Abstract: Recently Google invented an autonomous car without the steering wheel presumably aiming for supporting elderly and disable people. The fact addresses issues of how the robotic car performs the risk assessment such as accident predictions and managements of driver's comfort levels. In past related studies, the viability range in human driving was considered to be able to deal with a safety zone definition in Driver-Vehicle-Environment (DVE) state space that provide lines to separate three areas: the comfort zone to allow the driver the adaptive control, discomfort zone but still in the safely margin and the zone to lose the control. Thus the safety zone boundary is determined by driver conditions (skill levels, attention controls, feelings, health status and so on) and environmental factors around the vehicle (the complexity of situations including risk levels, road and weather conditions, and so on). It implies that a design of the systematic framework is necessary to visualize the brain capability to manage in the social context (or roadway law and morals) and dynamic environment, by investigating contextual changes of the attention selection and working memory capacity. Interestingly, the robot instructor or teacher attracts rising attention not only in the industrial field but also in childcare to enhance learning of social skills. The attention control in a complex situation needs to work effectively for maximizing retentions of environmental information related to the current task in execution and minimizing effects of disturbing factors, and it is considered as a significant relationship with the working memory capacity. According to the hypothesis, we present here a preliminary report of the neuro-psychological study to investigate the attention control in the experiment by using the humanoid robot NAO as an instructor providing multimodal information including oral representation (sound), behavioral instruction (finger pointing) and social context (joining a human mate together) (Fig.1). Subject attentions were monitored by the eye-tracker measurement and analyzed its temporal sequence and tendencies what they focused on, which reveals the relationship among the subject's attentional change, rich/poorness levels in multimodal instruction and the task seriousness that the subject was requested to perform during the instruction. American Automobile Association (AAA) reports that factors of distraction leading to a teen driver crash are interaction with other passengers (15%), cell phone usage (12%), looking at something in the vehicle (10%) and outside the vehicle (9%), singing/dancing to music (8%), personal grooming (6%) and reaching for an object (6%), and other distractions included eating/drinking, smoking, reading something such as a map and talking to oneself. A systematic approach to measure the attentional change and working memory capacity can be extended to analyses with a simultaneous recording of the eye-tracker and EEGs and it contributes to the establishment of the common evaluation method of social and driver competencies.

Biography: Hiroaki Wagatsuma started his career as a hardware engineer on personal computer at the NEC Corporation, and contributed to the first generation of the notebook-type computer, PC-98note, released in 1989. He received a M.S. in 1997 and a Dr. Sci. in Mathematical Sciences in 2005 from Tokyo Denki University. From 2000-2009, he belonged to RIKEN Brain Science Institute as postdoctoral researcher for studying computational neurosciences. He is currently Associate Professor of Kyushu Institute of Technology (KYUTECH) in the Graduate School of Life Science and Systems Engineering. His major is mathematical science especially on non-linear dynamics and hybrid dynamical systems, which was initiated a theoretical modeling of brain oscillations, such as episodic memory formation based on oscillatory neural network models, and expanded to applications to intelligent robots i.e. neurorobotics, as is simply introduced in his edited book “Neuromorphic and Brain-Based Robots” (Cambridge University Press 2011). He called his research area is “Brain-Inspired Systems (Brain-IS)” covering an adaptive and flexible intelligence, the body motion coordination and constraints as multi-body dynamics and its technological transfers to social demands, such as automatic driving, social and educational robots, and assistive devices for disable and elderly persons. Therefore he is contributing to multiple research projects, development of a multi-copter having advanced capabilities for finding damages in public infrastructure, under SIP with MLIT, automated driving system research project and advanced human-machine interaction cockpit design with industrial companies, JSPS Research Grant: extraction of the agricultural tacit knowledge by multi-stage data mining combining the group intelligence and mathematical modeling, and the establishment of a systematic analysis sport dynamics on sports-for-the-disabled and rehabilitation methods collaborating with Japan national coach of JWBF. Dr. Wagatsuma is author of over 50 scientific articles and joined international and domestic conferences as invited speakers, and is the Director, Intelligent Robots Education and Research Center at Joint Graduate School, and the chairperson of the Dynamic Brain Platform committee in which NIJC, RIKEN BSI supports as a prominent neuroinformatics project.