TU Berlin

Chair of Naturalistic Driving Observation for Energetic OptimisationNaturalistic Driving Observation

Fachgebiet FVB

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Contents and goals

The module provides a comprehensive overview of current methods of monitoring driver behavior and their areas of application with link to the driver assist systems. Students will learn processes and boundary conditions for the development of methods of driver behavior observation and will be qualified to independently analyze system relationships, develop evaluation methods as well as apply and arrange these in the context of statistical relevance. They will develop a substantive understanding of functioning and deductions from driving behavior observation and this can apply to future developments in the automotive industry, in particular Car2X communication.

The course is based on currecnt examples and research areas of existing and budding methods and techniques of driver behavior observation, their components (measurement technology, databases, simulation models, protocols) and includes the current issues regarding application (Car2X communication , optimizing fuel consumption, accident avoidance), opportunities (technical implementation, application areas away from the industry) and limitations (data processing, data protection, environmental influences). The methodology will be partly tested in practice.

Format and module contents

Naturalistic Driving Observation
ECTS (SWS)
6 ECTS (4 SWS)
Responsible

Form of teaching

The module is divided in lecture and practice, group work and group discussion. Addition: online support via ISIS and consultation hour. Lecture and practice will partly be as blended learning.
Dates and duration

The module is available during winter semester and can be finished in one semester.
Requirements

a) Mandatory: good knowledge of the German and English language; good transferable basic skills in automotive technology (acquired by successful completion of the module "Fundamentals of Vehicle Technology" and "Fundamentals of Vehicle Dynamics"
b) Obligatory: basic knowledge in the field of "big data", vehicle safety and dynamic simulations; presentation of technical results orally and in written form, social and good teamwork skills
Examination requirements

Two exercises in groups of two, a presentation and a final test will be graded. All partly grades will count equally for the final grade.

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