VehicletoInfrastructureChannelCharacterizationinUr

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基于滑移率的路面附着系数估计

Science &Technology Vision 科技视界0引言以自适应巡航、主动避撞、ABS 控制系统为代表的汽车纵向安全辅助系统对于改善整体交通环境、降低交通事故发生率、提高驾乘舒适性具有重要意义,其安全策略模型直接关系到系统的功能性、可靠性及用户认可度[1]。

当路面附着系数未知时,主动安全系统的性能通常无法充分发挥[2-3]。

如果能够实时估算出路面峰值附着系数,系统就可以根据当前路况调节控制策略,提高车辆安全[4]。

国内外都已经在路面附着系数识别领域做了很多研究。

仪器测量法利用光学传感器、电磁波传感器等,通过检测路面附着物质(如水,冰,雪等)估计路面附着系数。

该方法的优点是,在轮胎接触路面之前可以预先估计路面的附着系数。

缺点是,不能反映影响路面附着系数的其他因素,如轮胎气压、轮胎磨损等[5-6]。

该类方法对经过试验训练的路面具有较好的估计精度,对未经过训练的路面则难以得到满意的效果[7],试验存在可重复性差、成本较高及影响因素多等问题。

基于车辆动力学的方法是根据车辆侧向动力学特性,利用车载GPS 估计轮胎的侧偏角,然后根据车辆侧向动力学模型估计路面附着系数[8]。

此方法在车辆侧偏角较小的情况下,难以正确估计路面附着系数。

目前,能够直接测量路面附着系数或是轮胎力的传感器造价高昂且可靠性较低,因而大多采用估计的方式获得。

车辆行驶在不同附着系数的路面上,滑移率和利用附着系数表现出不同的关系。

利用这种特性进行路面附着系数识别是目前各类方法中最具实用前景的。

车轮滑移率s 和利用附着系数ρ的定义[9]分别为:s =rω-v max(rω,v )(1)ρ=F x 2+F y2√F z(2)式中,ω为轮速,r 为车轮半径,v 为车速,F x 为地面对车轮的纵向作用力,F y 为地面对车轮的横向作用力,F z 为车辆垂向载荷。

如果忽略轮胎横向力F y ,则有:ρ=F x F z(3)不同附着系数路面上的s-ρ关系不同,如图1所示。

openscenario标准

openscenario标准开场白：1. 介绍openscenario标准的背景和意义openscenario标准是一种用于描述仿真场景的规范化格式。

它旨在实现各个仿真环境之间的互操作性，以及使得场景描述可以被多种仿真工具所共享和重用。

openscenario标准的制定，对于推动自动驾驶技术和智能交通系统的发展具有重要意义。

在这篇文章中，我们将深入探讨openscenario标准的相关内容，并分析其在自动驾驶领域中的应用价值。

2. openscenario标准的核心要素openscenario标准主要包括以下核心要素：- 剧本描述（scenario）- 场景元素（entity）- 行为定义（action）- 时间线（timeline）3. openscenario标准的应用范围openscenario标准可以被广泛应用于自动驾驶仿真、交通流仿真、交通事故重现等领域。

其灵活的描述方式和丰富的元素设置，使得其可以适用于不同类型的场景描述和仿真需求。

4. openscenario标准的优势与价值openscenario标准相较于传统的场景描述方式，有着诸多优势和价值所在：- 规范化的描述格式，便于不同仿真工具之间的互操作性- 丰富的元素设置，可以更加真实地描述各种交通场景- 易读易编辑的格式，方便工程师和研究人员进行使用和修改- 促进仿真场景的共享和重用，加速自动驾驶技术的发展和应用5. openscenario标准的发展现状与未来展望openscenario标准目前已经得到了业界和学术界的广泛关注和认可，一些知名的仿真工具和自动驾驶系统已经开始使用openscenario标准进行场景描述和仿真测试。

未来，openscenario标准将继续发展完善，逐步完善其在自动驾驶领域的应用范围，为自动驾驶技术的发展和应用带来更多的可能性和机遇。

总结：通过对openscenario标准的介绍和分析，我们可以看到，这一标准的出现对于促进自动驾驶技术的发展具有非常重要的意义。

关于车联网发展的英语作文

The development of the Internet of Vehicles IoV has been a significant topic in the realm of technology and transportation. This essay will explore the concept of IoV, its current state, and potential future implications.The Internet of Vehicles refers to the integration of vehicles with information and communication technology, enabling them to connect with each other, the internet, and various infrastructures. This connectivity allows for a range of applications, from traffic management to driver assistance systems, and even autonomous driving.Current State of IoV Development1. Technological Advancements: The integration of sensors, cameras, and GPS systems in vehicles has been a major step forward. These technologies allow vehicles to collect and transmit data about their surroundings and conditions.2. Data Analytics: With the data collected, advanced analytics and artificial intelligence can be applied to predict traffic patterns, optimize routes, and even prevent accidents.3. Smart Infrastructure: Cities are beginning to implement smart traffic lights and road sensors that communicate with vehicles to improve traffic flow and reduce congestion.4. Safety Features: IoV technologies have led to the development of advanced safety features such as collision avoidance systems, lane departure warnings, and adaptive cruise control.Challenges in IoV Development1. Cybersecurity: As vehicles become more connected, they also become more vulnerable to cyberattacks. Ensuring the security of vehicle data and systems is a critical challenge.2. Privacy Concerns: The collection of data from vehicles raises privacy issues. Balancing the benefits of IoV with the need to protect personal information is a delicate task.3. Standardization: There is a need for standardization across different manufacturers and systems to ensure compatibility and seamless communication between vehicles and infrastructure.4. Regulatory Frameworks: Governments are still catching up with the pace of technology, and there is a need for clear regulations to guide the development anddeployment of IoV technologies.Future Implications of IoV1. Autonomous Vehicles: IoV is a stepping stone towards fully autonomous vehicles. The data and connectivity provided by IoV will be essential for selfdriving cars to navigate safely and efficiently.2. Smart Cities: The integration of IoV with urban infrastructure can lead to the creation of smart cities, where traffic is managed in realtime, reducing pollution and improving the quality of life for residents.3. Economic Impact: The IoV industry has the potential to create new job opportunities and drive economic growth through the development of new technologies and services.4. Environmental Benefits: Improved traffic management can lead to reduced fuel consumption and lower emissions, contributing to a more sustainable environment.In conclusion, the Internet of Vehicles is a rapidly evolving field with the potential to revolutionize transportation. While there are challenges to overcome, the benefits of IoV are vast, offering a glimpse into a future where transportation is safer, more efficient, and more integrated with our digital lives.。

毕业设计93基于连续隐马尔科夫模型的语音识别 (2)

SHANGHAI UNIVERSITY 毕业设计（论文）UNDERGRADUATE PROJECT (THESIS)论文题目基于连续隐马尔科夫模型的语音识别学院机自专业自动化学号03122669学生姓名金微指导教师李昕起讫日期2007 3.20—6.6目录摘要---------------------------------------------------------------------------2 ABSTRACT ------------------------------------------------------------------------2绪论---------------------------------------------------------------------------3第一章语音知识基础---------------------------------------------------------------6 第一节语音识别的基本内容-------------------------------------------6第二节语音识别的实现难点-------------------------------------------9第二章HMM的理论基础--------------------------------------------------------10 第一节HMM的定义----------------------------------------------------10第二节隐马尔科夫模型的数学描述---------------------------------10第三节HMM的类型----------------------------------------------------12第四节HMM的三个基本问题和解决的方-----------------------15第三章HMM算法实现的问题----------------------------------------------21 第一节HMM状态类型及参数B的选择---------------------------21第二节HMM训练时需要解决的问题-----------------------------23第四章语音识别系统的设计---------------------------------------------------32 第一节语音识别系统的开发环境-----------------------------------32第二节基于HMM的语音识别系统的设计------------------------32第三节实验结果---------------------------------------------------------49第五章结束语-------------------------------------------------------------------67致谢------------------------------------------------------------------------------68参考文献------------------------------------------------------------------------69摘要语音识别系统中最重要的部分就是声学模型的建立，隐马尔可夫模型作为语音信号的一种统计模型，由于它能够很好地描述语音信号的非平稳性和时变性，因此在语音识别领域有着广泛的应用。

A geometry-based stochastic MIMO model for vehicle-to-vehicle communications

A Geometry-Based Stochastic MIMO Model forVehicle-to-Vehicle CommunicationsJohan Karedal,Member,IEEE,Fredrik Tufvesson,Senior Member,IEEE,Nicolai Czink,Member,IEEE, Alexander Paier,Student Member,IEEE,Charlotte Dumard,Member,IEEE, Thomas Zemen,Senior Member,IEEE,Christoph F.Mecklenbr¨a uker,Senior Member,IEEE,and Andreas F.Molisch,Fellow,IEEEAbstract—Vehicle-to-vehicle(VTV)wireless communications have many envisioned applications in trafﬁc safety and congestion avoidance,but the development of suitable communications systems and standards requires accurate models for the VTV propagation channel.In this paper,we present a new wideband multiple-input-multiple-output(MIMO)model for VTV channels based on extensive MIMO channel measurements performed at 5.2GHz in highway and rural environments in Lund,Sweden. The measured channel characteristics,in particular the non-stationarity of the channel statistics,motivate the use of a geometry-based stochastic channel model(GSCM)instead of the classical tapped-delay line model.We introduce generalizations of the generic GSCM approach and techniques for parameterizing it from measurements andﬁnd it suitable to distinguish between diffuse and discrete scattering contributions.The time-variant contribution from discrete scatterers is tracked over time and delay using a high resolution algorithm,and our observations motivate their power being modeled as a combination of a (deterministic)distance decay and a slowly varying stochastic process.The paper gives a full parameterization of the channel model and supplies an implementation recipe for simulations.The model is veriﬁed by comparison of MIMO antenna correlations derived from the channel model to those obtained directly from the measurements.Index Terms—Channel measurements,MIMO,vehicular,non-stationary,Doppler,geometrical model,statistical model.Manuscript received June7,2008;revised December29,2008;accepted March5,2009.The associate editor coordinating the review of this paper and approving it for publication was H.Xu.This work was partially funded by Kplus and WWTF in the ftw.projects I0 and I2,and partially by an INGV AR grant of the Swedish Strategic Research Foundation(SSF),the SSF Center of Excellence for High-Speed Wireless Communications(HSWC)and COST2100.J.Karedal and F.Tufvesson are with the Dept.of Electrical and Infor-mation Technology,Lund University,Lund,Sweden(e-mail:{Johan.Karedal, Fredrik.Tufvesson}@eit.lth.se).N.Czink is with Forschungszentrum Telekommunikation Wien(ftw.), Vienna,Austria,and also with Stanford University,Stanford,CA,USA. A.Paier is with the Inst.f¨u r Nachrichtentechnik und Hochfrequenztechnik, Technische Universit¨a t Wien,Vienna,Austria.C.Dumard and T.Zemen are with Forschungszentrum Telekommunikation Wien(ftw.),Vienna,Austria.C.F.Mecklenbr¨a uker is with Forschungszentrum Telekommunikation Wien (ftw.),and also with the Inst.f¨u r Nachrichtentechnik und Hochfrequenztech-nik,Technische Universit¨a t Wien,Vienna,Austria.A.F.Molisch was with Mitsubishi Electric Research Laboratories(MERL), Cambridge,MA,USA,and the Dept.of Electrical and Information Technol-ogy,Lund University,Lund,Sweden.He is now with the Dept.of Electrical Engineering,University of Southern California,Los Angeles,CA,USA. Digital Object Identiﬁer10.1109/TWC.2009.080753I.I NTRODUCTIONI N recent years,vehicle-to-vehicle(VTV)wireless com-munications have received a lot of attention,because of its numerous applications.For example,sensor-equipped cars that communicate via wireless links and thus build up ad-hoc networks can be used to reduce trafﬁc accidents and facilitate trafﬁcﬂow[1].The growing interest in this area is also reﬂected in the allocation of75MHz in the5.9GHz band dedicated for short-range communications(DSRC)by the US frequency regulator FCC.Another important step was the development of the IEEE standard802.11p,Wireless Access in Vehicular Environments(W A VE)[2].Future developments in the area are expected to include,inter alia,the use of multiple antennas(MIMO),which enhance reliability and capacity of the VTV link[3],[4].It is well-known that the design of a wireless system re-quires knowledge about the characteristics of the propagation channel in which the envisioned system will operate.However, up to this point,only few investigations have dealt with the single-antenna VTV channel,and even fewer have considered MIMO VTV channels.Most importantly,there exists,to the author’s best knowledge,no current MIMO model fully able to describe the time-varying nature of the VTV channel reported in measurements[5].In general,there are three fundamental approaches to chan-nel modeling:deterministic,stochastic,and geometry-based stochastic[6],[7].In a deterministic approach,Maxwell’s equations(or an approximation thereof)are solved under the boundary conditions imposed by a speciﬁc environment. Such a model requires the deﬁnition of the location,shape, and electromagnetic properties of objects.Deterministic VTV modeling has been explored extensively by Wiesbeck and co-workers[8],[9],[10],and shown to agree well with(single-antenna)measurements.However,deterministic modeling by its very nature requires intensive computations and makes it difﬁcult to vary parameters;it thus cannot be easily used for extensive system-level simulations of communications systems.Stochastic channel models provide the statistics of the power received with a certain delay,Doppler shift,angle-of-arrival etc.In particular,the tapped-delay-line model,which is based on the wide-sense stationary uncorrelated scattering (WSSUS)assumption[11],is in widespread use for cellular system simulations[12],[13],[14].For the VTV channel, a tapped delay-Doppler proﬁle model was developed by Ingram and coworkers[15],[16]and also adopted by the1536-1276/09$25.00c 2009IEEEIEEE802.11p standards group for its system development [2].However,as also recognized by Ingram[17]and others, assuming aﬁxed Doppler spectrum for every delay,does not represent the non-stationary channel responses reported in measurements[5],in other words,the WSSUS assumption is usually violated in VTV channels[18].Geometry-based stochastic channel models(GSCMs)[19], [20]have previously been found well suited for non-stationary environments[21],[22]and this is the type of model we aim for in this paper.GSCMs build on placing(diffuse or discrete)scatterers at random,according to certain statistical distributions,and assigning them(scattering)properties.Then the signal contributions of the scatterers are determined from a greatly-simpliﬁed ray tracing,andﬁnally the total signal is summed up at the receiver.This modeling approach has a number of important beneﬁts:(i)it can easily handle non-WSSUS channels,(ii)it provides not only delay and Doppler spectra,but inherently models the MIMO properties of the channel,(iii)it is possible to easily change the antenna inﬂuence,by simply including a different antenna pattern,(iv) the environment can be easily changed,and(v)it is much faster than deterministic ray tracing,since only single(or double)scattering needs to be simulated.A few GSCMs where scatterers are placed on regular shapes around TX and RX have been developed for VTV communication,e.g.,two-ring models[23]and two-cylinder models[24].Such approaches are useful for analytical studies of the joint space-time cor-relation function since they enable the derivation of closed-form expressions.However,their underlying assumption of all scatterers being static does not agree with results reported in measurements[18].A more realistic placement of scatterers [22],rather reproducing the physical reality,can remedy this. The drawback compared to regular-shaped models is that closed-form expressions generally cannot be derived,but there is a major advantage in terms of easily reproducing realistic temporal channel variations.In this paper,we present such a model for the VTV channel and parameterize it based on the results from an extensive measurement campaign on highways and rural roads near Lund,Sweden.The main contributions of this paper are the following:•We develop a generic modeling approach for VTVchannels based on GSCM.In this context,we extend existing GSCM structures by prescribing fading statistics for speciﬁc scatterers.•We develop a high resolution method that allows extract-ing scatterers from the non-stationary impulse responses, and track the contributions over large distances.•Based on the extracted scatterer contributions,we param-eterize the generic channel model.•We present a detailed implementation recipe,and verify our parameterized model by comparing MIMO correla-tion matrices as obtained from our model to those derived from measurements.The remainder of the paper is organized as follows:Sec.II brieﬂy describes a measurement campaign for vehicle-to-vehicle MIMO channels that serves as the motivation for our modeling approach,Sec.III points out the most important channel characteristics to be included in the model,as well as methods for data analysis.The channel model is described in Sec.IV.First the model is outlined and then its different components are described in detail and parameterized from the measurements.Sec.V gives an implementation recipe for the model,whereas Sec.VI compares simulations of the model tothe measurement results it is built upon.Finally,a summary and conclusions in Sec.VII wraps up the paper.II.A V EHICLE-TO-V EHICLE M EASUREMENT C AMPAIGN In this section,we describe a recent measurement campaign for MIMO VTV channels that serves as the basis for thedevelopment of the channel model,i.e.,from which the model structure is motivated and the model parameters are extracted.For space reasons,we only give a brief summary;a more detailed description can be found in[5]and[25].A.Measurement SetupVTV channel measurements were performed with the RUSK LUND channel sounder that performs MIMO mea-surements based on the“switched array”principle[26].The equipment uses an OFDM-like,multi-tone signal to sound the channel and records the time-variant complex channel transferfunction H(t,f).Due to regulatory restrictions as well as limitations in the measurement equipment,a center frequencyof5.2GHz was selected for the measurements.This band is deemed close enough to the5.9GHz band dedicated to VTV communications such that no signiﬁcant differences inthe channel propagation properties are to be expected.The measurement bandwidth,B,was240MHz,and a test signal length of3.2μs was used,corresponding to a path resolutionof1.25m and a maximum path delay of959m,respectively. The transmitter output power ing built-in GPS receivers with a sampling interval of1s,the channel sounderalso recorded positioning data of transmitter(TX)and receiver (RX)during the measurements.The time-variant channel was sampled every0.3072ms,corresponding to a sampling frequency of3255Hz during a time window of roughly10s(a total of32500channel sam-ples);the time window was constrained by the storage capacityof the receiver.The sampling frequency implies a maximum resolvable Doppler shift of1.6kHz,which corresponds to arelative speed of338km/h at5.2GHz.TX and RX were mounted on the platforms of separate pickup trucks,both deploying circular antenna arrays at a height of approximately2.4m above the street level.Eacharray consisted of4vertically polarized microstrip antenna elements,1mounted such that their broadside directions were directed at45,135,225and315degrees,respectively,where 0degrees denotes the direction of travel(the3dB beamwidth was approximately85degrees).Thus,a4×4MIMO systemwas measured.B.Measured Trafﬁc EnvironmentsWe performed measurements in two different environments: a rural motorway(Ru)and a highway section(Hi),both located near Lund,Sweden.The rural surroundings,a one-lane motorway located just north of Lund,are mainly characterized byﬁelds on either side of the road,with some residential 1More precisely,on each array a subset of4elements out of a total of32 was selected evenly spaced along the perimeter.houses,farm houses and road signs sparsely scattered along the roadside.Little to no trafﬁc prevailed during these mea-surements.The surroundings of the two-lane highway can be best described as rural or suburban,despite being within the Lund city rge portions of the roadside consist ofﬁelds or embankments;the latter constituting a noise barrier for resi-dential areas.2Some road signs and a few low-rise commercial buildings are located along the roadside,but with the exception of the areas near the exit ramps,strong static scattering points are anticipated to be scarce along the measurement route. Measurements were taken during hours with little to medium trafﬁc density;the road strip had an average of33000–38000 cars per24hours during2006[27].Measurements were performed both with TX and RX driv-ing in the same direction(SM),and with TX and RX driving in opposite directions(OP).During each measurement,the aim was to maintain the same speed for TX and RX,though this speed was varied between different measurements in order to obtain a larger statistical ensemble.Also,the distance between TX and RX was kept approximately constant during each SM measurement,though it varied between different measure-ments.32SM and12OP measurements were performed in the rural scenario,whereas19SM and21OP measurements were performed in the highway scenario.III.VTV C HANNEL C HARACTERISTICSIn this section we analyze some measurement results in order to draw conclusions about the fundamental propagation mechanisms of the VTV channel.Since any channel model is a compromise between simplicity and accuracy,our goal is to construct a model that is simple enough to be tractable from an implementation point of view,yet still able to emulate the essential VTV channel characteristics.For space reasons,our discussions are rather brief;more results as well as discussions can be found in[5]and[25].A.Time-Delay DomainBy Inverse Discrete Fourier Transforming(IDFT)the recorded frequency responses H(t,f),using a Hanning win-dow to suppress side lobes,we obtain complex channel impulse responses h(t,τ).The inﬂuence of small-scale fading is removed by averaging|h(t,τ)|2over a sample time corre-sponding to a TX movement of20wavelengths,λ,resulting in average power delay proﬁles(APDPs).Fig.1shows a typical sample plot of the time-variant APDP for a highway measurement.In this measurement,TX and RX were driving in the same direction at a speed of 110km/h,separated by slightly more than100m,and the ﬁgure shows the antenna subchannel where both elements have their main lobes directed at315degrees.From the time-delay domain results,we draw the following conclusions:(i)the LOS path is always strong,(ii)signiﬁcant energy is available through discrete components,typically represented by a single tap(e.g.,the two components near0.8μs propagation delay in Fig.1),(iii)discrete components typically move through many delay bins during a measurement;this implies that 2Such arrangements are common for European cities.Propagation delay [μs]0.40.50.60.70.80.91 1.1 1.2 1.3 1.410987654321LOSDiscrete componentsFig. 1.Example plot of the time-varying APDP of a highway SM measurement with an approximate TX/RX speed of110km/h.The antenna channel in question uses elements directed at315degrees,i.e.,close to opposite the direction of travel.The reﬂections from two discrete scatterers, both cars following the TX/RX,are clearly visible in theﬁgure.00.51 1.52 2.5Normalized amplitudeRayleighLOS tap + 3LOS tap + 2LOS tap + 1LOS tapFig. 2.Example plot of the small-scale amplitude statistics for taps immediately following the LOS tap.Theﬁgure shows the result derived from the150ﬁrst temporal samples(corresponding to5ms or a TX/RX movement of20wavelengths)of a highway SM measurement with a TX/RX speed of 90km/h.the common assumption of WSSUS is violated,(iv)discrete components may stem from mobile as well as static scattering objects,and(v)the LOS is usually followed by a tail of weaker components.Analyzing the amplitude statistics of the taps immediately following the LOS tap shows that they can be well described by a Rayleigh distribution(see Fig.2).The recorded GPS-coordinates of the TX and RX units can be used in conjunction with the time-delay domain results. By using GPS coordinates of known objects along the mea-surement route,such as buildings,bridges and road signs,we can compute the theoretical time-varying propagation distance from TX to scatterer to RX,and compare it to the occurrence of discrete reﬂections in the time-delay domain.This way we can associate physical objects with contributions in the time-variant APDP.Propagation delay [μs]0.10.20.30.40.50.60.70.80.91100050005001000Equation (1)Discrete componentFig.3.Example plot of the Doppler-resolved impulse response of a highway SM measurement (though different to the one in Fig.1),derived over a time interval of 0.15s.A discrete component is visible at approximately 0.4μs propagation delay.Also plotted in the ﬁgure is the Doppler shift vs.distance as produced by (1),i.e.,for scatterers located on a line parallel to (and a distance 5m away from)the TX/RX direction of motion.B.Delay-Doppler DomainTo investigate the Doppler characteristics of the receivedsignal,Doppler-resolved impulse responses,h (ν,τ),were derived by Fourier transforming h (t,τ)with respect to t ;an example is shown in Fig.3.We draw the following conclu-sions:(i)the total Doppler spectrum can change signi ﬁcantly during a measurement,as scatterers change their position and speed relative to TX and RX,(ii)the Doppler spread of discrete scatterers is typically small,(iii)the tail of weaker components not only has a large delay spread,but also a large Doppler spread.In the sequel,we denote this part of the channel “diffuse”in order to distinguish it from the discrete components.For a single-re ﬂection process,simple geometric relations provides the relationship between angles of arrival/departure and scatterer velocity and thus can tell us whether a scatterer is mobile or static.The Doppler shift for a signal propagating from TX to RX,traveling in parallel at speeds v T and v R ,respectively,via a single bounce off a scatterer traveling in parallel to the TX/RX at a speed v p ,can be expressed asν(ΩT,p ,ΩR,p )=1λ[(v T −v p )cos ΩT,p +(v R −v p )cos ΩR,p ],(1)if the direction-of-arrival ΩR,p and the direction-of-departure ΩT,p are given relative to the direction of travel.We ﬁnd that for v p =0,the Doppler shift produced by scattering points on a line parallel to the direction of travel closely matches the Doppler characteristics of the tail of diffuse components (see Fig.3).Our conclusion is thus that proper delay as well as Doppler characteristics of the diffuse tail can be obtained by placing scatterers along the roadside.C.Tracking a Discrete ScattererFurther insights can be gained by looking at the time-varying signal contribution of each discrete scatterer,such asthe two distinct paths of Fig.1.We thus need a tool to track the signal over time.One way of doing so would be to assume an underlying physical propagation model based on the exact locations of TX,RX and each scatterer,and determine the best-ﬁt between model and measurement.However,such an approach is sensitive to model assumptions,as well as un-certainties in the measurements (more speci ﬁcally in the GPS data).For those reasons we choose a different approach.We ﬁrst estimate the delays τi and amplitudes αi of the multipath contributions at each time instant separately,and then perform a tracking of the components over large time scales.The ﬁrst part of this algorithm is achieved by means of a high-resolution approach that is based on a serial “search-and-subtract”of the contributions from the individual scatterers (this is similar to the CLEAN method [28]).We now describe the detailed steps of the algorithm.De ﬁne the vectorsh t =h (t )=[H t (f 0)...H t (f N −1)]T ,(2)p (τ)=e j 2πf 0τ...e j 2πf N −1τ T ,(3)where h t contains the measurement data sampled at time instant t at the frequencies f 0...f N −1and p (τ)is a vector of complex exponentials that is the same for all t .Furthermore,we introduce and initialize an auxiliary vector ˜ht (1):=h t .The search-and-subtract algorithm is carried out as an iteration of two steps,starting by setting the iteration counter l =1.In the ﬁrst step,we ﬁnd the delay 3corresponding tothe component of maximum power in ˜ht (l ),i.e.,ˆτ(l )=arg max τp T (τ)˜h t (l ) 2,(4)where (·)T denotes the matrix transpose,and then ﬁnd thecorresponding complex amplitude at ˆτ(l )byˆα(l )=p T (ˆτ(l ))˜ht (l )p T p.(5)In the second step,we subtract the contribution of {ˆα(l ),ˆτ(l )}from the measurement data by˜h t (l +1):=˜h t (l )−ˆα(l )p (ˆτ(l )).(6)The algorithm increases the iteration counter to l :=l +1and repeats from the ﬁrst step until l =L ,where L ,the number of multipath components,was set to 20in our evaluations.For every time instant m ,the delay and amplitude estimates arewritten as a row in the matrices ˆT∈R M ×L and ˆA ∈C M ×L ,respectively,where M =32500and L =20.Since this method works only on the impulse response for a given time instant,it might mistakenly include noise peaks as multipath components;however,those will be ﬁltered out by the tracking procedure described below.There is thus no requirement to perform aggressive thresholding of the individual impulse responses (such thresholding has undesired consequences like eliminating multipath components with low power).To track the time-varying delay and power of a re ﬂectedpath through the matrices ˆTand ˆA ,we use an algorithm with the following steps:3Notethat the delay resolution achieved in this search step is better thanthat of a simple IDFT-based estimate.Step 1:Find the row m m and column l m of the strongestremaining component in ˆAby {m m ,l m }=arg max m,lˆA (m,l ) .The corresponding delay estimate of this component is ˆT(m m ,l m ).Step 2:Look in the adjacent rows (time samples)of ˆT,m m −1and m m +1,and ﬁnd the column indices of the “closest”components in these rows,i.e.,l m −1=arg min lˆT (m m −1,:)−ˆT (m m ,l m ) ,l m +1=arg min lˆT (m m +1,:)−ˆT (m m ,l m ) ,where ˆT(m m ±1,:)de ﬁnes the (m m ±1):th row of ˆT ,and determinem −1= ˆT (m m −1,l m −1)−ˆT (m m ,l m ) , m +1= ˆT (m m +1,l m +1)−ˆT (m m ,l m ) .If neither m −1nor m +1are ≤1/2B ,discard the componentin {m m ,l m }by setting ˆT(m m ,l m )=ˆA (m m ,l m )=0and return to step 1.4Otherwise,store ˆT(m m −1,l m −1)and/or ˆT(m m +1,l m +1)and proceed.Step 3:Estimate the direction of the samples found so far by ﬁtting a regression line˜τ(m )=a +bm(7)to ˆT(m m −1...m m +1,l m −1...l m +1)(given that both samples were stored in the previous step).Then,ﬁnd ˆT(m m −2,l m −2)and τ(m m +2,l m +2)wherel m ±2=arg min lˆT (m m ±2,:)−˜τ(m m ±2)and determinem ±2=ˆT (m m ±2,l m ±2)−˜τ(m m ±2).If m −2, m +2are ≤1/2B ,store ˆT(m m −2,l m −2)and/or ˆT(m m +2,l m +2)and repeat this step until neither m −2nor m +2are ≤1/2B .Since the curvature of the tracked path may change over time,use at most the N d last (or N d ﬁrst,depending on direction)stored components when determining ˜τfrom (7)in the iterative process.Step 4:To cope with small temporal “gaps,”i.e.,situations where the components of a path are missing in one or a few consecutive time bins,search along ˜τat both ends for an additional N gap time bins;return to step 3if a sample is found.Proceed to step 5when there are “gaps”larger than N gap at both ends.Step 5:Store the amplitudes in ˆAthat correspond to the tracked components in ˆT,then remove the tracked components from ˆAand ˆT by setting the appropriate entries to 0.Measure the length,in terms of time bins,of the tracked path.Save only paths larger than N L time bins;paths shorter than that4Notethat we are making the implicit assumption that the delay of acomponent does not change more than 1/B ,where B is the measurement bandwidth,between any two consecutive time bins.This is an eminently reasonable assumption since the channel was sampled every 0.3072ms and the maximum speed of any involved vehicle is approximately 150km/h.Fig.4.High resolution impulse response of the measurement in Fig.1.are deemed not part of a discrete re ﬂection and discarded.Ifa stopping criterion,either in terms of residual power in ˆA,or in a maximum number of tracked paths,is met,proceed to step 6,otherwise return to step 1.Step 6:To cope with larger temporal “gaps”(due to a longer time period of path invisibility),estimate ˜τp,e and ˜τp,b as the start and end extrapolation,respectively,of each path p from (7).Let the row and column indices where p begin and end be {m p,b ,l p,b }and {m p,e ,l p,e },respectively,and ﬁnd the path q that minimizesJ =ˆT (m p,b ,l p,b )−˜τq,e (m p,b ) + ˆT (m q,e ,l q,e )−˜τp,b (m q,e )=J 1(q,p )+J 2(p,q ).Step 7:If both J 1(q,p )≤1/B and J 2(p,q )≤1/B ,combine paths p and q into one and return to step 6.If not,terminate.The choices for N d ,N gap and N L have to be done on a rather arbitrary basis;in this analysis,we selected N d =40wavelengths,N gap =5wavelengths and N L =40wave-lengths.Fig.4shows the outcome of the search-and-subtract algo-rithm,executed on the measurement in Fig.1.A drawback of the search-and-subtract approach is visible;any inaccuracy of the underlying model can lead to error propagation.For ex-ample,our evaluation assumes an antenna frequency response that is completely ﬂat over the measurement bandwidth;the actual frequency response varies on the order of a few dB.The subtraction thus induces an error seen as “ringing”com-ponents,especially around the LOS.However,we also ﬁnd that the “ringing”or “ghost”components are much weaker than the true components they are surrounding,and thus can be neglected for most practical purposes.5Fig.5shows the outcome of the tracking algorithm,where we especially observe the paths,denoted “19”and “25,”we saw already in Fig.1.The power of the tracked signal from the path denoted “19”is shown in Fig.6.Our general conclusion5Attemptsto equalize the antenna frequency response could lead to noiseenhancement and thus might not bene ﬁt the overall accuracy of the results.Fig.5.Extracted paths from Fig.4as given by the tracking algorithm.Fig.6.Extracted power as a function of propagation distance for the path denoted“19”in Fig.5.Theﬁgure also shows estimated distance decay (dashed)and the low-passﬁltered signal(red).from the tracked paths is thus that the signal from a discrete scatterer is time-variant,likely due to inclusion of one or several ground reﬂections in the total signal.Thus,the standard GSCM way of modeling the complex path amplitudes as non-fading is not well suited for this type of reﬂections.IV.A G EOMETRY-B ASED S TOCHASTIC MIMO M ODEL We are now ready to deﬁne our model.First,we give a general model outline,then we go through its parts in detail and describe how they are extracted from the measurement data.Finally,we give the full set of model parameters.A.General Model OutlineAs mentioned in the introduction,the basic idea of GSCMs is to place an ensemble of point scatterers according to a sta-tistical distribution,assign them different channel properties, determine their respective signal contribution andﬁnally sum up the total contribution at the receiver.We therefore deﬁne a two-dimensional geometry as in Fig.7,where we distinguish between three types of point scatterers:mobile discrete,static discrete,and diffuse.We model the double-directional,time-variant,complex impulse response of the channel as the superposition of N paths(contributions from scatterers)by[22]h(t,τ)=Ni=1a i e jkd i(t)δ(τ−τi)×δ(ΩR−ΩR,i)δ(ΩT−ΩT,i)g R(ΩR)g T(ΩT),(8) whereτi,ΩR,i andΩT,i are the excess delay,angle-of-arrival (AOA),and angle-of-departure(AOD)of path i,g T(ΩT) and g R(ΩR)are the TX and RX antenna patterns,respec-tively,a i is the complex amplitude associated with path i, e jkd i(t)is the corresponding distance-induced phase shift and k=2πλ−1is the wave number.We can thus easily obtain the channel coefﬁcients for different spatial subchannels of a MIMO system by summing up all our channel contributions according to(8)at the respective antenna elements,using the appropriate antenna patterns[29].Furthermore,the“standard”single antenna impulse response is clearly a special case of the above formulation.In agreement with our measurement results,we divide the impulse response of(8)into four parts:(i)the LOS compo-nent,which may contain more than just the true LOS signal, e.g.,ground reﬂections,(ii)discrete components stemming from reﬂections off mobile scatterers6(MD),(iii)discrete components stemming from reﬂections off static scatterers (SD)and(iv)diffuse components(DI).We thus have(omitting the AOA and AOD notation for convenience):h(t,τ)=h LOS(t,τ)+Pp=1h MD(t,τp)+Qq=1h SD(t,τq)+Rr=1h DI(t,τr),(9)where P is the number of mobile discrete scatterers,Q is the number of mobile static scatterers and R is the number of diffuse scatterers.Since the vast majority of the discrete components identiﬁed in the measurements are due to a single bounce,we assume such processes only7and hence the time-varying propagation distance d(t)of each path is immediately given by the geometry.Furthermore,based on our observations in Sec.III-C,we assume that the complex path amplitude of the LOS path as well as the discrete scatterers is fading,i.e., a LOS=a LOS(d),a p=a p(d)and a q=a q(d),which is in contrast to conventional GSCM modeling.This approach is thus a means of representing the combined contribution from several unresolvable paths by a single one,and we thus do all our(geometric)modeling in two dimensions only. The complex amplitudes of the diffuse scattering points are modeled as in standard GSCM,as will be discussed in the subsequent sections.6Note that usage of the word“scatterer”is a slight abuse of notation,since the discrete components are not due to scattering,but rather“interaction”with objects.7This assumption is also reasonable given the fairly low discrete scatterer density of our measurements.For denser environments,it is entirely possible that higher order reﬂections would have to be considered as well.。

无人驾车的优缺点英文作文

无人驾车的优缺点英文作文The Pros and Cons of Autonomous Driving.Introduction:As technology rapidly advances, so does the realm of transportation. Autonomous driving, or self-driving cars, are no longer a concept of the future but a reality that is slowly making its way onto our roads. With companies like Tesla, Waymo, and many others actively developing and testing these vehicles, the question arises: What are the advantages and disadvantages of this emerging technology? This essay aims to explore both sides of the argument, highlighting the potential benefits as well as the challenges that lie ahead.Advantages of Autonomous Driving:1. Safety: Autonomous vehicles are designed to be safer than human-driven cars. They lack the emotional andphysical limitations that can lead to accidents, such as fatigue, distraction, or aggressive driving. By using sensors, radars, and cameras, self-driving cars can detect obstacles and react much faster than a human brain can. Additionally, they can communicate with each other and the infrastructure, sharing information about road conditions and potential hazards.2. Efficiency: Autonomous vehicles can significantly improve the efficiency of our road systems. By eliminating human error and traffic jams caused by human driving habits, self-driving cars can reduce congestion and travel time. They can also be programmed to optimize routes based onreal-time traffic data, further reducing the time spent commuting.3. Accessibility: Autonomous driving has the potentialto make transportation more accessible to everyone. People with disabilities or those who cannot drive due to age or health reasons will have greater independence and freedomof movement. Autonomous vehicles can also be used in public transportation systems, providing a more convenient andcost-effective way for people to get around.4. Environmental Benefits: Autonomous vehicles can contribute to more sustainable transportation practices. They can be programmed to drive efficiently, reducing fuel consumption and emissions. Furthermore, by optimizing routes and reducing congestion, they can help lower overall carbon emissions from the transportation sector.5. Economic Growth: The development and deployment of autonomous vehicles will create new job opportunities and drive economic growth. The automotive industry, technology companies, and governments will need to invest in research, development, and infrastructure to support this new technology. This investment will lead to job creation and economic stimulus.Disadvantages of Autonomous Driving:1. Technology Reliability: While autonomous driving technology has made significant progress, it is still not perfect. There are concerns about the reliability andsafety of these systems, especially in complex and unpredictable environments. Ensuring the technology is robust enough to handle all possible scenarios is crucial before widespread deployment.2. Legal and Ethical Challenges: Autonomous vehicles raise numerous legal and ethical questions. Who is responsible when an accident occurs? How should decisions be made in situations where there is a potential for harm to pedestrians or other road users? These questions need to be addressed through legislation and ethical frameworks.3. Infrastructure Needs: Autonomous vehicles require a significant upgrade to our existing infrastructure. Roads, intersections, and signage need to be designed and maintained to support this new technology. This will require significant investment and cooperation between governments and private companies.4. Job Displacement: The widespread deployment of autonomous vehicles could lead to job displacement in the transportation sector. Drivers of commercial vehicles,taxis, and even personal cars may find their jobs at risk. This raises concerns about the economic and social implications of this technology.5. Privacy and Security: Autonomous vehicles rely heavily on data collection and analysis. This raises concerns about privacy and security. Who will have access to this data? How will it be used and protected? These are crucial questions that need to be addressed to ensure the trustworthiness of this technology.Conclusion:Autonomous driving represents a significant milestonein the evolution of transportation. It offers the promise of safer, more efficient, and accessible roads, but it also poses challenges that need to be carefully addressed. Technology reliability, legal and ethical frameworks, infrastructure investment, job displacement, and privacy and security are all areas that require further consideration and discussion. As we move forward with this technology, it is crucial that we balance the benefits withthe potential downsides to ensure that autonomous driving becomes a force for positive change in our society.。

3GPP TS 36.331 V13.2.0 (2016-06)

3GPP TS 36.331 V13.2.0 (2016-06)Technical Specification3rd Generation Partnership Project;Technical Specification Group Radio Access Network;Evolved Universal Terrestrial Radio Access (E-UTRA);Radio Resource Control (RRC);Protocol specification(Release 13)The present document has been developed within the 3rd Generation Partnership Project (3GPP TM) and may be further elaborated for the purposes of 3GPP. The present document has not been subject to any approval process by the 3GPP Organizational Partners and shall not be implemented.This Specification is provided for future development work within 3GPP only. The Organizational Partners accept no liability for any use of this Specification. Specifications and reports for implementation of the 3GPP TM system should be obtained via the 3GPP Organizational Partners' Publications Offices.KeywordsUMTS, radio3GPPPostal address3GPP support office address650 Route des Lucioles - Sophia AntipolisValbonne - FRANCETel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16InternetCopyright NotificationNo part may be reproduced except as authorized by written permission.The copyright and the foregoing restriction extend to reproduction in all media.© 2016, 3GPP Organizational Partners (ARIB, ATIS, CCSA, ETSI, TSDSI, TTA, TTC).All rights reserved.UMTS™ is a Trade Mark of ETSI registered for the benefit of its members3GPP™ is a Trade Mark of ETSI registered for the benefit of its Members and of the 3GPP Organizational PartnersLTE™ is a Trade Mark of ETSI currently being registered for the benefit of its Members and of the 3GPP Organizational Partners GSM® and the GSM logo are registered and owned by the GSM AssociationBluetooth® is a Trade Mark of the Bluetooth SIG registered for the benefit of its membersContentsForeword (18)1Scope (19)2References (19)3Definitions, symbols and abbreviations (22)3.1Definitions (22)3.2Abbreviations (24)4General (27)4.1Introduction (27)4.2Architecture (28)4.2.1UE states and state transitions including inter RAT (28)4.2.2Signalling radio bearers (29)4.3Services (30)4.3.1Services provided to upper layers (30)4.3.2Services expected from lower layers (30)4.4Functions (30)5Procedures (32)5.1General (32)5.1.1Introduction (32)5.1.2General requirements (32)5.2System information (33)5.2.1Introduction (33)5.2.1.1General (33)5.2.1.2Scheduling (34)5.2.1.2a Scheduling for NB-IoT (34)5.2.1.3System information validity and notification of changes (35)5.2.1.4Indication of ETWS notification (36)5.2.1.5Indication of CMAS notification (37)5.2.1.6Notification of EAB parameters change (37)5.2.1.7Access Barring parameters change in NB-IoT (37)5.2.2System information acquisition (38)5.2.2.1General (38)5.2.2.2Initiation (38)5.2.2.3System information required by the UE (38)5.2.2.4System information acquisition by the UE (39)5.2.2.5Essential system information missing (42)5.2.2.6Actions upon reception of the MasterInformationBlock message (42)5.2.2.7Actions upon reception of the SystemInformationBlockType1 message (42)5.2.2.8Actions upon reception of SystemInformation messages (44)5.2.2.9Actions upon reception of SystemInformationBlockType2 (44)5.2.2.10Actions upon reception of SystemInformationBlockType3 (45)5.2.2.11Actions upon reception of SystemInformationBlockType4 (45)5.2.2.12Actions upon reception of SystemInformationBlockType5 (45)5.2.2.13Actions upon reception of SystemInformationBlockType6 (45)5.2.2.14Actions upon reception of SystemInformationBlockType7 (45)5.2.2.15Actions upon reception of SystemInformationBlockType8 (45)5.2.2.16Actions upon reception of SystemInformationBlockType9 (46)5.2.2.17Actions upon reception of SystemInformationBlockType10 (46)5.2.2.18Actions upon reception of SystemInformationBlockType11 (46)5.2.2.19Actions upon reception of SystemInformationBlockType12 (47)5.2.2.20Actions upon reception of SystemInformationBlockType13 (48)5.2.2.21Actions upon reception of SystemInformationBlockType14 (48)5.2.2.22Actions upon reception of SystemInformationBlockType15 (48)5.2.2.23Actions upon reception of SystemInformationBlockType16 (48)5.2.2.24Actions upon reception of SystemInformationBlockType17 (48)5.2.2.25Actions upon reception of SystemInformationBlockType18 (48)5.2.2.26Actions upon reception of SystemInformationBlockType19 (49)5.2.3Acquisition of an SI message (49)5.2.3a Acquisition of an SI message by BL UE or UE in CE or a NB-IoT UE (50)5.3Connection control (50)5.3.1Introduction (50)5.3.1.1RRC connection control (50)5.3.1.2Security (52)5.3.1.2a RN security (53)5.3.1.3Connected mode mobility (53)5.3.1.4Connection control in NB-IoT (54)5.3.2Paging (55)5.3.2.1General (55)5.3.2.2Initiation (55)5.3.2.3Reception of the Paging message by the UE (55)5.3.3RRC connection establishment (56)5.3.3.1General (56)5.3.3.1a Conditions for establishing RRC Connection for sidelink communication/ discovery (58)5.3.3.2Initiation (59)5.3.3.3Actions related to transmission of RRCConnectionRequest message (63)5.3.3.3a Actions related to transmission of RRCConnectionResumeRequest message (64)5.3.3.4Reception of the RRCConnectionSetup by the UE (64)5.3.3.4a Reception of the RRCConnectionResume by the UE (66)5.3.3.5Cell re-selection while T300, T302, T303, T305, T306, or T308 is running (68)5.3.3.6T300 expiry (68)5.3.3.7T302, T303, T305, T306, or T308 expiry or stop (69)5.3.3.8Reception of the RRCConnectionReject by the UE (70)5.3.3.9Abortion of RRC connection establishment (71)5.3.3.10Handling of SSAC related parameters (71)5.3.3.11Access barring check (72)5.3.3.12EAB check (73)5.3.3.13Access barring check for ACDC (73)5.3.3.14Access Barring check for NB-IoT (74)5.3.4Initial security activation (75)5.3.4.1General (75)5.3.4.2Initiation (76)5.3.4.3Reception of the SecurityModeCommand by the UE (76)5.3.5RRC connection reconfiguration (77)5.3.5.1General (77)5.3.5.2Initiation (77)5.3.5.3Reception of an RRCConnectionReconfiguration not including the mobilityControlInfo by theUE (77)5.3.5.4Reception of an RRCConnectionReconfiguration including the mobilityControlInfo by the UE(handover) (79)5.3.5.5Reconfiguration failure (83)5.3.5.6T304 expiry (handover failure) (83)5.3.5.7Void (84)5.3.5.7a T307 expiry (SCG change failure) (84)5.3.5.8Radio Configuration involving full configuration option (84)5.3.6Counter check (86)5.3.6.1General (86)5.3.6.2Initiation (86)5.3.6.3Reception of the CounterCheck message by the UE (86)5.3.7RRC connection re-establishment (87)5.3.7.1General (87)5.3.7.2Initiation (87)5.3.7.3Actions following cell selection while T311 is running (88)5.3.7.4Actions related to transmission of RRCConnectionReestablishmentRequest message (89)5.3.7.5Reception of the RRCConnectionReestablishment by the UE (89)5.3.7.6T311 expiry (91)5.3.7.7T301 expiry or selected cell no longer suitable (91)5.3.7.8Reception of RRCConnectionReestablishmentReject by the UE (91)5.3.8RRC connection release (92)5.3.8.1General (92)5.3.8.2Initiation (92)5.3.8.3Reception of the RRCConnectionRelease by the UE (92)5.3.8.4T320 expiry (93)5.3.9RRC connection release requested by upper layers (93)5.3.9.1General (93)5.3.9.2Initiation (93)5.3.10Radio resource configuration (93)5.3.10.0General (93)5.3.10.1SRB addition/ modification (94)5.3.10.2DRB release (95)5.3.10.3DRB addition/ modification (95)5.3.10.3a1DC specific DRB addition or reconfiguration (96)5.3.10.3a2LWA specific DRB addition or reconfiguration (98)5.3.10.3a3LWIP specific DRB addition or reconfiguration (98)5.3.10.3a SCell release (99)5.3.10.3b SCell addition/ modification (99)5.3.10.3c PSCell addition or modification (99)5.3.10.4MAC main reconfiguration (99)5.3.10.5Semi-persistent scheduling reconfiguration (100)5.3.10.6Physical channel reconfiguration (100)5.3.10.7Radio Link Failure Timers and Constants reconfiguration (101)5.3.10.8Time domain measurement resource restriction for serving cell (101)5.3.10.9Other configuration (102)5.3.10.10SCG reconfiguration (103)5.3.10.11SCG dedicated resource configuration (104)5.3.10.12Reconfiguration SCG or split DRB by drb-ToAddModList (105)5.3.10.13Neighbour cell information reconfiguration (105)5.3.10.14Void (105)5.3.10.15Sidelink dedicated configuration (105)5.3.10.16T370 expiry (106)5.3.11Radio link failure related actions (107)5.3.11.1Detection of physical layer problems in RRC_CONNECTED (107)5.3.11.2Recovery of physical layer problems (107)5.3.11.3Detection of radio link failure (107)5.3.12UE actions upon leaving RRC_CONNECTED (109)5.3.13UE actions upon PUCCH/ SRS release request (110)5.3.14Proximity indication (110)5.3.14.1General (110)5.3.14.2Initiation (111)5.3.14.3Actions related to transmission of ProximityIndication message (111)5.3.15Void (111)5.4Inter-RAT mobility (111)5.4.1Introduction (111)5.4.2Handover to E-UTRA (112)5.4.2.1General (112)5.4.2.2Initiation (112)5.4.2.3Reception of the RRCConnectionReconfiguration by the UE (112)5.4.2.4Reconfiguration failure (114)5.4.2.5T304 expiry (handover to E-UTRA failure) (114)5.4.3Mobility from E-UTRA (114)5.4.3.1General (114)5.4.3.2Initiation (115)5.4.3.3Reception of the MobilityFromEUTRACommand by the UE (115)5.4.3.4Successful completion of the mobility from E-UTRA (116)5.4.3.5Mobility from E-UTRA failure (117)5.4.4Handover from E-UTRA preparation request (CDMA2000) (117)5.4.4.1General (117)5.4.4.2Initiation (118)5.4.4.3Reception of the HandoverFromEUTRAPreparationRequest by the UE (118)5.4.5UL handover preparation transfer (CDMA2000) (118)5.4.5.1General (118)5.4.5.2Initiation (118)5.4.5.3Actions related to transmission of the ULHandoverPreparationTransfer message (119)5.4.5.4Failure to deliver the ULHandoverPreparationTransfer message (119)5.4.6Inter-RAT cell change order to E-UTRAN (119)5.4.6.1General (119)5.4.6.2Initiation (119)5.4.6.3UE fails to complete an inter-RAT cell change order (119)5.5Measurements (120)5.5.1Introduction (120)5.5.2Measurement configuration (121)5.5.2.1General (121)5.5.2.2Measurement identity removal (122)5.5.2.2a Measurement identity autonomous removal (122)5.5.2.3Measurement identity addition/ modification (123)5.5.2.4Measurement object removal (124)5.5.2.5Measurement object addition/ modification (124)5.5.2.6Reporting configuration removal (126)5.5.2.7Reporting configuration addition/ modification (127)5.5.2.8Quantity configuration (127)5.5.2.9Measurement gap configuration (127)5.5.2.10Discovery signals measurement timing configuration (128)5.5.2.11RSSI measurement timing configuration (128)5.5.3Performing measurements (128)5.5.3.1General (128)5.5.3.2Layer 3 filtering (131)5.5.4Measurement report triggering (131)5.5.4.1General (131)5.5.4.2Event A1 (Serving becomes better than threshold) (135)5.5.4.3Event A2 (Serving becomes worse than threshold) (136)5.5.4.4Event A3 (Neighbour becomes offset better than PCell/ PSCell) (136)5.5.4.5Event A4 (Neighbour becomes better than threshold) (137)5.5.4.6Event A5 (PCell/ PSCell becomes worse than threshold1 and neighbour becomes better thanthreshold2) (138)5.5.4.6a Event A6 (Neighbour becomes offset better than SCell) (139)5.5.4.7Event B1 (Inter RAT neighbour becomes better than threshold) (139)5.5.4.8Event B2 (PCell becomes worse than threshold1 and inter RAT neighbour becomes better thanthreshold2) (140)5.5.4.9Event C1 (CSI-RS resource becomes better than threshold) (141)5.5.4.10Event C2 (CSI-RS resource becomes offset better than reference CSI-RS resource) (141)5.5.4.11Event W1 (WLAN becomes better than a threshold) (142)5.5.4.12Event W2 (All WLAN inside WLAN mobility set becomes worse than threshold1 and a WLANoutside WLAN mobility set becomes better than threshold2) (142)5.5.4.13Event W3 (All WLAN inside WLAN mobility set becomes worse than a threshold) (143)5.5.5Measurement reporting (144)5.5.6Measurement related actions (148)5.5.6.1Actions upon handover and re-establishment (148)5.5.6.2Speed dependant scaling of measurement related parameters (149)5.5.7Inter-frequency RSTD measurement indication (149)5.5.7.1General (149)5.5.7.2Initiation (150)5.5.7.3Actions related to transmission of InterFreqRSTDMeasurementIndication message (150)5.6Other (150)5.6.0General (150)5.6.1DL information transfer (151)5.6.1.1General (151)5.6.1.2Initiation (151)5.6.1.3Reception of the DLInformationTransfer by the UE (151)5.6.2UL information transfer (151)5.6.2.1General (151)5.6.2.2Initiation (151)5.6.2.3Actions related to transmission of ULInformationTransfer message (152)5.6.2.4Failure to deliver ULInformationTransfer message (152)5.6.3UE capability transfer (152)5.6.3.1General (152)5.6.3.2Initiation (153)5.6.3.3Reception of the UECapabilityEnquiry by the UE (153)5.6.4CSFB to 1x Parameter transfer (157)5.6.4.1General (157)5.6.4.2Initiation (157)5.6.4.3Actions related to transmission of CSFBParametersRequestCDMA2000 message (157)5.6.4.4Reception of the CSFBParametersResponseCDMA2000 message (157)5.6.5UE Information (158)5.6.5.1General (158)5.6.5.2Initiation (158)5.6.5.3Reception of the UEInformationRequest message (158)5.6.6 Logged Measurement Configuration (159)5.6.6.1General (159)5.6.6.2Initiation (160)5.6.6.3Reception of the LoggedMeasurementConfiguration by the UE (160)5.6.6.4T330 expiry (160)5.6.7 Release of Logged Measurement Configuration (160)5.6.7.1General (160)5.6.7.2Initiation (160)5.6.8 Measurements logging (161)5.6.8.1General (161)5.6.8.2Initiation (161)5.6.9In-device coexistence indication (163)5.6.9.1General (163)5.6.9.2Initiation (164)5.6.9.3Actions related to transmission of InDeviceCoexIndication message (164)5.6.10UE Assistance Information (165)5.6.10.1General (165)5.6.10.2Initiation (166)5.6.10.3Actions related to transmission of UEAssistanceInformation message (166)5.6.11 Mobility history information (166)5.6.11.1General (166)5.6.11.2Initiation (166)5.6.12RAN-assisted WLAN interworking (167)5.6.12.1General (167)5.6.12.2Dedicated WLAN offload configuration (167)5.6.12.3WLAN offload RAN evaluation (167)5.6.12.4T350 expiry or stop (167)5.6.12.5Cell selection/ re-selection while T350 is running (168)5.6.13SCG failure information (168)5.6.13.1General (168)5.6.13.2Initiation (168)5.6.13.3Actions related to transmission of SCGFailureInformation message (168)5.6.14LTE-WLAN Aggregation (169)5.6.14.1Introduction (169)5.6.14.2Reception of LWA configuration (169)5.6.14.3Release of LWA configuration (170)5.6.15WLAN connection management (170)5.6.15.1Introduction (170)5.6.15.2WLAN connection status reporting (170)5.6.15.2.1General (170)5.6.15.2.2Initiation (171)5.6.15.2.3Actions related to transmission of WLANConnectionStatusReport message (171)5.6.15.3T351 Expiry (WLAN connection attempt timeout) (171)5.6.15.4WLAN status monitoring (171)5.6.16RAN controlled LTE-WLAN interworking (172)5.6.16.1General (172)5.6.16.2WLAN traffic steering command (172)5.6.17LTE-WLAN aggregation with IPsec tunnel (173)5.6.17.1General (173)5.7Generic error handling (174)5.7.1General (174)5.7.2ASN.1 violation or encoding error (174)5.7.3Field set to a not comprehended value (174)5.7.4Mandatory field missing (174)5.7.5Not comprehended field (176)5.8MBMS (176)5.8.1Introduction (176)5.8.1.1General (176)5.8.1.2Scheduling (176)5.8.1.3MCCH information validity and notification of changes (176)5.8.2MCCH information acquisition (178)5.8.2.1General (178)5.8.2.2Initiation (178)5.8.2.3MCCH information acquisition by the UE (178)5.8.2.4Actions upon reception of the MBSFNAreaConfiguration message (178)5.8.2.5Actions upon reception of the MBMSCountingRequest message (179)5.8.3MBMS PTM radio bearer configuration (179)5.8.3.1General (179)5.8.3.2Initiation (179)5.8.3.3MRB establishment (179)5.8.3.4MRB release (179)5.8.4MBMS Counting Procedure (179)5.8.4.1General (179)5.8.4.2Initiation (180)5.8.4.3Reception of the MBMSCountingRequest message by the UE (180)5.8.5MBMS interest indication (181)5.8.5.1General (181)5.8.5.2Initiation (181)5.8.5.3Determine MBMS frequencies of interest (182)5.8.5.4Actions related to transmission of MBMSInterestIndication message (183)5.8a SC-PTM (183)5.8a.1Introduction (183)5.8a.1.1General (183)5.8a.1.2SC-MCCH scheduling (183)5.8a.1.3SC-MCCH information validity and notification of changes (183)5.8a.1.4Procedures (184)5.8a.2SC-MCCH information acquisition (184)5.8a.2.1General (184)5.8a.2.2Initiation (184)5.8a.2.3SC-MCCH information acquisition by the UE (184)5.8a.2.4Actions upon reception of the SCPTMConfiguration message (185)5.8a.3SC-PTM radio bearer configuration (185)5.8a.3.1General (185)5.8a.3.2Initiation (185)5.8a.3.3SC-MRB establishment (185)5.8a.3.4SC-MRB release (185)5.9RN procedures (186)5.9.1RN reconfiguration (186)5.9.1.1General (186)5.9.1.2Initiation (186)5.9.1.3Reception of the RNReconfiguration by the RN (186)5.10Sidelink (186)5.10.1Introduction (186)5.10.1a Conditions for sidelink communication operation (187)5.10.2Sidelink UE information (188)5.10.2.1General (188)5.10.2.2Initiation (189)5.10.2.3Actions related to transmission of SidelinkUEInformation message (193)5.10.3Sidelink communication monitoring (195)5.10.6Sidelink discovery announcement (198)5.10.6a Sidelink discovery announcement pool selection (201)5.10.6b Sidelink discovery announcement reference carrier selection (201)5.10.7Sidelink synchronisation information transmission (202)5.10.7.1General (202)5.10.7.2Initiation (203)5.10.7.3Transmission of SLSS (204)5.10.7.4Transmission of MasterInformationBlock-SL message (205)5.10.7.5Void (206)5.10.8Sidelink synchronisation reference (206)5.10.8.1General (206)5.10.8.2Selection and reselection of synchronisation reference UE (SyncRef UE) (206)5.10.9Sidelink common control information (207)5.10.9.1General (207)5.10.9.2Actions related to reception of MasterInformationBlock-SL message (207)5.10.10Sidelink relay UE operation (207)5.10.10.1General (207)5.10.10.2AS-conditions for relay related sidelink communication transmission by sidelink relay UE (207)5.10.10.3AS-conditions for relay PS related sidelink discovery transmission by sidelink relay UE (208)5.10.10.4Sidelink relay UE threshold conditions (208)5.10.11Sidelink remote UE operation (208)5.10.11.1General (208)5.10.11.2AS-conditions for relay related sidelink communication transmission by sidelink remote UE (208)5.10.11.3AS-conditions for relay PS related sidelink discovery transmission by sidelink remote UE (209)5.10.11.4Selection and reselection of sidelink relay UE (209)5.10.11.5Sidelink remote UE threshold conditions (210)6Protocol data units, formats and parameters (tabular & ASN.1) (210)6.1General (210)6.2RRC messages (212)6.2.1General message structure (212)–EUTRA-RRC-Definitions (212)–BCCH-BCH-Message (212)–BCCH-DL-SCH-Message (212)–BCCH-DL-SCH-Message-BR (213)–MCCH-Message (213)–PCCH-Message (213)–DL-CCCH-Message (214)–DL-DCCH-Message (214)–UL-CCCH-Message (214)–UL-DCCH-Message (215)–SC-MCCH-Message (215)6.2.2Message definitions (216)–CounterCheck (216)–CounterCheckResponse (217)–CSFBParametersRequestCDMA2000 (217)–CSFBParametersResponseCDMA2000 (218)–DLInformationTransfer (218)–HandoverFromEUTRAPreparationRequest (CDMA2000) (219)–InDeviceCoexIndication (220)–InterFreqRSTDMeasurementIndication (222)–LoggedMeasurementConfiguration (223)–MasterInformationBlock (225)–MBMSCountingRequest (226)–MBMSCountingResponse (226)–MBMSInterestIndication (227)–MBSFNAreaConfiguration (228)–MeasurementReport (228)–MobilityFromEUTRACommand (229)–Paging (232)–ProximityIndication (233)–RNReconfiguration (234)–RNReconfigurationComplete (234)–RRCConnectionReconfiguration (235)–RRCConnectionReconfigurationComplete (240)–RRCConnectionReestablishment (241)–RRCConnectionReestablishmentComplete (241)–RRCConnectionReestablishmentReject (242)–RRCConnectionReestablishmentRequest (243)–RRCConnectionReject (243)–RRCConnectionRelease (244)–RRCConnectionResume (248)–RRCConnectionResumeComplete (249)–RRCConnectionResumeRequest (250)–RRCConnectionRequest (250)–RRCConnectionSetup (251)–RRCConnectionSetupComplete (252)–SCGFailureInformation (253)–SCPTMConfiguration (254)–SecurityModeCommand (255)–SecurityModeComplete (255)–SecurityModeFailure (256)–SidelinkUEInformation (256)–SystemInformation (258)–SystemInformationBlockType1 (259)–UEAssistanceInformation (264)–UECapabilityEnquiry (265)–UECapabilityInformation (266)–UEInformationRequest (267)–UEInformationResponse (267)–ULHandoverPreparationTransfer (CDMA2000) (273)–ULInformationTransfer (274)–WLANConnectionStatusReport (274)6.3RRC information elements (275)6.3.1System information blocks (275)–SystemInformationBlockType2 (275)–SystemInformationBlockType3 (279)–SystemInformationBlockType4 (282)–SystemInformationBlockType5 (283)–SystemInformationBlockType6 (287)–SystemInformationBlockType7 (289)–SystemInformationBlockType8 (290)–SystemInformationBlockType9 (295)–SystemInformationBlockType10 (295)–SystemInformationBlockType11 (296)–SystemInformationBlockType12 (297)–SystemInformationBlockType13 (297)–SystemInformationBlockType14 (298)–SystemInformationBlockType15 (298)–SystemInformationBlockType16 (299)–SystemInformationBlockType17 (300)–SystemInformationBlockType18 (301)–SystemInformationBlockType19 (301)–SystemInformationBlockType20 (304)6.3.2Radio resource control information elements (304)–AntennaInfo (304)–AntennaInfoUL (306)–CQI-ReportConfig (307)–CQI-ReportPeriodicProcExtId (314)–CrossCarrierSchedulingConfig (314)–CSI-IM-Config (315)–CSI-IM-ConfigId (315)–CSI-RS-Config (317)–CSI-RS-ConfigEMIMO (318)–CSI-RS-ConfigNZP (319)–CSI-RS-ConfigNZPId (320)–CSI-RS-ConfigZP (321)–CSI-RS-ConfigZPId (321)–DMRS-Config (321)–DRB-Identity (322)–EPDCCH-Config (322)–EIMTA-MainConfig (324)–LogicalChannelConfig (325)–LWA-Configuration (326)–LWIP-Configuration (326)–RCLWI-Configuration (327)–MAC-MainConfig (327)–P-C-AndCBSR (332)–PDCCH-ConfigSCell (333)–PDCP-Config (334)–PDSCH-Config (337)–PDSCH-RE-MappingQCL-ConfigId (339)–PHICH-Config (339)–PhysicalConfigDedicated (339)–P-Max (344)–PRACH-Config (344)–PresenceAntennaPort1 (346)–PUCCH-Config (347)–PUSCH-Config (351)–RACH-ConfigCommon (355)–RACH-ConfigDedicated (357)–RadioResourceConfigCommon (358)–RadioResourceConfigDedicated (362)–RLC-Config (367)–RLF-TimersAndConstants (369)–RN-SubframeConfig (370)–SchedulingRequestConfig (371)–SoundingRS-UL-Config (372)–SPS-Config (375)–TDD-Config (376)–TimeAlignmentTimer (377)–TPC-PDCCH-Config (377)–TunnelConfigLWIP (378)–UplinkPowerControl (379)–WLAN-Id-List (382)–WLAN-MobilityConfig (382)6.3.3Security control information elements (382)–NextHopChainingCount (382)–SecurityAlgorithmConfig (383)–ShortMAC-I (383)6.3.4Mobility control information elements (383)–AdditionalSpectrumEmission (383)–ARFCN-ValueCDMA2000 (383)–ARFCN-ValueEUTRA (384)–ARFCN-ValueGERAN (384)–ARFCN-ValueUTRA (384)–BandclassCDMA2000 (384)–BandIndicatorGERAN (385)–CarrierFreqCDMA2000 (385)–CarrierFreqGERAN (385)–CellIndexList (387)–CellReselectionPriority (387)–CellSelectionInfoCE (387)–CellReselectionSubPriority (388)–CSFB-RegistrationParam1XRTT (388)–CellGlobalIdEUTRA (389)–CellGlobalIdUTRA (389)–CellGlobalIdGERAN (390)–CellGlobalIdCDMA2000 (390)–CellSelectionInfoNFreq (391)–CSG-Identity (391)–FreqBandIndicator (391)–MobilityControlInfo (391)–MobilityParametersCDMA2000 (1xRTT) (393)–MobilityStateParameters (394)–MultiBandInfoList (394)–NS-PmaxList (394)–PhysCellId (395)–PhysCellIdRange (395)–PhysCellIdRangeUTRA-FDDList (395)–PhysCellIdCDMA2000 (396)–PhysCellIdGERAN (396)–PhysCellIdUTRA-FDD (396)–PhysCellIdUTRA-TDD (396)–PLMN-Identity (397)–PLMN-IdentityList3 (397)–PreRegistrationInfoHRPD (397)–Q-QualMin (398)–Q-RxLevMin (398)–Q-OffsetRange (398)–Q-OffsetRangeInterRAT (399)–ReselectionThreshold (399)–ReselectionThresholdQ (399)–SCellIndex (399)–ServCellIndex (400)–SpeedStateScaleFactors (400)–SystemInfoListGERAN (400)–SystemTimeInfoCDMA2000 (401)–TrackingAreaCode (401)–T-Reselection (402)–T-ReselectionEUTRA-CE (402)6.3.5Measurement information elements (402)–AllowedMeasBandwidth (402)–CSI-RSRP-Range (402)–Hysteresis (402)–LocationInfo (403)–MBSFN-RSRQ-Range (403)–MeasConfig (404)–MeasDS-Config (405)–MeasGapConfig (406)–MeasId (407)–MeasIdToAddModList (407)–MeasObjectCDMA2000 (408)–MeasObjectEUTRA (408)–MeasObjectGERAN (412)–MeasObjectId (412)–MeasObjectToAddModList (412)–MeasObjectUTRA (413)–ReportConfigEUTRA (422)–ReportConfigId (425)–ReportConfigInterRAT (425)–ReportConfigToAddModList (428)–ReportInterval (429)–RSRP-Range (429)–RSRQ-Range (430)–RSRQ-Type (430)–RS-SINR-Range (430)–RSSI-Range-r13 (431)–TimeToTrigger (431)–UL-DelayConfig (431)–WLAN-CarrierInfo (431)–WLAN-RSSI-Range (432)–WLAN-Status (432)6.3.6Other information elements (433)–AbsoluteTimeInfo (433)–AreaConfiguration (433)–C-RNTI (433)–DedicatedInfoCDMA2000 (434)–DedicatedInfoNAS (434)–FilterCoefficient (434)–LoggingDuration (434)–LoggingInterval (435)–MeasSubframePattern (435)–MMEC (435)–NeighCellConfig (435)–OtherConfig (436)–RAND-CDMA2000 (1xRTT) (437)–RAT-Type (437)–ResumeIdentity (437)–RRC-TransactionIdentifier (438)–S-TMSI (438)–TraceReference (438)–UE-CapabilityRAT-ContainerList (438)–UE-EUTRA-Capability (439)–UE-RadioPagingInfo (469)–UE-TimersAndConstants (469)–VisitedCellInfoList (470)–WLAN-OffloadConfig (470)6.3.7MBMS information elements (472)–MBMS-NotificationConfig (472)–MBMS-ServiceList (473)–MBSFN-AreaId (473)–MBSFN-AreaInfoList (473)–MBSFN-SubframeConfig (474)–PMCH-InfoList (475)6.3.7a SC-PTM information elements (476)–SC-MTCH-InfoList (476)–SCPTM-NeighbourCellList (478)6.3.8Sidelink information elements (478)–SL-CommConfig (478)–SL-CommResourcePool (479)–SL-CP-Len (480)–SL-DiscConfig (481)–SL-DiscResourcePool (483)–SL-DiscTxPowerInfo (485)–SL-GapConfig (485)。

Glider Flying Handbook说明书

Glider Flying Handbook2013U.S. Department of TransportationFEDERAL AVIATION ADMINISTRATIONFlight Standards Servicei iPrefaceThe Glider Flying Handbook is designed as a technical manual for applicants who are preparing for glider category rating and for currently certificated glider pilots who wish to improve their knowledge. Certificated flight instructors will find this handbook a valuable training aid, since detailed coverage of aeronautical decision-making, components and systems, aerodynamics, flight instruments, performance limitations, ground operations, flight maneuvers, traffic patterns, emergencies, soaring weather, soaring techniques, and cross-country flight is included. Topics such as radio navigation and communication, use of flight information publications, and regulations are available in other Federal Aviation Administration (FAA) publications.The discussion and explanations reflect the most commonly used practices and principles. Occasionally, the word “must” or similar language is used where the desired action is deemed critical. The use of such language is not intended to add to, interpret, or relieve a duty imposed by Title 14 of the Code of Federal Regulations (14 CFR). Persons working towards a glider rating are advised to review the references from the applicable practical test standards (FAA-G-8082-4, Sport Pilot and Flight Instructor with a Sport Pilot Rating Knowledge Test Guide, FAA-G-8082-5, Commercial Pilot Knowledge Test Guide, and FAA-G-8082-17, Recreational Pilot and Private Pilot Knowledge Test Guide). Resources for study include FAA-H-8083-25, Pilot’s Handbook of Aeronautical Knowledge, FAA-H-8083-2, Risk Management Handbook, and Advisory Circular (AC) 00-6, Aviation Weather For Pilots and Flight Operations Personnel, AC 00-45, Aviation Weather Services, as these documents contain basic material not duplicated herein. All beginning applicants should refer to FAA-H-8083-25, Pilot’s Handbook of Aeronautical Knowledge, for study and basic library reference.It is essential for persons using this handbook to become familiar with and apply the pertinent parts of 14 CFR and the Aeronautical Information Manual (AIM). The AIM is available online at . The current Flight Standards Service airman training and testing material and learning statements for all airman certificates and ratings can be obtained from .This handbook supersedes FAA-H-8083-13, Glider Flying Handbook, dated 2003. Always select the latest edition of any publication and check the website for errata pages and listing of changes to FAA educational publications developed by the FAA’s Airman Testing Standards Branch, AFS-630.This handbook is available for download, in PDF format, from .This handbook is published by the United States Department of Transportation, Federal Aviation Administration, Airman Testing Standards Branch, AFS-630, P.O. Box 25082, Oklahoma City, OK 73125.Comments regarding this publication should be sent, in email form, to the following address:********************************************John M. AllenDirector, Flight Standards Serviceiiii vAcknowledgmentsThe Glider Flying Handbook was produced by the Federal Aviation Administration (FAA) with the assistance of Safety Research Corporation of America (SRCA). The FAA wishes to acknowledge the following contributors: Sue Telford of Telford Fishing & Hunting Services for images used in Chapter 1JerryZieba () for images used in Chapter 2Tim Mara () for images used in Chapters 2 and 12Uli Kremer of Alexander Schleicher GmbH & Co for images used in Chapter 2Richard Lancaster () for images and content used in Chapter 3Dave Nadler of Nadler & Associates for images used in Chapter 6Dave McConeghey for images used in Chapter 6John Brandon (www.raa.asn.au) for images and content used in Chapter 7Patrick Panzera () for images used in Chapter 8Jeff Haby (www.theweatherprediction) for images used in Chapter 8National Soaring Museum () for content used in Chapter 9Bill Elliot () for images used in Chapter 12.Tiffany Fidler for images used in Chapter 12.Additional appreciation is extended to the Soaring Society of America, Inc. (), the Soaring Safety Foundation, and Mr. Brad Temeyer and Mr. Bill Martin from the National Oceanic and Atmospheric Administration (NOAA) for their technical support and input.vv iPreface (iii)Acknowledgments (v)Table of Contents (vii)Chapter 1Gliders and Sailplanes ........................................1-1 Introduction....................................................................1-1 Gliders—The Early Years ..............................................1-2 Glider or Sailplane? .......................................................1-3 Glider Pilot Schools ......................................................1-4 14 CFR Part 141 Pilot Schools ...................................1-5 14 CFR Part 61 Instruction ........................................1-5 Glider Certificate Eligibility Requirements ...................1-5 Common Glider Concepts ..............................................1-6 Terminology...............................................................1-6 Converting Metric Distance to Feet ...........................1-6 Chapter 2Components and Systems .................................2-1 Introduction....................................................................2-1 Glider Design .................................................................2-2 The Fuselage ..................................................................2-4 Wings and Components .............................................2-4 Lift/Drag Devices ...........................................................2-5 Empennage .....................................................................2-6 Towhook Devices .......................................................2-7 Powerplant .....................................................................2-7 Self-Launching Gliders .............................................2-7 Sustainer Engines .......................................................2-8 Landing Gear .................................................................2-8 Wheel Brakes .............................................................2-8 Chapter 3Aerodynamics of Flight .......................................3-1 Introduction....................................................................3-1 Forces of Flight..............................................................3-2 Newton’s Third Law of Motion .................................3-2 Lift ..............................................................................3-2The Effects of Drag on a Glider .....................................3-3 Parasite Drag ..............................................................3-3 Form Drag ...............................................................3-3 Skin Friction Drag ..................................................3-3 Interference Drag ....................................................3-5 Total Drag...................................................................3-6 Wing Planform ...........................................................3-6 Elliptical Wing ........................................................3-6 Rectangular Wing ...................................................3-7 Tapered Wing .........................................................3-7 Swept-Forward Wing ..............................................3-7 Washout ..................................................................3-7 Glide Ratio .................................................................3-8 Aspect Ratio ............................................................3-9 Weight ........................................................................3-9 Thrust .........................................................................3-9 Three Axes of Rotation ..................................................3-9 Stability ........................................................................3-10 Flutter .......................................................................3-11 Lateral Stability ........................................................3-12 Turning Flight ..............................................................3-13 Load Factors .................................................................3-13 Radius of Turn ..........................................................3-14 Turn Coordination ....................................................3-15 Slips ..........................................................................3-15 Forward Slip .........................................................3-16 Sideslip .................................................................3-17 Spins .........................................................................3-17 Ground Effect ...............................................................3-19 Chapter 4Flight Instruments ...............................................4-1 Introduction....................................................................4-1 Pitot-Static Instruments ..................................................4-2 Impact and Static Pressure Lines................................4-2 Airspeed Indicator ......................................................4-2 The Effects of Altitude on the AirspeedIndicator..................................................................4-3 Types of Airspeed ...................................................4-3Table of ContentsviiAirspeed Indicator Markings ......................................4-5 Other Airspeed Limitations ........................................4-6 Altimeter .....................................................................4-6 Principles of Operation ...........................................4-6 Effect of Nonstandard Pressure andTemperature............................................................4-7 Setting the Altimeter (Kollsman Window) .............4-9 Types of Altitude ......................................................4-10 Variometer................................................................4-11 Total Energy System .............................................4-14 Netto .....................................................................4-14 Electronic Flight Computers ....................................4-15 Magnetic Compass .......................................................4-16 Yaw String ................................................................4-16 Inclinometer..............................................................4-16 Gyroscopic Instruments ...............................................4-17 G-Meter ........................................................................4-17 FLARM Collision Avoidance System .........................4-18 Chapter 5Glider Performance .............................................5-1 Introduction....................................................................5-1 Factors Affecting Performance ......................................5-2 High and Low Density Altitude Conditions ...........5-2 Atmospheric Pressure .............................................5-2 Altitude ...................................................................5-3 Temperature............................................................5-3 Wind ...........................................................................5-3 Weight ........................................................................5-5 Rate of Climb .................................................................5-7 Flight Manuals and Placards ..........................................5-8 Placards ......................................................................5-8 Performance Information ...........................................5-8 Glider Polars ...............................................................5-8 Weight and Balance Information .............................5-10 Limitations ...............................................................5-10 Weight and Balance .....................................................5-12 Center of Gravity ......................................................5-12 Problems Associated With CG Forward ofForward Limit .......................................................5-12 Problems Associated With CG Aft of Aft Limit ..5-13 Sample Weight and Balance Problems ....................5-13 Ballast ..........................................................................5-14 Chapter 6Preflight and Ground Operations .......................6-1 Introduction....................................................................6-1 Assembly and Storage Techniques ................................6-2 Trailering....................................................................6-3 Tiedown and Securing ................................................6-4Water Ballast ..............................................................6-4 Ground Handling........................................................6-4 Launch Equipment Inspection ....................................6-5 Glider Preflight Inspection .........................................6-6 Prelaunch Checklist ....................................................6-7 Glider Care .....................................................................6-7 Preventive Maintenance .............................................6-8 Chapter 7Launch and Recovery Procedures and Flight Maneuvers ............................................................7-1 Introduction....................................................................7-1 Aerotow Takeoff Procedures .........................................7-2 Signals ........................................................................7-2 Prelaunch Signals ....................................................7-2 Inflight Signals ........................................................7-3 Takeoff Procedures and Techniques ..........................7-3 Normal Assisted Takeoff............................................7-4 Unassisted Takeoff.....................................................7-5 Crosswind Takeoff .....................................................7-5 Assisted ...................................................................7-5 Unassisted...............................................................7-6 Aerotow Climb-Out ....................................................7-6 Aerotow Release.........................................................7-8 Slack Line ...................................................................7-9 Boxing the Wake ......................................................7-10 Ground Launch Takeoff Procedures ............................7-11 CG Hooks .................................................................7-11 Signals ......................................................................7-11 Prelaunch Signals (Winch/Automobile) ...............7-11 Inflight Signals ......................................................7-12 Tow Speeds ..............................................................7-12 Automobile Launch ..................................................7-14 Crosswind Takeoff and Climb .................................7-14 Normal Into-the-Wind Launch .................................7-15 Climb-Out and Release Procedures ..........................7-16 Self-Launch Takeoff Procedures ..............................7-17 Preparation and Engine Start ....................................7-17 Taxiing .....................................................................7-18 Pretakeoff Check ......................................................7-18 Normal Takeoff ........................................................7-19 Crosswind Takeoff ...................................................7-19 Climb-Out and Shutdown Procedures ......................7-19 Landing .....................................................................7-21 Gliderport/Airport Traffic Patterns and Operations .....7-22 Normal Approach and Landing ................................7-22 Crosswind Landing ..................................................7-25 Slips ..........................................................................7-25 Downwind Landing ..................................................7-27 After Landing and Securing .....................................7-27viiiPerformance Maneuvers ..............................................7-27 Straight Glides ..........................................................7-27 Turns.........................................................................7-28 Roll-In ...................................................................7-29 Roll-Out ................................................................7-30 Steep Turns ...........................................................7-31 Maneuvering at Minimum Controllable Airspeed ...7-31 Stall Recognition and Recovery ...............................7-32 Secondary Stalls ....................................................7-34 Accelerated Stalls .................................................7-34 Crossed-Control Stalls ..........................................7-35 Operating Airspeeds .....................................................7-36 Minimum Sink Airspeed ..........................................7-36 Best Glide Airspeed..................................................7-37 Speed to Fly ..............................................................7-37 Chapter 8Abnormal and Emergency Procedures .............8-1 Introduction....................................................................8-1 Porpoising ......................................................................8-2 Pilot-Induced Oscillations (PIOs) ..............................8-2 PIOs During Launch ...................................................8-2 Factors Influencing PIOs ........................................8-2 Improper Elevator Trim Setting ..............................8-3 Improper Wing Flaps Setting ..................................8-3 Pilot-Induced Roll Oscillations During Launch .........8-3 Pilot-Induced Yaw Oscillations During Launch ........8-4 Gust-Induced Oscillations ..............................................8-5 Vertical Gusts During High-Speed Cruise .................8-5 Pilot-Induced Pitch Oscillations During Landing ......8-6 Glider-Induced Oscillations ...........................................8-6 Pitch Influence of the Glider Towhook Position ........8-6 Self-Launching Glider Oscillations During Powered Flight ...........................................................8-7 Nosewheel Glider Oscillations During Launchesand Landings ..............................................................8-7 Tailwheel/Tailskid Equipped Glider Oscillations During Launches and Landings ..................................8-8 Aerotow Abnormal and Emergency Procedures ............8-8 Abnormal Procedures .................................................8-8 Towing Failures........................................................8-10 Tow Failure With Runway To Land and Stop ......8-11 Tow Failure Without Runway To Land BelowReturning Altitude ................................................8-11 Tow Failure Above Return to Runway Altitude ...8-11 Tow Failure Above 800' AGL ..............................8-12 Tow Failure Above Traffic Pattern Altitude .........8-13 Slack Line .................................................................8-13 Ground Launch Abnormal and Emergency Procedures ....................................................................8-14 Abnormal Procedures ...............................................8-14 Emergency Procedures .............................................8-14 Self-Launch Takeoff Emergency Procedures ..............8-15 Emergency Procedures .............................................8-15 Spiral Dives ..................................................................8-15 Spins .............................................................................8-15 Entry Phase ...............................................................8-17 Incipient Phase .........................................................8-17 Developed Phase ......................................................8-17 Recovery Phase ........................................................8-17 Off-Field Landing Procedures .....................................8-18 Afterlanding Off Field .............................................8-20 Off-Field Landing Without Injury ........................8-20 Off-Field Landing With Injury .............................8-20 System and Equipment Malfunctions ..........................8-20 Flight Instrument Malfunctions ................................8-20 Airspeed Indicator Malfunctions ..........................8-21 Altimeter Malfunctions .........................................8-21 Variometer Malfunctions ......................................8-21 Compass Malfunctions .........................................8-21 Glider Canopy Malfunctions ....................................8-21 Broken Glider Canopy ..........................................8-22 Frosted Glider Canopy ..........................................8-22 Water Ballast Malfunctions ......................................8-22 Retractable Landing Gear Malfunctions ..................8-22 Primary Flight Control Systems ...............................8-22 Elevator Malfunctions ..........................................8-22 Aileron Malfunctions ............................................8-23 Rudder Malfunctions ............................................8-24 Secondary Flight Controls Systems .........................8-24 Elevator Trim Malfunctions .................................8-24 Spoiler/Dive Brake Malfunctions .........................8-24 Miscellaneous Flight System Malfunctions .................8-25 Towhook Malfunctions ............................................8-25 Oxygen System Malfunctions ..................................8-25 Drogue Chute Malfunctions .....................................8-25 Self-Launching Gliders ................................................8-26 Self-Launching/Sustainer Glider Engine Failure During Takeoff or Climb ..........................................8-26 Inability to Restart a Self-Launching/SustainerGlider Engine While Airborne .................................8-27 Self-Launching Glider Propeller Malfunctions ........8-27 Self-Launching Glider Electrical System Malfunctions .............................................................8-27 In-flight Fire .............................................................8-28 Emergency Equipment and Survival Gear ...................8-28 Survival Gear Checklists ..........................................8-28 Food and Water ........................................................8-28ixClothing ....................................................................8-28 Communication ........................................................8-29 Navigation Equipment ..............................................8-29 Medical Equipment ..................................................8-29 Stowage ....................................................................8-30 Parachute ..................................................................8-30 Oxygen System Malfunctions ..................................8-30 Accident Prevention .....................................................8-30 Chapter 9Soaring Weather ..................................................9-1 Introduction....................................................................9-1 The Atmosphere .............................................................9-2 Composition ...............................................................9-2 Properties ....................................................................9-2 Temperature............................................................9-2 Density ....................................................................9-2 Pressure ...................................................................9-2 Standard Atmosphere .................................................9-3 Layers of the Atmosphere ..........................................9-4 Scale of Weather Events ................................................9-4 Thermal Soaring Weather ..............................................9-6 Thermal Shape and Structure .....................................9-6 Atmospheric Stability .................................................9-7 Air Masses Conducive to Thermal Soaring ...................9-9 Cloud Streets ..............................................................9-9 Thermal Waves...........................................................9-9 Thunderstorms..........................................................9-10 Lifted Index ..........................................................9-12 K-Index .................................................................9-12 Weather for Slope Soaring .......................................9-14 Mechanism for Wave Formation ..............................9-16 Lift Due to Convergence ..........................................9-19 Obtaining Weather Information ...................................9-21 Preflight Weather Briefing........................................9-21 Weather-ReIated Information ..................................9-21 Interpreting Weather Charts, Reports, andForecasts ......................................................................9-23 Graphic Weather Charts ...........................................9-23 Winds and Temperatures Aloft Forecast ..............9-23 Composite Moisture Stability Chart .....................9-24 Chapter 10Soaring Techniques ..........................................10-1 Introduction..................................................................10-1 Thermal Soaring ...........................................................10-2 Locating Thermals ....................................................10-2 Cumulus Clouds ...................................................10-2 Other Indicators of Thermals ................................10-3 Wind .....................................................................10-4 The Big Picture .....................................................10-5Entering a Thermal ..............................................10-5 Inside a Thermal.......................................................10-6 Bank Angle ...........................................................10-6 Speed .....................................................................10-6 Centering ...............................................................10-7 Collision Avoidance ................................................10-9 Exiting a Thermal .....................................................10-9 Atypical Thermals ..................................................10-10 Ridge/Slope Soaring ..................................................10-10 Traps ......................................................................10-10 Procedures for Safe Flying .....................................10-12 Bowls and Spurs .....................................................10-13 Slope Lift ................................................................10-13 Obstructions ...........................................................10-14 Tips and Techniques ...............................................10-15 Wave Soaring .............................................................10-16 Preflight Preparation ...............................................10-17 Getting Into the Wave ............................................10-18 Flying in the Wave .................................................10-20 Soaring Convergence Zones ...................................10-23 Combined Sources of Updrafts ..............................10-24 Chapter 11Cross-Country Soaring .....................................11-1 Introduction..................................................................11-1 Flight Preparation and Planning ...................................11-2 Personal and Special Equipment ..................................11-3 Navigation ....................................................................11-5 Using the Plotter .......................................................11-5 A Sample Cross-Country Flight ...............................11-5 Navigation Using GPS .............................................11-8 Cross-Country Techniques ...........................................11-9 Soaring Faster and Farther .........................................11-11 Height Bands ..........................................................11-11 Tips and Techniques ...............................................11-12 Special Situations .......................................................11-14 Course Deviations ..................................................11-14 Lost Procedures ......................................................11-14 Cross-Country Flight in a Self-Launching Glider .....11-15 High-Performance Glider Operations and Considerations ............................................................11-16 Glider Complexity ..................................................11-16 Water Ballast ..........................................................11-17 Cross-Country Flight Using Other Lift Sources ........11-17 Chapter 12Towing ................................................................12-1 Introduction..................................................................12-1 Equipment Inspections and Operational Checks .........12-2 Tow Hook ................................................................12-2 Schweizer Tow Hook ...........................................12-2x。

关于交通工具的手抄报英语

关于交通工具的手抄报英语Transportation is an essential part of our daily lives, allowing us to travel from one place to another efficiently. There are various modes of transportation, each with its own advantages and disadvantages. In this handout, we will explore different types of transportation and their impact on our lives.1. What are the different types of transportation?There are several types of transportation, including cars, buses, trains, airplanes, bicycles, and walking.2. What are the advantages of using a car as a mode of transportation?Using a car allows for convenience and flexibility in travel. Cars provide privacy and the ability to travel to remote locations not accessible by public transportation.3. What are the disadvantages of using a car as a modeof transportation?Cars contribute to air pollution and traffic congestion. They also require maintenance and are expensive to own and operate.4. What are the benefits of using public transportation?Public transportation is cost-effective and environmentally friendly. It reduces traffic congestion and offers a safe and reliable mode of travel.5. What are the drawbacks of using public transportation?Public transportation schedules may not always alignwith individual travel needs. It can also be crowded andless convenient for reaching certain destinations.6. How does air travel benefit society?Air travel allows for rapid long-distance travel and facilitates international trade and tourism. It connects people and cultures across the globe.7. What are the environmental impacts of air travel?Air travel contributes to carbon emissions and air pollution. The growth of the aviation industry raises concerns about its impact on climate change.8. Why is walking and cycling considered sustainable transportation?Walking and cycling are environmentally friendly modesof transportation that promote physical activity and reduce carbon emissions. They also contribute to a healthier lifestyle.9. How does the development of high-speed trains impact transportation?High-speed trains provide a fast, efficient, and comfortable mode of travel for both short and long distances. They reduce the reliance on automobiles and airplanes for intercity travel.10. What are the challenges of implementing high-speed train systems?The construction and maintenance of high-speed train infrastructure require significant investment. There may also be challenges in integrating high-speed trains with existing transportation networks.11. How does technology influence transportation?Advancements in technology have led to the development of electric and autonomous vehicles, as well as improvements in transportation infrastructure and traffic management systems.12. What is the future of transportation?The future of transportation is likely to involve a shift towards sustainable and interconnected modes of travel, including electric and autonomous vehicles, integrated public transportation systems, and smart city initiatives.交通工具是我们日常生活中不可或缺的一部分，它使我们能够高效地从一个地方去往另一个地方。

基于双向嵌套级联残差的交通标志检测方法

现代电子技术Modern Electronics Technique2024年3月1日第47卷第5期Mar. 2024Vol. 47 No. 50 引言汽车智能化是汽车产业一直在追寻的目标，而自动驾驶是汽车智能化不可或缺的一环。

要实现自动驾驶，必须为汽车加上一双眼睛和配套的处理系统，这套处理系统需要像人一样识别交通标志。

交通标志检测的实现方案主要有两大类：一类是基于计算机图形学的方案，比如依据颜色直方图、尺度不变特征变换特征、方向基于双向嵌套级联残差的交通标志检测方法江金懋，钟国韵（东华理工大学信息工程学院，江西南昌 330013）摘要：交通标志检测是自动驾驶领域的一个重要课题，其对于检测系统的实时性和精度都有非常高的要求。

目标检测领域中的YOLOv3算法是业界公认在精度和速度上都处于前列的一种算法。

文中以YOLOv3检测算法作为基础网络，提出一种双向嵌套级联残差单元（bid⁃NCR ），替换掉原网络中顺序堆叠的标准残差块。

双向嵌套级联残差单元的两条残差边采用相同的结构，都是一次卷积操作加上一次级联残差处理，两条边上级联的标准残差块的数量可以调节，从而形成不同的深度差。

然后将两条边的结果逐像素相加，最后再做一次卷积操作。

相较于标准残差块，双向嵌套级联残差单元拥有更强的特征提取能力和特征融合能力。

文中还提出跨区域压缩模块（CRC ），它是对2倍率下采样卷积操作的替代，旨在融合跨区域的通道数据，进一步加强主干网络输入特征图所包含的信息。

实验结果表明：提出的模型在CCTSDB 数据集上mAP （0.5）、mAP （0.5∶0.95）分别达到96.86%、68.66%，FPS 达到66.09帧。

相比于YOLOv3算法，3个指标分别提升1.23%、10.35%、127.90%。

关键词：交通标志检测；双向嵌套级联残差单元；跨区域压缩模块； YOLOv3；长沙理工大学中国交通标志检测数据集；特征提取；特征融合中图分类号： TN911.73⁃34； TP391 文献标识码： A 文章编号： 1004⁃373X （2024）05⁃0176⁃06Traffic sign detection method based on bi⁃directional nested cascading residualsJIANG Jinmao, ZHONG Guoyun(School of Information Engineering, East China University of Technology, Nanchang 330013, China)Abstract ： Traffic sign detection is an important topic in the field of autonomous driving, which has very high requirements for real ⁃time performance and accuracy of the detection system. The YOLOv3 algorithm in the field of target detection is recognized as one of the leading algorithms in terms of accuracy and speed. In this paper, by taking YOLOv3 detection algorithm as the base network, a bi⁃directional nested cascaded residual (bid⁃NCR) unit is proposed to replace the standard residual blocks sequentially stacked in the original network. The two residual edges of the bid⁃NCR unit is of the same structure, both of which are one convolutional operation plus one cascaded residual processing, and the number of cascaded standard residual blocks on the two edges can be adjusted to form different depth differences. The results of the two edges are then added pixel by pixel, and another convolutional operation is performed, finally. In comparison with the standard residual blocks, the bid ⁃NCR unit has stronger feature extraction capability and feature fusion capability. The cross ⁃region compression (CRC) module, which is an alternative to the 2⁃fold downsampling convolutional operation, is proposed. It aims to fuse the channel data across regions to further enhance the information contained in the input feature map of the backbone network. The experimental results show thatthe model proposed in this paper achieves mAP(0.5) and mAP(0.5∶0.95) of 96.86% and 68.66%, respectively, and FPS of 66.09 frames on the dataset CCTSDB. In comparison with YOLOv3 algorithm, the three indicators are improved by 1.23%, 10.35% and 127.90%, respectively.Keywords ： traffic sign detection; bid⁃NCR unit; CRC module; YOLOv3; CSUST Chinese traffic sign detection benchmark(CCTSDB); feature extraction; feature fusionDOI ：10.16652/j.issn.1004⁃373x.2024.05.031引用格式：江金懋，钟国韵.基于双向嵌套级联残差的交通标志检测方法[J].现代电子技术，2024，47（5）：176⁃181.收稿日期：2023⁃09⁃13 修回日期：2023⁃10⁃11176第5期梯度直方图特征[1]等，以上方法最大的问题在于这些人工提取的特征高度依赖于特定的场景，泛化能力很差；另一类是基于深度学习的方案，比如文献[2]提出的基于多尺度卷积神经网络的方案，设计了一个多尺度空洞卷积池化金字塔模块用于采样。

基于半无限流场的汽车外噪声预测

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关键词：统计能量分析；半无限流体；汽车；噪声

基于捕食搜索策略的混合动力汽车参数优化

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基于车辆构成和特征提取的交通状态预估模型

测控技术2019年第38卷第5期先进算法与人工智能・36・基于车辆构成和特征提取的交通状态预估模型67,谢兴生，王青松(中国科学技术大学信息科学技术学院，安徽合肥230022)摘要:准确的交通状态预估有利于车辆选择合理交通路线，缓解交通拥堵状态。

针对传统方法特征提取不充分、预估准确度依赖于监测器精度等问题,提出了一种基于车辆构成和特征提取的交通状态预估模型。

该模型以速度、流量、占用率和大型车辆为输入，将交通状态分成畅通、拥挤和拥堵三种状态，结合时间空间维度来预估交通状态。

通过卷积神经网络(Convolutional Neural Network,CNN)提取交通拥堵特征,得到的特征输入支持向量机(Support Vector Machine,SVM)进行交通状态预估。

实验表明，车辆构成车辆构成准确率提高1.12%,CNN-SVM模型预估准确度比CNN模型提升2.25%，是一种有效的交通状态预估模型。

关键词：智能交通;CNN-SVM；深度学习；交通状态预估中图分类号:TP399文献标识码：A文章编号：1000-8829(2019)05-0036-04doi：10.19708/j.ckjs.2019.05.008Traffic State Estimation Model Based on Vehicle Composition andFeature ExtractionSHE Hao,XIE Xing-sheng,WANG Qing-song(School of Information Science and Technology,University of Science and Technology of China,Hefei230022,China) Abstract：Accurate traffic state estimation is conducive to the vehicle to choose a reasonable traffic route and ease traffic congestion.In order to solve the problems that the traditional method extracts traffic congestion feature insufficiently and the estimation accuracy depends on the accuracy of the monitor,a traffic state estimation model based on vehicle composition and feature extraction is proposed.The model used speed,flow,occupancy and large vehicle weight as input,and divided the traffic state into three states:smooth,crowded and congested,and combined the time and space dimensions to estimate the traffic state.The convolutional neural network (CNN)extracted traffic congestion features automatically which would be used in SVM for traffic state estimation.Experiments show that the model considering vehicle composition increases the accuracy by1.12%compared with the model that ignores the vehicle composition.The CNN-SVM model estimation accuracy is2.25% higher than the CNN model,which is an effective traffic state estimation model.Key words：intelligent transportation;CNN-SVM;deep learning;traffic state estimation在诸多交通问题中，交通拥堵是发生频率最高、影响最大、时间持续最长的问题。

英语写作-私家车增多问题

Implement congestion charges and car purchase restrictions policies
Introduce congestion charges
implement tolls or fees on拥挤的道路或繁忙时段 to discourage driving during peak hours.
Greenhouse gas emissions
The rise in car usage has resulted in an increase in greenhouse gas emissions, contributing to climate change and global warming.
目录
• The impact of the increase in private cars
• The future development trend of increasing private cars
01
The phenomenon of increasing private cars
The trend of increasing the number os for the increase in private
cars
Economic development and increased income levels
The improvement of the overall economy and the expansion of the market have created more opportunities for the development of the automobile industry, making private cars more accessible.

teb参数inflation_dist接近小车半径

Teb软件包中的inflation_dist参数是一个非常重要的参数，它表示机器人对障碍物的膨胀距离，即其周围的一圈安全距离。

该参数直接决定了机器人路径规划时障碍物的避让策略。

当inflation_dist设置为接近小车半径时，可以减少路径的冗余，使得规划出的路径更加紧凑和高效。

同时，由于小车的半径是车辆的物理限制，设置inflation_dist接近小车半径可以更好地考虑车辆的运动特性。

然而，将inflation_dist接近小车半径可能会带来一些影响。

例如，它可能会使得机器人对障碍物的避让距离过小，导致机器人无法安全地绕过障碍物。

因此，在设置inflation_dist参数时，需要综合考虑机器人的运动特性和实际应用场景，以获得最佳的路径规划效果。

基于L1加权压缩感知下的车辆分类

基于L1加权压缩感知下的车辆分类作者：龚火青来源：《电脑知识与技术》2019年第06期摘要：压缩感知在信息技术和信号处理领域引起了广泛关注，因为它提供了一种替代的，无冗余的信号压缩和重建方法。

它利用信号的“稀疏性”来对序列进行欠采样并重建，而不添加由Shannon-Nyquist采样定理建立的混叠噪声。

然而，由于使用非线性重建多项式，重建方法是昂贵的。

本文为了增强声信号源在变换域中的稀疏性，提出一种L1-加权迭代软阈值算法（L1-IST），并与现有的稀疏信号恢复方法，压缩采样匹配追踪（CoSaMP）与迭代软阈值算法（IST）进行了比较，最后利用L1-IST对具有声信号源的车辆进行分类。

以奈奎斯特速率的一半对信号进行采样，然后使用L1-IST进行重建。

从多个变换域中提取诸如信号的均值，方差，偏度和峰度的各种特征。

从重建信号中提取的特征被馈送到KNN分类器，该分类器将目标信号分类为自行车、汽车、拖拉机或卡车。

关键词：压缩感知；CoSaMP算法；L1加权；迭代软阈值算法；K近邻算法中图分类号：TP18 文献标识码：A 文章编号：1009-3044（2019）06-0162-031 概述车辆检测和分类具有大量应用，包括交通监控，道路分流等，它在交通监控和管理中起着非常重要的作用。

有各种方法可用于车辆检测和分类[1]，比如基于概率、非概率和基于方形距离的方法用于检测和分类。

然而，由于信息爆炸或数据泛滥的挑战，需要以某种方式减少样本数量。

根据香农定理，必须以大于或等于信号占用带宽的两倍的频率对模拟信号进行采样。

在许多应用中，奈奎斯特速率可能很高，以至于我们最终得到的样本太多，因此我们必须压缩信号以便存储或传输它们。

传统的数据压缩方法包括两个步骤——统一采样数据，压缩数据。

压缩感知将上述采样和压缩步骤与有趣的特性相结合[2]。

信号随机欠采样，然后传输到远处，在接收器端，可以从较少的数据样本重新构造原始信号。

这大大减少了数据采集，存储和需要传输的数据量的时间。

火车

Vehicle System DynamicsV ol.46,Supplement,2008,737–750A study on the new wheel and rail tangential force model forthe high-speed railway vehiclesKoichi Sasaki a*and Yoshihiro Suda ba Research and Development Center,East Japan Railway,Saitama,Japan;b Center forCollaborative Research,The University of Tokyo,Tokyo,Japan(Received29July2007;ﬁnal version received6March2008)A new creep force model for a dynamic analysis of the wheel/rail tangential force of high-speedrailway vehicles has been devised.The test data of actual in-service Shinkansen vehicles at high speedwere analysed with the model,and the calculated results veriﬁed the validity of the model.The resultsconﬁrm that the lateral oscillation of the vehicle can be reduced by improving the suspension.Byraising the natural frequency of the bogie steer mode to greater than that of the body yawing mode atcommercial speed,bogie motions are controlled by the damping equipments and by the mass of thebody.The methodology that arranges the natural frequency of vehicle suspension in this manner hasbeen described,and it could be analysed more precisely by the new wheel/rail tangential force model.Keywords:high-speed railway vehicle;wheel/rail force;traction;lateral dynamics;suspension1.IntroductionSince the Tokaido Shinkansen,theﬁrst bullet train in Japan,started operation at the maximum speed of210km/h in1964,the Shinkansen,whose vehicles are the power-distributed trains, has been expanded greatly in the terms of new routes and upgraded vehicles.Especially after the privatisation of Japan Railways,the maximum operation speed was partially improved to 300km/h and the high-speed network was expanded to cover most of Japan,bringing enor-mous commercial beneﬁts to the country.Issues such as ride comfort and lateral oscillation, however,have been discussed for a long time,so much research and development on vehicle dynamics has been performed.As one method of improving these issues,the active lateral-oscillation control was introduced with remarkable effect.At present,however,to identify the mechanisms of lateral oscillation and to develop a new bogie for high-speed running,the accu-racy of the lateral oscillation analysis of high-speed railway vehicles must be further improved. In this article,a case study on the methodology for a more suitable design of a vehicle suspension is carried out,aimed to improve running stability and ride comfort.The model uses linear analysis in a straight line with a new creep force model.*Corresponding author.Email:koichi-sasaki@jreast.co.jpISSN0042-3114print/ISSN1744-5159online©2008Taylor&FrancisDOI:10.1080/00423110802037016738K.Sasaki and Y.Suda2.Numerical model of wheel/rail tangential forceTheﬁrst theory on the hunting motion of a wheelset was given by Klingel in1873.Further progress in the theory of high-speed railways was made at the Institute of Technology of the former Japanese National Railways around the time of the commencement of the Tokaido Shinkansen in Japan.In those days,however,the wheel/rail tangential force model was based on the‘contact theory’of Hertz,and revised on the basis experiments done on a one-ﬁfth-scaled vehicle model.The most accurate theory at present is that of Professor Kalker of Delft University[1];it considers the spin at the wheel/rail contact surface.The technique used for calculating the wheel/rail tangential forces given in the theory is the time-domain simulation nonlinear analysis,which is marketed widely as some software packages.A dynamic oscillation analysis of high-speed railway vehicles using either these software packages or Kalker’s theory leads to several problems in the data input process.These problems are how to treat the coefﬁcient of frictionμ,which is the adhesion limit,and whether the traction force to balance the running resistance during high-speed running and the spin lateral force of Kalker’s theory should be eliminated or not.With regard to these problems,several documents refer to the inﬂuence of the traction force of the locomotive[2],and that of the vehicle on a sharp curve[3],but none treats the inﬂuence of the traction force in the case of high-speed railway vehicles.In analysing the lateral oscillation of high-speed railway vehicles,it is important to consider carefully the interaction between the tangential forces of wheel and rail.Traction force has been considered only when analysing the power and brake performance,which is important when regarding acceleration and deceleration.It has not been considered in the analysis of lateral oscillation.In addition,the inﬂuence of the spin lateral force on vehicle dynamic analyses was easily treated by the modelling devised by Shen et al.[4].2.1.Adhesion limit and running resistance by airThere is insufﬁcient understanding of the adhesion limit at high speeds of over300km/h.In other words,the coefﬁcient of friction at the saturation limit of the wheel/rail tangential force under dry climate conditions must be determined.In contrast,with regard to brake and power performance,it is important to determine the adhesion limit under wet climate conditions[5]. In the case of the Shinkansen,an empirical formula for the adhesion limit in the case of running under rainy conditions has been used from early times.It is said that the adhesion limit that is obtained under dry conditions is doubled under wet conditions.In the present study, therefore,for the maximum value of the saturation characteristic of the wheel/rail tangential force to be used in the calculation of dynamic analysis depends on the following equation:μ=13.61.44v+85.(1)In the case of high-speed railway vehicles,like Shinkansen,running at almost constant speed,a traction force is necessary to counter running resistance,which mainly results from the air,and it increases in proportion to the square of the running speed.It is understood that the traction force is burdened by the wheel/rail tangential force acting in the longitudinal direction. The running resistance can be measured from an actual train.Accordingly,we measured the deceleration of the high-speed train in the state that did not act the traction force,corrected by the incline of the track in the measurement section,and statistically processed the measured deceleration to obtain the following expression for running resistance:F Re=α0+α1v+α2v2.(2)Vehicle System Dynamics739Figure1.Running resistance of a high-speed train.Required traction force per powered wheel is shown in Figure1.Thisﬁgure shows that traction force increases almost in proportion to the square of running speed.In addition,when the train is running in a tunnel,air resistance increases about50%compared with running in the open section.2.2.New wheel/rail tangential force modelThe wheel/rail tangential forces are expressed as follows in the article[1]:(F x,F y)=Fω·(ξ,η),FμN=1−(1−ω)3,ω≤1.(3)The longitudinal creepageξ,lateral creepageη,and their resultantωare expressed in the following equation:ξ=f11{˙ψw j/v+y w jλe/br0}3μN,η=f22{˙y w j(1+r0σ/b)/v−ψw j}3μN,ω=|ξ,μ|.(4)In the case of the power-distributed type train,like Shinkansen,running at high speed, traction force,which counters running resistance,is approximately equal to the spin lateral force,when a train has the1/16arc wheel tread with the1/40contact angle in the neutral position.Therefore,it is necessary to consider the inﬂuence of both traction and spin lateral force,which act continuously,when the train runs at constant high speed.To consider the inﬂuence on the wheel/rail tangential forces at the same time,the origin of the coordinates of Equation(3)is moved to the position where these forces act quasi-statically on the wheel tread,and the dynamic longitudinal and lateral creepage are not considered.Then,a new model of the wheel/rail tangential force is devised and expressed as follows:F μN =1−{1−(ω+ωtrs)}3−f trs,(5)f trs=|(F Re/n dw,f23¯εCRFδ0/r0)|μN,ωtrs=1−(1−f trs)1/3,¯εCRF=f trsωtrs/3.(6)740K.Sasaki and Y.SudaFigure 2.Saturation characteristics of the wheel–rail tangential forces.In this equation,f trs expresses the resultant of traction force and the spin lateral force,and ωtrs represents the vector of creepage by traction and spin.In addition,¯εCRF expresses the quasi-static non-dimensional creep coefﬁcient,that is,the ratio between quasi-static wheel /rail tangential force and creepage,in the case that only traction force and spin lateral force are assumed to act and that the dynamic longitudinal creepage and lateral creepage are assumed to be zero.The linear analysis in the vehicle dynamic oscillation is intended to perform prospectively,so the new tangential force model is similarly linearised.The describing function of Equation(5)can be expressed as follows:εCRF =(1−ωtrs )2− 83π ·(1−ωtrs )ω+14·ω2− 43π ·[f trs −{1−(1−ωtrs )3}]ω(7)In this equation,εCRF expresses the dynamic non-dimensional creep coefﬁcient,when longitudinal creepage and lateral creepage act effectively.When the high-speed train runs on a straight track,the resultant spin lateral force on the left and right wheels are almost eliminated,because the direction of these forces in the wheelset are opposite.In addition,the resultant yawing moment of the traction forces in a wheelset can also be ignored,because those forces are assumed to be almost the same and in the same longitudinal direction.Nevertheless,the non-dimensional creep coefﬁcient should be reduced,because the position of the origin in the saturation characteristic moves under the inﬂuence of traction and spin lateral force.Those relations are shown in Figure 2a–c.The curve that goes through the origin,where resultant creepage ωis zero,is the conventional theoretical curve.The new model of the saturation characteristic of the wheel /rail tangential force has the origin with coordinates moved in the y direction.The non-dimensional creep coefﬁcients εCRF ,in Figure 2,are results calculated when the dynamic resultant creepage ωis 0.3.Each dashed straight line is described as the incline at the origin,derived from the describing function,Equation (7).The quasi-static f trs is 0.4,calculated from the traction force and the spin lateral force during high-speed running at 320km /h,so the non-dimensional creep coefﬁcient εCRF becomes about 0.52,which should be used in the calculation of the linear dynamic oscillation analysis,see Figure 2a.Figure 2b shows the saturation characteristics of the wheel /rail tangential forces in the case without traction force but with spin lateral force on a vehicle without powered axles.In this case,non-dimensional creep coefﬁcient εCRF becomes about 0.59.In addition,Figure 2cVehicle System Dynamics741 describes the same characteristic in the case of a train running in a tunnel with traction force and spin lateral force.In this case,εCRF falls to0.44because of the increased traction force in a tunnel.It is thought that the inﬂuence of the traction force and the spin lateral force on the saturation characteristics of the wheel/rail tangential force should not be eliminated when aerodynamic resistance increases,as when a train is running in a tunnel,even in the case of power-distributed trains such as Shinkansen.3.Evaluation of a new model for wheel/rail tangential forceThe new wheel/rail tangential force model was validated with data on the lateral acceleration spectrum of the train,which were derived from the320km/h high-speed test runs of the Shinkansen.The model of the wheel/rail force described in the previous chapter is incorporated in the linear vehicle dynamic calculation.After that,the difference between the power spectrum density of the calculated and measured lateral accelerations is evaluated.3.1.Linearised vehicle dynamic oscillation modelThe model used for the calculation of linear vehicle dynamics is shown in Figure3.The model has17degrees of freedom,including an additional eight degrees of freedom, expressing the air suspension,the anti-yawing damper and the tilting of the rail.The air suspen-sion is the viscous-elasticity linear model,including the linearﬂuid resistance characteristic by the oriﬁce.The anti-yawing damper has aﬁrst-order delay characteristic for bogie resis-tance.For input to the Equation(8),the alignment and cross-level irregularity of the track are included,and the phase differences by the running speed to four pairs of wheelsets are considered.The equation for calculation of linear vehicle dynamics is expressed as follows: M¨x+C11(˙x−˙x0)+C12˙z+K11(x−x0)+K12z=0,(8)C21˙x+C22˙z+K21x+K22(z−z0)=0.Figure3.Model for calculation of the linear vehicle dynamics.742K.Sasaki and Y.SudaIn addition,the dynamic character matrix is d d t ¯X =A ¯X ,A =⎡⎣0I −M −1K 11+M −1C 12C −122K 21−M −1C 11+M −1C 12C −122C 21−C −122K 21−C −122C 210−M −1K 12+M −1C 12C −122K 22−C −122K 22⎤⎦.(9)For forced output,the equation is changed tod ¯X d t =A ¯X +B ¯X 0,B =⎡⎣000M −1K 11M −1C 11−M −1C −122C 12K 2200C −122K 22⎤⎦.(10)Moreover,the frequency responses are¯X =(jωI −A )−1B ¯X 0.(11)Furthermore,the lateral body acceleration of the vehicle at the ﬂoor on the front and rear bogies,and center are calculated as y b1,y b2,and y bc for the evaluation.The kinetic energy,the damping function,and the potential energy that enter into the above calculation are given as2Te =2m b (˙y 2b +i 2b φ˙ψ2b +i 2b ψ˙φ2b )+m t 2i =1(˙y 2t i +i 2t ψ˙ψ2t i +i 2t ψ˙φ2t )+m w 4 j =1(˙y 2w j +i 2w ψ˙ψ2w j )(12)2De =2i =1[2c 1b 21{2˙φt i −(˙φr (2i −1)+˙φr (2r ))}2+2c 2b 22(˙φs i −˙φt i )2+2c y b 23(˙ψb −˙ψs i )2+2c d {˙y b ±L ˙ψb +(h b −h d )˙φb −(˙y t i −(h d −h t )˙φt i )}2](13)2Ve =2i =1[2k 1b 21{2φt i −(φr (2i −1)+φr (2r ))}2+2k 2b 22(φb −φs i )2+2Nk 2b 22(φs i −φt i )2+2k w x b 21{(ψw (2i −1)−ψt i )2+(ψw (2i)−ψt i )2}+2k y b 23(ψt i −ψs i )2+2k wy {(y t i +aψt i +(h t −h p )φt i −y w (2i −1))2+(y t i −aψt i +(h t −h p )φt i −y w (2i))2}+2k b {y b ±Lψb +(h b −h s )φb −y t i +(h s −h t )φt i }2+k lc {(y b ±Lψb +(h b −h l )φb −y t i +(h l −h t )φt i )/2l c −ψt i }2+k lc {(y b ±Lψb +(h b −h l )φb −y t i +(h l −h t )φt i )/2l c −ψb }2]+2k rc 4j =1(y c j −y r j )2.(14)Vehicle System Dynamics 743The external forces produced by the wheel/rail tangential force characteristics areqe j =⎡⎢⎢⎢⎣−2f 22εCRF {˙y wj (1+r 0σ/b)−˙y c j }v −ψw j −ψwj −2P 0ε(y wj −y c j )b −2f 11εCRF b 2 ˙ψwj v +λe(y wj −y cj )br 0 ⎤⎥⎥⎥⎦.(15)In these equations,the equivalent conicity of the wheel tread,the contact angle,and the rolling index of the wheel are given as follows:λe =δ01−r R /r W ,ε=b r W −r R ,σ=δ01−r 0δ0/b .(16)Substituting these expressions into the Lagrange equation,we get the dynamic characteristic equations.In addition,there are iteration processes of the undecided constants of the quasi-static ¯εCRF in Equation (6)and εCRF in Equation (7).3.2.Evaluation with measured oscillation in vehicle test runsThe alignment irregularity and the cross-level irregularity of the track are used for the dynamic calculation of the input at the same time.The space–spectrum density functions of track irregularity are arranged to the approximate functions and are converted to the input for the oscillation in frequency dependence by the running velocity.The coherent function between the alignment irregularity and the cross-level irregularity shows that there are few correlations between them,so their vehicle responses are assumed to be added as follows:P sd (ω)yb 1,2,C =|R 2yb 1,2,C (ω)AI ·P sd (ω)AI |+|R 2yb 1,2,C (ω)SU ·P sd (ω)SU |,(17)P sd (ω)AI =a AI v ·(ω/2πv),P sd (ω)SU =a SU v ·(ω/2πv).(18)The calculated power spectrum density of body lateral acceleration,by the new model,which considers the traction force and the spin lateral force,is shown in Figure 4a,and the measured power spectrum density is shown in Figure 4b.Furthermore,the result of the calculation only taking account of track irregularities,which considers neither the traction nor the spin lateral force,is shown in Figure4c.Figure parison of calculated and measured PSD:(a)calculated with traction force and spin;(b)measured V =320[km /h];and (c)calculated without traction force and spin.744K.Sasaki and Y.SudaThe difference in the calculated results of theseﬁgures is recognised conspicuously at the peak of the oscillation at low frequency.Although there is actually a peak at1.5Hz(Figure4b), the calculation result has a peak near2Hz,which is provided by the conventional calculation method(Figure4c).The new method of calculation,which considers the traction force and the spin lateral force,results in slight errors in the size of the peak;however,the peak frequency can be determined by the prominent oscillation.It is also recognised that an error in the calculation depends on the situation of the modelling in the wheel/rail tangential force,even when track irregularities are comparatively few,as in the case of Shinkansen.In the case of the high-speed railway,the wheel/rail tangential force are decreased by the traction and spin lateral force,and the motion of the wheelset comes in a longer wavelength and a lower period;therefore,an error spreads in the oscillation of the low frequency in particular.This could result in poor vehicle suspension design.It is thought that the precision of the lateral oscillation analysis can be improved by the method proposed in this article. Furthermore,it is thought that this model is superior for the tunnel of Shinkansen or in the case of power-concentrated vehicles.4.Design of vehicle suspensionThe bogie suspension of a railway vehicle has been designed until now by assuming that the critical speed of the bogie hunting motion will be increased,even though this method suffers uncertainty in the calculation of the wheel/rail tangential forces.The characteristics of these forces will change according to the speed of the train and amplitudes of the track irregularities, so that it would be more difﬁcult to predict the vehicle behaviour at the critical speed in a very high-speed region.On the other hand,as for the vehicle dynamic analysis by the new model for the wheel/rail tangential forces suggested in this study,it is more important to precisely understand the traction force and the adhesion characteristics.Actually,the traction force can be measured, and the assumption of the adhesion limit under wet conditions could be possible,but it would not be easy to predict the adhesion limit in dry conditions.However,in the case of the high-speed railway,such as Shinkansen,the train is running on a straight track in almost all of the time at the maximum commercial speed,and the traction force is continuously competing against air resistance.In addition,careful maintenance keeps irregularities in the track condition to a minimum.So,the precision in the vehicle suspension design will be expected to improve stability and ride comfort at commercial speed,by an improved vehicle dynamic analysis.In the following,the results of such analysis performed in a case study of the design from such high-speed point of view are presented.4.1.Design parametersThe characteristic equation of oscillation,Equation(9),consists of the primary suspension between the wheelset and the bogie frame,the secondary suspension between the bogie frame and the vehicle body,each mass or inertia,and the characteristic of the wheel/rail tangential force.Each suspension consists of the spring constant and the damping coefﬁcient in the vertical(in rolling direction),lateral,and longitudinal(in yawing direction)directions. Substituting for direct sensitivity analysis in real suspension,the following design param-eters are introduced in this article to search for the optimal damping by performing the appropriate placement of the natural frequency.The spring constants of suspensions areVehicle System Dynamics745 rearranged to the uniﬁed spring constant and the spring constant ratio for each direction.The uniﬁed spring constants are derived from the series spring constant in the case the mass between primary and secondary suspension is thought to be eliminated.The damping coefﬁcients are rearranged to the uniﬁed damping coefﬁcients and the damping coefﬁcient ratio in a similar manner.Furthermore,given the inertia of the vehicle body in the rolling or yawing direction, both the uniﬁed natural frequency and the uniﬁed damping ratio are introduced as follows:κp=2k1k3,ν2f=k¯u fm b i2bφin k¯u f=2(1/2k1+1/k3)c p=2c1c3,ζ2f=c2¯u f(m b i2bφk¯u f)/4in c¯u f=2(1/2c1+1/c3)κx=2k wx b21k y b23,ν2x=k¯u xm b i2bψin k¯u x=2(1/2k wx b21+1/k y b23)(19)κy=2k wy a2k b L2,ν2y=k¯u ym b i2bψin k¯u y=2(1/2k wy a2+1/k b L2),ζ2y=c2dL2(m b ibψk¯u y),1νcy=c yk y,βt=m bm t,βw=m bm w.4.2.Damping ratio and natural frequencyFrom the characteristic equation,Equation(9),damping ratio and natural frequency of each oscillation mode are calculated with the eigenvalue of the characteristic matrix as follows:λ=eig A,δdpr=−real(λ),f frq=imag(λ)2π.(20)When the front and rear bogies have symmetric speciﬁcations,the solutions for damping ratio and natural frequency of the bogie frame and wheelset are derived for in-phase or anti-phase mode.This means that there are eight solutions for four pairs of wheelsets,and six solutions for the vehicle suspension system;consequently,the latter could be prescribed by six design parameters,three uniﬁed natural frequencies,and three spring constant ratios for the rolling,yawing,and lateral directions,in Equation(19).4.3.Methodology of suspension designIn this methodology for suspension design,values,such as mass,inertia,and dimensions, are already given.Theﬂow of the design process is described in Figure5.This methodology has the advantage that the low-frequency mode of the vehicle body and the high-frequency mode of the bogie can be handled and recognised individually in terms of the uniﬁed natu-ral frequency and spring constant ratio.This design methodology is based on the following assumptions regarding natural frequency and damping ratio for optimising running stability and ride comfort.(a)According to the optimisation process of vertical oscillation,an anti-rolling device shouldbe attached,when the natural frequency of body lower sway is too low[6].(b)The natural frequency of body yawing mode should be as close as possible to1.0Hz,aslong as the natural frequency of its lower sway mode is more than0.6Hz.(c)The damping ratio of the body yawing mode should be above0.3(Figure6).(d)The damping ratio of the bogie mode should be above0.1at least.746K.Sasaki and Y.SudaFigure5.Flow of suspension design process.The series order of the determination in the design parameters is thought not to fall into an inconvenient repetition loop in this methodology(Figure5).In one case study,the bogie share mode came near to the lower centre sway mode of the bogie frame in the higher speed area and the1/16arc proﬁle wheel tread was changed to1/32, which assumed only the contact angle in the neutral point to half value.The design parameters are listed in Table1.The result of the calculated power spectrum density of the body lateral acceleration is shown in Figure7a.In addition,the calculated results are shown in Figure8,in which the changes in the damping ratio and the natural frequency are described according to the train speed on the speciﬁcation before and after the optimisation.In theseﬁgures,εCRF is simplyﬁxed to a constant value.4.4.Evaluation of ride comfortThe frequency-weighting function in Japan for the evaluating ride comfort is based on the sensitivity curve given in ISO-2631.Established by the former Japan National Railway in 1982,the frequency-weighted function is multiplied by the accelerations of body oscillation at the evaluation points,their root mean square values are calculated,and the quality of rideVehicle System Dynamics747Figure6.Damping ratio and frequency in each mode byνx.Table1.Conventional and improved speciﬁcations of vehicle.Conventional speciﬁcations Improved speciﬁcations Unitλe1/161/32R r 1.0 1.0(m)R w0.60.6(m)δ01/401/80σ0.0250.013ε 1.88 1.88νf0.70.7×2π(rad/s)νy0.760.6×2π(rad/s)νx0.850.55×2π(rad/s)κy 1.10.5κx0.95 1.5ζy0.10.1νcy 1.00.8×2π(rad/s)βt 5.0 5.0βw8.28.2αdB Y b1−16.0(−13.9)−18.7(dB)αdB Y b2−12.4(−12.5)−15.6(dB)()measured over allcomfort is then evaluated by those values.In this article,the evaluations of ride comfort are described as follows:αdB=20log(αw),α2w=(wF2L P sd ybδf)(0dB=1m/s2).(21)The evaluated value about the actually measured(Figure4b),the calculated value (Figure4a),and the improved value(Figure7a)of the case study are shown in Table1. The distribution of the root mean square value with the weighted function in every1/1octave band,pursued from the power spectrum density of the lateral acceleration,are described in Figure7b for the evaluation point at theﬂoor of the rear bogie,for the difference between the measured,calculated,and improved values.In the results of the case study,the peak level of the oscillation of the low frequency decreases about4dB in the1and2Hz bands.However,according to the evaluation of the overall value748K.Sasaki and Y.SudaFigure7.Calculated PSD for the improved speciﬁcations.Figure8.Damping ratio and frequency characteristics.of the root mean square acceleration,weighted in frequency,the effect of reduction as a whole is not a serious value.In the conventional speciﬁcations,the bogie steer mode is in a condition to become over-damped,shown in Figure8a.However,in the improved vehicle speciﬁcations of the case study,the natural frequency of the bogie steer mode is higher than that of the body yawing mode at320km/h,shown in Figure8b.Both modes intersect when the train speed is near 240km/h.The resonance becomes sufﬁciently good for the vehicle to run at that speed.The hunting motion of the bogie is restrained not only by the damping equipment but also by the action of the body mass.The design of suspension is more precise by using this calculation model,so that the effect of the wheel/rail tangential force can be predicted more precisely in various situations.5.ConclusionsFor a high-speed railway vehicle,a new wheel/rail tangential force model was devised.This model is based on an analysis of linear lateral oscillation,in which the inﬂuences of tractionVehicle System Dynamics749 and spin lateral force are considered.Owing to these inﬂuences,the wavelength in the wheelset hunting motion gets longer and its frequency becomes lower.In particular,the low-frequency oscillation of the car body is generated because of the inﬂuence of this phenomenon.The calculation results are in good agreement with the measurements of car body lateral acceler-ations obtained in test runs of an in-service Shinkansen vehicle,particularly in the prominent frequency of the oscillation.With this model,a case study of the vehicle suspension design was undertaken.Design parameters for the calculation of the suspension characteristics were introduced.The method-ology that arranges the natural frequency of vehicle suspension was shown.By raising the natural frequency of the bogie steer mode to higher than that of body yawing mode at com-mercial speed,the bogie motions are controlled also by the mass of the body,not only by the damping equipment.These situations can be tested more precisely by using design calculations in which a new wheel/rail tangential force model is introduced.A study on vehicle behaviour at the time of travelling along a curve will be done in further research either by simulation or by using a real test vehicle.AcknowledgementsJR-East and the University of Tokyo are carrying out the joint research on vehicle dynamics by means of industry–university cooperation.This article is a part of the results of that research.References[1]J.J.Kalker,Three-Dimensional Elastic Bodies in Rolling Contact,Kluwer Academic Publishers,Dordrecht,1991/2002.[2]O.Polach,Creep forces in simulations of traction vehicles running on adhesion limit,Wear258(2005),pp.992–1000.[3]Y.Suda and J.Grencik,Inﬂuence of traction/braking force on steering ability of railway trucks,Trans.JSMEC62(1996),p.596.[4]Z.Y.Shen,J.K.Hedrick,and J.A.Elkins,A comparison of alternative creep force models for railway vehicledynamic analysis,Proceedings of the8th IA VSD,1983.[5]T.Ohyama,Study on inﬂuences of contact condition between wheel and rail on adhesion force and itsimprovement at high speeds,RTRI Rep.1(2)(1987),pp.1–77.[6]K.Sasaki andY.Suda,A study on improvement methods of vertical oscillation for railway vehicles,Proceedingsof J-Rail,(2005),pp.247–250.Nomenclaturev,V,r0speed[m/s],(capital[km/h]),wheel radius2a,2b,2L distance of wheelbase,wheel/rail contact points,bogie centrek1,c1stiffness and damping of primary suspensionk wx,k wy longitudinal and lateral stiffness of axle-box2b1,h p distance and height of primary suspensionk2,Nk2,c2,k3,c3stiffness and damping of air suspension in vertical directionk b,2b2,h s lateral stiffness,distance and height of air suspensionc d,hd damping constant and height of lateral damperk y,c y,2b3stiffness and damping constants of anti-yawing damperm w,m t,2m b mass of wheelset,bogie frame and bodyi wψ,i tψ,i bψinertia radius of wheelset,bogie frame and body in yawing directioni tφ,i bφinertia radius of bogie frame and body in rolling directionh t,h b centre of gravity height of bogie frame and bodyh f height ofﬂoor of the passenger cabink lc,l c,h l stiffness,length and height of traction rodλe,σ,εequivalent conicity,roll angle and contact angle differencef11,f22,f23longitudinal,lateral and spin lateral creep coefﬁcients by KalkerεCRF,¯εCRF dynamic and quasi-static non-dimensional creep coefﬁcientμ,N coefﬁcient of friction,nominal load on contact point of wheel/rail。

北京交通问题作文英语

Beijing,as the capital city of China,has been facing significant traffic issues over the years.The citys rapid development and increasing population have led to a surge in the number of vehicles on the roads,causing congestion and contributing to air pollution. Here are some key aspects of Beijings traffic problems and potential solutions:1.Population Growth and Vehicle Increase:With a population of over20million,Beijing has seen a dramatic increase in the number of vehicles,which has led to traffic jams, especially during peak hours.2.Public Transportation:Despite having an extensive public transportation system, including buses,subways,and taxis,the demand often exceeds the capacity,leading to overcrowding and delays.3.Traffic Management:The city has implemented various traffic management strategies, such as oddeven license plate regulations to limit the number of cars on the road on alternate days.However,these measures have had limited success in alleviating congestion.4.Road Infrastructure:The expansion of road infrastructure has not kept pace with the growth in vehicle numbers.This has resulted in bottlenecks at intersections and on major thoroughfares.5.Environmental Impact:Vehicle emissions are a significant contributor to air pollution in Beijing.The high levels of smog have raised health concerns among residents.6.Cycling and Walking:Encouraging cycling and walking as alternatives to driving can help reduce traffic congestion and improve air quality.The city has been promoting bikesharing programs and improving pedestrian facilities.7.Carpooling and Ridesharing:Promoting carpooling and ridesharing can reduce the number of vehicles on the road and help alleviate traffic congestion.8.Smart Transportation Systems:The use of technology,such as intelligent traffic management systems,can optimize traffic flow and reduce congestion.9.Urban Planning:Better urban planning,including the development of satellite cities and the improvement of public transportation in suburban areas,can help distribute the population and traffic more evenly.10.Public Awareness:Raising public awareness about the environmental and healthimpacts of excessive vehicle use can encourage more sustainable transportation choices. Addressing Beijings traffic problems requires a multifaceted approach that includes improving public transportation,investing in infrastructure,implementing effective traffic management strategies,and promoting sustainable transportation options.By taking these steps,Beijing can work towards a more efficient and environmentally friendly transportation system.。

rf ride new dictionary variable的用法 -回复

rf ride new dictionary variable的用法-回复一、什么是rf ride？RF Ride是RealFX的简称，是一种全新的激光雷达智能驾驶技术。

它可以对道路、障碍物和车辆进行高精度的三维扫描，以实现自动驾驶。

借助RF Ride，车辆可以在不受驾驶员控制的情况下进行行驶，并根据路况、交通信号和其他车辆的位置作出决策。

二、RF Ride如何实现自动驾驶？RF Ride利用激光雷达技术实现自动驾驶。

激光雷达通过向四周发射激光束并记录返回的反射信号，来获取环境的三维信息。

由于激光具有高方向性和高精度的特点，因此可以有效地检测路面、障碍物和车辆等，为车辆的智能决策提供重要的数据支持。

RF Ride通过新建一个字典变量来存储激光雷达扫描得到的三维数据。

这个字典变量包含了车辆位置、周围障碍物、交通信号和其他车辆的位置等信息。

通过不断更新这个字典变量的数值，车辆可以实时地了解到当前路况和所面临的风险，并相应地调整驾驶策略。

三、RF Ride的字典变量有哪些主要键值对？RF Ride的字典变量主要包含以下几个键值对：1. "vehicle_position"：表示车辆当前的位置。

通过全球定位系统（GPS）或惯性测量单元（IMU）等传感器获取。

2. "obstacles"：表示周围的障碍物。

包括其他车辆、行人、建筑物等。

激光雷达扫描得到的三维点云数据可以提供障碍物的位置、形状和大小等信息。

3. "traffic_signal"：表示交通信号。

通过视觉传感器或与交通管理系统的通信获取当前道路上的交通信号灯状态。

4. "nearby_vehicles"：表示附近其他车辆的位置和状态。

通过车载通信系统获取附近车辆的实时位置和速度等信息。

5. "road_conditions"：表示当前路况。

包括道路的曲率、交通流量、路面状况等。

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1 State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China 2 Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications, Beijing 100044, China 3 Future Mobile Communication Research Division, Electronics and Telecommunications Research Institute, Daejeon 34129, South Korea 4 School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, South Korea * The corresponding author, email: boai@
MILLIMETER AND THZ WAVE FOR 5G AND BEYOND
Vehicle-to-Infrastructure Channel Characterization in Urban Environment at 28 GHz
Longhe Wang1,2, Bo Ai1,2,*, Danping He1,2, Ke Guan1,2, Jiayi Zhang1,2, I. INTRODUCTION
Intelligent Transportation Systems (ITS) are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds. ITS play a critical role in the modern society and the field involves a wide range of technologies and applications such as automatic road enforcement, dynamic traffic light sequence, and autonomous vehicles [1]. Therefore, many researchers are focusing on this area, and ITS is also the best way to solve traffic congestion, improve travel safety, and enhance operating efficiency and so on [2].
Received: Oct. 5, 2018 Revised: Nov. 29, 2018 Editor: Yongming Huang
36
Abstract: Both ultra-reliable low latency and high-data-rate communications are required by connective vehicles. Millimeter wave (mmWave) with large bandwidth is a key technology to support high-data-rate communications. In this paper, the 28 GHz wideband vehicle-to-infrastructure channel is characterized for the urban environment in a major street in Manhattan. The deployment of the transmitter and the receiver, as well as the traffic models, are selected by considering the recommendation by 3GPP TR 37.885. Ray tracing simulator with calibrated electromagnetic parameters is employed in this work to practically conduct intensive simulations. The 3D environment model is reconstructed from OpenStreetMap. The power delay profile, path loss, root-meansquare delay spread, K-factor and so on, are extracted from the calibrated simulation results. The evolution of the parameters, as well as their statistical properties, are analyzed and modeled. The work of this paper helps the researchers understand the propagation channel for designing mmWave technologies and communication system in a similar scenario. Keywords: channel characterization; mmWave channel; ray tracing; urban environment; vehicular communication