车辆跟驰模拟中的驾驶行为与模糊逻辑控制

分析了车辆驾驶员信息处理过程及性格特征,在描述了基于驾驶员速度、距离判断跟车模式的基础上,应用模糊数学方法,建立了车辆跟驰驾驶行为的模糊逻辑控制模型.     

微观交通流仿真跟车行为ANN模型研究

微观交通流研究中的车辆跟驰模型是交通仿真的一个基本模型,由于实际道路上驾驶员信息的获取困难,建立的车辆跟驰模型难以标定或验证.应用人工神经网络和五轮仪试验系统获取的城市道路车辆跟驰数据,建立了车辆跟驰行为的神经网络模拟模型.     

改进分子动力学的车辆跟驰模型

为了更好地研究复杂情况下的车辆跟驰特性,将车辆跟驰行为类比为分子在一维管道中相互作用的结果.已有的基于分子动力学的车辆跟驰模型利用需求安全间距和车道限速作为因素建立分子跟驰模型,忽略了车辆相对速度对驾驶员跟驰行为的影响,不符合真实的跟驰情况.因此,将车辆相对速度纳入模型结构中,建立分子相互作用势函数和壁面势函数,并据此构建改进分子动力学的车辆跟驰模型.用高精度车载定位仪器对车辆跟驰过程中的参数进行采集,利用遗传算法对模型参数进行标定并对模型进行分析,分别验证模型在不同跟驰状态下的准确性,并与改进前的分子跟驰模型进行对比.结果表明,改进的分子跟驰模型可以更有效地预测车辆的跟驰行为.     

基于神经网络方法的集成式驾驶员跟车模型

为了提高驾驶辅助系统的跟车性能,基于神经网络方法建立了一种集成式驾驶员跟车模型.通过真实交通环境下的驾驶员实验获得了稳定跟车状态数据,并利用Kalman滤波器对数据进行了处理和估计.设计了以BP神经网络为核心的集成式模型结构,该模型以前车速度为输入,计算跟车过程中的两个特性参数并输入神经网络以模拟驾驶员控制的自车加速度.利用处理后的数据样本对网络进行了训练,并对该模型进行了仿真验证.仿真结果表明;神经网络模型具有模拟驾驶员跟车行为的能力,模型体现出较为准确的跟踪特性,并对不同的前车工况具有良好的适应性.     

应用五轮仪采集车辆跟驰过程描述参数

车辆跟驰模型是微观交通流模拟的一个基本模型 ,用来分析和描述在无法超车的同一车道上一辆车 (驾驶员 )跟随另一辆车的方式 .由于过去的实验数据主要是由两实验车在实验跑道上作跟驰运行或由驾驶员操纵驾驶模拟台获得的 ,难以获取实际道路上驾驶员的信息 ,建立的车辆跟驰模型难以标定或验证 .所介绍的应用五轮仪实验获取、处理和分析车辆跟驰过程描述参数的途径 ,为今后车辆跟驰模型的标定与验证提供了一条新的实验途径 .     

一种改进的微观跟驰模型

根据交叉口区域内车辆行为的特殊性，在交通仿真中采用跟驰理论对交通流进行研究．针对目前纯微观跟车模型没有考虑驾驶员反应时间的情形，提出了一种改进的微观跟驰模型．该模型根据车辆行驶特点对道路进行区域划分，能结合交叉口区域的特点，确定车辆最小和最大安全距离的界限值，并充分考虑了驾驶员反应时间造成的延迟对于车辆行驶速度和加速度的影响．通过仿真实验，进一步证实了模型的有效性．     

信号交叉口左转车辆跟驰行为建模

跟驰模型是交通流理论的核心内容之一,但左转车辆在交叉口转弯过程中跟驰行为的特征表现,尚缺少基于实际数据的深入研究。针对这个问题,设计了信号交叉口左转车辆跟驰实验,基于高精度全球定位系统(global positioning system,GPS)和移动地理信息系统采集车辆跟驰行为相关数据,分析了信号交叉口不同转弯半径下左转车辆跟驰速度时变规律及分布本征。在全速度差(full velocity difference,FVD)跟驰模型的基础上,考虑跟驰车驾驶员对前导车加、减速反应的非对称性,构建了改进的全速度差模型,并采用遗传算法对模型进行了参数标定。最后,以跟驰车加速度为检验指标,利用实测数据对改进的全速度差模型加、减速度过程的准确性进行了分析与评价。结果表明:信号交叉口左转跟驰车辆的平均运行速度与转弯半径成正相关;在不同转弯半径下跟驰车速度出现频数最高的数值随着转弯半径的增大而增大;改进的全速度差模型,能更好地描述交叉口左转车辆跟驰过程,驾驶员对前导车减速行为的反应比对加速行为的更强烈。     

基于数据驱动的城市地下快速路跟驰行为模型构建

为了揭示地下快速路交通流的运行特性,利用驾驶模拟器获得的高精度车辆轨迹数据,针对地下快速路提出一种基于数据驱动方法的车辆跟驰模型,并对该模型进行了标定与验证。首先,根据上海市北横通道东段场景模型进行驾驶模拟实验以获取车辆跟驰数据;其次,选择了采用支持向量回归（SVR）方法建立车辆跟驰模型,对模型改进并引入了驾驶行为约束条件;最后,利用实验数据对改进过的SVR车辆跟驰模型进行了标定与验证。结果表明,考虑驾驶行为约束的支持向量回归车辆跟驰模型能很好地描述地下快速路中的车辆跟驰行为;该模型具有一定的可移植性,在其他地下快速路上也有较高的精度。建立的车辆跟驰模型可以量化地分析地下快速路中跟驰车辆间的相互作用,为进行交通仿真和风险研究提供基础。     

考虑侧向车换道影响的理论和数据组合驱动的车辆跟驰模型

为分析受侧向车辆换道影响下的目标车辆跟驰行为，结合多速度差理论跟驰模型和深度学习方法，提出了一种理论-数据组合驱动跟驰模型。首先考虑了跟驰车辆对于前向车辆和侧向车辆保持安全车距和受车辆速度差影响的特性，提出了双车道多速度差跟驰模型（FS-MAVD模型），并利用差分进化算法进行模型参数标定。构建了CNN-Bi-LSTM-Attention数据驱动车辆跟驰模型，利用卷积神经网络层（CNN）充分提取前向和侧向车辆交通特征，双向长短期记忆网络层（Bi-LSTM）考虑驾驶员记忆效应，注意力机制层（Attention）用于分配模型权重，并基于数据进行驾驶员记忆时长、模型训练批次和训练轮数参数的训练。考虑理论模型广泛适用性和数据驱动模型接近真实值且平滑的特点，采用最优加权法将两种模型进行组合预测。利用无人机拍摄的快速路车辆轨迹数据，建立跟驰行为样本集，对所建模型进行训练和测试，并与LSTM模型、Bi-LSTM模型、CNN-Bi-LSTM-Attention模型、FS-MAVD理论模型的预测效果进行对比，并分别比对不同模型对不同车辆的预测精度和误差。结果表明，本研究构建的组合模型在加速度预测精度达到9...     

基于ACC系统的跟驰模型改进分析

目前,国内车辆并没有广泛应用ACC(Adaptive cruise control)系统。研究表明,在跟驰过程中,驾驶员通过感知改变自己跟驰状态,因此该系统具有很大的主观性。在常用的基于ACC的跟驰模型的基础上,建立了考虑驾驶员行为的跟驰模型。通过传统的跟驰模型,进一步研究车辆流之间关系。最后,借助频域分析法验证了该系统的稳定性。利用时域分析法分析得到在特定输入条件下的稳态误差及动态特性。     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.