Course detail

Processing of Vehicle Data

FSI-QD0Acad. year: 2020/2021

Overview of function and limitations of measuring equipment in the field of transport means. Analysis of physical causes of selected events and explanation of selected mathematical procedures. Examples from the practical use of the Matlab and Simulink programming environments.

Learning outcomes of the course unit

Understanding measurement issues, obtaining and processing valid data, evaluating individual variables and their interdependencies, objectivizing their influence on the behavior of the whole system (vehicles), algorithmic thinking.


Mathematics, Physics, Informatics


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Zaplatílek, K., Doňar, B.: MATLAB pro začátečníky. BEN-Technická literatura, 2005. (CS)
Hendl, J.: Přehled statistických metod: analýza a metaanalýza dat. Portál, Praha, 2012. (CS)

Planned learning activities and teaching methods

The course is taught through computer-aided exercises which are focused on practical topics.

Assesment methods and criteria linked to learning outcomes

Participation in seminar, solve of problems and answers on control questions.

Language of instruction


Work placements

Not applicable.


Students will be introduced to modern methods of computer processing and evaluation of data, practical application of measuring techniques and the basics of automation.

Specification of controlled education, way of implementation and compensation for absences

Elaboration of examples with teacher assistance, independent projects, answers to control questions

Classification of course in study plans

  • Programme N-ADI-P Master's, 1. year of study, summer semester, 2 credits, elective

  • Programme M2I-P Master's

    branch M-ADI , 2. year of study, summer semester, 2 credits, elective

Type of course unit


Computer-assisted exercise

26 hours, compulsory

Teacher / Lecturer


1. Types and principles of sensors of basic physical quantities
2. Data loggers
3. Global positioning systems
4. Signal disturbances and distortion
5-6. Introduction to Programming in Matlab
7-8. Digital filters
9-10. Statistical analysis
11. Data visualization
12-13. Simulink and basics of automation