基于船舶火灾蔓延态势的路径规划算法研究

船舶作为海上一个独立的建筑实体,非常容易发生火灾。本文以63500DWT油船船舱作为研究对象,通过对火灾蔓延模拟仿真实验数据进行图表分析,得出了在不同工作条件下在固定检测点位置的温度,CO浓度和烟气浓度变化规律。对基于火灾实时态势的导航网格动态生成方法以及对应的逃生路径规划方法进行研究,得出动态更新导航网格的具体算法,并对传统A*算法路径节点选择问题进行改进,得出适应船舱火灾蔓延信息的最短逃生路径规划算法,通过实验验证,该算法寻路效率更优。     

USV发展现状及展望

  目的  无人艇（USV）在复杂环境情况下会出现偏离目标航线的情况,为提高水面无人艇的抗干扰能力及实际航行的稳定性,实现对航迹的准确控制,提出一种改进的无人艇航迹控制方法。  方法  根据导航信号受环境影响的情况,对GPS信号有效和无效2种情况下的航迹控制分别进行分析,在自主可控平台上设计并实现了基于模糊控制可变船长比的视线导引算法（LOS）和自抗扰航向控制器(ADRC)相结合的航迹控制方法,并开展了双桨双舵无人艇湖上试验。  结果  仿真结果表明：该方法可满足航迹控制的要求,转弯后航向能够快速保持稳定,无频繁摆舵现象,且该方法能够完成真实环境下的航迹控制,航迹贴线误差均值约为0.1 m,方差约为0.03。  结论  湖上试验结果验证了该算法在实际工程应用中的可行性和有效性。     

点云技术在散货专业煤码头三维可视化中的应用

为了实现安全、可靠、真实的三维煤码头监控,通过GENESIS64软件平台导入3D建模,实现三维场景的展示。3D煤堆由先进的激光点云技术,产生海量测量点,使用点云灰度算法处理,再通过C#点云生成灰度图,在GENESIS64中生成真实的立体堆场画面。     

基于改进TRL校准算法的二极管参数测量

加载二极管的频率选择表面和能量选择表面（以下统称“自激励表面”）具有自适应的防护特征,能够防护强电磁攻击。二极管本身参数的测量是自激励表面设计中重要的环节,准确测得二极管特征参数对于设计出满足需求的防护表面至关重要。介绍传统去嵌入法,针对传统去嵌入法存在校准件制作精度要求高、相位延时有范围的缺点,改进了用于二极管参数测量的去嵌入算法;测量几种不同PIN型号的二极管,通过对比PIN参数手册与测试结果,验证了测试方法的有效性。

     

基于改进GA优化的水下机器人航向鲁棒控制

基于某型号水下机器人水平面线性化模型,针对水下机器人系统存在的多种不确定因素,工作环境复杂多变的问题,采用混合灵敏度法设计水下机器人航向鲁棒控制器。在设计中,通过罚函数小生境遗传适应度值作为桥梁建立起遗传寻优与混合灵敏度参数之间的关系,构成多目标优化问题寻优加权函数。实验结果表明,所用方法可在保证系统较强鲁棒性的同时,又能兼顾时域指标和混合灵敏度加权函数频域要求,获得综合性能指标最优的鲁棒控制器,控制效果较好。     

云南省民航客运发展预测

民航运输是云南省在进行综合交通运输建设的重点之一,也是该省在未来十四五(2021-2025年)和十五五(2026-2030年)规划期间的研究热点。本文以云南省为研究范围,以省内民航客运为研究对象,选取省内主要的社会经济因素为影响因子,运用主成分分析法(PCA)、反向传播神经网络算法(BP神经网络算法)和回归分析法,构建了省内民航客运的预测模型,得出省内各主要机场在十四五末和十五五末的预计旅客吞吐量,对省政府在进行机场改扩建上有一定的指导意义。     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.     

Modification of the Highway Capacity Manual two‐lane highway analysis procedure for Spanish conditions

The US Highway Capacity Manual (HCM) methodology is used in Spain to evaluate traffic operation and quality of service. The effect of passing manoeuvre on two‐lane highway operational performance is considered through adjustment factors to average travel speeds and percent time spent following. The procedure is largely based on simulations in TWOPAS and passing behaviours observed during US calibrations in the 1970s. It is not clear whether US driving behaviour and vehicles' performance are comparable with Spanish conditions. The objective of this research is to adapt the HCM 2010 methodology to Spanish driver behaviour, for base conditions (i.e. no passing restrictions). To do so, TWOPAS was calibrated and validated based on current Spanish passing field data. The calibration used a genetic algorithm. The case study included an ideal two‐lane highway with varying directional traffic flow rate, directional split and percentage of trucks. The updated methodology for base conditions is simpler than the current HCM 2010 and does not rely on interpolation from tables. Copyright © 2016 John Wiley & Sons, Ltd.     

高速公路场景下的电子稳像技术研究

为了去除高速公路监控视频中自身位置不稳定的事物给全局运动矢量估计带来误差,先通过Canny算子检测图像中的直线,并根据车道边界的特征筛选出道路边界,确定道路区域。再检测道路区域内的Harris角点信息,并与背景图中道路区域内的角点位置进行匹配,从而得到全局运动矢量,并计算出稳定的图像。实验表明,该算法能够满足高速公路场景下的稳像需求。     

Prioritizing road extension projects with interdependent benefits under time constraint

Since transportation projects are costly and resources are limited, prioritizing or sequencing the projects is imperative. This study was inspired by a client who asked: “I have tens of approved road extension projects, but my financial resources are limited. I cannot construct all the projects simultaneously, so can you help me prioritize my projects?” To address this question, the benefits and costs of all the possible scenarios must be known. However, the impacts (or benefit) of road extension projects are highly interdependent, and in sizable cases cannot be specified thoroughly. We demonstrate that the problem is analogous to the Traveling Salesman Problem (TSP). Dynamic change in travel demand during construction is another aspect of the complexity of the problem. The literature is yet to provide efficient methods for large cases. To this end, we developed a heuristic methodology in which the variation of travel demand during the construction period is considered. We introduce a geometrical objective function for which a solution-finding policy based on “gradient maximization” is developed. To address the projects’ interdependency, a special neural network (NN) model was devised. We developed a search engine hybridized of Ant Colony and Genetic Algorithm to seek a solution to the TSP-like problem on the NN based on gradient maximization. The algorithm was calibrated and applied to real data from the city of Winnipeg, Canada, as well as two cases based on Sioux-Falls. The results were reliable and identification of the optimum solution was achievable within acceptable computational time.