ECE 59500 - Introduction to Connected and Automated Vehicles

Course Details

Lecture Hours: 3 Credits: 3

Areas of Specialization:

  • Automatic Control

Counts as:

  • EE Elective
  • CMPE Selective - Special Content

Normally Offered:

Each Spring

Campus/Online:

On-campus and online

Requisites:

Prerequisites: Linear Algebra (MA 26500 or equivalent), Probability (ECE 30200 or equivalent), and Programming (ECE 20875 or equivalent)

Requisites by Topic:

Undergraduate understanding of Linear Algebra, Probability, and Programming

Catalog Description:

This course introduces the basic concepts, components, and technologies of connected and automated vehicles. Vehicle modeling, dynamics, control, and several advanced driver assistance systems (ADAS) will be introduced. Key technologies associated with automated driving, including sensors, perception, communication, mapping and localization, decision-making, and control will be presented and discussed. MATLAB/Simulink and its toolboxes will be used.

Required Text(s):

None.

Recommended Text(s):

  1. Advances in Intelligent Vehicles , Yaobin Chen and Lingxi Li (eds) , Academic Press , 2013 , ISBN No. 978-0123971999
  2. Autonomous Ground Vehicles (ITS) , Umit Ozguner, Tankut Acarman, and Keith Redmill , Artech House , 2011 , ISBN No. 978-1608071920
  3. Handbook of Intelligent Vehicles , Azim Eskandarian (ed.) , Springer , 2012 , ISBN No. 978-0857290847

Learning Outcomes

A student who successfully fulfills the course requirements will have demonstrated an ability to:

  • Explain the basic concepts related to CAVs development, vehicle structure, components, dynamics, and control.
  • Understand working principles of typical vehicular sensors and apply them into various advanced driver assistance system (ADAS) functions.
  • Explain various concepts and apply technical approaches in image processing and computer vision into CAV applications.
  • Compare and use various localization, decision-making, and control methods for CAV applications
  • Use computer-aided tools for the analysis and design of CAVs

Lecture Outline:

Unit Number Topic
1 Course overview
2 Introduction to connected and automated vehicles
3 Vehicle structure and components
4 Vehicle dynamics and control
5 Sensors and sensing technologies
6 Advanced driver assistance systems
7 Image processing and computer vision
8 Simultaneous localization and mapping
9 Decision-making and motion planning
10 Vehicle motion control

Assessment Method:

Homework, projects, exams. (11/2025)