TU Delft
Year
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NEDERLANDSENGLISH
Organization
2017/2018 Mechanical, Maritime and Materials Engineering Master Mechanical Engineering
ME41105
Intelligent Vehicles
ECTS: 4
Responsible Instructor
Name E-mail
Prof.dr. D. Gavrila    D.Gavrila@tudelft.nl
Instructor
Name E-mail
J.F.P. Kooij    J.F.P.Kooij@tudelft.nl
Contact Hours / Week x/x/x/x
2/2/0/0
2 lecture/lab hours per week (lectures and labs alternating)
Education Period
1
2
Start Education
1
Exam Period
2
3
Course Language
English
Required for
This course is obligatory for students in the “Vehicle Engineering” Track of the "Mechanical Engineering" Master program.
Expected prior knowledge
Linear algebra and probability theory. Good (MATLAB) programming skills.
Course Contents
[N.B.the course will be held 2017-2018 over two quarters, with lectures/labs running from Sept - Dec 2017]

“Intelligent Vehicles” is the introductionary 3ME Master course on the technology of automated driving.

The introductionary lecture discusses the motivation for automated driving, levels of automation, current driver assistance systems on the market, future vehicle use scenarios and the main stakeholders involved (industry, government, consumers).

Various lectures thereafter address the main technological components of an automated vehicle: sensor processing (vision, radar, lidar), sensor fusion, mapping and localization, situation analysis, motion planning and control. Concepts are further worked out in lab assignments (MATLAB programming).

The course also provides a sampling of recent research topics in the domain.
Course Contents Continuation
This course mainly addresses the technology allowing a vehicle to drive in automated fashion. Complementary to this course is CIE 5805 “Intelligent Vehicles for Safe and Efficient Traffic: Design and Assessment” which focuses more on automated vehicles as part of a larger intelligent transportation system (i.e. including smart infrastructure, connected/cooperative driving) and on associated issues at the macro level (e.g. traffic flow efficiency, fuel consumption, behavior adaptation).
Study Goals
At the end of the course students will understand the main technological components of a self-driving vehicle, and the underlying concepts. First-hand programming experiences will enrich this understanding.

More broadly, students will be able to express an educated opinion on the benefits and risks of automated driving, the current developments from driver assistance to self-driving cars, and the forces driving this transformation.
Education Method
Lectures / lab sessions (2 hours per week)
Self-study
Lab assignments (MATLAB programming)
Assessment
Lab assignments (MATLAB programming) and written final examination. Final examination only upon successful completion of lab assignments. Lab assignment grades remain valid for one year.
Tags
Artificial intelligence
Matlab
Programming