HCC: Medium: Cultural Differences in Driving Interaction

Cornell University, Ithaca NY

Investigators

Abstract

This research will work to capture and understand the ways that drivers communicate and coordinate with others on the road, and to assess how these driving interactions differ across cultures. Drivers communicate and negotiate with other drivers and road users through the movement of their cars, as well as through honking, verbal communication, body language, and eye-gaze. By using a multi-person virtual-reality driving simulator to conduct driving interaction studies in different countries, the research team will gather data to understand how drivers interact with one another in different driving situations. The research is expected to contribute to improving driving safety and reducing on-road accidents, particularly involving autonomous vehicles, by helping to identify mismatches in perception, understanding, and action among road users. It is expected to benefit society by considering different cultures in the development of advanced technologies to reduce risks associated with poor design, cultural bias, and unnecessary on-road testing. The scientific goal of this research is to develop new models of driving interaction that characterize the implicit and explicit communication and negotiation patterns that occur between road users. The research team will conduct controlled experiments using a multi-person virtual-reality driving simulator--in the US, in Israel, and in China--to study how drivers from different locations and cultures interact in different on-road driving situations. The instrumented virtual reality driving simulation environment will enable capture, replay and both qualitative and quantitative analysis of vehicle movement and signaling, as well as driver gaze, head orientation and body movement. The experimental design will also enable contextualized deployment of surveys to capture insight into each driver’s situation awareness. Data from the studies and subsequent analysis will be used to train models to elucidate parametric similarities and differences in driving interactions. By capturing how participants communicate with other drivers to coordinate joint action, implicitly through the movements of their virtual car or bodily movement, as well as explicitly through verbal or gestural exchange, this project is expected to develop new understandings of how driving interactions are likely to unfold differently across diverse situations and cultures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.