对铁路客站概算编制几个问题的探讨

铁路站房一般具有跨度大、空间大、荷载重等特点,他不同于一般的工业与民用建筑,在编制概预算时如果直接套用地方定额,会存在一定的不合理性.此文从站房基坑土方开挖、大体积混凝土支撑系统、大型钢结构安装工程、建筑装修支撑体系等方面,分析对编制项目概算的影响.通过分析与对比,提出采用地方定额的建议,以供在今后编制站房概算中借鉴.     

Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data

Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.     

融合可持续理念的交通规划方案比选方法——以亚特兰大大都市区为例

越来越多的机构开始为交通系统的可持续发展定义,并试图将这一概念融入区域交通规划过程.然而,只有极少数的区域规划机构意识到了交通系统和土地利用变化给经济、环境和社会生活质量(这三者通常被认为是可持续交通系统的三个基本方面)带来的广泛影响.首先,论述了使用多个可持续发展指标的多准则决策方法,并应用其评估亚特兰大大都市区的三...     

基于自然驾驶数据的驾驶人换道决策识别研究

为实现人机共驾模式下智能系统对驾驶人换道决策的准确识别,将换道决策细分并提出了基于改进的极端梯度提升(XGBoost)的换道决策识别模型。以实车试验采集的自然驾驶数据作为输入,并采用滑动时间窗法确定识别时刻,建立各识别时间窗口下基于XGBoost的换道决策识别模型,同时运用交叉检验和网格搜索(GS)算法进一步提升模型性能,最后利用验证集数据评估所构建GS-XGBoost模型的识别性能,并与机器学习及深度学习模型进行对比。结果表明,所提出的模型在具体换道决策辨识上具有较好的实时性和准确性,且在1.8 s和1.6 s时间窗下的识别准确率最高,达到86.2%。     

基于多属性决策的无人驾驶自主变道决策技术研究

在无人驾驶领域,随着车辆上布置的传感器不断丰富,无人驾驶系统可以从周围环境获得更多的信息,从而为车辆的自主判断行为决策带来可能。然而即使是有经验的驾驶员在进行变道动作的时候也需要格外的小心,因此无人驾驶系统的变道行为分析需要做到足够准确和谨慎,才能保证安全性,这也正是目前为止还没有非常完善的无人驾驶变道决策系统的原因。本文提出一种基于多属性决策的无人驾驶自主变道决策技术,帮助无人驾驶车辆在道路行驶中进行更有效、更安全的自主变道决策。     

论编制既有电气化增建二线铁路定额的必要性

随着我国电气化铁路的发展,在既有电气化铁路的基础上,增建二线电气化铁路的项目愈来愈多,而现行定额尚属空白.此文对该类项目的施工组织、方法、工艺、行车干扰以及人工和机械的消耗等方面的特殊之处,进行了具体分析,并提出了定额编制的建议.     

Driver requirements and road traffic informatics

Initially the driver's role as a link in the driver-vehicle-road-traffic control-chain is discussed in a historical perspective. The gradual changes and the advantages and problems arising from these changes are discussed from behavioural point of view.Then the driver tasks are analyzed. A separation is made between trip planning, navigation, road following, traffic interaction, rule compliance, other than traffic tasks, car handling and speed choice. The relations between and the weights of these subtasks are discussed. Some existing driver behaviour models are reviewed in relation to the above mentioned tasks.Finally an effort is made based on the analyses of driver tasks and driver models to specify some general and some more specific potential advantages and problems with expected future RTI-systems.     

Leave the expressway or not？ Impact of dynamic information

This study investigates drivers＇ diversion decision behavior under expressway variable message signs that provide travel time of both an expressway route and a local street route. Both a conventional cross-sectional logit model and a mixed logit model are developed to model drivers＇ response to travel time information. It is based on the data collected from a stated preference survey in Shanghai, China. The mixed logit model captures the heterogeneity in the value of ＂travel time＂ and ＂number of traffic lights＂ and accounts for correlations among repeated choices of the same respondent. Results show that travel time saving and driving experience serve as positive factors, while the number of traffic lights on the arterial road, expressway use frequency, being a middle-aged driver, and being a driver of an employer-provided car serve as negative factors in diversion. The mixed logit model obviously outperforms the cross-sectional model in dealing with repeated choices and capturing heterogeneity regarding the goodness-of-fit criterion. The significance of standard deviations of random coefficients for travel time and number of traffic lights evidences the existence of hetero- geneity in the driver population. The findings of this study have implications for future efforts in driver behaviormodeling and advanced traveler information system assessment.     

舰艇改装、退役评估论证的一种多属性模糊决策方法

针对影响舰艇改装、退役的主要因素进行了分析，给出各因素的评估模型，运用多属性模糊决策方法提出一种舰艇改装和退役评估论证方法，为舰艇改装退役决策提供了一定依据。     

基于黑板体系的CGF智能决策系统的构造

介绍了一种智能决策系统的结构设计，此设计以黑板体系为构架，通过内置的黑板结构、知识源结构及椎理控制策略为CGF提供一个简易、友好的智能决策系统。在决策推理决策中，由于不精确推理算法的使用，使得此智能决策系统决策快速而准确，满足了CGF智能决策的需求。