TY - JOUR 
A1 - Monsalve Piqueras, Borja
AU - Aliane, Nourdine
AU - Puertas Sanz, Enrique
AU - Fernández Andrés, Javier
T1 - Think Aloud Protocol and Decision Tree for Driver Behavior Modeling at Roundabouts
Y1 - 2023
SN - 2169-3536
UR - http://hdl.handle.net/11268/12050
AB - Learning from human driver’s strategies for undertaking complex traffic scenarios has the potential to improve decision-making methods for designing ADAS systems, as well as for design selfdriving rules for automated vehicles. This paper proposes a human-like decision-making algorithm built up from human drivers experiential naturalistic driving. The approach of this work consists of exploring two main techniques. Firstly, the use of ‘‘think aloud protocol’’ to build a dataset based on naturalistic driving, capturing driver’s intentions. Afterwards, the technique of decision tree is used to generate an algorithm to categorize driving patterns as a function of circumstantial driving parameters. The study is focused on simple roundabouts in presence of other vehicles. The decision tree is translated into algorithmic rules, where the
tree pathways are represented as ‘if-then’ clauses, resulting in a model of driver behavior at roundabouts.
Finally, the accuracy of the driver behavior model has been assessed, yielding promising results.
KW - Inteligencia artificial
KW - Análisis de datos
KW - Procesamiento de datos
LA - eng
ER -