Using ego motion feedback to improve the immersion in virtual reality environments

For any kind of assistant systems, the ability to interact with the human operator and taking into account his or her assumptions and expectations, is the basis for a reasonable behavior. As a consequence the human behavior have to be studied in order to generate driver models that are learned from human driving data. In this work we focus on the improvement of the immersion in driving simulation environment by developing and implementing a cheap and efficient method for head tracking. We also explain why head tracking feedback is crucial for the quality of collected behavioural data, especially for simulators with close screen distances.