ODOT Freight Modeling

Presented to the Ohio Conference on Freight

Toledo, OHSeptember 18, 2007

ByGregory Giaimo, PE

Ohio Department of Transportation

Context of Freight Modeling at State DOT’s

• Part of a larger statewide passenger and freight model

• Developed primarily to study intercity highway corridors

• Prior to 1990’s, very few such models due to lack of computers and methods

• Since then about half the states have developed or are developing models

Statewide Model Status

Source: NCHRP Synthesis 358, Statewide Travel Forecasting Models

Freight Model Types

• Freight modeling is handled in one of four ways by state DOT models

1. None

2. Traditional “4 Step” Techniques

3. Commodity Based

4. Integrated Land Use/ Economic/ Commodity Based

Source: TRB Electronic Circular E-C075: Statewide Travel Demand Modeling – A Peer Exchange

Freight Model Type by Peer Exchange Participants and

NonParticipants

0

1

2

3

4

5

6

7

8

9

None

Tradit

ional

Comm

odity

Econo

met

ric

Unkno

wn

Not

Peer Exchange

Statewide Models with No Freight Component

• Some small states have models exactly analogous to urban passenger travel demand models with no freight model

Commodity Based Models

• This approach models commodity flows

• These flows are then converted to trucks, trains etc., generally using static mode and payload factors by commodity

• This is the most common approach

Commodity Based Models (cont.)

• Obtain their commodity flow data from the Commodity Flow Survey or the Transearch database

• The Vehicle Inventory and Use survey is often used to develop payload factors

Integrated Land Use/ Economic/ Commodity Models

• This approach also models commodity flows

• The main difference from the previous type is the explicit econometric and land use models which feed commodity flows to the transport models

• Thus base year commodity flows are used to estimate these economic models instead of as direct model inputs

Ohio Model

• The five components directly related to the creation of freight flows will be hi-lighted:

1. Interregional Economic Model2. Land Use Model3. Activity Allocation Model4. Aggregate Commercial Vehicle Model5. Disaggregate Commercial Vehicle Model

Disaggregate Household Synthesis and

Employment Spatial Disaggregation Models

Ohio Integrated Land Use/Economic/Transport Model

Aggregate Commercial

Vehicle Model

Disaggregate Commercial

Vehicle Model

Interregional Economic

Model

Aggregate Demographic

Model

Land Development

Model

Activity Allocation

Model

Visitor ModelLong Distance Travel Model

Short Distance Travel Model

Assignment Model

Model Modules• Interregional economic model of production & consumption by

economic sector reflecting national forecasts

• Demographic model tied to economic activity reflecting migration and changes in population & household composition

• Activity allocation model to distribute model area economic and demographic forecasts to analysis zones with the related flows of goods & labor among zones from which travel demands are derived

• Land development model simulating developer behavior in response to demands & costs consistent with other development constraints

• Personal & household travel model reflecting person & household characteristics, zonal characteristics, inter-zonal economic flows & transport system supply characteristics, 2 components: short distance which looks like an activity/tour based urban area model and long distance, also tour based with purposes: business, recreation, other

Model Modules• Aggregate model of goods and services transport arising from

economic and demographic activity by zone very similar to the typical DOT commodity based transport model

• Disaggregate model of business-related person travel related to management functions, sales & support activities, provision of services and some short distance goods delivery.

• Model of visitor travel within and into the model area made by non-residents

• Transport system supply model incorporating air, intercity bus/rail, MPO transit & roadway networks with their corresponding level-of-service characteristics

Highway Network

Rail Network & Intermodals

Interregional Economic Model

• Establishes forecast flows of goods, services and labor (in $) between 14 regions of North America

• Uses exogenous national economic conditions and production composite utilities from the previous time step of the lower level models

• An inter-regional social accounting matrix based primarily upon IMPLAN data

Industry Employee Proprietor Indirect Total Output* Employment Compensation* Income* Income* Business Tax* Value Added*

Region1 $716,166 7,966,019 $228,234 $21,666 $97,448 $27,562 $374,910Region2 $549,640 5,250,326 $175,241 $11,328 $71,412 $19,524 $277,505Region3 $1,631,352 16,534,837 $580,641 $70,729 $272,386 $75,873 $999,630Region4 $1,258,568 12,878,897 $444,828 $47,631 $217,457 $61,111 $771,027Region5 $1,315,875 15,632,564 $464,473 $40,713 $211,292 $57,678 $774,155Region6 $159,981 1,927,710 $48,863 $5,282 $21,446 $7,229 $82,820Region7 $1,578,235 19,633,779 $533,452 $55,056 $245,220 $72,198 $905,927Region8 $277,576 3,077,661 $85,579 $8,885 $36,968 $9,938 $141,370Region9 $987,168 10,362,852 $323,315 $32,811 $149,933 $41,378 $547,438

Region10 $3,841,148 43,334,759 $1,251,396 $172,516 $613,615 $173,929 $2,211,456Region11 $1,814,957 20,563,180 $554,248 $84,581 $305,219 $80,778 $1,024,826

*Millions of dollars

$10,000$11,000$12,000$13,000$14,000$15,000$16,000$17,000$18,000$19,000$20,000

2005 2010 2015 2020 2025 2030

Bil

lio

ns Slow Growth

Moderate Growth

High Growth

Nation Economic Forecast Variables

National Economic Growth

Exogenous Economic Indicators

Industry Categories

1. Agriculture, Forestry, Fisheries2. Primary Metals (Steel)3. Light Industry4. Heavy Industry5. Transportation Equipment (Auto)6. Wholesale7. Retail8. Hotel9. Construction10. Health11. Transportation Handling12. Utilities13. Other Services14. Grade School Education15. Post-Secondary Education16. Government

Land Use Model

• Creates developed floor space by category by zone

• Land develops (if possible) in response to increases in households and employment in the previous analysis year (see activity allocation model) but also due to:

– Zoning– Flood plains– Slopes– School district quality

Water Service

Flood Plains

Severe Slope

Activity Allocation Model

• Subdivides activity to 5000 traffic analysis zones

– Population– Employment– Labor Flow– Commodity Flow

• Uses transport utility equations relying on accessibilities and changes in developed land to redistribute activities from year to year

Activity Allocation Model

• Inputs include:

– Regional flows from Interregional Economic Model

– Floor space by category by TAZ from Land Use Model

– Households from Aggregate Demographic Model

– Transport costs from previous iteration of Transport Models

Aggregate Commercial Vehicle Model

• With the commodity flows established, the aggregate commercial vehicle model itself is very similar to the commodity representation in other statewide models

• Input is dollars of flow of goods and labor at the Traffic Analysis Zone (TAZ) level

• Output is flows of trucks between TAZ’s

Aggregate Commercial Vehicle Model Flow Chart

Determine Mode

Convert Goods Flows

to Tons

Total Dollars flows

Determine Truck Type

Determine Number of

Truck Loads

Determine Trucks by

Hour of Day

Based on traffic counts, conversion from annual to weekday assumes 300 equivalent week days per year. This value is obtained as follows: (52 * 5) weekdays plus (52 * 2 * 0.44) weekday equivalents for weekends minus 6 holidays.

Trucks by type by hour by OD

TAZ

Fixed shares by commodity class, by distance for bulk commodities, mode choice model for inter-modal eligible commodities, based on CFS

By commodity class and distance, from CFS

By commodity class and distance, from VIUS

By commodity class and truck type, from VIUS

Truck Mode Shares by Distance and Commodity

SCTG DESCRIPTION < 5

0

50 to 9

9

100

to 2

49

250

to 4

99

500

to 7

49

750

to 9

99

1000

or m

ore

TO

TA

L

01 Live animals and fish 850 1,000 1,040 1,190 1,380 1,630 1,590 1,050 02 Cereal grains 110 110 140 150 500 550 1,030 120 03 Other ag products 520 520 810 790 580 720 1,000 610 04 Animal feed and products 220 350 380 520 470 830 1,170 310 05 Meat/fish/seafood 2,410 2,130 2,040 2,090 2,300 2,720 2,760 2,310 06 Milled grain and bakery products 1,210 1,160 1,220 1,210 1,350 1,350 1,440 1,240 07 Prepared foodstuffs, n.e.c. 770 800 910 1,150 1,420 1,580 1,720 920 08 Alcoholic beverages 1,260 1,180 920 870 1,000 820 1,350 1,140 09 Tobacco products 9,260 11,680 13,150 26,200 29,690 31,440 31,380 13,690 10 Monumental or building stone 100 230 360 320 580 650 1,070 160 11 Natural sands 10 10 30 80 290 - 600 10 12 Gravel or crushed stone 10 10 10 10 - 10 - 10 13 Non-metallic minerals, nec 20 90 140 190 170 160 280 50 14 Metallic ores 180 - 630 1,340 1,150 1,660 9,860 630 15 Coal 20 20 40 50 120 170 - 30 17 Gasoline and aviation fuel 280 260 260 290 - 250 - 280 18 Fuel oils 230 190 200 220 230 180 - 220 19 Petroleum products, n.e.c. 110 240 240 450 440 730 690 150 20 Basic chemicals 490 390 600 1,170 1,730 1,580 7,830 750 21 Pharmaceutical products 19,230 26,980 31,330 20,790 14,860 23,020 25,070 22,290 22 Fertilizers 190 180 210 220 210 250 320 190 23 Chemical products 2,310 1,980 1,970 2,270 2,710 3,100 3,710 2,410 24 Plastics and rubber 2,360 1,750 1,870 2,670 2,900 3,010 3,630 2,440 25 Forest products 30 30 70 - - 440 1,050 40 26 Wood products 330 280 460 530 750 1,000 1,290 410 27 Pulp/newsprint/paper 1,020 210,310 750 850 790 760 1,010 960 28 Converted paper products 1,110 1,110 1,320 1,660 1,890 1,850 2,280 1,340 29 Printed products 2,010 3,880 5,280 4,390 4,520 6,760 5,900 3,220 30 Textiles and leather products 6,710 8,510 6,460 7,620 8,830 10,740 13,260 8,230 31 Non-metallic mineral products 60 140 240 480 780 900 1,440 120 32 Base metals 720 750 900 1,110 1,350 1,790 2,510 940 33 Metal articles 2,330 1,940 1,950 2,140 2,190 2,170 4,050 2,270 34 Machinery 7,800 8,310 7,270 8,160 8,210 9,340 10,220 8,250 35 Computer equip. and software 20,990 16,760 17,150 15,310 15,140 23,000 28,350 20,040 36 Vehicles and parts 4,510 5,530 5,450 5,470 6,450 7,200 7,440 5,450 37 Transport equipment, n.e.c. 27,040 21,280 11,160 11,350 13,140 22,280 47,590 18,830 38 Precision instruments 54,400 27,600 39,850 50,200 37,240 64,300 68,480 50,890 39 Furniture and furnishings 5,330 4,440 4,590 4,680 4,610 4,780 5,120 4,880 40 Misc. manufactured products 1,620 3,850 3,970 5,080 6,080 6,860 9,800 3,630 41 Waste or scrap 160 140 240 320 400 680 580 200 43 Mixed freight 1,960 1,960 2,270 2,640 1,960 209,620 3,600 2,110

TOTAL 360 650 1,220 2,050 2,760 3,310 5,760 760

Dollar to Ton Conversion by Distance and Commodity

Truck Type by Distance and Commodity

VIUS2002 VEHICLE SIZEPROD# SCTG# SCTG DESCRIPTION LT MED LTHVY HVY ALL

01 01 Live animals and fish 1.25 2.64 5.22 20.02 14.8003 02 Cereal grains 1.80 3.45 6.77 19.03 16.5604 03 Other ag products 1.25 2.48 5.10 17.16 12.8402 04 Animal feed and products 1.09 3.00 5.48 18.75 13.8011 05 Meat/fish/seafood 0.79 2.13 4.20 20.24 15.9210 06 Milled grain and bakery products 0.93 1.47 4.41 18.53 7.4113 07 Prepared foodstuffs, n.e.c. 1.02 2.15 4.97 17.49 13.9309 08 Alcoholic beverages 1.05 2.14 4.67 14.00 11.3112 09 Tobacco products 0.88 1.39 6.50 18.37 8.3436 10 Monumental or building stone 1.09 2.24 4.83 19.10 16.1237 11 Natural sands 1.39 2.85 5.02 18.04 15.6434 12 Gravel or crushed stone 1.41 3.05 5.62 18.78 17.3621 13 Non-metallic minerals, nec 1.04 1.98 4.55 18.15 16.6735 14 Metallic ores - 3.51 5.00 22.64 20.3132 15 Coal 1.14 3.13 3.70 26.79 25.3440 17 Gasoline and aviation fuel 1.63 2.88 2.86 26.22 24.7939 18 Fuel oils 1.21 2.95 5.09 15.65 13.6842 19 Petroleum products, n.e.c. 0.92 2.56 4.35 15.42 12.0905 20 Basic chemicals 1.09 1.94 4.26 18.63 15.0907 21 Pharmaceutical products 1.00 2.15 3.77 10.08 3.6706 22 Fertilizers 0.98 3.01 5.70 14.75 11.6108 23 Chemical products 1.03 2.21 4.95 18.16 12.5441 24 Plastics and rubber 0.92 2.23 3.19 16.19 9.7414 25 Forest products 1.15 2.55 5.51 23.02 20.1018 26 Wood products 1.05 2.29 4.69 18.67 11.9817 27 Pulp/newsprint/paper 0.91 1.60 3.59 21.13 18.6315 28 Converted paper products 1.17 1.90 4.02 18.47 14.5216 29 Printed products 1.20 2.01 3.79 13.09 5.7929 30 Textiles and leather products 1.07 1.61 4.19 18.79 9.2038 31 Non-metallic mineral products 1.42 2.99 6.08 18.79 16.7720 32 Base metals 1.03 1.82 4.33 19.61 13.9919 33 Metal articles 0.86 1.66 3.68 15.25 7.9626 34 Machinery 0.98 1.81 4.22 18.62 14.9624 35 Computer equipment and software 0.81 1.51 3.87 14.81 6.0730 36 Vehicles and parts 1.23 2.11 3.97 15.66 8.8531 37 Transport equipment, n.e.c. 1.21 2.22 4.92 18.39 15.9528 38 Precision instruments 0.90 1.36 4.79 14.19 5.5425 39 Furniture and furnishings 0.72 1.55 3.60 14.87 6.90

22, 23, 27 40 Misc manufactured products 0.86 1.82 3.78 13.47 5.5144, 45 41 Waste or scrap 0.95 2.11 4.28 12.43 9.87

49 43 Mixed freight 0.94 2.03 3.82 17.90 16.7243 X2 Hazardous Waste 1.21 2.11 4.48 16.67 12.5246 X3 Mail 0.98 2.79 5.40 16.04 6.1247 X4 Empty Containers 0.91 1.55 2.28 13.74 9.7248 X5 Passengers 0.88 1.05 3.53 0.06 1.0950 X6 Multiple Categories 0.92 1.83 4.03 16.19 8.9499 X7 Other 1.09 3.25 5.42 14.55 12.51

ALL 0.92 2.09 4.65 17.08 11.86

Payload Factors by Distance and Commodity

Disaggregate Commercial Vehicle Model

• DCOM is designed to account for short distance commercial travel not related to the long distance shipping of freight (accounted for in ACOM)

• Long distance business travel is accounted for in the Long Distance Travel model of the personal transport model since these trips were obtained in the special long distance travel survey

Disaggregate Commercial Vehicle Model

• Employs a tour based microsimulation of employees

• Based on establishment surveys

• Analogous to HH based tour based model but based at the place of work

• Does not include route delivery vehicles

Zonal Land Use Data

Worker Traveler Generation

Vehicle Assignment

Starting Time Assignment

Post-Processor

Next Stop Purpose Choice

Model

Next Stop Location

Choice Model

Dynamic Activity Pattern Generation

Commercial Vehicle Trip List

Zonal Land Use Data

Worker Traveler Generation

Vehicle Assignment

Starting Time Assignment

Post-Processor

Next Stop Purpose Choice

Model

Next Stop Location

Choice Model

Dynamic Activity Pattern Generation

Commercial Vehicle Trip List

Disaggregate Commercial Vehicle Model

Disaggregate Commercial Vehicle Model

Employment categorized as:

• Industrial• Wholesale• Retail• Transportation Handling• Service

Disaggregate Commercial Vehicle Model

Trip purposes:

• Service• Meeting• Goods (delivery)• Other (includes such things as stopping

for lunch or fuel)

Outputs

Forecast Volumes

Traffic Flow Maps

District 2 Volumes Including Interstate

District 2 Volumes Excluding Interstate

Toll Sensitivity Analysis Showing Volumes Changes

Congestion Management

Daily VMT

0

5000000

10000000

15000000

20000000

25000000

30000000

1 2 3 4 5 6 7 8 9 10 11 12

Congested

Uncongested

By ODOT Districts

For Ohio Counties

Congestion Comparisons

User Costs by Alternative2035 Study Area Internal User Cost Com parison

$0.000

$10.000

$20.000

$30.000

$40.000

$50.000

$60.000

$70.000

$80.000

$90.000

$100.000

EXISTING NOBUILD ALT2 ALT3 ALT4 ALT5 ALT6

Alternative

Mill

ion

s $'

s

Vehicle Cost

Time Cost

Crash Cost

Predicted Changes by Economic Sector

Agriculture Production ($M)

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

2000 2005 2010 2015 2020 2025 2030

Primary Metal Products Production ($M)

0

20,000

40,000

60,000

80,000

100,000

120,000

2000 2005 2010 2015 2020 2025 2030

Total Economic Output ($M)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

2000 2005 2010 2015 2020 2025 2030

Employment Forecasts

  ODJFS Emp Forecast (Ohio) ISAM Emp Forecast (Ohio+Halo)

OSMP Industries 2002 2012 %Change 2002 2012mid %Change

Agriculture 92,500 85,100 -8% 184,588 174,443 -5%

Heavy Industry 493,100 473,000 -4% 749,212 705,277 -6%

Construction 235,700 269,100 14% 524,411 596,698 14%

Light Industry 180,900 177,900 -2% 310,594 303,279 -2%

Primary Metal Products 61,500 53,500 -13% 106,424 91,873 -14%

Transportation Equipment 159,900 147,900 -8% 179,874 166,250 -8%

Wholesale 239,100 261,400 9% 394,184 425,545 8%

Retail 1,020,800 1,138,000 11% 1,504,488 1,661,036 10%

Transportation Handling 160,700 184,700 15% 272,796 310,027 14%

Utilities Services 23,500 20,000 -15% 155,928 136,355 -13%

Other Services 1,321,800 1,520,100 15% 2,209,674 2,519,592 14%

Education 76,400 84,100 10% 730,246 829,958 14%

Health Care 622,800 757,300 22% 801,801 964,788 20%

Hotel and Accommodation 34,900 37,600 8% 55,383 59,553 8%

Government and Other 756,500 828,600 10% 334,501 368,899 10%

Education + Government 832,900 912,700 10% 1,064,747 1,198,857 13%

TOTAL 5,813,800 6,376,100 10% 8,514,104 9,313,573 9%

Interaction of Ohio’s Economy with the Rest of the US

Commodity Production

Changes in Commodity Production

Future Challenges

• Modeling community would like to move to more detailed freight modeling based upon econometrics and supply chains

• The main challenge that plagues this as well as current modeling efforts is the lack of geographically specific freight data

Top 10 Challenges Impeding Development of Freight Models

by State DOT’s1. Lack of DATA2. Lack of DATA3. Lack of DATA4. Lack of DATA5. Lack of DATA6. Lack of DATA7. Lack of DATA8. Lack of DATA9. Lack of Money10.Lack of better theoretical formulations (but

see 1-8 for why this is the case)

Questions?