Course syllabus for Connected fleets in data-driven engineering

Course syllabus adopted 2021-02-18 by Head of Programme (or corresponding).

Overview

  • Swedish nameAnslutna flottor för datadriven utveckling
  • CodeMMS210
  • Credits7.5 Credits
  • OwnerMPMOB
  • Education cycleSecond-cycle
  • Main field of studyAutomation and Mechatronics Engineering, Electrical Engineering, Mechanical Engineering
  • DepartmentMECHANICS AND MARITIME SCIENCES
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 89126
  • Block schedule
  • Open for exchange studentsYes

Credit distribution

0121 Written and oral assignments 7.5 c
Grading: TH		0 c0 c0 c7.5 c0 c0 c

In programmes

Examiner

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Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Aim

The purpose of the course is to aid engineers in data-driven decisions connected to vehicle features and development. By also adding continuous experimentation and remote system monitoring, the course will be vital in engineering processes around functional safety. Finally, as fully connected fleets also represent structural changes to transportation in society, it also includes deep and thorough discussion around automated data-collection connected to human activities, as a way to shift previous collect-all strategies into sound ethical engineering principles as endorsed by our governments through recent legislation such as GDPR.

Learning outcomes (after completion of the course the student should be able to)

  • Describe properties of hardware components needed in each unit of a connected fleet, including their software life-cycles
  • Describe properties of core software components needed in a backend environment, connected to the engineering process
  • Apply and monitor over-the-air updates to a fleet of mobile systems, and describe limitations from different underlying technologies
  • Apply software development connected to continuous integration and continuous deployment in heterogeneous ECU networks
  • Apply large-scale fleet monitoring, and describe involved technologies and how logged data can be used in the engineering process, such as for continuous experimentation and functional safety
  • Describe relevant cybersecurity measures to safeguard the connected fleet and the its generated data
  • Describe ethical aspects of fleet monitoring and over-the-air updates, and how such concepts can be combined with ethical engineering related to governmental intentions as defined by, for example, GDPR
  • Define complete engineering process involving all learning outcomes from the course

Content

This course is intended for engineering students to form a solid understanding och how connected product fleets can efficiently be used as an integrated part of the engineering process, and how connected fleets change society. The course is vital for further courses in active safety, autonomous vehicles, product fleet management, functional safety, and product life-cycle management. The course discusses such integration in connection to massive scale fleets, at least up to one million products, and how this can be scaled up in a backend cloud environment. By using the knowledge from the course, students should be able to understand and set up a complete DevOps engineering process in an organization, targeting all types of vehicles, including core backend technologies and basic insight into cybersecurity. Such process involves both continuous integration and continuous deployment (CICD) for heterogeneous computational platforms. The purpose of the course is to aid engineers in data-driven decision making connected to vehicle features and development. By also adding continuous experimentation and remote system monitoring, the course will be vital in engineering processes around functional safety. Finally, as fully connected fleets also represent structural changes to transportation in society, it also includes deep and thorough discussion around automated data-collection connected to human activities, as a way to shift previous collect-all strategies into sound ethical engineering principles as endorsed by our governments through recent legislation such as GDPR.

Organisation

The course will involve two main teaching elements: lectures, weekly individual home assignments. The home assignments will to a large extent use a common simulation resource that simulates a fleet of one million connected vehicles.

Literature

Lecture slides and video lectures.

Examination including compulsory elements

Each student is graded individually. The grade is a mean of all home problems, each graded with a passing grade of 3, 4, or 5. The home problems have a pre-set deadline, and to reach grade 4 or 5, the deadline needs to be met. Late submissions or re-submissions can only be awarded with grade 3. All home assignments needs to be passed in order to pass the course.

In the end of the course, each student will have a brief oral grade discussion with the examiner. During the meeting the student will be asked to explain some technical steps of their own submitted solutions as a final confirmation before the final grade is set. If there are any uncertainties around the own submitted solutions, further investigation will be conducted and further actions may be needed before any final grade can be considered.

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.