Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Environment Sensing in the Vehicle Industry
2. Subject name in Hungarian Járműipari környezetérzékelés
3. Code BMEKOKAM656 4. Evaluation type exam grade 5. Credits 4
6. Weekly contact hours 2 (10) Lecture 0 (0) Practice 2 (11) Lab
7. Curriculum
Vehicle Engineering MSc (J)
 8. Role
Specialization (sp) at Vehicle Engineering MSc (J)
9. Working hours for fulfilling the requirements of the subject 120
Contact hours 56 Preparation for seminars 18 Homework 0
Reading written materials 24 Midterm preparation 12 Exam preparation 10
10. Department Department of Control for Transportation and Vehicle Systems
11. Responsible lecturer Dr. Bécsi Tamás
12. Lecturers Dr. Bécsi Tamás, Dr. Aradi Szilárd, Törő Olivér
13. Prerequisites  
14. Description of lectures
The course aims the studying of the technologies developed for the tasks of environment sensing of an automated vehicle, the currently available technologies and the corresponding signal processing techniques.
First, the course introduces the inner sensors of the vehicles, such as position, velocity, translation or rotation, basics of their physical operation and their limitations. After this, the main principles of environment sensing, such as ultrasonic, radar, lidar and machine vision systems are introduced through application examples. To strengthen the robustness of the collected data, several typical sensor fusion techniques are also studied.
15. Description of practices
 
16. Description of labortory practices
During the laboratory courses of the subject, The main goal is the software implementation of the knowledge and methods learned during the lecture and the examination of the known algorithms .
17. Learning outcomes
A. Knowledge
  • is familiar with the sensors for measuring vehicle status, their operating principles
  • is familiar with the possibilities and limitations of environmental sensors used today (Radar, Lidar, Ultrasound, Camera Systems)
  • is familiar with the sensory fusion techniques used in environmental sensing
  • is familiar with the methods of processing the data of environmental sensors
B. Skills
  • can interpret the data of different sensors
  • is able to design an algorithm for simple determination of the environmental situation based on sensor data
  • is able to select an appropriate sensor architecture for the implementation of a designated driving support / autonomous vehicle function
C. Attitudes
  • is interested in the latest developments of automotive sensors
  • is interested in the algorithmization aspect of the sensor information processing tasks
D. Autonomy and Responsibility
  • Being able to work in a team responsibly to design an autonomous vehicle function
18. Requirements, way to determine a grade (obtain a signature)
Final exam can be taken in case the two midsemester exams are succesful
19. Opportunity for repeat/retake and delayed completion
One exam can be retried at the end of the semester
20. Learning materials
Lecture Notes
Effective date 10 October 2019 This Subject Datasheet is valid for Inactive courses