NGSIM使用手册（1）
美国NGSIM系统的使用手册，方便读者高效的利用NGSIM进行数据下载，完成交通领域的研究Technical Report Documentation Page1. Report No2. Government Accession no3. Recipients Catalog NoFHWA-HOP-06-0124. Title and subtitle5. Report DateNext Generation Simulation(NGSIM) Data Format Planly20046. Performing Organization Code7. Author(s8. Performing Organization report noVijay Kovvali, richard margiotta, Robert franc, vassiliAlexiadis9. Performing Organization Name and Address10. Work Unit NoCAMBRIDGE SYSTEMATIC INC150 CAMBRIDGE PARK DRIVE SUITE 400011. Contract or grant noCAMBRIDGE MA 02140DTFH61-02-C-0003612. Sponsoring Agency Name and Address13. Type of Report and Period CoveredDepartment of transportationFinal reportFederal Highway AdministrationJuly 2003-july 2004Office of Acquisition Management14. Sponsoring Agency Code400 Seventh Street SW, RM 4410Washington, DC 2059015. Supplementary notesFHWA COTR: John Halkias, Office of Operations, and James Colyar, Office of Operations r&d16. AbstractThe Next Generation Simulation Program(NGSIM) Data Format Plan was developed to define thestructure, documentation, and transfer requirements for data that will be collected for estimationcalibration, and validation of core behavioral algorithms. The development of the data Format Plan isbased on existing formats that are relevant to ngsim and augmented to fill in gaps. to this end, a reviewof existing data formats was undertaken and their relevance to NGSiM was assessed. The review includeddata standards developed for intelligent transportation systems(ITS), data formats developed specificallyfor traffic simulation models, and data formats developed for broader transportation applications. Thespecified data formats were developed with the objective of promoting efficient research by maintainingonsistency between data collection and research, and providing consistent storage and transmittalprotocols. On the other hand, this plan intentionally avoids over specification of data formats, so as tominimize unnecessary limitations to research. This document specifies the conceptual data model by meansof Unified Modeling Language UMl class diagrams; the data dictionary in the data standard prescribed bP1489-1999 format developed by the Institute of Electrical and Electronics Engineers(IEEE); the dataexchange structure for data transfer from user to user or from the database/repository to users; and theNGSIM metadata17. Key words1 8. Distribution StatementNext generation simulation, NGSIM, trafficNo restrictions. This document is available to thesimulation, high-level plan, traffic data collection, public through the National Technical Informationvehicle trajectory dataService, Springfield, VA2216119. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No of Pages22. PriceUnclassifiedUnclassifiedForm dot e1700.7(8-72)Reproduction of completed pages authorizedTABLE OF CONTENTSEXECUTIVE SUMMARY1.0 INTRODUCTION1.1High- Level plan context……垂垂垂垂·着垂垂垂垂非垂·非垂垂看垂音非非;·垂垂音看垂看垂1.2 Background1.3 Data Collection Types……1344581. 4 Data Conversion1.5 Data Formats·····.···············.··.···.·;···..·.··..·.···2.0 NGSIM DATA REQUIREMENTS22 Microsimulation Software Data format,…………172.1 NGSIM Data…192.3 Rcquirements for NgsiM data Collection..................193.0 RECOMMENDED NGSIM DATA FORMATS..m. 233.1 NGSIM Data model233.2 NGSIM Data Dictionary……………243.3 NGSIM Metadata.............................253.4 NGSIM Data Exchange Format273.5 File and Directory Naming Convention……293.6 Summary30REFERENCES31APPENDIX A-REVIEW OF EXISTING TRANSPORTATION DATA FORMATS3APPENDIX B-ACCURACY REQUIREMENTS FOR NGSIM DATACOLLECTION,45APPENDIX C-DATA MODEL∴….,,53APPENdIXD-DATA DICTIONARY.APPENDIX E-METADATA. ...........................................................................................99APPENdIX F-SYSTEM-STATE DATA看香音看音香n117List of FiguresFigure 1 Diagram. NGSIM task interdependencies4Figure2. Diagran. Data format classification relevant to ngsim1………Figure 3. Diagram. Top level data model of general traffic simulation55Figure4. Diagram. Influencing factors database packages………………56Figure 5. Diagram. Behavioral models packages57Figure6. Diagran. Facility type generalization…………18Figure 7. Diagram. Traffic management systems generalization......59Figure 8. Diagram. Transit management systems generalizationFigure9. Diagran. nvironment generalization.………………………0Figure 10. Diagram NTCIP Controller class diagram61Figure 11 Diagram Actuated traffic signal controller generalization2Figure12 Diagram. Generalized microsimulation data model………………63Figure 13 Diagram Data concept components and constructs(IEEE Std 1489-1999)66List of tablesTable 1. Example validation data by algorithm categoryTable 2. Summary of NGSiM categorizations for data formatsTable 3. Accuracy requirements for vehicle trajectory data. ..45Table 4. Accuracy requirements for instrumented vehicle data.........46Table 5. Accuracy requirements for wide-area detector data......... 47Table 6. Accuracy requirements for nctwork-rclated data48Table 7. Accuracy requirements for representative transportation managementsystems data52Table 8. Terminology for UMLmodeler54Table 9. Data dictionary for NgSim.67Table 10 processing documentation metadata for ngsimwwwwwm116Table1l. Requisite vehicle trajectory data…………………………117Table 12. requisite wide-area detector data requirements……118EXECUTIVE SUMMARYThe Next Generation Simulation Program(NGsim) Data Format plan was developed todefine the structure, documentation, and transfer requirements for data that will be col-lected for estimation, calibration, and validation of core behavioral algorithms. Thedevelopment of the data format plan is based on existing formats that are relevant toNGSIM and augmented to fill in gaps. To this end, a review of existing data formats wasundertaken and their relevance to ngsim was assessed. The review included data standards developed for intelligent transportation systems (ITS), data formats developed spe-cifically for traffic simulation models and data formats developed for broader transporta-tion applications. The specified data formats were developed with the objective of pro-moting efficient research by maintaining consistency between data collection andresearch, and providing consistent storage and transmittal protocols. On the other handthis plan intentionally avoids overspecification of data formats, so as to minimize unnecessary limitations to researchFour data format components were specified in this document, including: 1)data model,2)data dictionary, 3 )metadata, and 4) data exchange formatNGSIM Data Model- The conceptual data model for NGSIM data formats is pre-sented by means of Unified Modeling Language() class diagrams. Used in con-junction with the data dictionary, the data model allows for construction of a formaldatabase/repository for NGSIM validation dataNGSIM Data Dictionary This provides definition of individual data elementsrequired by NGsim. It follows the data standard prescribed by P1489-1999 formatdeveloped by the Institutc of Elcctrical and Electronics Engineers(ieee)NGSIM Data Exchange Format- The data cxchange structure dcfincs how datashould be transferred from user to user or from the database /repository to users. Thisdocument specifies the framework for developing data exchange formats by providingthe data model and the data dictionary; it also provides clear guidance on the formatstandards with which the data exchange format should conform Currently it doesnot provide specific schema for the data exchange formatsNGSIM Metadata- This includes both traditional metadata(definitions, specificationsand valid value lists for data elements and general information about the dataset andits availability); and processing metadata(what has happened to the data from data col-lection to data archival). Administrative metadata formats were adapted fromContent Standard for Digital Geospatial Metadata(FGDC-STD-001-1998), developedby the Federal Geographic Data Committee(FGDC). Recommendations for NGSiMprocessing metadata are based on the guidance provided in ASTM E2259-03, devel-oped by the American Society for Testing and Materials(ASTm)1.0 INTRODUCTIONThe objectives of the NGsim program include the followingDevelopment of a core set of open behavioral algorithms in support of traffic simulation with a primary focus on microscopic modelingCollection of extensive data that will be used for estimation calibration and validationof the core behavioral algorithms; and storing the data in a repository that can be uni-versally accessedThe High-Level Plan for DatasetsTask E3)identified different kinds of traffic data col-lection methods and technologies and recommended three kinds of data collection effortsfor ngsim, including vehicle trajectory data wide area detector data and instrumentedvehicle dataThis report Task F)presents the documentation, format structure, and transfer requirements for the ngsim data formats for these data collection efforts identified in task e3This report is organized as followsExecutive Summary -Provides an executive summary of this documentSection1.0-Provides an overview and introduction to this report, including the con-text of the data format plan within NGsIM, information on NGsim data collection anddata types, information on data conversion, general information on data formats, anda summary of available transportation data formats and their relevance for ngsimSection 2.0-Presents definitions and categorization for different data types, and pro-vides ngsim data requirementsSection 3.0-Presents data format recommendations for the NGsim program,including a data model, data elements for the data dictionary, metadata to describe thedata collection effort and data exchange formatsReferences-Presents references used in developing this data format planAppendix a-Presents a review of existing transportation data formatsAppendix B-Presents accuracy requirements for NGSiM data collectionAppendix C- Presents a UML representation of the ngsim data modelAppendix D-Presents a high-level NGSIM data dictionaryAppendix E- Presents metadata categories, dictionary, and recommended metadataformats for ngsim1.1 HIGH-LEVEL PLAN CONTEXTInterdependencies among NGSIM tasks are shown in figure 1. The High-Level Plan forDatasets(Task E. 3) presents an assessment of existing datasets of potential use for NGSIM,and makes recommendations on the focus for nGsim data collection methodologies. Thisreport on the data Format Plan task f) provides recommendations on the data exchangeformat(s) for NGSIM data collection efforts. The data formats are also influenced by theHigh-Level Verification and Validation Plan(task e 2)Task E 1-1Core algorithmAssessmentTask e,3Task e.1-2Task e2High-LevelCore AlgorithmHigh-Level Verificationlan for DatasetsPlanandⅤ alidation planTask eData format planFigure 1 Diagram. NGSIM task interdependencies.1.2 BACKGROUNDThe NGSiM field data collection effort pursues data required for developing, estimating,calibrating and validating traffic behavioral algorithms. Tactical route execution, opera-tional driving, and en-route strategic traveler behaviors were identified as the focus of theNGSIM core behavioral algorithm research in the identification and prioritization of coreAlgorithms Task D)report. The High-Level Verification and Validation Plan(task e2)provides an example of the data collection datasets for each algorithm category as shownin table 1. the table illustrates the extent over which data must be collected for each levelof algorithm. For example, for operational driving algorithms, a single stretch of roadwayon a freeway will likely be sufficient, while, for development of tactical driving algo-rithms, the data collection effort should be expanded to include the freeway section andmultiple entry and exit ramps that feed the freeway. The data formats developed in thisplan address the data, both static and dynamic, that are pertinent to the data collectionefforts necessary for developing and validating all three categories of driver behavioralalgorithms4
- 2020-12-05下载
- 积分：1
系统辨识大牛Ljung编写的MATLAB系统辨识使用手册
系统辨识大牛Ljung编写的MATLAB系统辨识使用手册，这本书详细地介绍了在MATLAB已经所属simulink环境下，系统辨识工具箱的一些使用办法，是一本非常经典的教材！Revision Historypril 1988First printingJuly 1991Second printingMay1995Third printingNovember 2000 Fourth printingRevised for Version 5.0(Release 12)pril 2001Fifth printingJuly 2002Online onlyRevised for Version 5.0.2 Release 13)June 2004Sixth printingRevised for Version 6.0.1(Release 14)March 2005Online onlyRevised for Version 6.1.1Release 14SP2)September 2005 Seventh printingRevised for Version 6.1.2(Release 14SP3)March 2006Online onlyRevised for Version 6.1.3(Release 2006a)September 2006 Online onlyRevised for Version 6.2 Release 2006b)March 2007Online onlyRevised for Version 7.0 ( Release 2007a)September 2007 Online onlyRevised for Version 7.1 (Release 2007bMarch 2008Online onlyRevised for Version 7.2(Release 2008a)October 2008Online onlyRevised for Version 7.2.1 Release 2008b)March 2009Online onlyRevised for Version 7.3(Release 2009a)September 2009 Online onlyRevised for Version 7.3.1(Release 2009b)March 2010Online onlyRevised for Version 7. 4 (Release 2010a)eptember2010 Online onlyRevised for Version 7.4.1(Release 2010b)pril 2011Online onlRevised for Version 7.4.2(Release 2011a)September 2011 Online onlyRevised for Version 7.4.3(Release 2011b)March 2012Online onlyRevised for Version 8.0( Release 2012aabout the DevelopersAbout the Developersystem Identification Toolbox software is developed in association with thefollowing leading researchers in the system identification fieldLennart Ljung. Professor Lennart Ljung is with the department ofElectrical Engineering at Linkoping University in Sweden. He is a recognizedleader in system identification and has published numerous papers and booksin this areaQinghua Zhang. Dr. Qinghua Zhang is a researcher at Institut Nationalde recherche en Informatique et en Automatique(INria) and at Institut deRecherche en Informatique et systemes Aleatoires (Irisa), both in rennesFrance. He conducts research in the areas of nonlinear system identificationfault diagnosis, and signal processing with applications in the fields of energyautomotive, and biomedical systemsPeter Lindskog. Dr. Peter Lindskog is employed by nira dynamiAB, Sweden. He conducts research in the areas of system identificationsignal processing, and automatic control with a focus on vehicle industryapplicationsAnatoli Juditsky. Professor Anatoli Juditsky is with the laboratoire JeanKuntzmann at the Universite Joseph Fourier, Grenoble, france. He conductsresearch in the areas of nonparametric statistics, system identification, andstochastic optimizationAbout the developersContentsChoosing Your System Identification ApproachLinear model structures1-2What Are Model objects?Model objects represent linear systemsAbout model data1-5Types of Model objectsDynamic System Models1-9Numeric Models1-11umeric Linear Time Invariant (LTD Models1-11Identified LTI modelsIdentified Nonlinear models1-12Nonlinear model structures1-13Recommended Model Estimation Sequence1-14Supported Models for Time- and Frequency-DomainData,,,,,,,1-16Supported Models for Time-Domain Data1-16Supported Models for Frequency-Domain Data1-17See also1-18Supported Continuous-and Discrete-Time Models1-19Model estimation commands1-21Creating Model Structures at the command Line ... 1-22about system Identification Toolbox Model Objects ... 1-22When to Construct a Model Structure Independently ofEstimation1-23Commands for Constructing Model Structures1-24Model Properties1-25See als1-27Modeling Multiple-Output Systems ......... 1-28About Modeling multiple-Output Systems1-28Modeling Multiple Outputs Directly1-29Modeling multiple outputs as a Combination ofSingle-Output Models.......1-29Improving Multiple-Output Estimation Results byWeighing Outputs During Estimation ....... 1-30Identified linear Time-Invariant models1-32IDLTI Models1-32Configuration of the Structure of Measured and Noise oRepresentation of the Measured and noise Components foVarious model Types1-33Components ....1-35Imposing Constraints on the Values of ModeParameters1-37Estimation of Linear models1-8Data Import and Processing2「Supported Data ...2-3Ways to Obtain Identification DataWays to Prepare Data for System Identification ... 2-6Requirements on Data SamplingRepresenting Data in MATLAB Workspace·····Time-Domain Data Representation2-9Time-Series Data Representation2-10ContentsFrequency-Domain Data Representation ....... 2-11Importing Data into the Gui2-17Types of Data You Can import into the GUi2-17Importing time-Domain Data into the GUI2-18Importing Frequency-Domain Data into the GUI2-22Importing Data Objects into the GUI ......... 2-30Specifying the data sampling interval2-34Specifying estimation and validation Data2-35Preping data Using Quick StartCreating Data Sets from a Subset of Signal Channelo2-362-37Creating multiexperiment Data Sets in the gUi2-39Managing data in the gui ............. 2-46Representing Time- and Frequency-Domain Data Usingiddata object2-55iddata constructor2-55iddata Properties.........2-58Creating Multiexperiment Data at the Command Line .. 2-61Select Data Channels, I/O Data and Experiments in iddataObjects2-63Increasing Number of Channels or Data Points of iddataObjects2-67Managing iddata Objects2-69Representing Frequency-Response Data Using idfrdObiec2-76idfrd Constructor2-76idfrd Properties2-77Select I/o Channels and Data in idfrd Objects ..... 2-79Adding Input or Output Channels in idfrd Objects2-80Managing idfrd Objects2-83Operations That Create idfrd Objects2-83Analyzing Data quality2-85Is your data ready for modeling?2-85Plotting Data in the guI Versus at the command line2-86How to plot data in the gui2-86How to plot data at the command line2-92How to Analyze Data Using the advice Command2-94Selecting Subsets of Data2-96IXWhy Select Subsets of Data?2-96Extract Subsets of Data Using the GUI2-97Extract Subsets of data at the Command Line2-99Handling Missing Data and outliers2-100Handling missing data2-100Handling outliers2-101Extract and Model Specific Data Segments2-102See also2-103Handling offsets and Trends in Data2-104When to detrend data2-104Alternatives for Detrending Data in GUi or at theCommand-Line2-105Next Steps After detrending2-107How to Detrend Data Using the Gui2-108How to detrend data at the Command line2-109Detrending Steady-State Dat109cending transient Dat2-109See also2-110Resampling Data2-111What Is resampling?...,,.,,,,,,,,,,,.2-111Resampling data without Aliasing Effects2-112See also2-116Resampling data Using the GUi.,,,,2-117Resampling Data at the Command line2-118Filtering Data2-120Supported Filters2-120Choosing to Prefilter Your Data2-120See also2-121How to Filter Data Using the gui2-122Filtering Time-Domain Data in the GuI........ 2-122Content
- 2020-12-11下载
- 积分：1
