Analyzing Driving Behavior: Towards Dynamic Driver Profiling

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Publication Details

Output type: Conference proceeding

UM6P affiliated Publication?: Yes

Author list: Ouardini A., El Ouazzany Ech-chahedy I., Bouhoute A., Berrada I., El Kamili M.

Publication year: 2021

Volume number: 345

Start page: 179

End page: 190


Languages: English (EN-GB)

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This paper aims to use driving data to create a profile of the driver behavior, which can be then added as an additional layer to the Local Dynamic Map of the vehicle. The main contribution of the paper consists of using the Spherical KMeans Clustering, an unsupervised clustering algorithm for multidimensional datasets, to segment the continuous driving data into multiple segments (hyperspheres). Unlike the state of the art, this helps in studying the behavior since all the data will be processed at the same time regardless of the number of features. The generated hyperspheres are an abstract form of the initial numerical values, and can be contribute to a better representation of the driver behavior. We used the UAH Dataset [9] to present the proposed approach, and the cross-validation technique to evaluate the segmentation results. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.


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Last updated on 2021-25-11 at 23:16