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.
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