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1.
The use of intelligent transport systems in the operation of driving schools : master's thesis
Nikola Božinić, 2022, master's thesis

Abstract: The aim of the master's thesis was to conduct research on the use of intelligent transport systems in the current training of future drivers and their knowledge of the content and also knowledge of the content of employees in teh field of training of future drivers The current methods of driver training in individual countries are presented, with a more detailed description of their implementation and the method of testing the acquired knowledge. At the same time, the survey was conducted in the Republic of Croatia and the information on how well people are generally familiar with the knowledge of intelligent transport systems, how they apply them and what do they consider as usable intelligent systems were collected. The research was also conducted among employees in the field of training of future drivers, also in the Republic of Croatia, where were obtained on what changes employees believe have to be done, or how changes in the automotive industry could affect their work, such as is the phenomenon of autonomous driving. After that, a comparison of driver training nowadays wth the proposal of future training with the use of intelligent transport systems is presented.
Keywords: novice drivers, traffic safety, driving education, intelligent vehicle systems, autonomous driving
Published in DKUM: 29.08.2022; Views: 533; Downloads: 44
.pdf Full text (4,33 MB)

2.
Passive testing of highly automated driving systems : master's thesis
Luka Šelih, 2021, master's thesis

Abstract: Driver assistance systems and automated driving have become one of the most important components of new vehicles. Enormous progress has been made with developing algorithms for autonomous control and perception, but the problems of safety validation remain. In this master thesis, we first briefly summarise safety and testing approaches in autonomous driving. Then we propose our own approach for testing automated/autonomous driving, which we call "Passive parallel Testing". The approach focuses on detecting discrepancies between the human driver and the control of the automated driving function, thus identifying potentially critical situations. The test method is demonstrated at the end in a simulation with the CARLA simulator.
Keywords: autonomous driving, testing, safety, CARLA, AEB
Published in DKUM: 18.10.2021; Views: 764; Downloads: 94
.pdf Full text (2,99 MB)

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