Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

基于最优回归理论的舰船辐射噪声指向性统计模型及分析方法研究

文章在已有单航次的舰船噪声空间特性建模分析方法等研究成果的基础上,进一步研究了若干航次条件下的统计建模及分析方法。该研究主要以单一部位垂向剖面的噪声指向性为例,建立了基于最优回归理论的舰船目标辐射噪声特性的统计模型及分析方法,并开展了海上实测研究,验证了该模型及分析方法的正确性和可行性。该项成果为深入分析不同航行工况下各类舰船目标的噪声空间特性及其统计规律等创造了条件。     

轨道交通与城市协同发展的空间差异性分析：以北京市为例

为识别轨道交通与城市协同发展程度的空间差异性,以及不同空间范围内城市发展水平对轨道交通客流影响的差异性,引入描述空间集聚特征的莫兰指数Moran's I 建立轨道站点周边城市发展水平评价方法,将轨道站点周边城市发展水平和站点客流空间集聚分布特征作为轨道交通与城市发展协同程度判断标准,划定若干研究区域,利用地理加权回归GWR 模型研究两者空间相关性和城市发展因素对轨道交通客流的影响. 实证研究表明：轨道站点周边城市发展水平与站点客流协同程度较高的区域,城市发展水平对站点客流影响更大;将城市发展因素对站点客流影响程度进行排序,密度高于交通便捷程度、功能多样化程度和发展紧凑度.     

内蒙古道路货运与现代物流业的融合

通过对内蒙古道路货运发展的现状分析,找出当前内蒙古道路货运业存在的问题,针对问题提出传统道路货运与现代物流融合的思路及具体措施。     

小型潜器纵向运动阻力试验研究

确定潜器纵向运动阻力试验方案,通过改变速度的不同水平来测试对应阻力。然后设计测试装置、卷扬机构、单片机的模块结构和主要功能,编写试验程序。用模拟潜器进行试验,获得大量数据,用最小二乘原理进行回归分析,得到回归方程(经验公式)。经过显著性检验、经验类比和方差计算,验证回归方程具有很高的可依赖性,从而证明本文设计的潜器纵向运动阻力试验的试验方法及试验装置技术可靠,具有实际应用价值。     

城市轨道交通客流增长滞后性与预测方法研究

城市轨道交通客流是确定城市轨道交通建设规模及投资决策的主要依据,然而客流增长速度并不与城市轨道交通建设同步.考虑到城市轨道交通客流增长的滞后性,利用上海城市轨道交通1996-2010年客流与建设数据,基于协整理论建立了向量自回归模型进行城市轨道交通客流预测.研究结果表明:城市轨道交通客流与城市轨道交通网络长度以及连接度存在协整关系;在城市轨道交通建设初期,客流增长对于网络长度具有显著滞后性,随着城市轨道交通系统的完善客流滞后性减弱;2011年上海城市轨道客流预测误差为9.3％.     

EMD在海洋内波研究中的应用

采用南海内波的实测资料,利用EMD方法对内波波动进行水平和垂向的分解,并由低频模态拟合函数并叠加得到了内波引起的温度波动的函数,由垂向位移得到了内波垂向模态的一种获取方法,为非线性的海洋内波研究提供了依据。     

基于偏最小二乘的两栖突击车作战效能预测

针对两柄突击车作战效能和偏最小二乘的特点,提出了基于偏最小二乘预测作战效能的方法。介绍了偏最小二乘回归的具体过程,在此基础上．对某型两栖突击车的作战效能进行了预测。得到了可靠的作战效能系数。