Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems (ITSC2016)(7795887), 2046–2051p. (2016) DOI:10.1109/ITSC.2016.7795887

On the track of social interaction – A non-linear quantification approach in traffic conflict research

C. Lehsing, M. Fleischer, K. Bengler

Humans interact. It is a basic prerequisite for the processes of their social life. Interaction is, among other definitions, described as the goal oriented, mutual behavior adaption process of individuals using verbal and non-verbal communication (i.e. speech, posture, gesture, and gaze) in their different social roles. One of these roles fulfil individuals when they participate in traffic. Traffic as a complex system does not always follow linear rules, as well as behavior adaption between road users that intend to claim the same infrastructural resource such as a road segment. Research in the field of transport engineering and traffic psychology apply sophisticated methods to reveal underlying processes and key factors in traffic that lead to dangerous situations or fatalities. Particularly in urban traffic as a classic example of complex systems, the processes as well as official and non-official regularities that contribute to a smooth, efficient and safe traffic flow are of special interest for traffic engineers and psychologists. Using driving simulators to investigate the behavior of traffic participants in selected situations is a common and broadly accepted method. Traffic in cities is, despite the legal regularities, strongly dependent upon the social interaction between drivers, cyclists and pedestrians. To analyze this behavior the common driving simulator approach lacks the vivid variety of human communication, verbal and non-verbal. Especially the latter plays a significant role in the discussed topic. To overcome this disadvantage of single simulator studies, a multi-participant simulator study was performed. A pedestrian simulator, based on motion tracking technology, and a driving simulator where linked so that the participants were able to communicate non-verbally. This approach enables the interaction between both in pedestrian crossing situations. Cross recurrence plots visualized this interaction and it was measured using cross recurrence quantification analysis. Results show remarkable differences in the quantification analysis metrics and interaction behavior could be classified within the cross recurrence plots. These findings have the potential to support the identification of crucial social interaction within the scope of environmental perception and situation understanding not only in pedestrian encounters but also within the research of automated vehicles.

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