Smart Mobility Research Center
In the context of daily life behavior, logistics behavior and driving behavior, this project focuses on (1) the integrated sensing technology to extract the features and the habit of users by measuring and collecting the normal behavior data, and (2) the individual adaptation technology based on the data mining/machine learning algorithm. These two core technologies provide the safety and security service of each context corresponding to the individual characteristics of users and the individual situation/environment. TUAT participated this research project in the context of automobile driving, aiming to design the individual adaptive driver assistance systems.
Focusing on driver assistance system in real-world situations, it is necessary to design the human-machine interface for driver assistance systems to obtain the satisfactory interaction in cooperative maneuver between safety system and human driver manual control. The design of cooperative control among these devices, which fits the driver behavior or intention, is required. Especially, in this research, the predetermined routine driving route as one’s commuting path is focused here to examine the driving behavior of the individuals. The required main functions of the system are
Recently, data collection along the predetermined route is conducted and driver behavior during each driving maneuver is modeled and analyzed to get the ordinary driving behavior of each individual.
This research is a part of the Core Research for Evolutional Science and Technology (CREST) research programs entitled “Mobility Sensing for Safety and Security”, funded by Japan Science and Technology Agency (JST).
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