TRON08021 2019 AV Sensor Systems
Full Title
AV Sensor Systems
Transcript Title
AV Sensor Systems
Code
TRON08021
Attendance
N/A %
Subject Area
TRON - Electronics
Department
COEL - Computing & Electronic Eng
Level
08 - Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2019 - Full Academic Year 2019-20
End Term
9999 - The End of Time
Author(s)
Sean Mullery, Eva Murphy, Shane Gilroy
Programme Membership
SG_EELEC_H08 202000 Bachelor of Engineering (Honours) in Electronics and Self Driving Technologies
SG_EROBO_H08 202000 Bachelor of Engineering (Honours) in Robotics and Automation
SG_EROBO_H08 202400 Bachelor of Engineering (Honours) in Robotics and Automation
SG_EROBO_H08 202500 Bachelor of Engineering (Honours) in Robotics and Automation
Description
This module investigates the physical and technical foundations, strengths and weaknesses of sensor systems used in Advanced Driver Assistance Systems and Self-Driving Vehicles.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Assess optical radiation, radiometric and photometric quantities.
2.
Explain the hardware architecture of visible and infrared spectrum camera systems and their role in the automotive environment.
3.
Summarise the functional characteristics and properties of modern Lidar, Radar, Ultrasonic and other relevant sensor systems and their applications in self-driving vehicles.
4.
Evaluate the strengths and weaknesses of sensing technologies for specific applications in autonomous vehicles.
5.
Select suitable sensor systems for perception and localisation tasks in self-driving vehicles
Teaching and Learning Strategies
Lecture & Practical
Module Assessment Strategies
CA & Final Exam
Repeat Assessments
Autumn
Indicative Syllabus
- Optical Sensor Systems
- Automotive Cameras
- Photodiode & pixel operation
- Image sensor operation and performance criteria
- Colour generation in digital cameras
- Hardware architecture of Mono and stereo camera systems
- Camera design considerations and their impact on performance - sensitivity, resolution, dynamic range, frame rate etc.
- Use cases, applications and limitations of camera systems for perception in the automotive environment
- Use cases, applications and limitations of camera systems for localisation in the automotive environment
- LIDAR system architecture. operational characteristics, quantities & performance criteria and applications & limitations in the automotive environment
- Radar system architecture. operational characteristics, quantities & performance criteria and applications & limitations in the automotive environment
- Ultrasonic sensor system architecture. operational characteristics, quantities & performance criteria and applications & limitations in the automotive environment
- GPS, Inertial measurement units, dead reckoning sensor systems for perception and localisation in the automotive environment
- Complementary technologies and sensor fusion
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
%
End of Semester / Year Formal Exam
%
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Coursework & Continuous Assessment | Coursework Assessment | Assessment | 40 % | OnGoing | 1,2,3,4 |
End of Semester / Year Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Final Exam | Final Exam | Closed Book Exam | 60 % | End of Semester | 1,2,3,4,5 |
Full Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Lecture Theatre | Lecture | 2 | Weekly | 2.00 |
| Practical / Laboratory | Computer Laboratory | Laboratory Practical | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Independent Learning | 3 | Weekly | 3.00 |
Total Full Time Average Weekly Learner Contact Time 4.00 Hours
Online Learning Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Not Specified | Lecture | 2 | Weekly | 2.00 |
| Directed Learning | Not Specified | Practical/Tutorial | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Independent Learning | 3 | Weekly | 3.00 |
Total Online Learning Average Weekly Learner Contact Time 2.00 Hours
Required & Recommended Book List
Recommended Reading
2017-10-25 Creating Autonomous Vehicle Systems Synthesis Lectures on Computer
ISBN 1681730073 ISBN-13 9781681730073
2017-10-25 Creating Autonomous Vehicle Systems Synthesis Lectures on Computer
ISBN 1681730073 ISBN-13 9781681730073
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map--plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
Recommended Reading
2017-04-17 Computer Vision in Vehicle Technology John Wiley & Sons
ISBN 9781118868072 ISBN-13 1118868072
2017-04-17 Computer Vision in Vehicle Technology John Wiley & Sons
ISBN 9781118868072 ISBN-13 1118868072
A unified view of the use of computer vision technology for different types of vehicles Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment). The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. Key features: Presents the latest advances in the field of computer vision and vehicle technologies in a highly informative and understandable way, including the basic mathematics for each problem. Provides a comprehensive summary of the state of the art computer vision techniques in vehicles from the navigation and the addressable applications points of view. Offers a detailed description of the open challenges and business opportunities for the immediate future in the field of vision based vehicle technologies. This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.
Recommended Reading
2011-01-01 CMOS/CCD Sensors and Camera Systems Society of Photo Optical
ISBN 0819486531 ISBN-13 9780819486530
2011-01-01 CMOS/CCD Sensors and Camera Systems Society of Photo Optical
ISBN 0819486531 ISBN-13 9780819486530
The fully updated edition of this bestseller addresses CMOS/CCD differences, similarities, and applications, including architecture concepts and operation, such as full-frame, interline transfer, progressive scan, color filter arrays, rolling shutters, 3T, 4T, 5T, and 6T. The authors discuss novel designs, illustrate sampling theory and aliasing with numerous examples, and describe the advantages and limitations of small pixels. This monograph provides the very latest information for specifying cameras using radiometric or photometric concepts to consider the entire system--from scene to observer. Numerous new references have also been added.
Module Resources
Journal Resources
IEEE Transactions on Intelligent Transportation Systems