to define components and principles of operation of autonomous vehicles
2	Will be able to design autonomous vehicle hardware and software
3	Will be able to apply localization and mapping methods using LIDAR, IMU, GPS and other sensors.
4	Will be able to develop simultaneous localization and mapping packages using ROS
5	Will be able to test the performance and reliability of autonomous vehicles under lab and industrial conditions

Course Description

In this course, localization, object recognition, tracking, sensor fusion, mapping, avoiding obstructions in autonomous vehicles will be explained and Python based perception, motion planning and navigation techniques using Robot operating System (ROS) environment will be taught.

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Introduction to Autonomus Driving, Sensing, Perception, Object Recognition & Tracking, ROS	Shaoshan Liu et. al, “Creating Autonomous Vehicle Systems”, 2018, Chap1
2	Sensing and Perceiving the Environment using wheel encoders, GPS, IMU, Ultrasonic Sensor & LIDAR	Shaoshan Liu et. al, “Creating Autonomous Vehicle Systems”, 2018, Chap2
3	Introduction to Robot Operating System (ROS)	Shaoshan Liu et. al, “Creating Autonomous Vehicle Systems”, 2018, Chap1
4	Introduction to Robot Operating System (ROS) Running ROS on Riders Cloud Platform	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
5	Creating And Configuring ROS Messages, publishers, subscribers and topics	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
6	ROS services, client – server applications	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
7	Kalman and Extended Kalman Filters, sensor fusion	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
8	Map based Navigation using ROS: Navigating a Autonomous Vehicle using Gazebo and RVIZ simulators in ROS	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
9	Tuning Navigation Stack Parameters, Pose of Vehicle And Transformation in 2D and 3D Reference Frames	https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn
10	Prediction & Routing, Traffic Prediction, Lane Level Routing	Shaoshan Liu et. al, “Creating Autonomous Vehicle Systems”, 2018, Chap5
11	Project work on TurtleBot3 using LIDAR, IMU, and Ultrasonic Sensor and Image Processing	TurtleBot3 Burger available in Mechatronics Lab
12	Project work on TurtleBot3 using LIDAR, IMU, and Ultrasonic Sensor and Image Processing	TurtleBot3 Burger available in Mechatronics Lab
13	Project work on TurtleBot3 using LIDAR, IMU, and Ultrasonic Sensor and Image Processing	TurtleBot3 Burger available in Mechatronics Lab
14	Project Presentations
15	Review of the Course
16	Final Exam

Course Notes/Textbooks	1. Creating Autonomous Vehicle Systems, Shaoshan Liu, Liyun Li, Jie Tang, Shuang Wu, Jean-Luc Gaudiot, Morgan & Claypool Publishers, 2017 2. Introduction to Driverless Self-Driving Cars, Lance B. EliotLBE Press Publishing, 2018.
Suggested Readings/Materials	1. Markus Maurer · J. Christian Gerdes Barbara Lenz · Hermann Winner, Autonomous Driving, Springer open, 2016 2. https://www.udemy.com/autonomous-cars-deep-learning-and-computer-vision-in-python/learn/ 3.http://emanual.robotis.com/docs/en/platform/turtlebot3/overview/

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project	1	45
Seminar / Workshop
Oral Exams
Midterm	1	25
Final Exam	1	30
Total

Weighting of Semester Activities on the Final Grade	2	70
Weighting of End-of-Semester Activities on the Final Grade	1	30
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16	5	80
Study Hours Out of Class			0
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments			0
Presentation / Jury			0
Project	1	50	50
Seminar / Workshop			0
Oral Exam			0
Midterms	1	22	22
Final Exam	1	25	25
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Understands and applies the foundational theories of Computer Engineering in a high level.		-	-	-	-	-
2	Possesses a great depth and breadth of knowledge about Computer Engineering including the latest developments.		-	-	-	-	-
3	Can reach the latest information in Computer Engineering and possesses a high level of proficiency in the methods and abilities necessary to comprehend it and conduct research with it.		-	-	-	-	-
4	Conducts a comprehensive study that introduces innovation to science and technology, develops a new scientific procedure or a technological product/process, or applies a known method in a new field.		-	-	-	-	-
5	Independently understands, designs, implements and concludes a unique research process in addition to managing it.		-	-	-	-	-
6	Contributes to science and technology literature by publishing the output of his/her academic studies in respectable academic outlets.		-	-	-	-	-
7	Interprets scientific, technological, social and cultural developments and relates them to the general public with a commitment to scientific objectivity and ethical responsibility.		-	-	-	-	-
8	Performs critical analysis, synthesis and evaluation of ideas and developments in Computer Engineering.		-	-	-	-	-
9	Performs verbal and written communications with professionals as well as broader scientific and social communities in Computer Engineering, by using English at least at the European Language Portfolio C1 General level, performs written, oral and visual communications and discussions in a high level.		-	-	-	-	-
10	Develops strategies, policies and plans about systems and topics that Computer Engineering uses, and interprets the outcomes.		-	-	-	-	-