血液酒精浓度对驾驶行为的影响研究

为了探讨饮酒对驾驶员驾驶行为的影响,以驾驶模拟器为平台,测试了13名驾驶人员在不同血液酒精浓度（0mg/dl,20mg/dl,50 mg/dl,80 mg/dl）、不同场景下加速、刹车情况并调查了其主观感受。进行数据分析后初步得到一些结论：饮酒（特别是在较高血液酒精浓度的情况下）确实会对驾驶行为产生影响并可能会导致某些危险驾驶行为;性别和驾驶经验也会对不同酒精浓度下的驾驶行为产生影响。     

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.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。     

大型船舶企业组织管理的柔性控制

介绍了上海船厂船舶有限公司实施企业组织管理柔性控制的背景、主要内容、具体方法,以及取得的初步效果。     

200万桶FPSO涂装生产模式的探索与实践

论述了上海外高桥造船有限公司（SWS）涂装部在建造200万桶浮式生产储油船（FPSO）时采用的生产组织管理模式,这对于SWS后续建造类似项目的涂装施工提供了良好的借鉴。     

武汉市过长江交通流量特征分析

武汉市过长江交通是武汉市最主要的交通流向之一。根据流量观测数据分析长江交通流量特征,表明武汉市区过长江交通饱和,交通需求总量大,出行目的种类多。过长江交通没有明显、固定的高峰日和高峰小时,除通勤交通外。还有公务等大量非通勤交通。其中武昌与汉口之间交通是主流向,需要适当新增通道缓解过江难问题。     

基于神经网络的道路通行能力与交通需求匹配度判别研究

交通的供需是否匹配关系到城市和枢纽的发展前景。文中在探讨道路通行能力与需求匹配特性的基础上,用BP神经网络理论建立一种交通匹配预测模型。该模型发挥神经网络的优势,对数据并行处理和分布存储,通过训练、学习产生一个非线性映射,自适应地对数据进行预测。通过相关数据实验证明,该神经网络模型有较高的精度,并有较好的适用性。     

计算组织的测试环境分析

对目前普遍采用的两种计算组织测试环境—分布式动态决策模拟器(Distributed Dynamic Decision-making,DDD)与组织虚拟测试的Extend环境进行分析,指出两种途径各自的优缺点,针对未来计算组织测试的需求提出测试技术的发展趋势。