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An Integrated Tour-basedTruck Travel Forecasting Model
Ian Harrington
Central Transportation Planning Staff
Boston, Massachusetts
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Outline of Presentation
• Why prepare a new truck model?• Identifying available data• Trip generation model structure• Trip distribution model structure• Trip table adjustment• Forecasting future truck travel
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Why Prepare a New Truck Model?
• Previous truck trip tables based on old survey data
• Using truck trip tables allows for no estimation of impact of changes in demographics, infrastructure, tolls, or other changes in regional transportation system
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Data Available forTruck Travel Forecasts
• Truck ownership data• Truck/Vehicle Inventory and Use Surveys• Residential location and characteristics• Survey of sample of local businesses• Field observations of trucks• Truck trip generation rates• Interregional truck trip table• Vehicle classification counts
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Trip Generation Model Structure
Trucks fall into the following use categories:• Tankers• Household Goods• Truckload/Less-than-Truckload• Food and Warehouse Distribution• Intermodal• Package• Heavy• Retail• Pickup/Van
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Trip Generation Model Structure
Truck tours consist of the following trip types:• Regional Truck Tour Ends• Intermediate Starts and Stops• Regional Truck Entrances/Exits• External Truck Entrances/Exits• Through Truck Entrances/Exits
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Regional Truck Tour EndsNumber of truck tour ends is a function of:• Number of trucks• Number of tours per day• Portion of days each truck active
TE = 2 * Trucks * Tours * % Days Active Day
Estimated for each truck use category
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Regional Truck Tour Ends
Number of trucks per employee by industrial sector based on CTPS survey
AverageSector Trucks/EmpGovernment 0.060Manufacturing 0.045
Agric, Mining, & Constr 0.539Transport, Comm, & Util 0.262
Service 0.030Fin, Insur, & Real Estate 0.003
Retail 0.039Wholesale 0.147
0.076
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Regional Truck Tour Ends
Cross-classification of trucks by use category and industry based on CTPS field observations
Hhld LTL & Food & PickupSector TankersGoods TruckloadWarehouseIntermodalPackage Heavy Retail and VanGovernment 0.0% 0.0% 0.0% 0.0% 0.0% 20.0% 48.0% 0.0% 32.0%Manufacturing 0.0% 0.0% 0.0% 42.2% 0.0% 0.0% 31.0% 1.7% 25.0%AMC 0.3% 0.0% 0.0% 0.3% 0.0% 0.0% 42.1% 0.3% 57.2%TCU 2.7% 13.2% 34.2% 1.5% 4.0% 11.9% 13.5% 0.2% 18.8%Service 0.7% 0.0% 0.0% 1.2% 0.0% 0.0% 27.6% 0.5% 69.8%FIRE 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 23.1% 0.0% 76.9%Retail 19.9% 0.0% 0.0% 11.2% 0.0% 0.0% 2.7% 53.4% 12.8%Wholesale 5.9% 0.0% 0.0% 78.6% 0.0% 0.0% 2.7% 5.9% 6.8%
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Regional Truck Tour Ends
Trucks in Government and Manufacturing industries have distinct distributions by use category
Hhld LTL & Food &Sector TankersGoods TruckloadWarehouseIntermodalGovernment 0.0% 0.0% 0.0% 0.0% 0.0%Manufacturing 0.0% 0.0% 0.0% 42.2% 0.0%
PickupSector PackageHeavy Retail and VanGovernment 20.0% 48.0% 0.0% 32.0%Manufacturing 0.0% 31.0% 1.7% 25.0%
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Regional Truck Tour EndsOperational data from TIUS/VIUS data for
MassachusettsDays Tours
Active per DayTankers 61.0% 2.01
Household Goods 63.8% 0.9LTL/TL 91.2% 0.9
Food/Warehouse 81.5% 1Intermodal 88.5% 0.95Package 81.5% 1.2Heavy 68.8% 1.15Retail 94.0% 1.1Pickup/Van 86.9% 1.3
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Intermediate Starts and Stops
Based upon truck trip generation rates in literature with adjustments for Eastern MA
Hhld LTL Food & Inter- PU/Tankers Goods /TL Warehouse modal Package Heavy Retail Van Total
Government 0.0034 0.0004 0 0.05 0 0.04 0.02 0.015 0.09 0.219
Manufacturing 0.004 0.0003 0.05 0.09 0.003 0.05 0.06 0.021 0.15 0.428
Agric, Mining, & Constr 0.003 0.00005 0.05 0.05 0 0.03 0.03 0.02 0.1 0.283
Transport, Comm, & Util 0.0035 0.0003 0.05 0.05 0.001 0.044 0.044 0.01 0.05 0.253
Service 0.0017 0.0004 0 0.05 0 0.06 0.019 0.015 0.09 0.236
Fire, Insur, & Real Estate 0.003 0.0005 0 0.05 0 0.05 0.02 0.015 0.09 0.229
Retail 0.003 0.0002 0.01 0.53 0.0003 0.04 0.02 0.01 0.09 0.704
Wholesale 0.002 0.0001 0.05 0.06 0.0023 0.04 0.02 0.01 0.11 0.294
Households 0.0095 0.0009 0 0.002 0 0.03 0.035 0.015 0.121 0.213
Group Quarters 0.0010 0.0011 0 0.0008 0 0.0115 0.0035 0.0058 0.0465 0.070
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Intermediate Starts and Stops
Truck trips generated per employee at government and manufacturing worksites
Hhld LTL Food & Inter-Tankers Goods /TL Warehousemodal
Government 0.0034 0.0004 0 0.05 0Manufacturing 0.004 0.0003 0.05 0.09 0.003
PU/Package Heavy Retail Van Total
Government 0.04 0.02 0.015 0.09 0.2188Manufacturing 0.05 0.06 0.021 0.15 0.4283
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Intermediate Starts and Stops
Supply of intermediate starts and stops based on operational data:
S&S = Stops/Tour * Tour Ends/2
Stops Stopsper Tour per Tour
Tankers 7 Package 21Household Goods 2 Heavy 4LTL/Truckload 4 Retail 6Food & Warehouse 14 Business PU/Van 4Intermodal 2
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Intermediate Starts and Stops
Intraregional truck tour starts and stops:
Intra S&S = Tour Ends/2 * (1 - % Tours Ext)
* Stops/Tour
Pct Trips Pct TripsExternal External
Tankers 24.0% Package 2.0%Household Goods 16.5% Heavy 11.0%LTL/Truckload 39.3% Retail 5.0%Food & Warehouse 8.5% Business PU/Van 18.0%Intermodal 50.0%
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Intermediate Starts and Stops
Regional truck interregional tour
starts and stops:
Reg IX S&S = Tour Ends/2 * % Tours Ext
* Stops/Tour
Assume interregional tours have one-half the number of stops per tour within region
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Intermediate Starts and Stops
External truck intermediate starts and stops:
Ext S&S = Total S&S – Intra S&S
– Local IX S&S
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Regional Truck Entrances/Exits
Regional truck interregional tour external tour ends:
Reg IX Ext TE = 2 * Reg IX S&S Stops/Tour
Assume interregional tours have one half the number of stops per tour within region
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External Truck Entrances/Exits
External truck tour ends
Ext TE = 2 * Ext S&S Stops/Tour
Assume interregional tours have one-half the number of stops per tour within region
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Through Truck Entrances/Exits
Based on external survey truck volumes, subtract estimated crossings from total
Thru TE = Tot Vol – Reg IX Ext TE – Ext TE
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Truck Trip Distribution
• Use estimated trip ends and adjust initial gamma functions to match estimated regional trip length frequencies by use category based on TIUS/VIUS data for Massachusetts and an interregional trip table
• Use double-TAZ setup to match appropriate trip end pairs in trip tables
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Truck Trip Distribution
Match appropriate pairs of trip productions and attractions for intraregional and through truck trips
TAZ A Ext A TAZ B Extern BAttrs Attrs Attrs Attrs
TAZ A P:Local Reg TEsProds A:Local Reg S&Ss
Ext AProds
TAZ B P:Local Reg S&Ss P:Local Reg S&SsProds A:Local Reg TEs A:Local Reg S&Ss
Ext B P:Thru TEsProds A:Thru TEs
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Truck Trip Distribution
Match appropriate pairs of trip productions and attractions for interregional truck trips
TAZ A Ext A TAZ B Extern BAttrs Attrs Attrs Attrs
TAZ A P:Reg IX S&Ss P:Reg IX S&SsProds A:Reg IX Ext S&Ss A:Reg IX Ext TEs
Ext A P:Reg IX Ext TEs
Prods A:Reg IX S&Ss
TAZ B P:Ext S&Ss P:Ext S&SsProds A:Ext S&Ss A:Ext TEs
Ext B P:Ext TEsProds A:Ext S&Ss
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Trip Table Estimation
• Since estimated truck trip tables are based on so many assumptions, need to check distribution results
• Create set of truck vehicle counts by use category using vehicle classification counts and a cross-classification of truck use category and FHWA truck class
• Use resultant trip table as seed for new gamma functionsThree Five Six Seven Eight Nine Ten Eleven Totals
Tankers 757 2,499 587 12 336 800 43 0 5,033 2.2%Household Goods 1,722 532 12 0 67 136 0 0 2,470 1.1%LTL/Truckload 60 943 185 0 1,027 1,066 64 58 3,404 1.5%
Food & Warehouse 7,956 5,056 834 0 865 1,242 12 12 15,978 7.1%Intermodal 0 0 0 0 386 326 0 0 711 0.3%Package 9,032 3,681 125 0 0 0 0 0 12,837 5.7%Heavy 7,403 19,215 4,744 850 1,107 2,342 423 0 36,085 16.1%Retail 19,970 1,636 12 0 48 106 0 0 21,772 9.7%Business PU/Van 125,174 1,348 0 0 0 0 0 0 126,521 56.3%TOTALS 172,073 34,910 6,498 862 3,836 6,019 543 70 224,812
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Forecasting Future Truck Travel
• Apply truck trip generation model -- with future scenario employment, household, group quarters, and external station trip ends -- to estimate tour ends, starts and stops, and entrances/exits
• Apply gamma functions and productions and attractions for initial estimate of truck trip tables
• Apply trip table adjustment factors to produce future-year truck trip tables based upon future-year demographics and network characteristics
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Summary
• Now our truck travel forecasting model is sensitive to changes in regional demographic characteristics, infrastructure, tolls, and the regional transportation system.
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Contact Information
Chief Transportation Planner
David S. [email protected]
Central Transportation Planning Staff to the Boston Region Metropolitan Planning Organization (www.bostonmpo.org)