Recognition of the Driving Style in Vehicle Drivers
Por:
Cordero, Jorge, Aguilar, Jose, Aguilar, Kristell, Chavez, Danilo, Puerto, Eduard
Publicada:
1 may 2020
Resumen:
This paper presents three different approaches to recognize driving
style based on a hierarchical-model. Specifically, it proposes a
hierarchical model for the recognition of the driving style for advanced
driver-assistance systems (ADAS) for vehicles. This hierarchical model
for the recognition of the style of the car driving considers three
aspects: the driver emotions, the driver state, and finally, the driving
style itself. In this way, the proposed hierarchical pattern is composed
of three levels of descriptors/features, one to recognize the emotional
states, another to recognize the driver state, and the last one to
recognize the driving style. Each level has a set of descriptors, which
can be sensed in a real context. Finally, the paper presents three
driving style recognition algorithms based on different paradigms. One
is based on fuzzy logic, another is based on chronicles (a temporal
logic paradigm), and the last is based on an algorithm that uses the
idea of the recognition process of the neocortex, called Ar2p (Algoritmo
Recursivo de Reconocimiento de Patrones, for its acronym in Spanish). In
the paper, these approaches are compared using real datasets, using
different metrics of interest in the context of the Internet of the
Things, in order to determine their capabilities of reasoning,
adaptation, and the communication of information. In general, the
initial results are encouraging, specifically in the cases of chronicles
and Ar2p, which give the best results.
Filiaciones:
Cordero, Jorge:
Univ Tecn Particular Loja, Dept Ciencias & Comp & Elect, Loja 110107, Ecuador
Aguilar, Jose:
Univ EAFIT, Grp Invest Desarrollo & Innovac TIC, Medellin 050021, Colombia
Univ Los Andes, Ctr Microcomp & Sistemas Distribuidos, Merida 5101, Venezuela
Aguilar, Kristell:
Univ Los Andes, Ctr Microcomp & Sistemas Distribuidos, Merida 5101, Venezuela
Chavez, Danilo:
Escuela Politec Nacl, Quito 170525, Ecuador
Puerto, Eduard:
Univ Francisco Paula Santander, Grp Invest Inteligencia Artificial, Cucuta 540001, Colombia
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