İzmir Ekonomi Üniversitesi
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  • GRADUATE SCHOOL

    Ph.D. In Electrical-Electronics 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
    Course Lecturer(s)
    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

    The students who succeeded in this course;

    • Will be able to define components and principles of operation of autonomous vehicles
    • Will be able to design autonomous vehicle hardware and software
    • Will be able to apply localization and mapping methods using LIDAR, IMU, GPS and other sensors.
    • Will be able to develop simultaneous localization and mapping packages using ROS
    • 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
    X
    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 Weigthing
    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
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information.
    -
    -
    -
    X
    -
    2 Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations.
    -
    -
    -
    X
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines. Knows and applies the research methods in studies of the area with a high level of skill.
    -
    X
    -
    -
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    X
    -
    -
    5 Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions. Can independently realize novel studies that bring innovation to the field, or methods, or design, or known methods.
    -
    -
    X
    -
    -
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    -
    X
    -
    7 Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process. Performs critical analysis, synthesis and evaluation of new and complex ideas.
    -
    -
    -
    X
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
    -
    -
    -
    X
    -
    9 Engages in written and oral communication at least in Level C1 of the European Language Portfolio Global Scale.
    -
    -
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    -
    X
    -
    11 Evaluates the results of scientific, technological and engineering research and development activities in terms of the social, environmental, health, safety and legal aspects. Examines social relations and norms related to the field, and develops and makes attempts to change them if necessary. Knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.
    -
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.
    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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