信息融合技术在交通流量预测中的应用

交通流量预测是智能运输系统的一个重要组成内容，但传统的数学方法一直未能取得令人满意的预测效果。信息融合技术是最近十多年来新兴的技术。它通过合理协调多源数据，充分综合有用信息，在较短的时间内，以较小的代价获得对未来交通流量的预测。实验证明，借助信息融合理论建立的聚类分析模型和神经网络模型对未来交通流量的预测比较准确，有实际意义。     

列车通信网结构及其协议的研究

介绍了列车通信网的主要功能和特点。在此基础上，对列车通信网规范进行了研究，将几种通用局域见及流行的现场总线的特点进行了对比，提出目前我国列车通信网可采用的体系结构和网络协议。     

机场货运交通量预测方法研究

该文首先分析了机场货运交通的特点,针对这些与常规交通预测不同的特点,构建了机场货运交通预测模型,模型中不但考虑了机场货邮吞吐量,而且考虑了货运业务的客运需求。最后,以深圳机场规划为例,进行了货运交通预测。     

基于双目视觉计算的车辆跟驰状态实时感知系统

双目视觉技术能够实现目标的识别与距离计算，在自动驾驶领域有很大的应用空间。然而，现阶段双目视觉存在光照干扰、遮挡、弱纹理区域歧义匹配等问题，影响其测量的准确性和可靠性。提出基于双目视觉的跟驰状态实时感知系统，该系统采用基于车辆跟驰模型的扩展卡尔曼滤波方法对车辆跟驰状态进行实时估计，包括跟驰距离、前后车速度差等。通过实际道路试验，证明了该系统能够识别并修正测量数据中的异常值，解决弱纹理区域误匹配问题。试验结果表明：25 mm焦距与12 mm焦距的双目系统跟驰间距测量值的平均误差分别为2.66%与9.14%；在相对速度测量方面，2种焦距系统的测量精度基本相同，平均误差均为1 m·s^-1左右。所提出的方法在自动驾驶车辆环境感知领域有较好的应用前景。     

接触网系统各部件内部应力概率分布规律

采用有限元并结合改进算法的径向基神经网络RBF,判别接触网系统各部件内部应力的随机分布规律。以兰新线武嘉段接触网腕臂为算例,把安装角度、冰负载、承力索覆冰风负载、接触线覆冰风负载等参量作为基本变量,按各变量的分布规律随机地产生50组样本数据,通过有限元计算出每一组参数对应的内部最大应力,依据随机抽样规律抽取40组,按经验分布计算出对应的应力分布函数值。利用RBF进行模式识别得到应力符合威布尔分布,并用回归分析计算出正态分布、指数分布、威布尔分布、对数正态分布二个变量的相关系数。从相关系数和拟合图可以看出,应力符合威布尔分布最好,服从指数分布的可能性最小,RBF识别的结果与回归分析的结果是一致的。     

战时铁路网络生存性定量评价研究

引入了铁路网络临界截面的概念,通过寻求铁路网络的临界截面,从而确定出铁路网络中生存能力较弱的区段,为改进、增强和提高战时铁路网络的生存能力提供科学依据,对于顺利完成铁路军事运输任务具有十分重要的意义。     

油船主船体隔舱划分的神经网络专家系统

本文在总结专家系统（ＥＳ）发展与现状的基础上，描述了油船舱划划分的神经网络专家系统（ＴＡＧＮＥＳ）的基本原理与结构，以及基于 ＴＡＧＮＥＳ的知识表示，获取与推理，提出了ＴＡＧＮＥＳ与其它领域神经网络专家系统的组合，系统地阐述了ＴＡＧＮＥＳ的理论体系，同时给出３８０００吨油船分舱仿真设计的部分算例，说明了应用神经网络专家系统这一新理论来进行油船分舱智能设计的有效性和实用性。     

Fault Diagnosing System of Steam Generator for Nuclear Power Plant Based on Fuzzy Neural Networks

All kinds of reasons are analysed in theory and a fault repository combined with local expert experiences is establishedaccording to the structure and the operation characteristic of steam generator in this paper. At the same time, Kohonen algo-rithm is used for fault diagnoses system based on fuzzy neural networks. Fuzzy arithmetic is inducted into neural networks tosolve uncertain diagnosis induced by uncertain knowledge. According to its self-association in the course of default diagnosis. thesystem is provided with non-supervise, self-organizing, self-learning, and has strong cluster ability and fast cluster velocity.     

光纤分布式接触网开关远程监控系统的应用

结合工程实际,介绍一种新型的基于光纤现场总线的铁路枢纽接触网开关监控系统。     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.