Quantifying Realistic Behaviour of Traffic Agents in Urban Driving Simulation Based on Questionnaires

Abstract

Driving simulation is becoming an increasingly important component of research and development in the automotive industry. When performing simulator studies in urban scenarios, the challenge is to create a realistic driving context including natural interactions between the subject and artificial traffic participants, which are simulated by agent models. These traffic agents should behave as similar as possible to real humans. This raises the question of how to define realistic or human-like behaviour of traffic agents and how to measure this. Furthermore, it is necessary to investigate the influence of the surrounding traffic on the driver’s behaviour and perception of reality in the simulator. Accordingly, we present a method for quantifying the degree of realism of virtual traffic agents’ behaviour and their impact on subjects’ experience in a simulator experiment. By means of questionnaires, participants rated their perception of reality and the behaviour of present agent models. The experiment shows that surrounding traffic has a positive effect on subjects’ perception and behaviour, indicating that more realistic traffic agents have the potential to improve the validity of simulator studies. Moreover, our results provide new insights regarding required characteristics for the development of human-like traffic agents and give an overview of current strengths and weaknesses.