ENG09025 2020 ADAS and Autonomous System Architecture

General Details

Full Title
ADAS and Autonomous System Architecture
Transcript Title
ADAS and Autonomous System Arc
Code
ENG09025
Attendance
N/A %
Subject Area
ENG - Engineering
Department
MENG - Mech. and Electronic Eng.
Level
09 - NFQ Level 9
Credit
05 - 05 Credits
Duration
Semester
Fee
Start Term
2020 - Full Academic Year 2020-21
End Term
9999 - The End of Time
Author(s)
Eva Murphy
Programme Membership
SG_EAUTO_E09 202000 Certificate in Automotive Artificial Intelligence SG_ESENS_E09 202000 Postgraduate Certificate in Sensors for Autonomous Vehicles SG_ECONN_O09 202000 Postgraduate Diploma in Engineering in Connected and Autonomous Vehicles SG_ECONN_M09 202000 Master of Engineering in Connected and Autonomous Vehicles SG_ECOFT_O09 202000 Postgraduate Diploma in Engineering in Connected and Autonomous Vehicles SG_ECONN_M09 202100 Master of Engineering in Connected and Autonomous Vehicles SG_ECONN_O09 202100 Postgraduate Diploma in Engineering in Connected and Autonomous Vehicles SG_ECOFT_O09 202100 Postgraduate Diploma in Engineering in Connected and Autonomous Vehicles SG_EAUTO_E09 202100 Postgraduate Certificate in Automotive Artificial Intelligence
Description

ADAS and Autonomous System Architecture provides the learner with an appreciation for the bigger picture of the automotive industry. The student will gain an understanding of the multi-disciplinary nature of the industry, as well as knowledge of its supply chain. Different system architectures and design constraints are introduced.

Learning Outcomes

On completion of this module the learner will/should be able to;

1.

Demonstrate an understanding of the automotive landscape, including its supply chain, and the associated roles and responsibilities.

2.

Assess Automotive System Architectures, past, present and future. Create an accurate conclusion on where the technology is currently at, both from hardware and software viewpoints.

3.

Apply the theory of Vehicle Networking to critically analyse the data flow of increasingly complex future vehicle networks.

4.

Conduct an analysis of the design constraints within automotive and use this information to appraise the decision-making behind current design.

5.

Effectively collaborate and communicate with the engineering community on what is topical in the automotive industry.

Teaching and Learning Strategies

A lecture will be provided weekly. Up-to-date reading materials, for example relevant chapters in a
book, will be made available before the lecture with the intended purpose of providing foundation
knowledge for the lecture. Where relevant, further reading in the form of papers and patents will be
available for reading post-lecture.
The assessments, one individual and the other group, will be designed in such a way
as to develop life-long skills of the student in the areas of technical writing, presenting their findings and
interaction with the engineering community and with society at large.

Module Assessment Strategies

Two assignments will be given to assess the module.
The individual assessment will be designed in such a way as to familiarise the student with the skills of
understanding an engineering issue in the automotive industry and evaluating its current solution.

A group assessment will be carries out on what is topical in the automotive industry. The group  will communicate their findings on their topic coherently to a wider engineering audience.

Repeat Assessments

An opportunity to submit assessment work will be available for the repeat sitting.

Indicative Syllabus

  • Overview of the automotive landscape and associated vocabulary (LO1)
  • The supply chain, and associated roles and responsibilities (LO1)
  • Difference between advanced driver assistance systems, automated driving and autonomous vehicles (LO1)
  • Introduction to Automotive System architecture - understanding the traditional car, the modern version (ADAS), the emerging and the future (LO2)
  • Current driving hardware architectures (LO2)
  • Current driving software architectures (LO2)
  • Characteristics of Vehicle networks, including bandwidth, latency, fault tolerance (LO3)
  • CAN and FlexRay Overview (LO3)
  • Networking trends, including V2 , V2X (LO3)
  • Understanding the data flow and data flood associated with autonomous vehicles (LO3)
  • Design constraints of Automotive as an embedded system, including cost, power availability, thermal dissipation, size and weight (LO4)
  • Real-time systems when applied to automotive (LO4)
  • RTOS vs. OS (LO4)
  • Design considerations for real-time (LO4)
  • Topical issues within automotive (LO5)

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
100 %

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Assignment 1 - Individual Coursework Assessment Assignment 60 % Week 10 1,2,3,4
2 Assignment 2 - Group Project Group Project 40 % Week 7 1,2,5
             

Full Time Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Lecture Theatre Lecture 2 Weekly 2.00
Independent Learning Not Specified Independent Learning 7 Weekly 7.00
Problem Based Learning Not Specified Assignment Activity 2 Fortnightly 1.00
Total Full Time Average Weekly Learner Contact Time 3.00 Hours

Online Learning Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Not Specified Weekly Lecture 1 Weekly 1.00
Independent Learning Not Specified Independent Learning 8.5 Weekly 8.50
Problem Based Learning Not Specified Assignment Activity 1 Fortnightly 0.50
Total Online Learning Average Weekly Learner Contact Time 1.50 Hours

Required & Recommended Book List

Recommended Reading
2016-05-31 Autonomous Driving: Technical, Legal and Social Aspects Springer
ISBN 3662488450 ISBN-13 9783662488454
Recommended Reading
2018-01-01 Introduction to Driverless Self-Driving Cars: The Best of the AI Insider LBE Press Publishing
ISBN 0692052461 ISBN-13 9780692052464

Module Resources

Journal Resources

IEEE Transactions

URL Resources

https://library.itsligo.ie/