Fuzzy Logic-based Techniques for Human Driver Behavior Modelling during a Simple Lane-changing Task

Abstract

The paper presents an experiment with fuzzy-logic-based models for approximating data representing human driver behavior during a simple lane-changing task. Data are acquired via the self-developed car driving simulator under defined conditions. Three fuzzy-logic-based models are considered: fuzzy Hammerstein model, fuzzy PD controller with a fixed structure (analogy to the linear PD controller) and fuzzy PD controller with an optimized structure. A comparison of the effectiveness of the individual approaches was evaluated using a criterion representing the fitness of the model output and the measured data. Although only one dataset was considered in the frame of this paper, the results indicate an investigative potential of the fuzzy models for this kind of task connected with the modelling of human behavior.The paper presents an experiment with fuzzy-logic-based models for approximating data representing human driver behavior during a simple lane-changing task. Data are acquired via the self-developed car driving simulator under defined conditions. Three fuzzy-logic-based models are considered: fuzzy Hammerstein model, fuzzy PD controller with a fixed structure (analogy to the linear PD controller) and fuzzy PD controller with an optimized structure. A comparison of the effectiveness of the individual approaches was evaluated using a criterion representing the fitness of the model output and the measured data. Although only one dataset was considered in the frame of this paper, the results indicate an investigative potential of the fuzzy models for this kind of task connected with the modelling of human behavior.