Программа обучения Automated Driving and Vehicle Safety

Программа обучения "Automated Driving and Vehicle Safety" в Ingolstadt University of Applied Sciences

Automatisiertes Fahren und Fahrzeugsicherheit

Currently, two fundamental technical developments have the potential to make dramatic changes of the automotive sector: the electrification of the drive and the digitization of the vehicle in the form of automated driving. The latter requires in-depth knowledge of both computer science and engineering. Processing operations performed in a network of microcontrollers have to run in real time and must implement an interaction of sensors, algorithms and actuators. In addition, in the development of automated moving vehicles engineering knowledge is required too, which is related to the changes of the vehicle itself and their modeling for e.g. to deal with functional safety. Safety-relevant systems must be configured redundantly. However, knowledge of sensors and actuators as well as the interaction between man and machine including the necessary data transmission systems are required in the various phases of the development of systems for automated and safe driving.

Общая Информация по Программе обучения "Automated Driving and Vehicle Safety"

  • Уровень: Магистратура
  • Диплом: Master of Engineering (M.Eng.)
  • Язык обучения: Немецкий
  • Начало обучения: Зимний семестр
    Летний семестр
  • Срок обучения: 3 семестров
  • Форма обучения: Полная
  • Учебные кредиты: 90 ECTS
  • Стоимость: € 0 / Семестр
  • Семестровый взнос: € 42 / семестр
  • Правила приема: На основе конкурса
  • Минимальный уровень немецкого: B2
  • Минимальный средний балл (нем): 2.5

Карьерные перспективы по завершению программы обучения "Automated Driving and Vehicle Safety"

The job profile of the graduates is characterized by tasks in the areas of research and development of algorithms, safety concepts, sensor/actuator systems for safe, automated driving.

Учебный план программы обучения "Automated Driving and Vehicle Safety"

The aim of the Master's programme is to extend the theoretical and scientific knowledge of students in order to give them either a doctorate or work in the field of science.

The complexity of automated driving, in particular the transformation of the otherwise highly complex cognitive processes perceived by the driver into a fully automated solution, poses particular challenges to the system design and to the qualification and certification of such systems, which will have a lasting effect on all phases of the development process. The master program addresses this requirement: How can a development and test process be designed in the light of the scope and complexity of possible environmental situations, which allows a sufficiently high overlap? Which architectural concepts meet the extremely high demands on functional safety and real-time capability for the highly complex procedures? Which system components have to be designed with which degree of redundancy in order to ensure functional safety?

In addition, students' analytical, methodological and key competences will be further strengthened, their ability to reflect on their own actions and behaviors will be a topic, and leadership and leadership skills will be taught.

The modules of the program are mainly held in German and supplemented by some courses in English.

Structure

The modules of the Master's programme were defined with the aim of further qualifying students in three areas important to the development of automated and safe driving systems:

  • components: Automated driving has an impact on all areas of the vehicle: drive, brake, steering, display instruments, navigation and sensors as well as networking inside and outside the vehicle. What is needed is a deep understanding of the components of these areas.
  • concepts: Automated vehicles must recognize patterns, make smart decisions, and process a variety of data based on image and sensor data to navigate the street. The basis of every development and further development of such systems are knowledge of the concepts of machine learning in connection with those of integrated vehicle safety.
  • methods: Of crucial importance for the successful realization of automated driving systems are methods of creating a system architecture or a functional safety concept, methods of test concepts and their management as well as the performance of tests and simulations.
  • Учебный план / модули: https://www.thi.de/fileadmin/daten/fakultaetE/Modulhandbuecher_abWS1718/MHBuch_AUF-M.pdf
  • Факультет

    Faculty of Electrical Engineering and Computer Science
    Ingolstadt University of Applied Sciences

    At this moment, the faculty offers seven bachelor and four master degree courses to more than 1400 international students.

    Методика оценки заявок

    Qualified applicants are subject to a suitability procedure in which an overall grade is determined for the ranking of the admission procedure, consisting of

    • the final grade of the Bachelor's programme with weight 0.6
    • a grade with a weight of 0.4, with which a subject-specific suitability, independent scientific work and experience in the field of the design of mechatronic systems is evaluated and determined on the basis of the following criteria:
      - Knowledge in the areas of automotive engineering, control engineering, signal processing, sensors / actuators, modeling and simulation of mechatronic systems, electronics, microcomputer technology, programming, methods of artificial intelligence
      - Practical experience (comparable to a practical semester) in the field of designing or testing mechatronic systems including their software development
      - Project work in the Bachelor's programme with a thematic reference to the vehicle or methods of vehicle automation, which required knowledge of the areas design of mechatronic vehicle components, control engineering, electronics, modeling / simulation, control devices and their programming, methods of artificial intelligence.

    The aptitude is considered to have been determined if the aptitude test is rated at least with the overall grade "good" (2.5).

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