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An Integrated Tour-based Truck Travel Forecasting Model

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  1. An Integrated Tour-basedTruck Travel Forecasting Model Ian Harrington Central Transportation Planning Staff Boston, Massachusetts

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. Regional Truck Tour Ends Number 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

  8. Regional Truck Tour Ends Number of trucks per employee by industrial sector based on CTPS survey Average Sector Trucks/Emp Government 0.060 Manufacturing 0.045 Agric, Mining, & Constr 0.539 Transport, Comm, & Util 0.262 Service 0.030 Fin, Insur, & Real Estate 0.003 Retail 0.039 Wholesale 0.147 0.076

  9. Regional Truck Tour Ends Cross-classification of trucks by use category and industry based on CTPS field observations Hhld LTL & Food & Pickup Sector Tankers Goods Truckload Warehouse Intermodal Package Heavy Retail and Van Government 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%

  10. Regional Truck Tour Ends Trucks in Government and Manufacturing industries have distinct distributions by use category Hhld LTL & Food & Sector Tankers Goods Truckload Warehouse Intermodal Government 0.0% 0.0% 0.0% 0.0% 0.0% Manufacturing 0.0% 0.0% 0.0% 42.2% 0.0% Pickup Sector Package Heavy Retail and Van Government 20.0% 48.0% 0.0% 32.0% Manufacturing 0.0% 31.0% 1.7% 25.0%

  11. Regional Truck Tour Ends Operational data from TIUS/VIUS data for Massachusetts Days Tours Active per Day Tankers 61.0% 2.01 Household Goods 63.8% 0.9 LTL/TL 91.2% 0.9 Food/Warehouse 81.5% 1 Intermodal 88.5% 0.95 Package 81.5% 1.2 Heavy 68.8% 1.15 Retail 94.0% 1.1 Pickup/Van 86.9% 1.3

  12. Intermediate Starts and Stops Based upon truck trip generation rates in literature with adjustments for Eastern MA 1995 Intermediate 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

  13. Intermediate Starts and Stops Truck trips generated per employee at government and manufacturing worksites Hhld LTL Food & Inter- Tankers Goods /TL Warehouse modal Government 0.0034 0.0004 0 0.05 0 Manufacturing 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 0.2188 Manufacturing 0.05 0.06 0.021 0.15 0.4283

  14. Intermediate Starts and Stops Supply of intermediate starts and stops based on operational data: S&S = Stops/Tour * Tour Ends/2 Stops Stops per Tour per Tour Tankers 7 Package 21 Household Goods 2 Heavy 4 LTL/Truckload 4 Retail 6 Food & Warehouse 14 Business PU/Van 4 Intermodal 2

  15. Intermediate Starts and Stops Intraregional truck tour starts and stops: Intra S&S = Tour Ends/2 * (1 - % Tours Ext) * Stops/Tour Pct Trips Pct Trips External 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%

  16. 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

  17. Intermediate Starts and Stops External truck intermediate starts and stops: Ext S&S = Total S&S – Intra S&S – Local IX S&S

  18. 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

  19. 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

  20. 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

  21. 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

  22. Truck Trip Distribution Match appropriate pairs of trip productions and attractions for intraregional and through truck trips TAZ A Ext A TAZ B Extern B Attrs Attrs Attrs Attrs TAZ A P:Local Reg TEs Prods A:Local Reg S&Ss Ext A Prods TAZ B P:Local Reg S&Ss P:Local Reg S&Ss Prods A:Local Reg TEs A:Local Reg S&Ss Ext B P:Thru TEs Prods A:Thru TEs a

  23. Truck Trip Distribution Match appropriate pairs of trip productions and attractions for interregional truck trips TAZ A Ext A TAZ B Extern B Attrs Attrs Attrs Attrs TAZ A P:Reg IX S&Ss P:Reg IX S&Ss Prods A:Reg IX Ext S&Ss A:Reg IX Ext TEs P:Reg IX Ext TEs Ext A A:Reg IX S&Ss Prods TAZ B P:Ext S&Ss P:Ext S&Ss Prods A:Ext S&Ss A:Ext TEs Ext B P:Ext TEs Prods A:Ext S&Ss a

  24. 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 functions Three 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

  25. 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

  26. Summary • Now our truck travel forecasting model is sensitive to changes in regional demographic characteristics, infrastructure, tolls, and the regional transportation system.

  27. Contact Information Ian Harrington ianh@ctps.org Chief Transportation Planner David S. Kruse dkruse@ctps.org Central Transportation Planning Staff to the Boston Region Metropolitan Planning Organization (www.bostonmpo.org)