Estimation of the wave direction of ship waves generated by a small vessel using the multiple signal classification method

It is very important to estimate the waves generated by a small vessel so as to investigate their effects on floating bodies within the scope of fisheries and ocean engineering. Simplified methods for estimating the wave heights and periods of ship waves have been presented in previous studies. However, estimating the direction of ship waves is not easy. The focus of the present study is to develop an analytical technique to determine the direction of ship waves based on the measurements in field experiments. The multiple signal classification (MUSIC) method is newly proposed for determining the direction of ship waves. For high ship speeds, the directional spectrum of ship waves estimated by MUSIC resulted in a sharp monotone peak, and the estimated directions of ship waves were very similar to the results of field experiments using an actual small vessel. The proposed MUSIC method has thus been confirmed to be effective in estimating ship wave directions with high resolution.     

在东京中心区开通第二条环状轨道系统的影响

东京是世界上最大的城市之一,对全球的经济、政治和文化都有很大的影响力.但是,从50年代起日本进入高速经济发展阶段之后,东京的人口急剧增加,社会基础设施日渐落后.铁路运输严重阻塞,车辆拥挤不堪,交通日益恶化的状况成为铁路运营公司、地方以及中央政府必须解决的问题.铁路作为公共交通的主要手段,发挥了积极疏导作用,使得交通阻塞得到一定缓解,但没有从根本上解决问题.从长远观点看,考虑到保护环境的重要性,小汽车的数量还要大大缩减,更多的乘客要转到铁路运输上来.     

可模拟车辆实际应用工况的油压减振器试验设备的开发

介绍了所开发的能够模拟车辆实际应用情况的油压减振器试验设备,重点阐述了减振器特性的自动识别功能.     

An investigation of factors contributing to major crash types in Japan based on naturalistic driving data

Traffic accident statistics suggest that the human errors contributing to major crash types in Japan are predominantly failures in safety confirmation and hazard recognition that result in delayed response. A naturalistic driving data acquisition system was developed to investigate the human factors that contribute to such accidents. A preliminary analysis was performed to evaluate the efficiency of the collected naturalistic data. An analysis of vehicle-to-motorcycle conflict data demonstrated that types of recognition failure differ by types of traffic situation encountered. This result suggests that naturalistic driving data can provide valuable information for investigating the factors that contribute to the risk of human error.