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Breath alcohol interlock systems are used in Europe and the U.S. for drunk driving offenders, and a certain effect has been revealed in the prevention of drunk driving. Nevertheless, problems remain to be solved with commercialized detectors, i.e., a person taking the breath alcohol test must strongly expire to the alcohol detector through a mouthpiece for every test, more over the determination of the breath alcohol concentration requires more than 5 seconds. The goal of this research is to develop a device that functions suitable and unobtrusive enough as the interlock system. For this purpose, a new alcohol detector, which does not require a long and hard blowing to the detector through a mouthpiece, has been investigated. In this paper, as a tool available on board, a contact free alcohol detector for the prevention of drunk driving has been developed.

A few reports suggest differences in injury outcomes between cadaver tests and real-world accidents under almost similar conditions. This study hypothesized that muscle activity could primarily cause the differences, and then developed a human body finite element (FE) model with individual muscles. Each muscle was modeled as a hybrid model of bar elements with active properties and solid elements with passive properties. The model without muscle activation was firstly validated against five series of cadaver test data on impact responses in the anterior-posterior direction. The model with muscle activation levels estimated based on electromyography (EMG) data was secondly validated against four series of volunteer test data on bracing effects for stiffness and thickness of an upper arm muscle, and braced driver's responses under a static environment and a brake deceleration.

This paper gives an outline of the steering assistance system (hereinafter, SAS) and a description of its key technology: the lane recognition algorithm. To accommodate a variety of driving styles, the SAS is equipped with a lane keeping assistance mode (LKA mode) and a lane departure warning mode (LDW mode) that can be selectively set by the driver. The former mode works in combination with adaptive cruise control (ACC) and carries the advantage of relieving the driving load that is placed on the driver. The latter mode has the benefit of reducing the danger of lane departure accidents caused by the driver dozing off and taking his eyes off the road. The newly developed lane recognition ECU has a simple hardware set-up of two 32-bit microcomputers. The lane recognition algorithm was constructed on the basis of a logic process that analyzes pattern edge points and selects a set of edge points that most closely resemble lanemarks.