Andrew Stryker| PB | 503-417-9360 | stryker@pbworld.com

Ohio Statewide Travel Model:Framework, Freight, and Initial Calibration

11th National Transportation Planning Applications ConferenceMay 6-10, 2007, Daytona Beach, Florida

Session 6:

Acknowledgements

This presentation was primarily developed by Pat Costinett.

Topics

Ohio Statewide Modeling Framework Micro-simulation Integrates:

Economic Land use Transport Models

Aggregate Commercial Model (ACOM) Preliminary calibration results

General Model Structure

Integrated micro-simulation based Model economic activity & land use Build synthetic population

Tour-based Home tours Establishment/Work tours

Aggregate commodity movements

Model Components & Flows

SPG1

SPG2

LD

AA

ISAM JobData

ISAM Activity Data

GS GridCellData

ISAM E-E Flows, Import/Export Region Shares

PT

Floorspace Inventory by TAZ

Model Area Households by

Category

Activity Locations by TAZ, Labor Flows &

Commodity Flows by AMZ

VMModel Area Synthetic

Population

Visitor Synthetic Population

TAZ Data

ACOM

Weekday Trips/ToursEmployment by Type

Household/Person DataMC Logsums

DCOM

ASSIGNTruck Vehicle Trips by Type

Employee Trips

Loaded NetworksAuto & Transit Skims

Auto & Transit Skims

Next Time Period

SPG1

SPG2

LD

AA

ISAM JobData

ISAM Activity Data

GS GridCellData

ISAM E-E Flows, Import/Export Region Shares

PT

Floorspace Inventory by TAZ

Model Area Households by

Category

Activity Locations by TAZ, Labor Flows &

Commodity Flows by AMZ

VMModel Area Synthetic

Population

Visitor Synthetic Population

TAZ Data

ACOM

Weekday Trips/ToursEmployment by Type

Household/Person DataMC Logsums

DCOM

ASSIGNTruck Vehicle Trips by Type

Employee Trips

Loaded NetworksAuto & Transit Skims

Auto & Transit Skims

Next Time Period

Model Components & Flows

Economic Activity byGeography

ISAM Input-output economic model

Represents trading commodities Exogenous to the model system

1 = Model Area

ISAM Input-output economic model

Represents trading commodities Exogenous to the model system

Region to region commodity flows Shares of commodity flows from the model area

to regions

Economic Activity & Land Development Approximately 700 districts and 4000 zones Distribution of economic activities & flows by

sector to analysis districts Production of goods & services by zone Consumption demand for goods & services by zone Flows of commodities (goods, services & labor) among zones In response to exchange prices

Interacting with a grid-based representation of land supply, develop types, zoning, water & sewer service, flood plains, steep slopes, other protected land uses and land prices

Economic Activity & Land Development Results:

Flows of commodities between districts Floor space allocated to activities by zone

Model Components & Flows

SPG1

SPG2

LD

AA

ISAM JobData

ISAM Activity Data

GS GridCellData

ISAM E-E Flows, Import/Export Region Shares

PT

Floorspace Inventory by TAZ

Model Area Households by

Category

Activity Locations by TAZ, Labor Flows &

Commodity Flows by AMZ

VMModel Area Synthetic

Population

Visitor Synthetic Population

TAZ Data

ACOM

Weekday Trips/ToursEmployment by Type

Household/Person DataMC Logsums

DCOM

ASSIGNTruck Vehicle Trips by Type

Employee Trips

Loaded NetworksAuto & Transit Skims

Auto & Transit Skims

Next Time Period

Transport Models

Types of Trip Making Modeled

Personal Travel /Household Travel (PT): person movements arising from household (or

population) production and consumption, separated into short distance (50 mi or less) and long

distance Visitor Travel (VM):

person movements made by non-residents staying at locations in the internal model area

Business/Services Travel (DCOM): movements arising as part of the rest of the ‘business

cycle’ apart from the physical delivery of commodities Goods Transport (ACOM):

shipments of commodities arising from economic activity production and consumption

Commercial Travel Incorporates long-haul commodity shipment,

localized goods delivery, service provision & work-related tours

Long-haul shipment related directly to commodity flows

Establishment survey of goods delivery, service provision & work-related tours

Micro-simulation of commercial tours for each employee (a first at this scale)

Why a freight model?

Need to be consistent with economic models Freight movements are important to Ohio:

Interest in impact of Turnpike tolls on trucks. Interest in road-rail diversion. Relatively large impact on traffic LOS

Underlying “Theory” Commodities are carried by trucks, rail, and other

modes Commodity flow patterns determine truck flow

patterns Truck characteristics vary substantially by commodity type and shipment distance

Mode share Average value per ton Size mix Average payload weight

Unlike personal travel, commodity shipment choices are influenced very little by network LOS measures

What does it do?

ACOM translates dollar flows of commodities from ISAM and AA into truck trips by four size categories ISAM for E-E AA for I-I Both for E-I and I-E

ACOM and Economic Models Relationships

Internal to Internal

External to Internal External toExternal

Internal toExternal

ISAM

AA

AA

ISA

M

General Model Flow

Production andConsumption Weights

Distribute to Commodity Flow

Matrices

Convert toTruck Trips

by STCC

ISAM

AA

Distance

Production andConsumption Weights

Distribute to Commodity Flow

Matrices

Convert toTruck Trips

by STCC

External to External Flow

ISAM

AA

Distance

Region to regionE-E flows

by commodity

Expand regionsto ETAZs

Expand usingdistance

Production andConsumption Weights

Distribute to Commodity Flow

Matrices

Convert toTruck Trips

by STCC

Internal to Internal Flow

ISAM

AA

Distance

Districts todistricts flows

and floor space by TAZby commodity

Allocate districtsto TAZs

Expand usingdistance

Production andConsumption Weights

Distribute to Commodity Flow

Matrices

Convert toTruck Trips

by STCC

Internal to External Flow

ISAM

AA

Distance

Region shares ofcommodities

District exportsand floor space by TAZ

by commodity

Allocate districtsto TAZs,

regions toETAZs

Distribute usingsingly constrained

gravity model

$ Flows to Truck Trips by Size

Truck $’s toTruck tons

Split Truck tons by Truck Size

Convert toTruck trips

DistanceFactorsTotal $’s to Truck $’s

Convert to time periods

by STCC

Calibration

Each of the models uses a gamma function to calculate deterrence as a function of distance and three parameters

The parameters can be adjusted up or down to match trip lengths and distribution shapes

Calibration Targets Ohio county to external state for Statewide

Cordon Roadside Survey Selected MPO County to other Ohio counties truck

trips from MPO Roadside Surveys Average trip lengths by area from CFS97 and

Transearch

Average Truck Trip LengthsSTCC DESCRIPTION Intra-MA MA Origin

MA Destination Non-MA

1 Farm products 140 645 1370 23188 Forest products - - - -9 Fish/marine products - - - -10 Metallic ores - - - -11 Coal 163 355 315 41713 Petroleum/natural gas/gasoline - - - -14 Non-metallic minerals - - - -19 Ordnance - - - -20 Food and kindred products 139 654 619 121221 Tobacco products 269 874 543 104322 Textile mill products 126 566 624 136223 Apparel 142 1038 738 203724 Lumber and wood products 141 621 575 101625 Furniture and fixtures 123 809 673 140426 Pulp/paper/allied products 132 749 672 118427 Printed matter 128 631 570 132228 Chemicals and allied products 146 788 717 116429 Petroleum and coal products 149 411 375 82530 Rubber and plastics 131 786 706 118431 Leather and leather goods 152 874 1274 236332 Clay/concrete/glass/stone 140 585 479 90833 Primary metal products 120 604 467 95334 Fabricated metal products 134 712 535 108835 Machinery 139 908 788 133536 Electrical machinery 123 759 984 137137 Transport equipment 143 584 694 105838 Instruments and precision goods 100 1403 1435 194439 Misc manufactured products 123 925 1117 171040 Waste or scrap - - - -41 Miscellaneous freight shipments - - - -48 Hazardous materials or waste - - - -

TOTAL

Average Truck Trip LengthsSTCC DESCRIPTION OHIO

ADJACENT STATES

ALL OTHER STATES

ALL STATES

1 Farm products 35 220 739 2548 Forest products 38 - - 389 Fish/marine products 55 152 683 164

10 Metallic ores - - 333 8011 Coal 89 176 - 10013 Petroleum/natural gas/gasoline 29 54 - 3014 Non-metallic minerals 28 169 464 3119 Ordnance 56 202 844 38620 Food and kindred products 52 220 645 22821 Tobacco products 50 - - 4622 Textile mill products 67 193 849 40423 Apparel 67 193 849 40424 Lumber and wood products 58 185 693 13325 Furniture and fixtures 49 192 1114 39826 Pulp/paper/allied products 55 182 748 26727 Printed matter 24 225 653 11228 Chemicals and allied products 55 230 811 38329 Petroleum and coal products 32 195 682 5230 Rubber and plastics 77 164 821 42231 Leather and leather goods 67 193 849 40432 Clay/concrete/glass/stone 44 186 813 15433 Primary metal products 76 221 606 24334 Fabricated metal products 56 202 844 38635 Machinery 60 192 858 38036 Electrical machinery 44 286 1142 71737 Transport equipment 56 218 718 35038 Instruments and precision goods 52 219 896 44639 Misc manufactured products 63 236 879 45340 Waste or scrap 56 162 426 8641 Miscellaneous freight shipments 63 153 378 9348 Hazardous materials or waste 29 138 200 36

TOTAL 43 186 783 175

S3 Calibration OD Checks

Total auto and total truck trips crossing model area and Ohio cordons versus counts

Ohio county to external state auto and truck trips versus roadside survey for Ohio cordon

For counties entirely within MPO roadside survey cordon, OD flows to counties entirely outside MPO cordon versus MPO roadside survey

MPO Roadside Survey Cordons

OD Analysis Districts

Initial results for auto vehicle trip OD (1)

-50000

0

50000

100000

150000

200000

250000

300000

0 50000 100000 150000 200000 250000 300000

MODEL

OBSERVED

MODEL versus OBSERVED AUTO VEHICLE OD FLOWS

Initial results for auto vehicle trip OD (2)

-25000

0

25000

50000

75000

100000

125000

150000

0 25000 50000 75000 100000 125000 150000

MODEL

OBSERVED

MODEL versus OBSERVED AUTO VEHICLE OD FLOWS

S3 Calibration Global Assignment Checks VMT by FUNCLASS

Model Area Ohio MPO county groups

Major Screenline Volumes by FUNCLASS Model Area cordon Ohio cordon MPO cordons

Source of independent VMT estimates? Counts versus “counts”

Initial Unconstrained Auto Assignment ResultsSum of Link Flows for Links with Actual Year 2000 Counts (20,751 links)

Fed FC ADT ASSIGN1 17034 300962 4657 43236 2752 22797 1335 7028 559 1349 708 166

11 41459 4879112 18190 1600914 8250 742616 5493 309017 2807 100019 1420 91022 5098 5622

5 10 15 20 25

Federal Functional Class

ADT

ASSIGN

0

10000

20000

30000

40000

50000

60000

0 5 10 15 20 25

Sum

of L

ink

Flow

s

Federal Functional Class

ADT

ASSIGN

Initial Unconstrained Auto Assignment ResultsSum of Link Flows for Links with Actual Year 2000 Counts (20,751 links)

Fed FC COUNT SUM_ADT SUM_ASN PDIF VMT_ADT VMT_ASN PDIFV1 143 17,034 30,096 77% 2,386,481 4,218,090 77%2 1,012 4,657 4,323 -7% 3,667,264 3,443,332 -6%6 1,610 2,752 2,279 -17% 2,444,532 2,137,080 -13%7 4,410 1,335 702 -47% 3,652,151 1,912,224 -48%8 742 559 134 -76% 288,970 64,982 -78%9 660 708 166 -77% 403,467 81,879 -80%

Rural Sum 8,577 27,045 37,700 39% 12,842,865 11,857,586 -8%1112 861 41,459 48,791 18% 14,190,190 15,964,581 13%14 528 18,190 16,009 -12% 4,029,882 3,450,107 -14%16 3,753 8,250 7,426 -10% 9,568,824 8,034,644 -16%17 3,901 5,493 3,090 -44% 6,618,715 3,240,280 -51%19 2,266 2,807 1,000 -64% 2,372,230 655,208 -72%22 865 1,420 910 -36% 454,124 193,429 -57%

Urban Sum 12,174 77,620 77,227 -1% 37,233,965 31,538,249 -15%Total 20,751 104,664 114,927 10% 50,076,830 43,395,835 -13%

Initial Unconstrained Auto Assignment ResultsAll Links

Fed FC # Links SUM_ADT SUM_ASN PDIF VMT_ADT VMT_ASN PDIFV1 2,032 51,948 81,225 56% 24,334,774 38,854,206 60%2 7,764 13,997 12,267 -12% 17,733,928 16,397,958 -8%6 12,516 7,956 6,499 -18% 12,518,167 10,701,876 -15%7 46,989 4,994 2,187 -56% 20,006,755 11,048,497 -45%8 23,360 1,744 295 -83% 1,810,714 471,872 -74%9 93,460 1,381 518 -63% 1,263,701 439,466 -65%

Rural Sum 186,121 82,021 102,990 26% 77,668,040 77,913,875 0%11 4,869 119,668 139,624 17% 59,121,970 64,664,572 9%12 3,145 49,018 40,894 -17% 14,868,693 12,167,979 -18%14 21,636 22,793 20,060 -12% 32,061,908 26,567,182 -17%16 33,105 12,721 7,586 -40% 18,644,515 10,182,826 -45%17 34,679 8,183 2,957 -64% 10,948,984 3,190,649 -71%19 42,234 4,193 3,085 -26% 4,389,536 2,795,015 -36%22 6,426 9,660 10,225 6% 4,279,929 4,186,428 -2%

Urban Sum 146,094 226,238 224,432 -1% 144,315,534 123,754,651 -14%Total 332,215 308,259 327,422 6% 221,983,574 201,668,527 -9%

Conclusions

This framework allows us to be consistent. Calibration results look good so far. More work to be done.

Questions for Pat?