1、Designation: E2759 10 (Reapproved 2018)Standard 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 revisi
2、on. A number in parentheses 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,acceptanc
3、e, summarization, and reporting. Through thisdisclosure, truth-in-data permits traffic monitoring summarystatistics to 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 activiti
4、es and permanent data gatheringinstallations share a common interest in, and need for, theability to check and confirm reported traffic statistics. This isthe irreducible minimum for both sharing traffic data over timewithin an agency, and at a point of time and over time amongagencies.1.1.2 Truth-i
5、n-data also permits 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-di
6、nal assessment of traffic 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
7、 data amongdiverse 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 fo
8、rinformation only and 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, health, and environmental practices and deter-mine the ap
9、plicability of regulatory limitations prior to use.1.4 This international standard was developed in accor-dance with internationally recognized principles on standard-ization established in the Decision on Principles for theDevelopment of International Standards, Guides and Recom-mendations issued b
10、y the World Trade Organization TechnicalBarriers to Trade (TBT) Committee.2. Referenced Documents2.1 ASTM Standards:2E177 Practice for Use of the Terms Precision and Bias inASTM Test MethodsE2259 Guide forArchiving and Retrieving Intelligent Trans-portation Systems-Generated DataE2300 Specification
11、for Highway Traffic Monitoring De-vicesE2468 Practice for Metadata 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 Intersec
12、tion Turning Move-ment Traffic Data3. Terminology3.1 Definitions: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 advanc
13、e oftesting of a traffic monitoring device (TMD), which has 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 ha
14、ve notbeen adjusted. E26673.1.4 base data integrity, nretention of traffic monitoringfield measurements without modification. Base data integrity isa component of truth-in-data. E26671This practice is under the jurisdiction of ASTM Committee E17 on Vehicle -Pavement Systems and is the direct respons
15、ibility of Subcommittee E17.52 onTraffic Monitoring.Current edition approved Sept. 1, 2018. Published September 2018. Originallyapproved in 2010. DOI:10.1520/E2759-10R18.2For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annu
16、al Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United StatesThis international standard was developed in accordance with internationally r
17、ecognized principles on standardization established in the Decision on Principles for theDevelopment of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.13.1.5 bias, nthe difference between the expectation of thete
18、st results, such as values indicated by a TMD, and a relatedreference value.3.1.5.1 DiscussionBias is the total systematic 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
19、 isreflected by a larger bias value. E1773.1.6 metadata, ndefinitional and descriptive data thatprovide information 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 Dif
20、ference5 (1)?TMD Output Value 2 Accepted Reference Value?Accepted Reference Value3100where:TMD = traffic monitoring device.E23003.1.8 precision, nthe closeness of agreement betweenindependent test results obtained under stipulated conditions3.1.8.1 DiscussionPrecision depends on random errorsand is
21、not related to the accepted reference value or set ofaccepted reference values. E1773.1.9 sensor, na device for acquiring a signal that providesdata to indicate the presence or passage of a vehicle or of avehicle component over a detection area with respect to time(for example, vehicle flow, number
22、of axles and their spacing);or, one or more distinctive features of the vehicle such asheight or mass. E23003.1.10 traffc monitoring device, nequipment that countsand classifies vehicles and measures vehicle flow characteris-tics such as vehicle speed, lane occupancy, turning movements,and other ite
23、ms typically used to portray traffic movement.TMD components include sensor input, electronics that con-vert an impulse 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
24、transmitted and separately processed. E23003.1.11 variability, nsources that affect the precision andbias of the results of a repeated application. The sources ofvariability include personnel training and operation,technology, environment, sample, and time-span over whichmeasurements are made. E1773
25、.2 Definitions of Terms Specific to This Standard:3.2.1 adjustment factor, na multiplicative factor that ad-justs 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.Cl
26、uster analysis sorts through raw data and groups them intoclusters. Objects in a cluster are similar to each other. They arealso dissimilar to objects outside the cluster, particularlyobjects in other clusters. Cluster analysis may be used to groupdata from continuous traffic recorders. Similarly gr
27、ouped datamay be used to calculate adjustment factors.3.2.3 grade, nthe slope (ratio of change in elevation tochange 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 co
28、unt, ntraffic data collected from thefield observations by one or more persons.3.2.5 traffc monitoring data, ndata collected,summarized, and reported to estimate travel characteristics forone or more traffic monitoring infrastructure segments orpoints.3.2.6 traffc monitoring infrastructure, nfor mot
29、orizedtransportation, traffic monitoring infrastructure may be a roadnetwork segment or point. For non-motorized 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
30、collection, evaluation, acceptance, summari-zation and reporting.4. Significance and Use4.1 There are general 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
31、as well as among agencies in howtruth-in-data is implemented. In the absence of a standardpractice for truth-in-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 respon
32、se to a specific request to understanda specific traffic data set or summary statistic from a traffic dataset. This practice provides a consistent approach to truth-in-data implementation.4.1.1 Traffc Monitoring StagesTraffic monitoring truth-in-data describes how base data are treated at each traff
33、icmonitoring stage from field data collection through evaluation,acceptance, summarization, and reporting.4.1.2 BenefitsTruth 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
34、 assumptions or adjustment factors, ifany, were applied to reported traffic summary statistics. If anadjustment factor 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 bet
35、ter position to understand the data set andsummary statistics, ask questions, and appropriately apply thedata. Truth-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-d
36、ata does notaddress subsequent use of the data and summary statistics as inlongitudinal studies. Traffic monitoring 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 analysi
37、s, depends on the dataE2759 10 (2018)2clarity and integrity identified by implementing truth-in-data.Traffic monitoring truth-in-data 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
38、from storage. The metadata structure for archiveddata management systems (ADMS) recommended for trafficmonitoring data is presented in Specification E2665.AnADMS is the information management system used to storetraffic data with integrity over time.5. Procedure5.1 The procedure documents traffic mo
39、nitoring activitiesby identifying data elements for each traffic monitoring stageand is incorporated into reported traffic summary 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
40、 Resources:5.2.1.1 People:(1) Training of person(s) collecting traffic monitoring data.(2) Years experience of person(s) collecting 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
41、and repair his-tory.(3) Device(s) calibration.5.2.1.3 Standards or Guidelines Implemented for Field DataCollection:(1) Device manufacturer 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)
42、 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) of week.(c) Time(s) of day.5.2.2.2 Technolo
43、gy Based (consistent with the technologieslisted in 5.2.1.2, and with automated data collection, TestMethods E2532, Appendix X2):(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)
44、 Types 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.(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 Pos
45、itioning System (GPS) Location:(1) Device type.(2) Measurement error.(3) Datum.35.2.3.2 Other Location Identification:(1) Methodology.(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) M
46、onitoring Location or Locations:(a) Manual count staff.(b) Technology.(2) Potential Sources of Traffc Disruption That May Affectthe Traffc Data Collected:(a) Infrastructure construction or maintenance.(b) Other (specify).5.2.4.3 Weather.5.3 Evaluation Identification of Missing, Incomplete, orErroneo
47、us Traffc Monitoring Data:5.3.1 Resources:5.3.1.1 People:(1) Training:(a) Training of person(s) evaluating traffic monitoringdata.(b) Years experience of person(s) evaluating traffic moni-toring data.(2) Traffc Monitoring Staff Evaluation of Base Data:(a) Documentation:(i) Documented, formally adopt
48、ed procedure.(ii) Documented, informal procedure.(iii) Undocumented procedure.(b) Methodology:(i) Percent difference between traffic monitoring countand reference dataset: Acceptance tests. Indicator of accuracy and bias.3Federal Geographic Data Committee (FGDC) Content Standards for DigitalGeospati
49、al Metadata (FGDC-STD-001-1998).E2759 10 (2018)3(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 for review withoutability to modify the rules.(ii) Evaluation rules are provided for review with theability to modify the rules.(iii) Evaluation rules are internal to the device and are notprovided for review.(b) Results of applying the methodology:(i) Data results of applying the rules are provided fo
