元胞自动机在作战舰艇生命力评估中的应用

作战舰艇生命力是衡量舰艇作战能力的重要因素,其评估是对复杂系统的研究过程.元胞自动机是一种"自下而上"的动态模拟建摸框架,具有自组织性和模拟复杂系统时空演化过程的能力.从元胞自动机的概念、构成和原理入手,分析和总结了元胞自动机的基本特征,将元胞自动机应用到对作战舰艇的生命力进行评估,很好地解决了作战舰艇生命力的评估问题.     

黑白数字图像的有穷状态自动机表示方法

自动机理论是理论计算机科学的基础理论之一，在很多领域自动机有着广泛的应用，在将黑白图像进行像素地址编码的基础上使用语言来描述数字图像，从而得到用自动机来描述数字图像的方法，任意有穷分辨率黑白图像均可以用有穷状态自动机来表示，多分辨率图像能够用有穷状态自动机来描述当且仅当该图像中不同形状的子图像的个数为有限个．     

基于元胞自动机的舰艇生命力评估

从元胞自动机的理论入手,阐明多次打击评估的基本依据,并通过仿真模拟计算完成生命力的评估并对评估进行分析和提出改进方法。     

A cellular automata traffic flow model combined with a BP neural network based microscopic lane changing decision model

The purpose of this study is to propose a cellular automata (CA) traffic flow model with high accuracy for lane change decision and name it LCCAM. A driving simulator experiment was conducted to find factors affecting lane changing decisions. A back-propagate (BP) neural network was used to obtain the lane changing rules for the microscopic lane changing decision model (LCDM), and the collected accurate vehicular trajectory data were used to train the BP neural networks for the prediction of lane changes. After comparing different input variable combinations, the most accurate input setting was determined, including the locations and velocities of neighboring vehicles, inner/outer lane indicator, and the speed limits of the corresponding lane. Then, the determined BP neural network was adopted in the LCCAM as the LCDM. Simulation results showed that the LCCAM can capture important characteristics such as the mean velocities and the number of lane changes well, by comparing with observed traffic flow. Meanwhile, the LCCAM illustrates a better performance in replicating the number of lane changes than the other reference CA models. The research results show that the LCCAM proposed in this study will have potential and value for autonomous driving and active safety analysis in the future.     

An improved cellular automata model for heterogeneous work zone traffic

This paper aims to develop an improved cellular automata (ICA) model for simulating heterogeneous traffic in work zone. The proposed ICA model includes the forwarding rules to update longitudinal speeds and positions of work zone vehicles. The randomization probability parameter used by the ICA is formulated as a function of the activity length, the transition length and the volumes of different types of vehicles traveling across work zone. Compared to the existing cellular automata models, the ICA model possesses a novel and realistic lateral speed and position updating rule so that the simulation of vehicle’s lateral movement in work zone is close to the reality. The ICA model is calibrated and validated microscopically and macroscopically by using the real work zone data. Comparisons of field data and ICA for trajectories, speed and speed–flow relationship in work zone show very close agreement. Finally, the proposed ICA model is applied to estimate traffic delay occurred in work zone.     

基于元胞自动机的自行车流蛇行、穿插模型

通过重新定义元胞尺寸、状态值及元胞邻域,建立了自行车元胞自动机基本模型,并在基本模型中引入随机偏移概率来表达自行车不遵循车道行驶的特性.通过模型模拟运行,并对获得的自行车流参数进行分析,结果表明引入随机偏移概率能很好地描述自行车不遵循车道随机蛇行、穿插的特性.     

基于GIS的城市交通元胞自动机模拟——以上海市为例

在转换规则的确定上,以区域人口及经济等属性及路网密度等空间及非空间属性来衡量道路流入流出量.在模拟方法上,以随机数确定车流方向,体现城市交通流的复杂性,但未增加算法的复杂度.最后以上海市18个区及1个县的高速公路系统为例进行了实证研究,实验表明迭代20次后系统达到稳定态,且徐汇区和长宁区平均车辆数最大,较容易出现拥堵的状况.     

港区车辆坡度跟驰模型研究及工程应用分析

基于对港区交通特性的分析,从分析车辆跟驰行为中的基本特征入手,结合定量和定性的方法,研究港区车辆上坡行驶特性,并通过修正车辆及线形参数,建立仿真模型来获取合理的道路线形参数。通过工程实例,仿真结果得到验证。     

基于视频检测数据的自行车元胞尺寸标定

由于自行车流交通流微观特征的复杂性,造成对宏观特征三参数的认识也比较困难。而自行车元胞自动机模型的基本单元尺寸来源于其微观特征,所以这里重点描述基于现场视频检测数据的自行车元胞单元尺寸标定方法。通过尺寸标定后模型的演化,说明该改进模型能有效地克服采用固定元胞尺寸所带来的交通流宏观特征数据的不合理性。     

城市公共汽电车中途站人流仿真研究

针对公共汽电车中途站行人运行仿真问题,研究了基于NetLogo仿真平台的中途站人流仿真模型。首先分析了基于Agent的建模方法,并以此为据采用元胞自动机建模技术进行行人仿真,在此之上开发了基于NetLogo的用于中途站行人交通流仿真的行人仿真分析平台,并介绍了该仿真平台在分析中途站行人交通组织中的应用。