ohio statewide travel model: framework, freight, and initial calibration
DESCRIPTION
Session 6:. Ohio Statewide Travel Model: Framework, Freight, and Initial Calibration. 11th National Transportation Planning Applications Conference May 6-10, 2007, Daytona Beach, Florida. Acknowledgements. This presentation was primarily developed by Pat Costinett. Topics. - PowerPoint PPT PresentationTRANSCRIPT
Andrew Stryker| PB | 503-417-9360 | [email protected]
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?