This paper presents a model of navigational habituation for human passengers riding an autonomous robotic wheelchair. We present an example on how robot technology is utilized to understand human behavior which is useful to build human-like navigation models. The work consists of three parts, data collection from manual driving participants, habituation modeling and autonomous navigation experimentation. Manual driving data collection consisted of recording human driving control behavior using a robotic wheelchair in a complex labyrinth-like environment, while measuring physiological activity and emotional state via subjective reports (questionnaires). The purpose of this first part was to collect a sufficient representation of the evolution of human driving behavior in a complex environment (23 participants), such that a numerical model could be found to approximate the trend in velocity usage; velocity usage characterizes navigational habituation. The complex environment habituation model was tested and evaluated, on a different set of 16 participants, in a fully autonomous navigation setting where the robotic wheelchair followed a pre-recorded path. Self-reports and physiological measures confirmed that the proposed habitation velocity regulation model provides a more comfortable ride compared to slow and fast pre-defined static velocity profiles.