Abstract
Interaction between human drivers and programmed agents under specific experimental conditions is the most common approach in driving simulation research nowadays. Social interaction, especially in transient, complex situations such as those occurring in urban traffic, is a multi-facetted, multidirectional, and above all dynamic phenomenon. The programmable traffic participants (bots) in simulations may thus encounter interaction constraints. This chapter describes the UR:BAN approach, where the narrow spectrum of human-bot interaction is expanded. The apparatus consists of a multiparty simulator. A car driver in a driving simulator encounters a pedestrian in a second simulator in varying situations. Both meet in the same simulated environment and are able to mutually adapt their behaviors relative to the other road user. Traditional safety-oriented data analysis, involving for example time to arrival, post-encroachment time, and deceleration-to-safety time, was conducted and supported by novel approaches using cross correlation, cross recurrence quantification analysis, frequency analysis, sense of presence, and immersion assessment to take the features of social interaction into account.
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Lehsing, C., Feldstein, I.T. (2018). Urban Interaction – Getting Vulnerable Road Users into Driving Simulation. In: Bengler, K., Drüke, J., Hoffmann, S., Manstetten, D., Neukum, A. (eds) UR:BAN Human Factors in Traffic. ATZ/MTZ-Fachbuch. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-15418-9_19
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DOI: https://doi.org/10.1007/978-3-658-15418-9_19
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