We conduct experimental studies on designing and evaluating vehicle motion and eHMI (external Human Machine Interface) of automated vehicle to realize safe, secure and smooth communication between automated vehicle and peripheral traffic participant, based on psychological and cognitive aspects of the traffic participants.

Vehicle Routing Problem with Drones (VRPD) is a constraint optimization problem to minimize the routes of ground vehicles and drones (unmanned aerial vehicles), based on the number of vehicles, link cost (travel time), load capacity of each vehicle, battery capacity of each drone and regulations of the drone flight. We study fast algorithm of meta-heuristic solving VRPD in order to help the ground vehicles in serving customers, especially focusing on optimizing routes of drones and ground vehicles when permitting the drones are launched from the roof of ground vehicles.

We conduct experimental studies of driver cognitive characteristic and driving maneuver in transition from automated driving to manual driving in level-3 automated vehicles. Based on the fundamental characteristics of driver behavior in the transition, we study method or assistance on the safe and smooth transition, especially information contents and human machine interface.

The research subject includes the approach to build quality in process by data analysis in order to get high customer satisfaction. The major directions are theory and application of design of experiments, data analysis of customer usage data for design process and total quality management in organization.

Nowadays, in various fields, the use of data analysis attracts attention. In the field of marketing, analysis of data for customer questionnaire survey and the Web environment are conducted. In the medical and sports fields, the use of data analysis is being practiced. We present several data analyses, such as case studies of quantifying customer satisfaction, analysis for management, marketing, medical and sports data.

Distributed and cooperative control problems for large-scale networked systems are studied in Namerikawa laboratory via both of control theoretical and application approaches. The current main topic of Namerikawa Lab is the developments of safe, reliable and resilient control/prediction methodologies for electrical power network and smart city and smart infrastructure. The other important topic is the developments of cooperative formation control strategies for multi-agent systems including unmanned aerial vehicles.

Our research goal is to realize navigation technique for evacuees by real-time planning and notification of an adequate evacuation plan. In order to make the adequate plan, it’s necessary to combine various techniques, such as agent-based simulation, physical simulation of disasters, IoT sensor Technology, and virtual reality techniques for visualization.