Presentation on theme: "Axle and Length Classification Steven Jessberger"— Presentation transcript:
1 Axle and Length Classification Steven Jessberger Federal Highway Administration2012 Highway Information SeminarSession 3B
2 Presentation Acronyms AASHTO – American Association of State HighwayTransportation OfficialsASTM – American Society of Testing and MaterialsALEDA – Advanced Loop Event Detection AnalyzerAVC – Automatic Vehicle Classifier (class)ATR – Automatic Traffic Recorder (volume)DOW – Day of WeekFHWA – Federal Highway AdministrationHPMS – Highway Performance Monitoring SystemHVTIS – Heavy Vehicle Travel Information SystemLTPP – Long Term Pavement Performance (SHRP)MEPDG – Mechanistic Empirical Pavement Design GuideNCHRP – National Cooperative Highway Research ProgramOD – Origin and DestinationSBIR – Small Business Investment ResearchTMAS – Travel Monitoring Analysis SystemTVT – Traffic Volume TrendsTMG – Traffic Monitoring GuideUPACS – User Profile and Access Control System
3 Getting Results - 4 Steps Construction of the siteSupport/MaintenanceProcessing of the dataReporting of the InformationTurn your Data into Information
4 Class – 2001 TMG Classification counts – why do them? 25% - 30% of volume counts should be classCoverage countsHighway linksAnnualized dataLength classification
5 Classification Reporting TMAS 2.0 is now accepting all class data on a per site basis by month.TMAS 2.0 replaces the HVTISNew TMG formats for class data (C-card)Time Intervals 5, 15 or 60 minuteState specific axle class algorithmVerify what you are usingCalibrate your classtree algorithmsLTPP classtree research (completed in 2012)Numerous States and Types of Classtrees Checked
6 Axle Class Factoring Factoring for Trucks Factoring for Motorcycles Variability by DOW and month of yearImproves reporting on trucks for:HPMSFreight MovementsPavement DesignsFactoring for MotorcyclesCorrect for the weekday portable countsCorrect for the month of year varianceUse processes and collection methods that correctly classifies motorcyclesFactoring for Other Vehicle Types (see 2012 TMG)
7 Vehicle Length Class Data FlexibilityDual loops – last longerAllows for non-intrusive technologiesSide fire technologyOver head technologyUnder the road technologyAll States are welcome to join FHWA sponsored pooled fundsLoop Length Based Class Pooled FundTest and verify your bins
8 Vehicle Length Class Data Calibrate your sitesTest and verify your binsVariances for length used in classes 2-3 bin18’, 19.5’, 20’, 21’, 21.8’ and 22.5’Example of possible bins:Bin 1 class 1Bin 2 classes 2-3Bin 3 classes 4-7Bin 4 classes 8-10Bin 5 classes 11-13What do you use?
9 Example of length class vs. axle class Vehicle Length ClassExample of length class vs. axle class
10 Loop - Length Based Class Pooled Fund Table - Results
12 Pooled Fund ResultsThe length thresholds for these four length bins are: DRAFTMotorcycle: 0 to 6.5 feetShort vehicle: 6.5 to 21.5 feetMedium vehicle: 21.5 feet to 48 feetLong vehicle: 48 feet and larger
13 Traffic Data Research LTPP Pooled Fund and Falcon Work NCHRP (motorcycle, trucks…)High Resolution DetectorsLoop Sensitivity Tuning – Dr. Yinhai Wang (ALEDA)State Research - what are you doing?Small Business Investment Research (2012)Phase I – $150,000Phase II - $800,000Truck Re-Identification using Loop Signatures and other vehicle attributes
14 Inductive Signature Technology Axle class with loops onlyRe-identification of vehiclesCalibration transfer between sitesCharacteristics of Traffic Stream transfer between sites for:OD studies – freight movement and loadingsImproved Pavement DesignsTravel TimesModel Inputs for Travel PatternsImproved Safety
18 Standards FHWA - Traffic Monitoring Guide FHWA – HPMS Field Manual ASTM documents related to classification countsInstalling & Using Pneumatic Tubes with Roadway Traffic Counters and ClassifiersHighway Traffic Monitoring DevicesInstalling Piezoelectric Highway Traffic SensorsDeveloping Axle Count Adjustment FactorsMetadata to Support Archived Data Management SystemsEvaluating Performance of Highway Traffic Monitoring DevicesAASHTOLoop Detector Handbook 2006Guidelines for Traffic Data Programs 2009WIM Successful Practices 1997
19 MEPDG Required Classification Inputs Level 1 DesignSite specific class data (continuous or 4 seasons)Level 2 DesignRegional class data (continuous or 4 seasons)Level 3 DesignNational class data (system defaults)
20 How to improve your class data? Full width axle sensors (motorcycles)road tubespiezoAxle Sensors as primary sensor for class sitesLength can detect motorcycles as bin 1More class sites for proper factoringClass data QC (TMAS/LTPP/Pooled Fund)Collect per vehicle format records (Idaho)Calibrated your class algorithm(s) –2011 State Survey – only 15 States use State specific treesBy lane class checks – done dailyCalibrate class sites annually
21 State/Vendor Best Practices What practices have you experienced that others could benefit from?What problems have you encountered that need to be dealt with?
22 Questions?? FHWA – Headquarters Office of Highway Policy Information Travel Monitoring and Surveys DivisionWashington D.C.Steven JessbergerFHWA Highway Community Exchange (CoP)https://www.transportationresearch.gov/dot/fhwa/hcx/default.aspx
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