1 New Truck Models National Capital Region TPB Travel Forecasting Subcommittee William G. Allen, Jr., P.E. Transportation Planning Consultant 18 July 2008

2 Timeline Feb. 04 – Apr. 07: COM model developedFeb. 04 – Apr. 07: COM model developed 18 May 2007: COM presentation to TFS18 May 2007: COM presentation to TFS May 2007: truck models startedMay 2007: truck models started Jan. 2008: truck models completedJan. 2008: truck models completed Jan. – Jul. 08: TPB truck model testingJan. – Jul. 08: TPB truck model testing 23 May 2008: TPB truck presentation to TFS23 May 2008: TPB truck presentation to TFS

3 Vehicle Types Commercial: Light-duty vehicle (car, van, pickup) used for non-personal transportationCommercial: Light-duty vehicle (car, van, pickup) used for non-personal transportation Medium Truck: 2 axles, 6 tires (FHWA class 5)Medium Truck: 2 axles, 6 tires (FHWA class 5) Heavy Truck: 3+ axles (FHWA classes 4 and 6-13)Heavy Truck: 3+ axles (FHWA classes 4 and 6-13) –Includes Buses

4 Definitions Heavy Truck: 3+ axles, more than 6 tiresHeavy Truck: 3+ axles, more than 6 tires Medium Truck: 2 axle, 6 tiresMedium Truck: 2 axle, 6 tires Commercial: light duty vehicles used for businessCommercial: light duty vehicles used for business

5 Truck model history Original model developed from 1968 truck O-D surveyOriginal model developed from 1968 truck O-D survey Original truck types: light, medium, heavyOriginal truck types: light, medium, heavy Models updated in 1985, based on limited count data and 1968 surveyModels updated in 1985, based on limited count data and 1968 survey

6 A new approach Truck surveys don’t workTruck surveys don’t work Use new method developed for COM modelUse new method developed for COM model Trip-based method consistent with current modelling proceduresTrip-based method consistent with current modelling procedures Borrow a starting modelBorrow a starting model Use counts to synthesize more countsUse counts to synthesize more counts Use counts to adjust starting tripsUse counts to adjust starting trips Use trip difference to refine the starting modelUse trip difference to refine the starting model Same method used for BMC, ARC, Ohio DOTSame method used for BMC, ARC, Ohio DOT

7 Truck Counts Primary data source: MDOT countsPrimary data source: MDOT counts –6 permanent counts –315 short-term counts Secondary data sources:Secondary data sources: –DC classification counts (11) –Virginia classification counts (33) –TPB 4-hour class. counts (148) –(2003) TPB External Truck Survey (10 sites)

8 Daily truck count statistics Truck percentage: MTK=3.3%, HTK=3.2%Truck percentage: MTK=3.3%, HTK=3.2% TRK % range: 0.9% to 26.1% (US 1 in Jessup, MD)TRK % range: 0.9% to 26.1% (US 1 in Jessup, MD) TRK vol. range: 27 – 14,700 (I-95, Howard Co.)TRK vol. range: 27 – 14,700 (I-95, Howard Co.) Approx. TOD split: 19% AM, 14% PM, 67% OPApprox. TOD split: 19% AM, 14% PM, 67% OP

9 Synthesized Counts Model % HTK, % MTK by link using count dataModel % HTK, % MTK by link using count data Logit function: % TRK = 1 / (1 + e U )Logit function: % TRK = 1 / (1 + e U ) U  lanes, facility type, area type, jurisdictionU  lanes, facility type, area type, jurisdiction Apply to all links with countsApply to all links with counts TRK “count” = est % TRK * countTRK “count” = est % TRK * count Thorough manual reviewThorough manual review Use actual counts where availableUse actual counts where available

10 % TRK analysis findings Synthesizing counts provides data for DC and VASynthesizing counts provides data for DC and VA % TRK goes up with:% TRK goes up with: –Less developed areas –Higher facility types –Increasing lanes (MTK); decreasing lanes (HTK)

11 Borrow a starting model Simple linear regression model, from BMC modelSimple linear regression model, from BMC model Based on employment by type (industrial, office, retail, other) and HHsBased on employment by type (industrial, office, retail, other) and HHs Adjustments for area type, truck zoneAdjustments for area type, truck zone F’s from BMC and Quick Response Freight ManualF’s from BMC and Quick Response Freight Manual TOD percentages from MDOT count dataTOD percentages from MDOT count data

12 Truck Zones Zones with identifiable truck generatorsZones with identifiable truck generators Business districts, warehouses, manufacturing, transfer, airport, deliveryBusiness districts, warehouses, manufacturing, transfer, airport, delivery 1/0 flag1/0 flag 35 zones identified35 zones identified 3-5 times higher truck trip rate per job3-5 times higher truck trip rate per job

13 Model Statistics Retail, Industrial empl are most importantRetail, Industrial empl are most important Higher trip rate (per empl) in less developed areasHigher trip rate (per empl) in less developed areas External share  distance from cordonExternal share  distance from cordon 2005 trip totals: MTK=474 K, HTK=192 K, total=666 K2005 trip totals: MTK=474 K, HTK=192 K, total=666 K Avg. trip length: MTK=24 min., HTK=58 min., total=34 min.Avg. trip length: MTK=24 min., HTK=58 min., total=34 min. Prior model: 553K trips, 43 min. avgPrior model: 553K trips, 43 min. avg

14 “Adaptable Assignment” Assign trips Skim loads & counts Adjust trips Final trip table Delta trip table Repeat (7 iter.) Starting trip table Starting model Inform

15 Delta analysis Subtract starting trips from new tripsSubtract starting trips from new trips Analyze trip end summary of differenceAnalyze trip end summary of difference Correlate with HH, employmentCorrelate with HH, employment Use to inform model (revise coeffs.)Use to inform model (revise coeffs.) Keep “delta” table as adjustmentKeep “delta” table as adjustment

16 Calibration adjustment O/D table of mostly small adjustmentsO/D table of mostly small adjustments Accounts for random error in assignmentAccounts for random error in assignment Table totals: MTK=7.8 K, HTK=25.7 KTable totals: MTK=7.8 K, HTK=25.7 K Tend to be short trips; no other patternTend to be short trips; no other pattern Carried along for forecasting, added to model’s starting trip tableCarried along for forecasting, added to model’s starting trip table

17 Validation results (2005) Prior model (v2.1D, fall 2005)Prior model (v2.1D, fall 2005) –% RMSE: 104%, volume/count: 1.16 –553 K trips Starting modelStarting model –% RMSE: 111%, volume/count: 1.33 –632 K trips Final modelFinal model –% RMSE: 51%, volume/count: 1.07 –666 K trips

18 More results 2005 VMT2005 VMT –Current: 11.4 M –New: 10.8 M (-5%) –Trips go up, average length goes down 2030 estimate2030 estimate -Trips: 916 K (+38%) -VMT: 17.3 M (+60%)

19 Conclusions TPB wanted a cost-effective, practical, proven approachTPB wanted a cost-effective, practical, proven approach Goods movement approach not readyGoods movement approach not ready Truck trips are complex -- not suited to an aggregate four-step approachTruck trips are complex -- not suited to an aggregate four-step approach Truck travel is related to national policy and macroeconomic factors beyond our knowledgeTruck travel is related to national policy and macroeconomic factors beyond our knowledge Don’t wait 20 years to revisit the truck modelsDon’t wait 20 years to revisit the truck models