2022

Journal

This work presents an adaptive driving model using fuzzy logic and software agents to imitate human car-following behavior. Validated with the Federal Highway Administration dataset, the model shows high similarity with human trajectories.

Studying driver behaviors has become a major concern for the transportation community, businesses, and the public. Thus, based on the simulation, we proposed an adaptive driving model in the car-following driving behavior and based on the normative behavior of the driver during decision-making and anticipation, whose intention is to ensure the objectives of imitation of ordinary human behavior and road safety. The presented model is based on a software agent paradigm to model a human driver and the Fuzzy Logic Theory to reflect the driver agent’s reasoning. To validate our model, we used the dataset from the program of the US Federal Highway Administration. In this context, we notice an excellent homogeneity in the deviation of the adopted trajectory of the autonomous driver agent from the adopted trajectories by the human drivers. Moreover, the advantage of our model is that it works with different velocities.

 

@article{doi:10.3233/JIFS-213498,
author = {Anouer Bennajeh and Lamjed Ben Said},
title ={Autonomous agent adaptive driving control based on fuzzy logic theory and normative behavior},

journal = {Journal of Intelligent \& Fuzzy Systems},
volume = {43},
number = {5},
pages = {5973-5983},
year = {2022},
doi = {10.3233/JIFS-213498},

URL = {


https://journals.sagepub.com/doi/abs/10.3233/JIFS-213498

},
eprint = {


https://journals.sagepub.com/doi/pdf/10.3233/JIFS-213498

}
,
abstract = { Studying driver behaviors has become a major concern for the transportation community, businesses, and the public. Thus, based on the simulation, we proposed an adaptive driving model in the car-following driving behavior and based on the normative behavior of the driver during decision-making and anticipation, whose intention is to ensure the objectives of imitation of ordinary human behavior and road safety. The presented model is based on a software agent paradigm to model a human driver and the Fuzzy Logic Theory to reflect the driver agent’s reasoning. To validate our model, we used the dataset from the program of the US Federal Highway Administration. In this context, we notice an excellent homogeneity in the deviation of the adopted trajectory of the autonomous driver agent from the adopted trajectories by the human drivers. Moreover, the advantage of our model is that it works with different velocities. }
}