Course syllabus

Course-PM

MMS210 Connected fleets in data-driven engineering - lp4 (7.5 hp)

The course is offered by the Department of Mechanics and Maritime Sciences in collaboration with the Department of Computer Science and Engineering.

Contact details

Please contact the course staff for any further questions about the teaching or course subjects. If a meeting is required, please make contact by email to request an appointment (during office hours).

Examiner and lecturer

Ola Benderius, 031-772 2086, ola.benderius@chalmers.se

Teaching assistant

Avaneesh Upadhyaya, avaneesh.upadhyaya@chalmers.se

Study administrator

Jamal Nasir, jamal.nasir@chalmers.se

Course purpose

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. 

Schedule

TimeEdit

Course literature

Lecture notes, source code templates, and web material. The material will be made available via the course web page.

Course design

The course consist of lectures, exercises, and home assignments. In the lectures the theoretical parts will be covered which will provide the students with a broad overview of the subject area. Then, the students are expected to apply the knowledge from the lectures in the exercises and home assignments.

The mandatory home assignments has to be carried out individually by each student. Please read further details regarding assessment and grading below.

Learning objectives and syllabus

• Apply large-scale fleet monitoring, and describe involved technologies and how logged data can be used in the engineering process
  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
• 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

Link to the syllabus on Studieportalen

Study plan

Examination form

The examination consists of graded individual homework assignments, and a series of group discussions (counted as one assignment).

See the following subsections for details regarding assessment and grading. Refer also to the below section regarding plagiarism and the use of tools such as ChatGPT.

Grades

The grades that are given in this course are the following: 5, 4, 3, U (not passed).

Homework assessment

The homework consists of mandatory assignments. Each assignment will be graded and given the grade 3, 4, or 5. A minimum grade of 3 is required on each assignment in order to pass the course. Re-submissions of home assignments will be allowed, but then only to reach the lowest grade. Refer to the home assignments descriptions for details regarding their individual grading. The home assignments correspond to 60% of the final course grade.

Exercises

Each week there is a scheduled exercise. The first six of these will be dedicated for a mandatory group discussion where a topic is given in class. The exercises correspond to 40% of the final course grade, where the five best results are averaged. The groups will be randomized, and different every time. To pass you need to attend at least five group assignments. The grade of the group assignment is the mean grade on all group submissions. After each group discussion, two groups will be selected on random to present their key points.

Final course grade

The student’s final course grade will be determined according to the mean grade of the assignment grades (3, 4, or 5) and the mean grade of the five best exercises (3, 4, or 5), combined as 0.6*<assignment mean> + 0.4*<exercise mean>. The resulting value, rounded to the nearest integer value, is the final individual grade of the course.

Course closure

The course will be open throughout September, and re-submissions given within this time frame will be graded. If all assignments are approved, the final individual evaluation will be offered. If all submission are not completed within the given time frame, then any missing submissions needs to be given the following year (the examiner is free to define an individual plan for completion, based on the current progress and learning outcomes).

Regarding plagiarism

Briefly, plagiarism occurs when someone present ideas, concepts, texts, or other structures from someone else, as their own. I.e. without appropriately acknowledging the original source. See further in the document about Academic integrity and honesty at Chalmers (link).

The reports (and other submitted materials such as e.g. programming code) should be original work in order to be passed. Therefore, all reports and texts that you submit for grading and examination will be checked with Ouriginal, a tool to detect plagiarism.

Avoid using tools like ChatGPT without understanding the underlying principles. It's very likely that you will get errors in your solution by trusting such tool. If you use such tools, you MUST document and submit ALL dialogue with the bot, and how the answers were incorporated in your solution.

Note: All suspected cases of plagiarism (not only those detected by Ouriginal) will be reported to the university disciplinary committee (disciplinnämnden)!