基于自然驾驶数据的信号交叉口车辆跟驰行为特征分析

为明确城市信号交叉口的车辆跟驰行为特性,基于自然驾驶试验数据,对车辆在减速、加速跟驰状态的车头间距、车头时距和相对速度进行了分布特征分析以及与跟驰速度的相关性分析。结果表明：减速跟驰状态的相对速度主要集中于[-3m/s,1m/s],加速跟驰状态主要集中于[-1m/s,3m/s];减速跟驰状态和加速跟驰状态的车头时距随后车跟驰速度变化趋势相同,确定了跟驰速度小于20km/h的车头时距阈值;去掉跟驰速度小于6km/h的数据后得到的减速跟驰、加速跟驰状态车头时距和车头间距均呈正偏态分布,车头间距集中于5-30m,车头时距集中于1.5s-3.5s;两种跟驰状态车头间距、车头时距的5th、50th、95th特征值与跟驰速度具有较强的相关性。     

跟驰行驶状态下的驾驶模拟有效性研究

为验证驾驶模拟技术在跟驰行为研究中的有效性,设计了实车实验与驾驶模拟实验。选取了跟驰距离、跟驰距离标准差、车头时距及驾驶员反应延迟时间作为分析指标,并采用Wilcox检验、生存分析方法分别验证了非时间数据、时间数据的有效性。结果表明跟驰距离、车头时距、驾驶员反应延迟时间具备绝对有效性,两种不同实验环境下跟驰距离标准差随跟驰速度变化趋势相同,具备相对有效性。实车实验中,前车加速度、前后车相对距离、前车加速度变化状态显著影响驾驶员反应延迟时间。有效性分析结果为基于驾驶模拟实验的跟驰行为研究提供前提条件,生存分析结果可用于驾驶员反应延迟时间建模及跟驰模型优化。     

混合交通环境下降雨对车辆跟驰行为的影响分析与模型构建

针对混合交通环境下车辆跟驰分析时缺少对降雨环境考虑的问题,通过研究驾驶人在降雨环境下驾驶行为的改变,构建在不同降雨强度下适用的跟驰模型。首先,通过Python程序从云控平台数据库中提取车辆跟驰数据和降雨强度数据,分析了车辆在不同降雨强度和交通流状态下的跟驰速度、加速度和车头间距等变化特征以及其相互作用关系,进一步探索了降雨与正常天气下车辆跟驰行为的差异。其次,从优化速度跟驰模型出发,使用加速度衡量跟驰行为特性,综合考虑降雨对前后车相对距离和相对速度的影响,提出了适用于不同降雨强度下的安全间距和驾驶人期望速度确定方法,构建了不同降雨强度下的跟驰模型,并采用遗传算法对新模型进行了参数标定。最后,通过交叉验证方法对标定结果进行了评估,计算了模型输出值与实际值之间的误差。研究结果表明：降雨环境下车辆速度和加速度随着降雨强度的增加有不同幅度的降低,但是车辆加速度变化程度比车辆速度变化程度明显,这说明加速度对于降雨反应更加灵敏;降雨环境下,车头间距受前车速度影响,进而控制后车跟驰速度,不同降雨强度和不同前车速度区间都影响车头间距大小,后车跟驰速度随着车头间距的增大而增大;模型计算结果与实测值的均方...     

路段多车型混合车流通行能力

利用概率论方法,通过对由多种车型构成的混合车流不同跟驰序列,不同组合概率的研究,得到了跟驰车头时距路段多车型混合车流通行能力模型.基于经典车头间距模型,通过对混合车流不同跟驰序列下最小车头间距的研究,得到了多车型混合车流的组合车头间距,进而得到了跟驰车头间距路段多车型混合车流通行能力模型.推广了由大、小2种车型构成的混合车流的通行能力模型.研究表明,路段多车型混合车流通行能力不仅与反应时间、车辆速度、车辆长度、制动性能等有关,还与混合车流的车辆组成状况及跟驰序列相关.最后实例分析了不同小型车混入率情况下路段通行能力的变化状况.     

冰雪路面城市快速路跟驰模型研究

针对冰雪路面城市快速路的跟驰模型进行了研究。首先对两种常见的冰雪路面进行了交通调查。根据调查结果对不同冰雪路面城市快速路交通流的自由流速度、平均速度、速度分布,相邻跟驰车辆的车头时距、车头时距与相对速度的相互关系等微观特性进行统计分析,定量地研究不同冰雪路面形态对城市快速路跟驰行为的影响。其次,对不同类型的优化速度函数特征进行对比分析,依据Greenshields速度-密度关系建立期望车速模型,依据车辆不同跟驰状态建立冰雪路面最小安全距离模型,并由此构建冰雪路面优化速度模型。基于现有跟驰理论研究成果,以线性跟驰模型建模思想对全速度差模型进行改造,结合冰雪路面优化速度模型构建适用于冰雪路面的新跟驰模型。最后,利用实测数据对模型参数进行标定,并通过设计实验分析模型的稳定性、加速度非对称性。同时,利用调查数据对新模型和全速度差模型进行模拟分析,结果证明该模型更贴近冰雪路面城市快速路实际交通流,可以为冰雪路面下交通管理措施的制定提供理论支持。     

GPS数据驱动的车辆跟驰行为建模与分析

为研究道路交通流特性,基于车载高精度GPS跟驰试验数据进行车辆跟驰建模研究,结合深度学习理论和数据驱动方法,构建了基于粒子群优化(particle swarm optimization, PSO)的长短期记忆(long short term memory, LSTM)车辆跟驰模型。首先,清洗和平滑车辆轨迹数据,并对驾驶特征行为参数及相关关系进行研究,如加速度、车头时距以及速度与跟驰距离特性关系等。在此基础上,制定跟驰状态筛选规则;其次,构建考虑时间序列的PSO-LSTM模型,识别跟驰数据样本集,将当前时刻的前车速度、车头间距和上一时刻的车头时距作为模型输入,预测当前时刻的跟驰车速度;接着,选用25辆车跟驰试验的高精度GPS数据验证PSO-LSTM模型性能;最后,为验证该模型的优越性,选用传统机器学习SVR(support vector regression)模型以及深度学习LSTM模型作为对比。结果表明,基于粒子群优化的长短期记忆模型预测精度高达0.993,整体预测效果高于SVR模型和LSTM模型,其中预测误差指标MAPE(mean absolute percentage error)较SVR和LSTM分别降低了60.02%、1.52%。PSO算法进行超参数优化后的PSO-LSTM模型,能更好地模拟车辆的跟驰行为。     

考虑驾驶员模糊感知的深度学习跟驰模型

为模拟驾驶人记忆效应以及模糊感知特性,设计了基于模糊感知时间窗的深度学习跟驰模型。提取highD数据集跟驰轨迹,以0.2 s最小时间间隔,连续3 s本车速度、前后车速度差、车头间距的时序数据作为模型输入,模拟驾驶记忆。训练深度学习跟驰模型,得出单层32个输出维度的门控循环单元（GRU）网络可以很好拟合实际数据。在每次输入模型的时序数据中,用模型预测值替换部分真实跟驰状态值,作为驾驶员对场景的估计,即模糊感知。实验得出对同一场景的不同模糊感知,可产生不同跟驰行为,模拟了驾驶行为的异质性,可为异质交通行为仿真提供方法。     

基于动态安全车距的车辆跟驰模型及稳定性分析

为了更好地模拟车辆的跟驰特性,在全速度差(full velocity difference, FVD)模型的基础上考虑前车与跟随车的车头间距、速度差、速度和加速度等因素,建立了一种基于动态安全车距的改进FVD跟驰模型。构建了可变车头时距模型量化前车加速度对跟驰车头间距的影响程度;应用小振幅扰动分析和长波展开进行了模型线性稳定性分析,推导了改进FVD模型的临界稳定性条件;设计环形道路上微扰动数值仿真实验,分析了扰动后的车辆跟驰行为特性,解析加速度参数对模型抗扰能力的影响。研究结果表明：考虑前车加速度信息可以降低扰动演化时的波动振幅,有助于提高车流的稳定性。     

基于自然驾驶数据的分心状态特征分析与跟驰行为建模

基于行为特征对分心跟驰行为进行分类和建模,根据模型标定的方法探究不同状态下跟驰模型的适应性。首先从持续开展3年有余的上海自然驾驶数据中提取了大量分心跟驰样本,基于驾驶行为刺激反应框架对分心状态特征进行了初步分类,得到了5类分心跟驰行为;其次分析了现有4类经典跟驰模型（GHR、GIPPS、IDM和Wiedemann）对分心跟驰行为的适应性,同时根据五折交叉验证适应性结果对分心跟驰行为分类进一步优化,最终得到3类分心跟驰行为（麻木反应、过激反应和延迟反应）;最后探讨了分心状态下的2种跟驰行为建模策略（AIDM和TDIDM）。结果表明,对IDM模型进行合理标定即可较准确地描述不同类型的分心跟驰行为。     

考虑前车驾驶风格的改进自适应巡航控制跟驰模型及仿真

为了提高自适应巡航控制跟驰模型的效率和安全性,考虑不同驾驶员驾驶行为的差异性,根据驾驶员以往的驾驶行为特性,利用k-均值聚类算法对驾驶风格进行判别和分类,作为优化自适应巡航控制跟驰行为的依据;提出智能网联环境中自适应巡航控制跟驰优化方法,基于对不同驾驶风格车辆的动力学分析,引入驾驶风格修正系数、安全冗余修正系数、响应延迟时间,针对不同前车驾驶风格,建立改进的自适应巡航控制跟驰模型,并对所建立的模型、原自适应巡航控制跟驰模型及对比模型进行仿真分析。结果表明,相比原自适应巡航控制跟驰模型和对比模型,所建立模型的加速度曲线和车头间距曲线均更平缓,可以有效提高跟驰效率,同时具有更高的安全性。     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

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.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

A computer generator for randomly layered structures

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

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.     

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。     

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.     

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

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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