1、Designation: E2759 10Standard Practice forHighway Traffic Monitoring Truth-in-Data1This standard is issued under the fixed designation E2759; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of last revision. A number in pa
2、rentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 Traffic monitoring truth-in-data is the disclosure of howdata are managed from field data collection through evaluation,acceptance, summarization a
3、nd reporting. Through this disclo-sure, truth-in-data permits traffic monitoring summary statisticsto be recalculated from the base data.1.1.1 Truth-in-data can be applied in all traffic monitoringprograms at all levels of investment and development. Tempo-rary manual field activities and permanent
4、data gatheringinstallations share a common interest in and need for the abilityto check and confirm reported traffic statistics. This is theirreducible minimum for both sharing traffic data over timewithin an agency, and at a point of time and over time amongagencies.1.1.2 Truth-in-data also permits
5、 alternative assessment ofthe base data. The ability to recalculate traffic statistics frombase data provides the opportunity to use different assumptionsor to apply different adjustment factors. As understanding oftraffic data proceeds, truth-in-data permits equivalent longitu-dinal assessment of t
6、raffic summary statistics through consis-tent adjustment and treatment of base data over a study period.1.1.3 Truth-in-data is the foundation for all traffic monitor-ing programs because of its applicability to all traffic monitor-ing programs, its support of meaningful sharing of data amongdiverse
7、programs, and its contribution to understanding andapplying data for the improvement of traffic management.1.2 UnitsThe values stated in inch-pound units are to beregarded as the standard. The values given in parentheses aremathematical conversions to SI units that are provided forinformation only a
8、nd are not considered standard.1.3 This standard does not purport to address all of thesafety concerns, if any, associated with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitatio
9、ns prior to use.2. Referenced Documents2.1 ASTM Standards:2E177 Practice for Use of the Terms Precision and Bias inASTM Test MethodsE2259 Guide for Archiving and Retrieving IntelligentTransportation Systems-Generated DataE2300 Specification for Highway Traffic Monitoring De-vicesE2468 Practice for M
10、etadata to Support Archived DataManagement SystemsE2532 Test Methods for Evaluating Performance of High-way Traffic Monitoring DevicesE2665 Specification for Archiving ITS-Generated TrafficMonitoring DataE2667 Practice for Acquiring Intersection Turning Move-ment Traffic Data3. Terminology3.1 Defini
11、tions:3.1.1 accepted reference value, na particular quantity (forexample, number of vehicles in a particular class defined bynumber of axles and interaxle spacing, vehicle count, laneoccupancy, or vehicle speed) that is agreed upon in advance oftesting of a Traffic Monitoring Device (TMD), which has
12、 anuncertainty appropriate for the given purpose. E23003.1.2 accuracy, ncloseness of agreement between a testresult, such as a value indicated by a TMD, and an acceptedreference value. E1773.1.3 base data, ntraffic field measurements that have notbeen adjusted. E26673.1.4 base data integrity, nreten
13、tion of traffic monitoringfield measurements without modification. Base Data Integrityis a component of ruth in Data. E26673.1.5 bias, nthe difference between the expectation of thetest results, such as values indicated by a TMD, and a relatedreference value.1This practice is under the jurisdiction
14、of ASTM Committee E17 on Vehicle -Pavement Systems and is the direct responsibility of Subcommittee E17.52 onTraffic Monitoring.Current edition approved May 1, 2010. Published June 2010. DOI:10.1520/E275910.2For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer
15、 Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.3.1.5.1 DiscussionBias is the total sys
16、tematic error ascontrasted to random error. There may be one or moresystematic error components contributing to the bias. A largersystematic difference from the accepted reference value isreflected by a larger bias value. E1773.1.6 metadata, ndefinitional and descriptive data thatprovide information
17、 about or documentation of other datamanaged within an application or environment. E26653.1.7 percent difference, npercent difference is defined asan absolute value given by:Percent Difference 5 (1)?TMD Output Value Accepted Reference Value?Accepted Reference Value3 100where:TMD = Traffic Monitoring
18、 DeviceE23003.1.8 precision, nthe closeness of agreement betweenindependent test results obtained under stipulated conditions3.1.8.1 DiscussionPrecision depends on random errorsand is not related to the accepted reference value or set ofaccepted reference values. E1773.1.9 sensor, na device for acqu
19、iring a signal that pro-vides data to indicate the presence or passage of a vehicle or ofa vehicle component over a detection area with respect to time(for example, vehicle flow, number of axles and their spacing);or, one or more distinctive features of the vehicle such asheight or mass. E23003.1.10
20、 traffc monitoring device, nequipment that countsand classifies vehicles and measures vehicle flow characteris-tics such as vehicle speed, lane occupancy, turning movements,and other items typically used to portray traffic movement.TMD components include sensor input, electronics that con-vert an im
21、pulse into an electrical signal, then amplify, filter,and otherwise condition the signal. The signal may be trans-lated into vehicle data within the device, downloaded orelectronically transmitted and separately processed. E23003.1.11 variability, nsources that affect the precision andbias of the re
22、sults of a repeated application. The sources ofvariability include personnel training and operation; technol-ogy; environment; sample; and time-span over which measure-ments are made. E1773.2 Definitions of Terms Specific to This Standard:3.2.1 adjustment factor, na multiplicative factor that ad-jus
23、ts a parameter for a base condition to represent a prevailingcondition.3.2.2 cluster analysis, na class of statistical techniquesthat can be applied to data to identify natural groupings.Cluster analysis sorts through raw data and groups them intoclusters. Objects in a cluster are similar to each ot
24、her. They arealso dissimilar to objects outside the cluster, particularlyobjects in other clusters. Cluster analysis may be used to groupdata from continuous traffic recorders. Similarly grouped datamay be used to calculate adjustment factors.3.2.3 grade, nthe slope (ratio of change in elevation toc
25、hange in distance) of a roadway typically given in percent.Grade is considered in traffic monitoring to ensure that vehiclespeeds are operating in free flow condition.3.2.4 manual traffc count, ntraffic data collected from thefield observations by one or more persons.3.2.5 traffc monitoring data, nd
26、ata collected, summa-rized and reported to estimate travel characteristics for one ormore traffic monitoring infrastructure segments or points.3.2.6 traffc monitoring infrastructure, nfor motorizedtransportation, traffic monitoring infrastructure may be a roadnetwork segment or point. For non-motori
27、zed transportation,traffic monitoring infrastructure may be a road lane, sidewalk,path or trail segment or point.3.2.7 traffc monitoring stages, nthe steps of traffic moni-toring field data collection, evaluation, acceptance, summari-zation and reporting.4. Significance and Use4.1 There are general
28、references to the principle of truth-in-data as found in Guide E2259 and Practice E2667. While thesereferences are helpful, without clarification differences occurwithin agencies over time as well as among agencies in howtruth-in-data is implemented. In the absence of a standardpractice for truth-in
29、-data, documentation in some governmen-tal agencies is neither comprehensive nor consistent. For someorganizations, truth-in-data is an exception to common practiceand occurs only in response to a specific request to understanda specific traffic data set or summary statistic from a traffic dataset.
30、This practice provides consistent approach to truth-in-dataimplementation.4.1.1 Traffc Monitoring StagesTraffic monitoring truth-in-data describes how base data are treated at each trafficmonitoring stage from field data collection through evaluation,acceptance, summarization and reporting.4.1.2 Ben
31、efitsTruth in data provides a means of address-ing if and how missing or questionable data are modified aspart of data acceptance and use. The benefit arises fromunderstanding what data assumptions or adjustment factors, ifany, were applied to reported traffic summary statistics. If anadjustment fac
32、tor or factors were applied, consistent withtruth-in-data the source and adjustment factor source charac-teristics are disclosed. With this type of information, the datauser is in a better position to understand the data set andsummary statistics, ask questions, and appropriately apply thedata. Trut
33、h-in-data ensures that traffic data can be correctlyinterpreted and appropriately used to improve highway opera-tions safety and efficiency.4.1.3 ExceptionsTraffic monitoring truth-in-data does notaddress subsequent use of the data and summary statistics as inlongitudinal studies. Traffic monitoring
34、 truth-in-data estab-lishes the basis for appropriate current and longer-term use ofbase data and summary statistics. Critical use of traffic moni-toring data such as in safety analysis depends on the dataclarity and integrity identified by implementing truth-in-data.Traffic monitoring truth-in-data
35、 does not address data storage.Traffic monitoring truth-in-data describes the conditions lead-ing to acceptance of data for storage and the reporting of dataretrieved from storage. The metadata structure for archiveddata management systems (ADMS) recommended for trafficmonitoring data is presented i
36、n Practice E2665. An ADMS isthe information management system used to store traffic datawith integrity over time.E2759 1025. Procedure5.1 The procedure documents traffic monitoring activitiesby identifying data elements for each traffic monitoring stageand is incorporated into reported traffic summa
37、ry statistics. Ifinformation sought is not applicable, “NA” should be entered.If information sought was not collected, “NC” should beentered.5.2 Field Data Collection:5.2.1 Resources:5.2.1.1 People:(1) Training of person(s) collecting traffic monitoring data.(2) Years experience of person(s) collect
38、ing traffic moni-toring data.5.2.1.2 Technology:(1) Traffic monitoring device manufacturer and type,model, and software version.(2) Device(s) purchase or installation date and repairhistory.(3) Device(s) calibration.5.2.1.3 Standards or Guidelines Implemented for Field DataCollection:(1) Device manu
39、facturer recommended practice.(2) National standard or guideline (specify).5.2.2 Types of Traffc Monitoring:5.2.2.1 Manual:(1) Type(s) of Facilities:(a) Road segments:(i) Functional Classification.(ii) Access control.(b) Road intersections or other points.(c) Sidewalks.(d) Trails.(e) Paths.(2) Types
40、 of Data Collected:(a) Motorized traffic.(b) Non-motorized traffic.(3) Period of Data Collection:(a) Month and year.(b) Day(s) of week.(c) Time(s) of day.5.2.2.2 Technology-Based (consistent with the technologieslisted in 5.2.1.2, and with automated data collection, PracticeE2532, Appendix X2):(1) T
41、ype(s) of Facilities:(a) Road segments:(i) Functional Classification.(ii) Access control.(b) Road intersections or other points.(c) Sidewalks.(d) Trails.(e) Paths.(2) Types of Data Collected:(a) Motorized traffic.(b) Non-motorized traffic.(3) Period of Data Collection:(a) Month and year.(b) Day(s) o
42、f week.(c) Time(s) of day.(d) Break or interruption in the count:(i) Time.(ii) Duration.(iii) Cause.5.2.3 Traffc Monitoring Location identification:5.2.3.1 Global Positioning System (GPS) Location:(1) Device type.(2) Measurement error.(3) Datum.35.2.3.2 Other Location Identification:(1) Methodology.
43、(2) Measurement error.5.2.4 Traffc Monitoring Site Conditions:5.2.4.1 Physical Characteristics:(1) Grade.(2) Lanes.(3) Other.5.2.4.2 Operational Characteristics:(1) Monitoring Location or Locations:(a) Manual count staff.(b) Technology.(2) Potential Sources of Traffc Disruption that May Affectthe Tr
44、affc Data Collected:(a) Infrastructure construction or maintenance.(b) Residual queues.(c) Other (specify).5.2.4.3 Weather.5.3 EvaluationIdentification of Missing, Incomplete orErroneous Traffc Monitoring Data:5.3.1 Resources:5.3.1.1 People:(1) Training:(a) Training of person(s) evaluating traffic m
45、onitoringdata.(b) Years experience of person(s) evaluating traffic moni-toring data.(2) Traffc Monitoring Staff Evaluation of Base Data:(a) Documentation:(i) Documented formally adopted procedure.(ii) Documented, informal procedure.(iii) Undocumented procedure.(b) Methodology:(i) Percent difference
46、between traffic monitoring countand reference dataset: Acceptance tests. Indicator of accuracy and bias.(ii) Repeatability (side-by-side counts).(iii) Other (specify).5.3.1.2 Technology:(1) Traffc Monitoring Device Internal Software DataEvaluation:(a) Documentation:(i) Evaluation rules are provided
47、for review withoutability to modify the rules.3Federal Geographic Data Committee (FGDC) Content Standards for DigitalGeospatial Metadata (FGDC-STD-001-1998).E2759 103(ii) Evaluation rules are provided for review with theability to modify the rules.(iii) Evaluation rules are internal to the device an
48、d arenot provided for review.(b) Results of applying the methodology:(i) Data results of applying the rules are provided forreview.(ii) Data results of applying the rules are internal to thedevice and are not provided for review.(2) Post-processing Evaluation of Traffc Data UsingComputer Software:(a
49、) Software source, name, and version.(b) Evaluation of data:(i) Data evaluated are reported for review:Attribute Accuracy Report (from Practice E2468).Other (specify).(ii) Data evaluated are not reported for review.5.4 AcceptanceModification of Traffc Data Prior to TheirInclusion in the Calculation of Summary Statistics:5.4.1 Resources Used to Modify Traffc Data as a Conditionof Acceptance:5.4.1.1 People:(1) Training:(a) Training of person(s) in modifying traffic data.(b) Years experience of person(s) modifying traffic data.(2) Documen
