aalto1 untyped-item.component.html
Data driven decision-making: The future of motorsports with modern data analysis
Loading...
Files
Aalto login required (access for Aalto Staff only).
URL
Journal Title
Journal ISSN
Volume Title
School of Business |
Bachelor's thesis
Electronic archive copy is available locally at the Harald Herlin Learning Centre. The staff of Aalto University has access to the electronic bachelor's theses by logging into Aaltodoc with their personal Aalto user ID. Read more about the availability of the bachelor's theses.
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
23 + 2
Series
Abstract
This thesis explores how data-driven approaches enhance vehicle and driver performance in motorsports. With the rise of affordable data logging technologies and increased availability of data, the industry is shifting from intuition-based to data-centric strategies. The transition from intuition- based to data-centric point of view is ongoing. Data-driven approaches are being used more and the need for making motorsports data more intuitive and comprehensive is rising. This literature review investigates the data-analysis side in motorsports and moves into broader subjects, such as race strategy and decision-making.
The priority of motorsports team is to perform on a higher level than their competitors, so they need to be integrating new ways of working. To optimise performance teams, use models, simulations, and different ways of analysing data and to improve their processes. Even drivers are analysed to find aspects of improvement and to find better understanding of how performance builds in motorsport.