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Deceleration patterns of an expert driver will be formulated using the perceptual risk index for approach and proximity of a preceding vehicle as an example of comfortable braking pattern. It will be shown that the formulated braking pattern can generate smooth deceleration profile uniformly for many conditions of approaching conditions. In addition, brake initiation timing of expert driver will be successfully formulated using the alternative index. Finally, an automatic braking system will be proposed based on the formulated brake initiation model and the velocity profile. Twenty five expert drivers experienced the automatic braking installed in an experimental car. It will be shown that the proposed system can generate smooth profile and realize secure brake patterns based on subjective evaluation.

Driving is an action that depends strongly on visual information. For displays in the cockpit, a combination of “ease of viewing” to inform the driver of danger early and “annoyance reduction” to avoid drops in the driver’s perception is needed. In this study, we tried to capture “ease of viewing” and “annoyance” in one fixed-quantity indicator. We took up a Camera Monitor System (CMS) as the subject and analyzed the effect that annoyance with the display used in CMSs has on driving behavior. Based on our analysis, we hypothesize that evaluating carelessness in viewing behavior is related evaluating to annoyance. Next, we chose a Detection Response Task (DRT) technique as a method to evaluate driving behavior influenced by this annoyance.

This paper presents detection technology for a driver monitoring system using JINS MEME, an eyewear-type wearable device. Serious accidents caused by human error such as dozing while driving or inattentive driving have been increasing recently in Japan. JINS MEME is expected to contribute to reducing the number of traffic deaths by constantly monitoring the driver with an ocular potential sensor. This paper also explains how a driver’s drowsiness level can be estimated from information on their blink rate, which can be calculated from the ocular potential.

Head-up displays (HUDs) give visual information to drivers in an easy to understand manner and prevent traffic accidents. Augmented reality head-up displays (AR-HUDs) display the driving information overlaid on the actual scenery. The AR-HUD must allow the visual information and the actual scene to be viewed at the same time, and a sense of depth and distance are key factors in achieving this. Binocular parallax used in stereoscopic 3D display is one of the most useful methods of providing a sense of depth and distance. Generally, stereoscopic 3D displays must limit the image range to within Panum’s fusional area to ensure fusion of the stereoscopic images. However, when using a stereoscopic 3D display for an AR-HUD, the image range must extend beyond Panum’s fusional area to allow the visual information and the actual scene to be displayed at the same time.