Vehicle dynamics in automated traffic

Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data

Master Thesis (2020)
Author(s)

J. Staiger (TU Delft - Mechanical Engineering)

Contributor(s)

Peter E. Pfeffer – Mentor

SC Calvert – Mentor (TU Delft - Transport and Planning)

M. Wang – Graduation committee member (TU Delft - Transport and Planning)

Faculty
Mechanical Engineering
Copyright
© 2020 Julian Staiger
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Julian Staiger
Graduation Date
27-05-2020
Awarding Institution
Delft University of Technology, , , , , , , , ,
Faculty
Mechanical Engineering
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Abstract

Significant developments in the field of Advanced Driver Assistance Systems (A prove traffic management and prediction, driver comfort, and vehicle safety. However, a detailed knowledge of the way vehicles move is crucial for these applications. The mobility behavior has also changed over the last decades significantly. Both individual mobility and the mobility of goods is nowadays an essential part of our economy. The latest trends in vehicle automation are the predicted first signs of a partially/autonomous future of mobility. Whether this
future will be with or without individual vehicle ownership will become apparent in the coming years. For the moment, all researchers can do is to work on new topics tomake the future of mobility faster, more efficient, quieter, and safer. Detailed knowledge of state-of-the-art automation systems is essential in order to gain further insights into their effects, e.g., on traffic, the travel behavior of people, the security gaps caused by these systems, and passenger comfort.

Files

MT_Staiger_VDIAT_1_.pdf
(pdf | 17 Mb)
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