<div class="csl-bib-body">
<div class="csl-entry">Kim, D., Kim, H., & Jun, C. (2023). Development of Aggressive Driving Detection Method for two-wheeled vehicles. In <i>Proceedings of the 18th International Conference on Location Based Services</i> (pp. 164–168). https://doi.org/10.34726/5722</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/194731
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dc.identifier.uri
https://doi.org/10.34726/5722
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dc.description.abstract
In the rapidly growing two-wheeled vehicle industry, there is an increasing need to detect and prevent aggressive driving behaviors. In this study, we propose an effective method to identify aggressive driving behaviors of simulated two-wheeled vehicles using limited data from the Carla simulator. We focus on two types of aggressive driving behaviors: sharp turning and sharp lane changing. By utilizing acceleration, angular velocity, and position data, we establish a foundation for detecting these behaviors. For sharp turning, a multi-stage classification method is adopted using gyroscope and acceleration data. Sharp lane changings are detected using an XGBoost mode
en
dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Two-wheeled vehicles
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dc.subject
aggressive driving detection
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dc.subject
sharp turning
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dc.subject
sharp lane changing
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dc.title
Development of Aggressive Driving Detection Method for two-wheeled vehicles
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dc.type
Inproceedings
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dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.identifier.doi
10.34726/5722
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dc.contributor.affiliation
University of Seoul, Korea (the Republic of)
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dc.contributor.affiliation
University of Seoul, Korea (the Republic of)
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dc.contributor.affiliation
University of Seoul, Korea (the Republic of)
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dc.relation.doi
10.34726/5400
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dc.description.startpage
164
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dc.description.endpage
168
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dc.rights.holder
Authors
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the 18th International Conference on Location Based Services
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tuw.relation.ispartof
10.34726/5400
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tuw.researchTopic.id
I5
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tuw.researchTopic.name
Visual Computing and Human-Centered Technology
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E000 - Technische Universität Wien
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dc.identifier.libraryid
AC17202950
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dc.description.numberOfPages
5
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
tuw.event.name
18th International Conference on Location Based Services (LBS 2023)
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dc.description.sponsorshipexternal
Ministery of the Interior and Safety (MOIS, Korea)