铁路桥梁地质图形的反演算法研究

分析地质钻孔图和地质纵断面图特征,从地质钻孔图着手,批量提取各钻孔编号、里程和土层分界点高程存人钻孔存储表中,通过表中里程和高程数据在地质纵断面图中找到钻孔土层分界点位置,与钻孔连线进行匹配,确定钻孔连线的上下土层信息存入表中,根据地质数据表设计反演算法,可得到任意里程位置处土层信息.将该方法应用于铁路桥梁设计任务量高峰期,可缩短桥梁基础设计时地质资料处理时间,在工期短、人员少的情况下,保质保量地按时完成任务.结果表明:该算法反演速度快、结果准确,可实现桥梁专业与地质专业的无缝衔接.     

地质雷达测试技术研究

论述了地质雷达的工作特性与工作原理,分析了介质因素对雷达检测的影响,归纳了隧道检测典型缺陷对应的雷达图,应用地质雷达检测,可以从地质因素对隧道病害进行辅助分析。     

客运专线网络列车开行方案与运行图综合优化方法

基于旅客列车开行方案和运行图的铁路企业运营效益和旅客出行费用,以铁路企业效益最大化为优化目标,以车站整备能力、车辆总数和列车编组辆数等能力资源限制以及列车到发作业相容性为约束,建立旅客列车开行方案与运行图综合优化的双层规划模型;分别基于旅客列车开行方案和列车运行图的换乘网络进行客流分配,将旅客列车开行方案和列车运行图优化有效结合起来,设计了基于模拟退火的综合优化算法。算例分析表明列车开行方案与运行图的综合优化既能保证铁路企业的收益,又能够有效提高旅客换乘质量。     

基于列车运行时间偏离的地铁列车运行图缓冲时间研究

根据地铁系统的特点,分析追踪列车间隔时间与列车区间运行时间和停站时间的关系。在非晚点情况下,根据列车区间运行时间和停站时间与图定时间的偏离,建立描述列车运行图缓冲时间与干扰概率、随机干扰变量之间关系的概率模型。采用适当的分布函数对随机干扰变量进行分布拟合,计算不同干扰水平下的缓冲时间。以某条地铁线路为例,将其1 d的实际列车区间运行时间和停站时间作为基础数据,采用给出的模型和计算方法,计算得到不同干扰水平下的最小缓冲时间,用于确定地铁列车运行图合理的追踪列车间隔时间。     

提速车辆油压减振器阻力特性及示功图分析

以KONI垂向单循环双作用减振器为例,简单介绍了其工作原理和内部结构,分析了其循环过程、阻尼特性及示功图含义,并对常见不合格油压减振器的主要原因进行了分析.     

基于Timed-UML顺序图的RBC交接形式化建模与分析

在CTCS-3级列控系统中,采用RBC技术将线路划分成多个管辖区段。当列车行驶并跨越相邻RBC交界区域时,控制权将会移交至前方相邻RBC,整个过程称为RBC交接。在运行中,RBC交接过程能否实时安全可靠地执行,直接影响着列车的行车效率和乘客的生命安全。采用一种基于添加实时约束的UML顺序图与时间自动机结合的模型来建立RBC交接场景。以双车载电台的RBC切换策略出发,建立切换的Timed-UML顺序图模型,然后按照UML-TA转换规则,建立得到完整的时间自动机网络模型。并利用UPPAAL验证工具对RBC交接模型进行形式化建模及分析,对模型的死锁和功能实现做了验证,从而达到对CTCS-3级RBC子系统的实时性以及设计规范合理性的验证目的。     

关于CTC系统列车运行图功能优化的探讨

结合调度指挥工作实际,指出现行CTC系统列车运行图管理子系统功能中存在的不足,并提出改进方案,达到提高CTC系统安全性、可靠性、实用性的目标。     

全路列车运行图编制系统设计的研究

提出全路列车运行图编制系统建设的远期目标和近期目标,设计了包括铁道部和铁路局2级层次的系统总体结构,并对系统的功能和实现技术进行了研究．给出了以铁路局和铁路分局数据库为基础,合并建立全路列车运行因数据库．并以区间作为基本数据描述单元,进行数据库设计和单双线合一的列车运行图编制思想和方法．针对系统研究的技术关键问题,如系统的数据组织及数据结构设计、编图算法求解及系统的人机交互功能设计等进行了介绍和探讨．     

列流线偏移描绘自动化

基于图论理论分析了列流图的组成特性,以解决列流线折点自动搜索问题.提出列流线折点搜索算法和列流线偏移描绘算法.采用基于节点信息表绘制列流图.开发了列流图自动生成数据库系统.用实例表明了算法及软件有效性和可行性.     

Deriving macroscopic fundamental diagrams from probe data: Issues and proposed solutions

Well-defined relationships between flow and density averaged spatially across urban traffic networks, more commonly known as Macroscopic Fundamental Diagrams (MFDs), have been recently verified to exist in reality. Researchers have proposed using MFDs to monitor the status of urban traffic networks and to inform the design of network-wide traffic control strategies. However, it is also well known that empirical MFDs are not easy to estimate in practice due to difficulties in obtaining the requisite data needed to construct them. Recent works have devised ways to estimate a network’s MFD using limited trajectory data that can be obtained from GPS-equipped mobile probe vehicles. These methods assume that the market penetration level of mobile probe vehicles is uniform across the entire set of OD pairs in the network; however, in reality the probe vehicle market penetration rate varies regionally within a network. When this variation is combined with the imbalance of probe trip lengths and travel times, the compound effects will further complicate the estimation of the MFD.To overcome this deficit, we propose a method to estimate a network’s MFD using mobile probe data when the market penetration rates are not necessarily the same across an entire network. This method relies on the determination of appropriate average probe penetration rates, which are weighted harmonic means using individual probe vehicle travel times and distances as the weights. The accuracy of this method is tested using synthetic data generated in the INTEGRATION micro-simulation environment by comparing the estimated MFDs to the ground truth MFD obtained using a 100% market penetration of probe vehicles. The results show that the weighted harmonic mean probe penetration rates outperform simple (arithmetic) average probe penetration rates, as expected. This especially holds true as the imbalance of demand and penetration level increases. Furthermore, as the probe penetration rates are generally not known, an algorithm to estimate the probe penetration rates of regional OD pairs is proposed. This algorithm links count data from sporadic fixed detectors in the network to information from probe vehicles that pass the detectors. The simulation results indicate that the proposed algorithm is very effective. Since the data needed to apply this algorithm are readily available and easy to collect, the proposed algorithm is practically feasible and offers a better approach for the estimation of the MFD using mobile probe data, which are becoming increasingly available in urban environments.