基于元胞自动机的港湾公交站间距影响研究

公交系统对城市交通流的影响十分显著，在对现有经典交通流元胞自动机模型进行总体分析的基础上，提出了一种考虑公交车辆和港湾式公交停靠站影响的多速混合车辆双车道元胞自动机模型，重新标定了元胞长度、运行车速和随机慢化机制，引入了公交车停靠站，改进了车辆变换车道规则。通过计算机模拟，再现了传统交通流三参数之间的关系，为更好地描述城市混合交通流奠定了基础。     

大型客车影响的双车道多速混合交通流CA模型研究

在对现有经典交通流元胞自动机模型进行总体分析的基础上,结合我国高速公路特点,通过重新标定元胞长度、运行车速、随机慢化机制,制定车道转换规则,构建了周期边界条件下考虑大型客车影响的双车道多速混合交通流元胞自动机模型,并通过计算机模拟分析了速度、密度、流量三参数之间关系,寻找出了大型客车占有率、大型客车随机慢化概率、变换车道车辆数等因素对交通流的影响规律,为合理的组织高速公路交通管理提供了理论依据。     

基于元胞自动机扩展模型的图的最短路径算法

利用元胞自动机在元胞空间上的并行特性，采用元胞动态邻居，时间段自适应调整的方法，构造出一种新的基于元胞自动机扩展模型的最短路径搜索算法，即通过简单规则的元胞状态演化，得到带权图的最短路径；该方法经过优化，能够达到Dijkstra算法的时间效率；并且为基于元胞自动机扩展模型解决图的问题的提供了新的思路。     

大型货车影响的高速交通流元胞自动机模型

高速公路上的车辆到达是随机的,且含有车型大、运行速度低的大型货车,其对交通流影响很大。结合我国高速公路特点,通过重新标定元胞长度、运行车速、随机慢化机制和制定车道转换规则,建立了开放边界条件下大型货车影响的双车道多速混合交通流元胞自动机模型;通过计算机模拟分析了速度、密度、流量三参数之间关系,寻找出了大型货车占有率、随机慢化概率等因素对交通流的影响规律。     

基于二维元胞自动机的网络模型*

针对一维元胞自动机网络模型的转发过程随机化,二维模型缺乏拥塞特性分析的缺陷,提出了一种基于二维元胞自动机的网络模型。根据TCP/IP拥塞控制协议设计了元胞更新规则,并设置不同的元胞队列长度以增强网络的异构性。利用该模型仿真得到了拥塞相态下的节点负载、节点处理延时具有白噪声特性和1/f噪声特性。通过该模型观测到局部网络与整个网络负载特性的关系,表明该二维元胞自动机网络模型具有可扩展性,适用于大规模网络的行为建模研究。     

周期边界条件下多速混合车流的双车道元胞自动机模型

在对现有经典交通流元胞自动机模型进行总体分析的基础上,结合我国部分高速公路已不再有行车道和超车道之分的特点,重新标定了元胞长度、运行车速、随机慢化机制和换道超车规则,构建了周期边界条件下多速混合车流的双车道元胞自动机模型,通过计算机模拟分析了交通流三参数之间关系,大型货车占有率对交通流的影响及大货车占有率不变且交通流密度变化的情况下的时空斑图比较。结果表明,在高速公路不分行车道和超车道的情况下,大型货车的占有率对混合车流的速度影响不大,车辆的随机减速概率会对混合车流的运动状态起重要作用。     

一种改进的NS元胞自动机模型

研究改进了基于元胞自动机的一维NS交通模型，细化了元胞长度和时间步长，对静止车辆的加速能力进行了约束，用简单的方法解决了该模型中车辆的速度演化规则与前车速度无关的缺点。同时，考虑了交通密度对随机慢化概率的影响。计算机仿真表明：改进模型不仅得到了一些与其他元胞自动机模型共有的性质，且得到的基本图更加接近实测数据。     

基于元胞自动机的交通流计算机模拟

元胞自动机是把复杂系统量化为简单的个体,在元胞自动机模型中.空间、时间都被离散化,每一个相互作用的单元仅为有限的状态.以元胞自动机理论为基础,把车辆在路段上交通流中运动的变化规律表述为元胞自动机的演化规则,建立了基于元胞自动机理论的交通流模拟模型,标定了元胞长度和最大速度等参数,分析了元胞变换的原则;详细探讨了元胞自动机在道路交通模拟中的应用,设计出了交通元胞自动机的结构,分析了交通元胞自动机所采取的状态变换原则,建立了一维(单车道)交通流模拟模型;并利用C语言编程实现模拟.模拟结果符合实际交通流的特点.     

一维交通流仿真变长度虚坡模型

元胞自动机方法反映了交通流问题的一些主要特征,但仍有其不足.特别是元胞自动机不能有效反映车辆行驶惯性,给出连续变化的车辆速度.虚坡模型能给出连续的车速,但原有虚坡模型中虚坡长度保持不变,易于造成车辆分得太开或相靠太近的情形.为了提高速度精度和改善车流问题,提出变化虚坡长度的概念,确保车辆的加速度不超过限定值,同时又能保证车辆在慢速行驶条件下安全且充分地接近.对一个具有2200辆车的较大规模问题进行了仿真计算,结果表明模型能为实际运行提供参考.     

面向对象的有限空间内人群流动CA模型研究

为了模拟在有限空间中大量人员的流动分布，基于面向对象技术，在已有交通流模型和行人流模型的基础上，建立了一个在有限空间内高密度人群流动的元胞自动机模型。采用面向对象思想的建模方法，使得模型具有很好的适用性、扩展性和复用性。并根据出现高密度人群的一般情况和控制对象的需求，提出“元胞控制块”的概念，使整个模型架构具有很强的应用转化能力。计算机模拟验证的结果良好，充分显示了元胞自动机模型对复杂人群流动的模拟能力。     

A simulation study comparing GT vs. job shop manufacturing systems

Two discrete simulation models were developed, one representing a typical job shop (JS) manufacturing system (process layout) and the other representing group technology (GT) manufacturing system (cellular layout). Hypothetical data generated by FORTRAN program and MICRO-CRAFT layout package were used to validate the two models. Simulations were performed using SLAM II. The two layouts were compared with one another under controlled experimental conditions using various combinations of four operating variables: batch size, demand rate, ratio of setup time to process time, and transporter speed. Six indicators of systems performance were used in the study. These were: average time in system, products completed, jobs in process, average machine utilization, average queue length, and average waiting time.

The study found that for environment as set for the models, GT system outperformed JS system as expected. However, using large batch size (more than 75) in Experiment 1 (changing batch size) allowed JS system to perform as well as GT system. Certain specific changes in batch size also allowed to establish optimum results in both systems. No individual change of demand rate (Experiment 2), ratio of setup time to process time (Experiment 3), or transporter speed (Experiment 4) allowed JS system to outperform GT system.     

自适应变步长高斯混合模型的工业烟尘目标分割方法

工业烟尘排放时的烟气黑度自动监测对提高环保质量和指导生产过程具有重要的应用价值, 针对传统的 高斯混合模型在进行背景建模时, 参数是在固定帧值的基础上进行参数更新, 导致烟尘检测不准确等问题, 提出一 种自适应变步长高斯混合模型的工业烟尘图像分割方法. 根据烟尘变化速度不均匀的特点, 通过分析检测出烟尘 与实际烟尘的检出率和检准率的和的最大值, 计算熵值差变化率对应的最佳步长, 得到熵值差变化率与最佳步长的 模型. 以熵值差变化率为依据, 确定最佳步长, 得到一个关于熵值差变化率与最佳步长的模型. 以熵值差变化率为 输入, 以最佳步长为输出, 在广义回归神经网络(GRNN)得到适用于本文工业烟尘图像分割的网络模型. 最后, 在多 个场景的烟尘视频中进行分割实验, 结果表明, 本文中方法能够有效的分割出视频中烟尘区域, 且具有一定的适用 性.     

Effects of cell size and configuration in cellular automata based prey–predator modelling

Cellular automata (CA) have shown to be a viable approach in ecological modelling, in particular when dealing with local interactions between species and their environment. In CA modelling complex patterns emerge on a global scale through the evolution of interactions at a local level. Although the validity of a cell-based approach has successfully been demonstrated in numerous cases, very few studies have been reported that address the effects of cell size and configuration on the behaviours of CA-based models. In this paper, the performance of a cellular automaton based prey–predator model (EcoCA) developed by the author was first calibrated against the classical Lotka–Volterra (LV) model. The model was then used to investigate effects of cell size and cellular configurations (viz. the ‘computational stencil’). By setting up systematic simulation scenarios it was observed that the choice of a particular cell size has a clear effect on the resulting spatial patterns, while different cellular configurations affect both spatial patterns and system stability. On the basis of these findings, it is proposed to use the principal spatial scale of the studied ecosystem as CA model cell size and to apply the Moore type cell configuration. Methods for identifying principal spatial scales have been developed and are presented here.     

A traffic cellular automata model based on road network grids and its spatial and temporal resolution’s influences on simulation

Microscopic Traffic Simulation Model based on Cellular Automata (CA) has become more and more popular since it was firstly introduced by Creamer and Ludwig in 1986. Cellular automata are simpler to implement on computers, provide a simple physical picture of the system and can be easily modified to deal with different aspects of traffic. However, in a traditional traffic CA model, the spatial resolution of CA and temporal resolution of simulation are low. Take TRANSIMS for example. The size of cellular automata is 7.5 m and the time step equals 1 s. In such a case, if a vehicle drives at a speed of 4 cells per s, the speed difference between 95 km/h (3.5 1 7.5 m/s) and 121 km/h (4.4999 1 7.5 m/s) will not be distinguished by simulation models. And the temporal resolution of 1 s makes the system hard to model different drivers’ reaction time, which plays a very important role in vehicular movement models. In this paper, a microscopic traffic cellular automata model based on road network grids is proposed to overcome the low spatial and temporal resolutions of traditional traffic CA models. In our model, spatial resolution can be changed by setting different grid size for lanes and intersections before or during simulation and temporal resolution can be defined according to simulation needs to model different drivers’ reaction time, whereas the vehicular movement models are still traditional CA models. By doing so, the low spatial and temporal resolution of CA model can be overcome and the advantages of using CA to simulate traffic are preserved. The paper also presents analyses of the influences on simulation of different 1D lane grid size, 2D intersection grid size and different combinations of temporal resolution and mean drivers’ reaction time. The analysis results prove the existence of spatial and temporal resolution thresholds in traffic CA models. They also reveal that the size of grids, the combinations of different temporal resolutions and mean drivers’ reaction time do pose influences on the speed of vehicles and lane/intersection occupancy, but do not affect the volume of traffic greatly.     

考虑个体行为的改进CA模型人员疏散研究

为更好模拟行人疏散过程中微观个体行为,考虑行人身材半径及在疏散过程中行人步行速度随运动状态变化,将社会力模型运行规则引入元胞自动机模型,建立了一种社会力模型计算步行速度、空间离散化程度和步行速度较高的疏散模型,用于模拟紧急情况下的行人疏散过程。在该模型中空间划分为更小网格,每个行人占用一到多个单元格,行人的身材半径不再不变,每个行人移动的距离由其速度决定,根据基于速度的出口选择方法和行人运动规律,通过数值模拟分析,研究了疏散过程中的动态性。研究表明基于速度的网格移动数量、行人数量、期望速度、行人身材半径、松弛时间等参数影响疏散效率,结合连续模型的优点能够更加客观真实刻画疏散过程,有助于离散模型描述行人疏散微观行为特征。     

基于SSDA的新型地板尺寸测量方法

SSDA是一种冰于特征的图像配准算法,由于相对于其他图像配准算法SSDA易实现并且处理速度快,因而经常用于实时系统中,针对生产流水线上地板长度测量存在的偏转问题,提出丁一种基于SSDA的地板尺寸测量方法,该方法结合了机器视觉和决策级图像融合的相关技术,应用SSDA和边缘提取算法,实现了对运动中地板的尺寸测量,实验验证了方法的有效性．