In the last years, several safety automotive concepts have been proposed, for instance the cruise control and the automatic brakes systems. The proposed systems are able to take the control of the vehicle when a dangerous situation is detected. Less effort was produced in driver aggressiveness in order to mitigate the dangerous situation. In this paper we propose an approach in order to identify the driver aggressiveness exploring the usage of unsupervised machine learning techniques. A real world case study is performed to evaluate the effectiveness of the proposed method.
Cluster Analysis for Driver Aggressiveness Identification
F Martinelli;F Mercaldo;A Orlando;
2018
Abstract
In the last years, several safety automotive concepts have been proposed, for instance the cruise control and the automatic brakes systems. The proposed systems are able to take the control of the vehicle when a dangerous situation is detected. Less effort was produced in driver aggressiveness in order to mitigate the dangerous situation. In this paper we propose an approach in order to identify the driver aggressiveness exploring the usage of unsupervised machine learning techniques. A real world case study is performed to evaluate the effectiveness of the proposed method.File in questo prodotto:
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