ENG09028 2019 Modelling, Simulation and Test Methods for Advanced Driver Assistance Systems

General Details

Full Title
Modelling, Simulation and Test Methods for Advanced Driver Assistance Systems
Transcript Title
Modelling, Simulation and Test
Code
ENG09028
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
2019 - Full Academic Year 2019-20
End Term
9999 - The End of Time
Author(s)
Shane Gilroy
Programme Membership
SG_ECONN_M09 201800 Master of Engineering in Connected and Autonomous Vehicles SG_ECONN_O09 201800 Postgraduate Diploma in Engineering in Connected and Autonomous Vehicles SG_EAUTO_E09 201900 Certificate in Automotive Artificial Intelligence
Description

This module introduces systems engineering concepts such as the modelling and simulation of driver assistance functions as well as an overview of the test and validation requirements and processes for autonomous vehicles.

Learning Outcomes

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

1.

Critically evaluate model-based approaches for the development and test of advanced driver assistance systems and autonomous vehicles.

2.

Summarise the System Engineering process in the development of technology for autonomous vehicles

3.

Use computer aided tools to model and simulate real-world scenarios for the development of advanced driver assistance systems

4.

Evaluate goal orientated architecture and the levels of abstraction for modelling of advanced driver assistance systems

5.

Compare validation requirements, technologies and methods for advanced driver assistance systems and autonomous vehicles.

Teaching and Learning Strategies

A lecture will be provided each week. In advance of the lecture students will be asked to review key text book chapters and academic papers that are relavent to the lecture. 

A significant focus will be placed on project based learning through the completion of both individual and group projects in order to prepare the student for the fast paced development in this field.

Module Assessment Strategies

This module will be 100% continuous assessment. The student will complete two individual assignments in addition to a significant group project. 

Repeat Assessments

Repeat project work can be submitted at the repeat exam series each year.

Indicative Syllabus

  • Overview of Systems Engineering process and typical bottlenecks in the design and development of technology for autonomous vehicles (LO1, LO2)
  • Overview of modern modelling methods and tools for the development of advanced driver assistance systems (LO1, LO4)
    • Requirements for real-time modelling regarding accuracy, operating range, simulation speed, handling/knowledge, robustness, information content and portability
    • Inductive vs. deductive modelling, approximation capability of a model, regarding local / global as well as static and dynamic mapping
    • Hybridization of model structures
    • Simulation configuration from model to hardware in loop (MiL to HiL)
    • V-Model in advanced driver assistance systems
    • ADAS Camera Modelling
  • Overview of test and simulation methods methods and tools for the development of advanced driver assistance systems (LO1, LO3, LO5)
  • Modern Modelling and Simulation Techniques for ADAS (LO1, LO3, LO4, LO5)
  • Representation and Analysis of Modelling and Simulation Results (LO3, LO5)
  • Overview of Neural Networks & ADAS for modelling and simulation (LO1, LO5)
  • Implementation of modelling, simulation and data analysis for advanced driver assistance systems in a real-world scenario: (LO3, LO4, LO5)
    • Road / Environment Modelling;
    • Driver Manoeuvre Modelling;
    • Vehicle/Sensors Modelling

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
100 %

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Assignment 1 Continuous Assessment Assignment 20 % Week 5 1
2 Assignment 2 Practical Assignment 30 % Week 8 2,4
3 Assignment 3 Project Group Project 50 % OnGoing 3,5

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
Laboratory Practical Not Specified Practical 1 Weekly 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 Online Lecture 1 Weekly 1.00
Independent Learning Not Specified Independent Learning 8.5 Weekly 8.50
Laboratory Practical Not Specified Practical 0.5 Weekly 0.50
Total Online Learning Average Weekly Learner Contact Time 1.50 Hours

Required & Recommended Book List

Recommended Reading
2016-05-04 Simulation and Testing for Vehicle Technology: 7th Conference, Berlin, May 12-13, 2016 Springer
ISBN 331932344X ISBN-13 9783319323442
Recommended Reading
2018-03-06 Modelling and Simulation for Autonomous Systems: 4th International Conference, MESAS 2017, Rome, Italy, October 24-26, 2017, Revised Selected Papers (Lecture Notes in Computer Science) Springer

This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Modelling and Simulation for Autonomous Systems, MESAS 2017, held in Rome, Italy, , in October 2017.



The 33 revised full papers included in the volume were carefully reviewed and selected from 38 submissions. They are organized in the following topical sections: M&S of Intelligent Systems AI, R&D and Applications; Autonomous Systems in Context of Future Warfare and Security Concepts, Applications, Standards and Legislation; Future Challenges and Opportunities of Advanced M&S Technology.

Recommended Reading
2017-05-22 Signal Processing for In-Vehicle Systems: Dps, Driver Behavior, and Safety (Signal Processing for In-Vehicle Systems, Driver Behavior, a) Imprint unknown
ISBN 1501504126 ISBN-13 9781501504129

Module Resources

Journal Resources

IEEE Transactions on Intelligent Transportation Systems
 

URL Resources

https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Other Resources

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Additional Information

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