Yuzuru Yamakage

Assessment and prediction of older drivers' driving performance

Traffic accidents involving older drivers have been increasing all over the world. In order to assess elder driving performance and predict the risk of traffic accidents, we analyzed data from specific license renewal tests that are obligatory for Japanese drivers aged 70 years old or older, which includes a driving simulator test and an on-road test. As a result of the analysis, we found that aging affects several test results, such as the percentage of correct answers and the reaction times in multiple judgment tasks tests. In order to be able to classify a driver as a high accident risk, we performed an outlier analysis using a one-class SVM to investigate performance characteristics, and also performed a logistics regression analysis. Using parameters strongly related to cognitive decline, we found a viable way to classify impaired drivers. Driving is a complex task requiring integration of cognition, judgment, and operation skills. Deterioration of these skills is likely to increase the risk of traffic accidents. Although our final objective was to support elderly drivers suffering such deterioration, we initially studied a measurement method to detect the area and extent of deterioration effectively.

A New Optical System for Holographic Memory Applying a Finite Objective Lens

We have developed a new objective lens for a holographic storage system to increase areal density. To balance focal length and working distance, we adopted a finite objective lens. By incorporating phase conjugate reproduction into the finite objective lens, we obtained practically applicable and adequate signal quality. We measured shift selectivity and the effect of crosstalk and evaluated book size, which was reduced by ca. 0.8. The areal density was estimated to increase by about 1.6 times when using the new objective lens.

First surface magneto-optical recording of over 36 Gbit/in2 using domain expansion media

First surface magneto-optical (FSMO) recording offers great potential for high-density recording. We have developed a domain expansion media for FSMO recording that uses a finely structured seed layer. Additionally, we clarified the relationship between drop-out and the recording resolution of this type of media. We realized a clear magnetic domain with continuous marks, a low drop-out, and a signal reproduction of 65 nm using domain expansion media. This domain has drastically improved the recording resolution. This was achieved by forming a finely structured seed layer under the memory layer. This technique enables a recording density of over 36 Gbit/in2.