Framework of Tailormade Driving Support Systems and Neural Network Driver Model

Drivers are positioned as the nucleus of driving helped by driving support systems of ITS. An automatic driving system in the future may release drivers partially from driving but will never release them completely. This is because automobiles are a door-to-door means of transport, and the concept of an automobile is a driver controlled vehicle system in essence. Therefore, it is desirable for driving support systems of automobiles to have a reasonable interface with a focus placed on personal characteristics of drivers. Today, various systems aimed at pre-crash safety of drivers and reduction in driving loads are being made fit for practical application. These systems have excellent mechanical functions but systems are not good enough to fit driving feelings. This is because the driver models of these systems are the same, though each driver has different driving characteristics. Nowadays, tailormade medical treatment is receiving much attention in the field of medical care. It is also desirable for driving support systems to reflect the driving characteristics of individuals as much as possible, begin monitoring the driver when a driver starts driving and calculates the driver model, and supports them with a model that makes the driver feel quite normal. That is the construction of Tailormade Driving Support Systems (TDSS). This research proposes a concept and a framework of TDSS, and presents a driver model that uses a neural network to build the system. As for the feasibility of this system, the research selects braking as a typical constituent element, and illustrates and reviews the results of experiments and simulations.