TRANSPORTATION RESEARCH BOARD. Spatial Modeling for Highway Performance Monitoring System Data: Part 2. Tuesday, March 6, :00-3:00 PM ET

Transcription

1 TRANSPORTATION RESEARCH BOARD Spatial Modeling for Highway Performance Monitoring System Data: Part 2 Tuesday, March 6, :00-3:00 PM ET

2 The Transportation Research Board has met the standards and requirements of the Registered Continuing Education Providers Program. Credit earned on completion of this program will be reported to RCEP. A certificate of completion will be issued to participants that have registered and attended the entire session. As such, it does not include content that may be deemed or construed to be an approval or endorsement by RCEP.

3 Purpose Discuss how to use spatial modeling and statistical tools to enhance the quality and productivity of travel monitoring data. Learning Objectives At the end of this webinar, you will be able to: Describe the HPMS travel data validation rules and create pseudo-code queries that incorporate HPMS based validation rules Understand how to apply standard visualizing tools for the purpose of highlighting and identification of potential problems Understand the need to balance multimodal solutions within the system Understand how to create HPMS data items and summary data using a relational database

4 TRB WEBINAR: SPATIAL MODELING FOR HIGHWAY PERFORMANCE MONITORING SYSTEM DATA PART 2 - MARCH 6, 2018 Maaza Christos Mekuria, PhD, PE, PTOE Dan P. Seedah, PhD Stephen Cropley 1

5 2 WEBINAR OUTLINE Spatio-temporal Relationships Spatial Clustering Applications to HPMS Data Items Generation of Summary Tables Ramp Balancing Opportunities and challenges for Probe data Q & A session

6 RECAP FROM PART 1 WEBINAR 3 Overview of HPMS Description of HPMS Travel Data Items Relationship between HPMS Data items Linear Referencing System Sample Panels and HPMS items Leveraging Spatial Analysis

7 4 SPATIAL RELATIONSHIPS Dimensionality Adjacency Connectivity Containment B A

8 TEMPORAL RELATIONSHIPS 5 Time of Day Day of Week Month Year

9 HIGHWAY PERFORMANCE MONITORING SYSTEM (HPMS) 6 Sample Panels (Sections/Links/Segments) Assign Counts to Monitored Sections Expand to Unmonitored Sections Generate Summaries [Ref. FHWA]

10 HPMS SAMPLE PANEL GENERATION 7 FHWA HPMS Tool ArcGIS Spatial Oracle PL/SQL QGIS/Python Spatialite/Python/C++ etc. Sample Panels [Adapted from FHWA - CPI Manual 2001]

11 TOPS GROUP SECTIONS SAMPLE CODES 8 CASE WHEN "aadt"/"thrulanes" <= 2500 THEN 'Very Low' WHEN "aadt"/"thrulanes" <= 5000 THEN 'Low' WHEN "aadt"/"thrulanes" <= THEN 'Moderate' WHEN "aadt"/"thrulanes" <= THEN 'High' WHEN "aadt"/"thrulanes" <= THEN 'Very High' WHEN "aadt"/"thrulanes" > THEN 'Super High' END

12 TOPS GROUP SECTIONS 9 QUERY Group all roadways by functional class and order by number of records in each county

13 TOPS GROUP SECTIONS Number of Segments Very Low Low Moderate High Very High Super High Volume Group Per Lane

14 TOPS GROUP SECTIONS 11 FC_FacilityType_UrbanCode_Low_SampleCode

15 HPMS VOLUME GROUPS 12 CASE WHEN "aadt" <= 500 THEN 1 WHEN "aadt" <= 1000 THEN 2 WHEN "aadt" <= 2500 THEN 3 WHEN "aadt" <= 5000 THEN 4 WHEN "aadt" <= THEN 5 WHEN "aadt" <= THEN 6 WHEN "aadt" <= THEN 7 WHEN "aadt" <= THEN 8 WHEN "aadt" <= THEN 9 WHEN "aadt" <= THEN 10 WHEN "aadt" <= THEN 11 WHEN "aadt" > THEN 12 END

16 13 HPMS VOLUME GROUPS 2500 Number of HPMS Volume Group Segments 2000 Number of Segments HPMS Volume Group

17 HPMS VOLUME GROUPS ESTIMATION FORMUAR 14 Table 6.2 Confidence Level Z Z Squared 90 Percent Percent Percent [Ref. FHWA Field manual 2016]

18 HPMS TOPS CLUSTERS Number of TOPS Segment Groups

19 HPMS LINK TRAVEL DATA ASSIGNMENT 16

20 COUNTED HPMS SECTIONS FOR A GIVEN YEAR 24/7 continuous counters Short Term Counters? No Counters 17 Section Boundaries?????

21 HPMS FIELD MANUAL GUIDANCE - VOLUME DATA For AADT (Pages 4-51 and 4-52) For two-way facilities, provide the bidirectional AADT; for one-way roadways, and ramps, provide the directional AADT. All AADTs shall reflect application of day of week, seasonal, and axle correction factors, as necessary; no other adjustment factors shall be used. Growth factors shall be applied if the AADT is not derived from current year counts. AADTs for the NHS, Interstate, Principal Arterial (OFE, OPA) roadway sections shall be based on traffic counts taken on a minimum threeyear cycle. AADTs for the non-principal Arterial System (i.e., Minor Arterials, Major Collectors, and Urban Minor Collectors) can be based on a minimum six-year counting cycle.

22 TRAVEL MONITORING : AADT LINK ASSIGNMENT -- Year 19 Sample Panels Data Attr./ Spatial Merge Volume Stations Are all Sections Assigned? No Earlier year meets FC criterion? Yes Yes No END Section to be revised for HPMS Submission

23 HPMS TRAFFIC STATIONS ASSIGNMENT RESULTS 20

24 AADT COUNT ASSIGNMENT - MAUI 21

25 AADT COUNT ASSIGNMENT - KAUAI 22

26 AADT COUNT ASSIGNMENT - KAUAI 23

27 AADT COUNT ASSIGNMENT - KAUAI 24

28 2016 HPMS FIELD MANUAL GUIDANCE CLASS DATA 25 For Single Unit and Combination Unit AADT (Pages 4-52 to 4-57) AADT values shall be updated annually to represent current year data. Section specific measured values are requested based on traffic counts taken on a minimum three-year cycle. If these data are not available, values derived from classification station data on the same route, or on a similar route with similar traffic characteristics in the same area can be used

29 TRAVEL MONITORING : CLASS LINK ASSIGNMENT 26 Find the adjacent section on same route with similar FC, thru lanes, and urban code, and assign class data* * Preference is given to permanent stations over shortterm stations

30 AADT CLASS COUNT ASSIGNMENT 27

31 CONSIDERATIONS FOR APPLYING GROWTH RATES 28 Growth rates are applied on a statewide level Further investigation required on applying growth rates based on: Urban area codes Rate computed from just the permanent stations Considerations for: Low volume rural roadways Large area vs. small area Sections that traverse multiple boundaries e.g. interstates

32 CONSIDERATIONS FOR USING JOINS 29 Attribute Joins Attribute joins can use MILEPOINT and ROUTE information with respect to Section start and end mile points. More accurate, if and only if, data attributes are correctly set in both the Station and Link records. Spatial Joins Point is typically matched to a target line which is closest/intersects/contains the point Uses a search radius or tolerance Issues include wrongly assigned joins e.g. ramp counts with coordinates placed close to the interstate Best compromise is a spatial join with attribute join

33 AADT CLASS COUNT ASSIGNMENT 30 The result of the processing is HPMS Network with AADT, Class, Peak Hour Count Data assigned to links

34 AADT ASSIGNMENT COMPARISON 31

35 AADT ASSIGNMENT COMPARISON 32

36 TRUCK AADT COMPUTATION TRUCK AADT for each section 33 Using the Permanent Stations Adjust Short Term Class Stations Truck Single Unit = (Daily Single Unit Trucks (Class 5-7) + Bus ) Percent Peak Combination = (Daily Combination Unit Trucks, FHWA class 8-13 )

37 AADT K, D FACTOR ASSIGNMENT 34 Both K-factor ( the design hour volume - 30 th largest hourly volume for a given calendar year) as a percentage of AADT) and the Directional Factor (D) ( the percent of design hour volume - 30th largest hourly volume for a given calendar year flowing in the higher volume direction) are assigned to AADT links via permanent station factor groups.

38 VALIDATION FOR TRAFFIC DATA ITEMS 35 FHWA Validation Queries are heavily dependent on user table structure, yet they are as simple as a single query once the table data are generated. Samples will be provided when requested.

39 PEAK HOUR ASSIGNMENT Peak Hour AADT for each section 36 Using the Permanent Stations Adjust Short Term Class Stations Percent Peak Single = (Peak Hour Daily Single Unit Trucks + Bus ) / (AADT ) Percent Peak Combination = (Peak Hour Daily Combination Unit Trucks ) / (AADT )

40 VEHICLE SUMMARY 37 Step 1 - Create Average View of the AADT Link Class data table by FHWA Highway System Group create view vwhpms2016avgvehicleclass as Select Year,t2.State_Code, t2.fs_group, Round(avg(t1.cycles),2) Pct_MC, round(avg(t1.pc),2) Pct_Cars, round(avg(t1.vcls3),2) Pct_Lgt_Trucks, round(avg(t1.bus),2) Pct_Buses,round(avg(t1.SU),2) Pct_SU_Trucks, round(avg(t1.cu),2) Pct_CU_Trucks from HPMS2016VEHICLECLASS t1, FHWA_HIGHWAY_Class_Group t2 where t1.func_class = t2.func_class group by t1.year,t2.state_code, t2.fs_group Order by t2.year, t2.state_code, t2. FS_GROUP ;

41 VEHICLE SUMMARY 38 Step 2 - Create Summary View of the AADT Link Class data by FHWA Highway System Group create view vwhpms2016sumvehicleclass as t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC+ t2.pct_cars + t2.pct_lgt_trucks+ t2.pct_buses + t2.pct_su_trucks + t2.pct_cu_trucks),2) TotPct from vwhpms2016avgvehicleclass t2 Order by t2.year_record,t2.state_code,t2.fs_group;

42 VEHICLE SUMMARY 39 Step 3 - Create Export for FHWA by FHWA Highway System Group select t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC/t1.TotPct*100),2) Pct_MC, Round((t2.Pct_Cars/t1.TotPct*100),2) Pct_Cars, Round((t2.Pct_Lgt_Trucks/t1.TotPct*100),2) Pct_Lgt_Trucks, Round((t2.Pct_Buses/t1.TotPct*100),2) Pct_Buses, Round((t2.Pct_SU_Trucks/t1.TotPct*100),2) Pct_SU_Trucks, Round((t2.Pct_CU_Trucks/t1.TotPct*100),2) Pct_CU_Trucks from vwhpms2016avgvehicleclass t2 inner join vwhpms2016sumvehicleclass t1 on t1.fs_group = t2.fs_group Order by t2.year_record, t2.state_code, t2.fs_group;

43 VEHICLE SUMMARY TO BE EXPORTED TO FHWA 40

44 VEHICLE SUMMARY VMT BASED 41 Step 1 - Create Summary View of the Link VMT Class data by FHWA Highway System create view vwhpms2016vehicleclassvmtsum as select t2.year_record, '15' State_Code, t2.fs_group, Round(sum(t1.cycles*(t2.EMP-t2.BMP)*t2.AADT),2) Pct_MC, round(sum(t1.pc*(t2.emp-t2.bmp)*t2.aadt),2) Pct_Cars, Round(sum(t1.VCLS3*(t2.EMP-t2.BMP)*t2.AADT),2) Pct_Lgt_Trucks, round(sum(t1.bus*(t2.emp-t2.bmp)*t2.aadt),2) Pct_Buses, round(sum((t1.su)*(t2.emp-t2.bmp)*t2.aadt),2) Pct_SU_Trucks, round(sum(t1.cu*(t2.emp-t2.bmp)*t2.aadt),2) Pct_CU_Trucks from HPMS2016VEHICLECLASS t1, HPMS2016AADT t2, FHWAClass t3 where t2.route = t1.route_id and t2.bmp = t1.bmp and t2.emp = t1.emp and t2.fs_group = t3. FS_GROUP group by t2.year_record, t3. FS_GROUP Order by t2.year_record, t3. FS_GROUP ;

45 VEHICLE SUMMARY VMT BASED 42 Step 2 - Create Summary View of the Total VMT Class data create view vwhpms2016vmtsum as select t2.year_record, '15' State_Code, t3. FS_GROUP, Round(sum((t2.EMPt2.BMP)*t2.AADT),2) VMT from HPMS2016AADT t2, FHWAClass t3 where t2.fs_group = t3. FS_GROUP group by t2.year_record, t3. FS_GROUP Order by t2.year_record, t3. FS_GROUP;

46 VEHICLE SUMMARY VMT BASED 43 Step 3 Divide Link VMT (Step 1) by VMT Totals (Step 2) create view vwhpms2016vmtvehicleclasssum as select t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC/t1.VMT),2) Pct_MC, Round((t2.Pct_Cars/t1.VMT),2) Pct_Cars, Round((t2.Pct_Lgt_Trucks/t1.VMT),2) Pct_Lgt_Trucks, Round((t2.Pct_Buses/t1.VMT),2) Pct_Buses, Round((t2.Pct_SU_Trucks/t1.VMT),2) Pct_SU_Trucks, Round((t2.Pct_CU_Trucks/t1.VMT),2) Pct_CU_Trucks from vwhpms2016vehicleclassvmtsum t2 inner join vwhpms2016vmtsum t1 on t1.fs_group = t2.fs_group Order by t2.year_record, t2.state_code, t2.fs_group ;

47 VEHICLE SUMMARY VMT BASED Step 4 - Create Total view of the AADT Link Class data by FHWA Highway System Group from Step 3 44 create view vwhpms2016sumvehicleclass as t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC+ t2.pct_cars + t2.pct_lgt_trucks+ t2.pct_buses + t2.pct_su_trucks + t2.pct_cu_trucks),2) TotPct from vwhpms2016vmtvehicleclasssum t2 Order by t2.year_record,t2.state_code,t2.fs_group;

48 VEHICLE SUMMARY VMT BASED 45 Step 5 - Create Export for FHWA Step 3 / Step 4 select t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC/t1.TotPct*100),2) Pct_MC, Round((t2.Pct_Cars/t1.TotPct*100),2) Pct_Cars, Round((t2.Pct_Lgt_Trucks/t1.TotPct*100),2) Pct_Lgt_Trucks, Round((t2.Pct_Buses/t1.TotPct*100),2) Pct_Buses, Round((t2.Pct_SU_Trucks/t1.TotPct*100),2) Pct_SU_Trucks, Round((t2.Pct_CU_Trucks/t1.TotPct*100),2) Pct_CU_Trucks from vwhpms2016avgvehicleclass t2 inner join vwhpms2016sumvehicleclass t1 on t1.fs_group = t2.fs_group Order by t2.year_record, t2.state_code, t2.fs_group ;

49 VEHICLE SUMMARY VMT BASED Step 5 - Create Export for FHWA Step 3 / Step 4 46 select t2.year_record, t2.state_code, t2.fs_group, Round((t2.Pct_MC/t1.TotPct*100),2) Pct_MC, Round((t2.Pct_Cars/t1.TotPct*100),2) Pct_Cars, Round((t2.Pct_Lgt_Trucks/t1.TotPct*100),2) Pct_Lgt_Trucks, Round((t2.Pct_Buses/t1.TotPct*100),2) Pct_Buses, Round((t2.Pct_SU_Trucks/t1.TotPct*100),2) Pct_SU_Trucks, Round((t2.Pct_CU_Trucks/t1.TotPct*100),2) Pct_CU_Trucks from vwhpms2016avgvehicleclass t2 inner join vwhpms2016sumvehicleclass t1 on t1.fs_group = t2.fs_group Order by t2.year_record, t2.state_code, t2.fs_group ;

50 VEHICLE SUMMARY TO BE EXPORTED TO FHWA 47 Vehicle Summaries Simple Average Year_Record State_Code FS_GROUP Pct_MC Pct_Cars Pct_Lgt_Trucks Pct_Buses Pct_SU_Trucks Pct_CU_Trucks TotPct VMT Based Year_Record State_Code FS_GROUP Pct_MC Pct_Cars Pct_Lgt_Trucks Pct_Buses Pct_SU_Trucks Pct_CU_Trucks TotPct

51 CLUSTER PROCESSING 48

52 HPMS SAMPLE PANEL CLUSTER SIZE = 50 49

53 HPMS SAMPLE PANEL CLUSTER SIZE = 25 50

54 HPMS COUNT STATION SELECTION 51

55 RAMP BALANCING PROCEDURES 52

56 PURPOSE OF RAMP BALANCING Need to report traffic (AADT) on all interstate mainline sections. Hard to count some sections, so Ramp balancing can be used to estimate traffic volumes on roads where portable counts cannot be performed safely (TMG 2017) Its called ramp balancing because AADT values are adjusted so they balance along the computed sections. 53

57 DIFFERENCE BETWEEN INTERCHANGE AND MAINLINE RAMP BALANCING 54 This needs to be spelled out! WE ARE DISCUSSING THIS!! Interchange Ramp Balancing (Computes ramp volumes at interchanges) Mainline Ramp Balancing

58 A TYPICAL SETUP 55 Anchor Points (Continuous, Known) Ramp On (Known) Ramp Off (Known) Computed Mainline

59 SETTING UP FROM SPATIAL ANALYSIS 56 Continuous counters are called Anchor points. They are not changed by the computation. Determine which ramps are part of a given computation. Some ramps are actually connectors. They are On for computing one highway segment but Off for another. The order in which On and Off ramps appear in the computation is essential. Use mile points and look closely at the map. The compass directions (N, S, E, W) that ramps flow towards are essential in computation

60 EXAMPLE: COMPUTING VOLUMES 57 Point Counted COMPUTED CHANGE CCS 1 START Ramp 1 ON MID POINT Ramp2 OFF Ramp3 ON CCS2 END 11, , (-)1,053 11, , ,053 DIFF -402 * The Ramp Off below ramp1 is ignored in this example for simplicity. It would normally be included.

61 58 EXAMPLE: COMPUTING VOLUMES Point Counted Adjusted GEH Accuracy CCS 1 START 11,995 Ramp 1 ON 923 1, MID POINT 13,052 Ramp2 OFF Ramp3 ON CCS2 END (-)1, ,053 GEH Statistic 1.0 Excellent 2.0 Good 5.0 Acceptable 10.0 Rubbish

62 CONSIDERATIONS FROM SPATIAL ANALYSIS 59 - Direction of traffic - Order of ramps - Ramp counts may have happened on different days - Missing ramp values must be imputed: They are not calculated here 2017 Highway Computation Points Georgia DOT

63 RESOURCES USED IN EXAMPLES 60 TMG AADT Reporting on Mainlines and Ramps Source: (Example 4 is from the 2001 TMG)

64 OPPORTUNITIES AND CHALLENGES FOR PROBE DATA 61

65 TRAVEL MONITORING: THE IDEAL ENVIRONMENT 62

66 TRAVEL MONITORING: THE IDEAL ENVIRONMENT 24/7 continuous counters 63

67 64 TRAVEL MONITORING: AN EVEN BETTER ENVIRONMENT Autonomous Self-Reporting Vehicles

68 TRAVEL MONITORING: PROBE DATA 65

69 PROBE DATA OPPORTUNITIES 66 Cost Coverage Frequency Origin/Destination

70 PROBE DATA CHALLENGES 67 Cell tower vs. GPS vs. Location-Based Data Sample sizes for different functional classes Urban vs. rural settings Black box vs. open estimation algorithms HPMS six vehicle class data requirement Validation

71 REFERENCES 68 HPMS 2016 Field Manual Turner, Shawn, and Pete Koeneman. Using Mobile Device Samples to Estimate Traffic Volumes. No. MN/RC Minnesota. Dept. of Transportation. Research Services & Library, I-95 Corridor Coalition s Vehicle Probe Project (VPP)

72 CONTACT INFORMATION 69 Maaza Christos Mekuria, PhD, PE, PTOE Hawaii Department of Transportation Dan P. Seedah, PhD Asst. Research Scientist, Texas A&M Transportation Institute Stephen Cropley Director, Technology Transmetric America Inc.

73 70 APPENDIX A : HPMS NUMBER OF SAMPLES SELECTION 2500 Number of HPMS Volume Group Segments 2000 Number of Segments HPMS Volume Group

74 HPMS NUMBER OF SAMPLES SELECTION 71

75 HPMS NUMBER OF SAMPLES SELECTION SELECT t1.yr, t1.hpmsvgrp, Count(t1.countycode) NumRecs, Round(stddev_samp(t1.AADT)/avg(t1.AADT),3) CV, ceil((pow(1.64,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.05,2)))/ (1+(1/count(t1.Id))*(((pow(1.64,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.05,2))-1))))) NumSamp FROM HiDOTRtesHPMS2016BIKEFLDSMDS t1 GROUP BY t1.yr, t1.hpmsvgrp ORDER BY t1.yr,t1.hpmsvgrp,stddev_samp(t1.aadt)/avg(t1.aadt) desc,count(t1.countycode) Desc 72 Year HPMSVGrp NumRecs CV NumSamp

76 HPMS NUMBER OF SAMPLES SELECTION RURAL AREAS SELECT t1.yr,t1.hpmsvgrp, floor(avg(t1.funclass)) FunClsAvg, Count(t1.countycode) NumRecs, Round(stddev_samp(t1.AADT)/avg(t1.AADT),3) CV, ceil((pow(1.28,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.1,2)))/ (1+(1/count(t1.Id))*(((pow(1.28,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.1,2))-1))))) NumSamp FROM HiDOTRtesHPMS2016BIKEFLDSMDS t1 where t1.urbcode = GROUP BY t1.yr, t1.hpmsvgrp ORDER BY t1.yr,t1.hpmsvgrp,stddev_samp(t1.aadt)/avg(t1.aadt) desc,count(t1.countycode) Desc 73 yr HPMSVGrp FunClsAvg NumRecs CV NumSamp

77 HPMS NUMBER OF SAMPLES SELECTION RURAL + SMALL URBAN COLLECTOR AND ABOVE SELECT t1.yr,t1.hpmsvgrp, floor(avg(t1.funclass)) FunClsAvg, Count(t1.countycode) NumRecs, Round(stddev_samp(t1.AADT)/avg(t1.AADT),3) CV, ceil((pow(1.28,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.1,2)))/ (1+(1/count(t1.Id))*(((pow(1.28,2) * pow(stddev_samp(t1.aadt)/avg(t1.aadt),2)/(pow(0.1,2))-1))))) NumSamp FROM HiDOTRtesHPMS2016BIKEFLDSMDS t1 where t1.urbcode in ( 99999,99998) and t1.funclass >= 5 GROUP BY t1.yr, t1.hpmsvgrp ORDER BY t1.yr,t1.hpmsvgrp,stddev_samp(t1.aadt)/avg(t1.aadt) desc,count(t1.countycode) Desc 74 Yr HPMSVGrp FunClsAvg NumRecs CV NumSamp

78 Today s Participants Coco Briseno, California Department of Transportation, coco.briseno@dot.ca.gov Maaza Mekuria, Hawaii Department of Transportation, maaza.c.mekuria@hawaii.gov Daniel Seedah, Texas A&M Transportation Institute, d-seedah@tti.tamu.edu Stephen Cropley, Transmetric America, Inc., stephen.cropley@transmetric.com

79 Get Involved with TRB Getting involved is free! Join a Standing Committee ( Become a Friend of a Committee ( Networking opportunities May provide a path to become a Standing Committee member Sponsoring committee: ABJ60 For more information: Create your account Update your profile

80 Receiving PDH credits Must register as an individual to receive credits (no group credits) Credits will be reported two to three business days after the webinar You will be able to retrieve your certificate from RCEP within one week of the webinar