Master Thesis Online
Master Thesis : Road Condition Measuring
Naa, Marco 
Promotor(s) :
Geurts, Pierre
;
Tromme, Emmanuel
Date of defense : 26-Jun-2023/27-Jun-2023 • Permalink : http://hdl.handle.net/2268.2/17709
Details
| Title : | Master Thesis : Road Condition Measuring |
| Translated title : | [fr] Mesure de l'état des routes en utilisant des techniques d'apprentissage automatique |
| Author : | Naa, Marco
|
| Date of defense : | 26-Jun-2023/27-Jun-2023 |
| Advisor(s) : | Geurts, Pierre
Tromme, Emmanuel |
| Committee's member(s) : | Wehenkel, Louis
Marée, Raphaël
|
| Language : | English |
| Number of pages : | 80 |
| Keywords : | [fr] Road condition measuring machine learning transformer kpi |
| Discipline(s) : | Engineering, computing & technology > Computer science |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en science des données, à finalité spécialisée |
| Faculty: | Master thesis of the Faculté des Sciences appliquées |
Abstract
[fr] Nowadays, vehicles are equipped with sensors for a multitude of purposes, such as to ensure
an optimal vehicle stability or anti-lock braking system (ABS).
Besides, by analysing collected data, new opportunities can be generated. For instance, these
data could be used to indirectly measure road conditions and then, advice drivers on the best
driving strategy.
File(s)
Document(s)
s175610TFE.pdf
Description:
Size: 19.62 MB
Format: Adobe PDF
Annexe(s)
s175610Appendix.pdf
Description:
Size: 10 MB
Format: Adobe PDF
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The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.