城市滨水道路建设研究及实践

针对上海苏州河中心城段静安区两岸滨水道路的建设,分析了现状滨水道路存在的问题,结合苏州河两岸的建设规划及现状,明确了以慢行功能、游憩功能、景观功能为主,机动车通行功能为辅的道路定位,确定了弱化交通功能、释放慢行空间和亲水平台,多元化、亲水可见水的设计理念.在此基础上,从整体断面改造、贯通断点及亮点打造、地块出行等方面,研究了具体实施方案.最后总结提出,滨水道路的建设应从需求出发提升公共空间环境品质,从空间体验出发进行工程技术处理.     

基于时空GPSO-SVM的短时交通流预测

为了提高城市道路短时交通流预测的精度,提出了一种基于时空遗传粒子群支持向量机的短时交通流预测模型.通过主成分分析法对路网原始交通流量进行时空相关性分析,用较少的主成分代替原始交通流量并作为预测因子,在粒子群算法中引入遗传算法的交叉和变异因子,避免粒子群算法陷入局部最优.利用改进后的粒子群算法优化支持向量机参数,得到最优的支持向量机模型,并实现城市道路的短时交通流预测.以长春市路网的实测数据为基础进行了实例验证,结果表明,优化支持向量机参数时,遗传粒子群算法不会陷入局部最优,优化效果更好;与粒子群支持向量机模型和遗传粒子群支持向量机模型相比,所提出预测模型的相对误差波动较稳定,平均预测精度分别提高了4.96%和3.41%.     

船舶吊舱SSP推进电机的无模型自适应矢量控制方法

考虑具有不确定动态和航行中负载变化与海况干扰的船舶吊舱SSP推进电机控制问题, 提出了一种无模型自适应矢量控制方法, 推导了SSP推进电机的动态线性方程, 设计了基于速度跟踪误差无模型自适应矢量控制器和进行了收敛性证明, 在线调整伪偏导数, 保证了推进电机控制系统跟踪误差一致有界, 并对比了无模型自适应矢量控制器与自整定PI矢量控制器的控制性能。计算结果表明: 基于复合无模型自适应矢量控制的SSP推进系统在恶劣海况下转速平均振荡小于6 r·min^-1, 转矩平均振荡小于8.20×104 N·m, 机动航行时对应的值分别小于7 r·min^-1与1.08×105 N·m, 而采用自整定PI矢量控制时, 在恶劣海况下转速平均振荡达到13 r·min^-1, 转矩平均振荡达到2.13×105 N·m, 机动航行时对应的值分别达到12 r·min^-1与2.81×105 N·m, 因此, 复合无模型自适应矢量控制下的转速与转矩抖动和稳态运行静差较小, 具有良好的动态响应。     

北京轨道交通站点周边步行空间连续性影响因素分析

以北京三环到四环片区的70个轨道交通站点为样本,从宏观层面步行网络的整体度和微观层面步行路径的通畅度两大层面分析站点周边步行空间的连续性,借助卫星图观测、地图标记及实地勘察等方法探寻其主导问题及影响因素.研究表明:北京城区站点周边步行网络整体度受主干道、快速路、高架桥三者影响最大,河流和铁路次之,少部分站点受轨道交通高...     

考虑空车调配协调的货物列车开行方案优化研究

为实现空车调配与货物列车开行方案协调优化,结合基本运行图架构与车流径路,构建货运时空服务拓展网络。考虑配空与装卸取送、集编发等环节的时间接续要求,节点与区段不对流空车要求,以重车流全程运送与空车配送等广义总费用最少为目标,建立整数规划弧路模型。针对既有算法设计局限性,结合重车或空车配空的时间接续要求,提出将不同的 k 短路重车流方案与空车配空方案相关联的改进可行解构造方法,设计混合差分进化求解算法。实例研究表明,考虑空车调配进行重车、空车流组织协调优化,能够减少空车走行费用,及时满足装车需求,有效保证作业车流配合中转车流集结编组及时挂线,提高方案可实施性。     

Categorizing bicycling environments using GPS-based public bicycle speed data

A promising alternative transportation mode to address growing transportation and environmental issues is bicycle transportation, which is human-powered and emission-free. To increase the use of bicycles, it is fundamental to provide bicycle-friendly environments. The scientific assessment of a bicyclist’s perception of roadway environment, safety and comfort is of great interest. This study developed a methodology for categorizing bicycling environments defined by the bicyclist’s perceived level of safety and comfort. Second-by-second bicycle speed data were collected using global positioning systems (GPS) on public bicycles. A set of features representing the level of bicycling environments was extracted from the GPS-based bicycle speed and acceleration data. These data were used as inputs for the proposed categorization algorithm. A support vector machine (SVM), which is a well-known heuristic classifier, was adopted in this study. A promising rate of 81.6% for correct classification demonstrated the technical feasibility of the proposed algorithm. In addition, a framework for bicycle traffic monitoring based on data and outcomes derived from this study was discussed, which is a novel feature for traffic surveillance and monitoring.     

Analyzing passenger train arrival delays with support vector regression

We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.     

Dynamic stride length adaptation according to utility and personal space

Pedestrians adjust both speed and stride length when they navigate difficult situations such as tight corners or dense crowds. They try to avoid collisions and to preserve their personal space. State-of-the-art pedestrian motion models automatically reduce speed in dense crowds simply because there is no space where the pedestrians could go. The stride length and its correct adaptation, however, are rarely considered. This leads to artefacts that impact macroscopic observation parameters such as densities in front of bottlenecks and, through this, flow. Hence modelling stride adaptation is important to increase the predictive power of pedestrian models. To achieve this we reformulate the problem as an optimisation problem on a disk around the pedestrian. Each pedestrian seeks the position that is most attractive in a sense of balanced goals between the search for targets, the need for individual space and the need to keep a distance from obstacles. The need for space is modelled according to findings from psychology defining zones around a person that, when invaded, cause unease. The result is a fully automatic adjustment that allows calibration through meaningful social parameters and that gives visually natural results with an excellent fit to measured experimental data.     

密闭空间空气净化用滤材检测设备设计研究

随着机动车辆的普及,人们呆在密闭空间即驾乘室以及室内的时间会逐渐拉长,如何有效的控制密闭空间的PM2.5浓度值值得我们去探讨和研究。通过对密闭空间空气净化原理的分析,采用激光粒子计数方法,设计了密闭空间空气净化检验流程及相配套的检测设备,将密闭空间(含室内及驾乘室)大气中的PM2.5含量控制在标准要求的浓度值以内。     

桨-舵间距对其组合系统水动力性能的影响

本文通过CFD方法对敞水桨、桨-舵组合以及优化间距的桨-舵组合装置开展了数值仿真研究，分析了桨-舵间距对其组合系统的水动力性能影响。螺旋桨敞水工况的计算值与物理模型试验值吻合良好，验证了数值计算方法的可行性。通过对比桨-舵间距大于推荐值的三个工况，发现在较低进阶系数下系统的节能效率有稍许增加，然而随着间距的增大，节能效率呈现降低的趋势；在高进阶系数下，随间距增大节能效率逐步降低。适当减小桨-舵间距，在较低和中等进阶系数下，随间距减小节能效率呈现逐步升高的趋势，在间距减少10mm时，组合体的节能效率最大可增加1.937%；不过在高进阶系数下，随间距减小节能效率却有下降趋势。