完整街道扫描仪:智慧城市人居环境感知新技术

完整街道扫描仪以"连通"为目的构建,以移动载具的形式在未来城市的路网中部署、载人运行,借助其上搭载的传感器、车联网功能扩展出对交通流、街道环境、行人进行扫描、记录、分析、影响的能力,成为一种面向未来智慧城市的人居环境感知系统。当完整街道扫描仪成规模部署后,其作用将不仅限制于交通领域,还将深入参与进共享经济、数据安全、城市发展规划,有潜力成为一种新的经济发展模式。本文聚焦从单车智能到人居环境智能的城市管理智能化维度需求演变,从未来交通管理、未来城市管理与数字经济产业支撑三个方向对完整街道扫描仪满足未来智慧城市的需求进行阐述。同时,也总结出了完整街道扫描仪的原型系统概念模型,以及已搭建进行的示范应用。     

Towards data-driven car-following models

Car following models have been studied with many diverse approaches for decades. Nowadays, technological advances have significantly improved our traffic data collection capabilities. Conventional car following models rely on mathematical formulas and are derived from traffic flow theory; a property that often makes them more restrictive. On the other hand, data-driven approaches are more flexible and allow the incorporation of additional information to the model; however, they may not provide as much insight into traffic flow theory as the traditional models. In this research, an innovative methodological framework based on a data-driven approach is proposed for the estimation of car-following models, suitable for incorporation into microscopic traffic simulation models. An existing technique, i.e. locally weighted regression (loess), is defined through an optimization problem and is employed in a novel way. The proposed methodology is demonstrated using data collected from a sequence of instrumented vehicles in Naples, Italy. Gipps’ model, one of the most extensively used car-following models, is calibrated against the same data and used as a reference benchmark. Optimization issues are raised in both cases. The obtained results suggest that data-driven car-following models could be a promising research direction.     

Wheat interchanges in Europe: Transport optimization reduces emissions

Numerous Life Cycle Analysis of bread pointed out that wheat production and transportation have important impacts on the environment. But wheat is grown all around the world and it is not always consumed where it is produced. In this paper an analysis of the wheat movements around Europe is done, taking special attention on the Spanish situation. An optimization of wheat exchanges is done eliminating the import–export overlapping. This optimization entails a reduction of the number of trips by 34% and the CO₂ emissions reduction due to transportation is calculated to be 121.175 tones. Consequently less trips, fewer trucks, less traffic and lower emissions that brings economic, social and environmental benefits.     

Optimal development of alternative fuel station networks considering node capacity restrictions

A potential solution to reduce greenhouse gas (GHG) emissions in the transport sector is the use of alternative fuel vehicles (AFV). As global GHG emission standards have been in place for passenger cars for several years, infrastructure modelling for new AFV is an established topic. However, as the regulatory focus shifts towards heavy-duty vehicles (HDV), the market diffusion of AFV-HDV will increase as will planning the relevant AFV infrastructure for HDV. Existing modelling approaches need to be adapted, because the energy demand per individual refill increases significantly for HDV and there are regulatory as well as technical limitations for alternative fuel station (AFS) capacities at the same time. While the current research takes capacity restrictions for single stations into account, capacity limits for locations (i.e. nodes) – the places where refuelling stations are built such as highway entries, exits or intersections – are not yet considered. We extend existing models in this respect and introduce an optimal development for AFS considering (station) location capacity restrictions. The proposed method is applied to a case study of a potential fuel cell heavy-duty vehicle AFS network. We find that the location capacity limit has a major impact on the number of stations required, station utilization and station portfolio variety.     

基于混沌蚁群算法的最短路径选择研究

如何解决最短路径选择问题一直是城市交通流诱导系统的关键之一.基于群体仿生理论的蚁群算法是解决此问题的一种方法,针对采用蚁群算法进行最短路径选择时易出现的陷入局部最优解问题,引入混沌理论,采用混沌蚁群算法利用混沌初始化进行改善个体质量和利用混沌扰动避免在蚁群算法搜索过程中陷入局部极值,同时降低了蚁群算法的时间复杂度,从而更好的解决了最短路径选择问题.     

积分分离PID控制算法在炉温控制系统中的应用

积分分离PID控制算法是当被控量与设定值偏差较大时,取消积分作用,以提高系统的稳定性,减小系统的偏差,当被控制量接近设定值时,引入积分控制。本文以工业中常用的炉温控制系统为例进行仿真试验分析,验证积分分离PID控制算法的作用。     

C2/C3等级转换设置方案优化探讨

根据列车运行控制系统C2/C3等级转换的相关规范、RBC和ATP设备C2/C3级间转换时的处理过程,对工程实施过程中存在的C2/C3级间转换设置问题进行了分析研究,并提出相应的优化措施。     

SS_(4G)型电力机车车轮轮心裂损的检测

根据SS4G型电力机车铸钢车轮轮心和整体辗钢车轮裂损情况,分析裂损原因,介绍目视检查、磁粉探伤、超声波探伤及脉冲涡流探伤的裂损检测方法。结合实际,提出减少轮心裂损发生的措施和出现裂损时的应对方法。     

地铁架空刚性接触网平面设计软件的优化

当前地铁设计任务的不断增加对接触网辅助设计软件提出更高的要求。介绍架空刚性接触网平面设计软件的优化内容,采用先进的编程语言实现分布式软件架构,对架空刚性接触网平面设计中的底图处理、锚段智能划分、悬挂点智能布置及冲突检测和调整、拉出值自动计算、汇流排和渡线设计、工程量统计及图幅处理等算法进行优化设计。实际应用表明,本软件提高了地铁架空刚性接触网平面设计的成图质量及设计效率,可满足高质、高效的出图需求。     

鲁棒实时钢轨表面擦伤检测算法研究

应用图像处理和模式识别技术,分析高速线阵扫描相机采集的钢轨数字图像,提出鲁棒实时的钢轨表面擦伤检测算法。这种算法首先分析采集图像在垂直方向的投影曲线,提取准确钢轨图像;之后,借鉴人类视觉对比度感知机理,将钢轨灰度图转换为灰度对比图,并基于最大熵原理进行二值化处理,分割出可疑擦伤区域;然后根据经验知识判定钢轨表面的可疑擦伤。实验验证表明:新算法的检测性能高,平均准确率为90.7%,平均漏检率为3.95%;检测速度快,平均检测时间不超过40 ms。