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Event

Python Algorithms for Automotive Engineering [SS202114862]

Type

lecture (V)

Term

SS 2020

SWS

Language

Deutsch

Appointments

Links

ILIAS

Lecturers

Stephan Rhode

Organisation

KIT-Fakultät für Maschinenbau

Part of

Brick Python Algorithm for Vehicle Technology | Industrial Engineering and Management (M.Sc.)
Brick Python Algorithm for Vehicle Technology | Industrial Engineering and Management (B.Sc.)

Literature

A Whirlwind Tour of Python, Jake VanderPlas, Publisher: O'Reilly Media, Inc. Release Date: August 2016, ISBN: 9781492037859 link
Scientific Computing with Python 3, Olivier Verdier, Jan Erik Solem, Claus Führer, Publisher: Packt Publishing, Release Date: December 2016, ISBN: 9781786463517 link
Introduction to Machine Learning with Python, Sarah Guido, Andreas C. Müller, Publisher: O'Reilly Media, Inc., Release Date: October 2016, ISBN: 9781449369880, link
Clean Code, Robert C. Martin, Publisher: Prentice Hall, Release Date: August 2008, ISBN: 9780136083238, link

Note

Teaching content:

Introduction to Python and useful tools and libraries for creating algorithms, graphical representation, optimization, symbolic arithmetic and machine learning
- Anaconda, Pycharm, Jupyter
- NumPy, Matplotlib, SymPy, Scikit-Learn
Methods and tools for creating software
- Version management GitHub, git
- Testing software pytest, Pylint
- Documentation Sphinx
- Continuous Integration (CI) Travis CI
- Workflows in Open Source and Inner Source, Kanban, Scrum
Practical programming projects to:
- Road sign recognition
- Vehicle state estimation
- Calibration of vehicle models by mathematical optimization
- Data-based modelling of the powertrain of an electric vehicle

Objectives:

The students have an overview of the programming language Python and important Python libraries to solve automotive engineering problems with computer programs. The students know current tools around Python to create algorithms, to apply them and to interpret and visualize their results. Furthermore, the students know
basics in the creation of software to be used in later programming projects in order to develop high-quality software solutions in teamwork. Through practical programming projects (road sign recognition, vehicle state estimation, calibration, data-based modelling), the students can perform future complex tasks from the area of driver assistance systems.