NAMIDA: How to reduce the cognitive workload of driver

This paper presents NAMIDA, social interface consisting of three robots that help the driver to navigate by considering him as a bystander in a multi-party conversation between the agents. Through this model the cognitive workload of the driver can be reduced compared to the conventional one-to-one communication based approach that directly addresses the driver. We set up an experiment to compare the multiparty conversation based NAMIDA (MPCN) and the one-to-one conversation based NAMIDA (OOCN) to explore the effects of both methods on the cognitive workload factors and attention behaviours of the participants. The results showed that the MPCN system yields reduction in certain workload factors which can help the driver in increasing his attention on the road.