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Automated and Connected Driving



Module name (EN):
Name of module in study programme. It should be precise and clear.
Automated and Connected Driving
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Computer Science and Communication Systems, Master, regulation 01.10.2019
Module code: KIM-AVF
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
4S (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
6
Semester: 2 or 3
Mandatory course: no
Language of instruction:
German
Assessment:
Composition (33%), presentation (33%), oral examination (33%)

[updated 29.10.2026]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

E2913 (P211-0134, P211-0135, P211-0136) Electrical Engineering and Information Technology, Master, regulation 01.04.2019 , semester 2, mandatory course, technical
KIM-AVF Computer Science and Communication Systems, Master, regulation 01.10.2019 , optional course, informatics specific
TIM-AVF Technical Computer Science, Master, regulation 01.10.2026 , optional course, informatics specific
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 180 hours (equivalent to 6 ECTS credits).
There are therefore 135 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Jonas Vogt, M.Sc.
Lecturer: Jonas Vogt, M.Sc.

[updated 07.11.2020]
Learning outcomes:
After successfully completing this module, students will have a solid understanding of in-vehicle and connected communication. They will be able to compare common vehicle bus systems based on specific criteria, taking into account their advantages and disadvantages, and assign them to specific automotive application domains. Students will be able to encode and decode sensor and actuator data on the CAN bus, adapt specified addressing schemes as needed, and perform systematic error analyses in the event of communication failures. In addition, they will be able to relate the data streams generated in the vehicle directly to the functionality of modern driver assistance systems. In the area of cooperative intelligent transportation systems (C-ITS), students will be able to identify the technological rationale, reconstruct standardized use cases, and independently design the necessary message formats for given scenarios. Finally, they will be able to calculate optimal propagation paths to solve routing problems in dynamically networked transportation environments.


[updated 29.10.2026]
Module content:
Digital infrastructure
Connected driving
IT security in C-ITS networks
Car-2-Car and GeoNetworking
Car-2-Car and GeoNetworking
   - Wrong-way driver warning
   - Traffic light assistant
   - Intersection assistant
   - Emergency vehicle warning system
  
Communication-based assistance systems

[updated 29.10.2026]
Teaching methods/Media:
Lecture notes, transparencies and video projector

[updated 29.10.2026]
Recommended or required reading:
 


[updated 29.10.2026]
Module offered in:
WS 2021/22, WS 2020/21 
[Sat Oct 31 16:15:05 CET 2026, CKEY=emE2913, BKEY=kim2, CID=KIM-AVF, LANGUAGE=en, DATE=31.10.2026]