Travel Demand Model - OKI

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OKI/MVRPC Travel Demand Model – Version 6.03. Base-Year Truck Model ResultsThe base-year truck model results presented in this section included summaries of county-to-county truckflows, summaries of trip ends by FAZ, link truck volume percentages, trip-length distribution profiles, andcount validations statistics. Together, these statistics portray a truck trip model that produces verycredible truck flow patterns. In addition, the validation statistics indicate that the assigned truck triptables provide an acceptable fit to observed traffic count data.3.1 Truck County-to-County MovementsThe estimated daily truck flows for the 1995 base-year model are shown in Tables 3.1, 3.2 and 3.3,below, summarized by county-to-county and external station movements. In terms of total trucks, theexternal stations and the more urbanized counties produce and attract the most trips. While asubstantial portion of truck movements takes place between Hamilton and Montgomery Counties(Cincinnati and Dayton), it is also apparent that the less-urbanized counties exhibit prevailing flowpatterns that suggest a trade linkage to a primary market area in either Cincinnati or Dayton. Forexample, Warren County’s heaviest flows are to and from Butler and Hamilton Counties. A similarrelationship appears to exist between Miami and Montgomery Counties.The SU truck movements shown in Table 3.2 are characterized by heavier SU flows between O-D pairs inclose proximity, including many intra-county flows. In contrast, SU flows between distant, predominantlyrural counties such as between Dearborn and Miami Counties are non-existent. These patterns areconsistent with the predominant use of SU trucks for local pick up and delivery and short-haul drayageassignments.MU truck movements are dominated by heavy flows between external stations and between FAZs andexternal stations, as shown in Table 3.3. The predominant use of MU trucks for longer-haul, largerfreight shipments is reflected in greater frequencies of trips between distant O-D pairs, even between theless-developed counties at opposite ends of the study area. Intra-county MU truck flows are also shownto be much less frequent, compared with intra-county SU truck movements.Truck Model - Base-Year Truck Model Results 29
OKI/MVRPC Travel Demand Model – Version 6.0Table 3.1. Estimated 1995 County-to-County Daily Total Truck FlowsDestination CountyCampbell Clermont DearbornGreene Hamilton Kenton Miami Montgomery WarrenOrigin County Boone KY Butler OH KY OH IN External OH OH KY OH OH OH Grand TotalBoone, KY 4,835 239 777 426 333 2,087 42 2,443 2,370 30 158 80 13,820Butler, OH 300 12,266 45 369 137 2,323 156 6,320 279 168 1,534 2,119 26,016Campbell, KY 703 108 1,030 187 147 920 18 1,097 2,017 11 74 52 6,364Clermont, OH 362 419 181 4,062 69 1,399 88 2,773 357 23 263 204 10,200Dearborn, IN 517 139 150 70 1,043 1,212 4 1,148 567 7 52 20 4,929External 2,368 2,395 813 1,425 1,298 22,276 2,056 7,298 792 1,288 4,602 1,287 47,898Greene, OH 36 174 16 107 9 2,314 3,420 524 45 290 4,160 320 11,415Hamilton, OH 2,380 6,654 1,169 2,781 1,114 6,937 465 35,909 2,938 352 2,364 2,257 65,320Kenton, KY 2,113 221 2,313 293 486 778 30 2,940 2,757 29 182 110 12,252Miami, OH 30 170 2 34 5 1,355 276 353 38 3,066 2,757 101 8,187Montgomery, OH 201 1,309 18 230 56 5,448 4,020 2,220 201 3,002 31,553 1,335 49,593Warren, OH 67 2,285 45 238 26 1,173 510 2,219 111 101 1,279 1,691 9,745Grand Total 13,912 26,379 6,559 10,222 4,723 48,222 11,085 65,244 12,472 8,367 48,978 9,576 265,739Truck Model - Base-Year Truck Model Results 30
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APPENDIX F • TRAVEL DEMAND MODEL
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OKI/MVRPCTravel Demand ModelVersion
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Table of ContentsPart IPart IIPart
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OKI/MVRPC Travel Demand Model - Ver
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Table A.1 (cont.)Zone System Equiva
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Table A.2Zone System Equivalences -
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Table A.3Zone System Equivalences -
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Table B.1External Stations in the C
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Table B.1External Stations in the C
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User Documentation forAutomated Acc
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[Transit Format][New Link Attribute
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distance for each centroid or node.
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Figure 1Example Control File for th
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LinkType = 99VolumeDelay = 99Lanes
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NetworkScale = 1.0 Scale factor to
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Figure 4Example Output from DRVLINK
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Appendix ASample EMME/2 Transit Lin
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Appendix FTravel Demand ModelingTec
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Index of TablesTable 2-1 Socio-Econ
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Appendix FTravel Demand ModelingTec
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Index of TablesTable 2-1 Trip Lengt
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Table of Contents1. Background ....
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Index of FiguresFigure 2-1 Alternat
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NORTH-SOUTH TRANSPORTATION INITIATI
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Run # 63: Start with 7.17 estimatio
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Run # 67:Split parking cost from ot
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Run # 70a:Include zero-auto segment
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Run # 71c:Repeat #71a with zero aut
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Run # 71g:Repeat #71d with wait tim
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Run # 73:Include residential densit
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Run # 76:Nest: auto vs transitVaria
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Run # 79:Repeat #72 with zero autos
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Run # 80:Nest: auto vs. all othersV
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Run # 82:(071h) nested: auto vs tra
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Run #3VariableModeDrive Shared Ride
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Run #8VariableModeDrive Shared Ride
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Run #12 test: make aoc=10.5 instead
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Run #29VariableModeDrive Shared Rid
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Run #33VariableModeDrive Shared Rid
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Run #37vot constrained to $7.00Vari
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Run #30bSame as #30a, combine cost
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Run #140 (same as run #40)vot const
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Run #140b (same as run #40)vot cons
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Run #141avot constrained to $3.00 &
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Run #141cvot constrained to $3.00 &
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Run # 1:Base RunVariablesModesDA Sh
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Run # 5:Base Run with walk time set
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Part VITRIP ASSIGNMENT ANDVALIDATIO
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Index of TablesTable 2-1 Average Ve
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VOBFigure 4-8 Screenline Location -
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2759OKI/MVRPC Travel Demand Model -
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Page 369 and 370: OKI/MVRPC Travel Demand Model - Ver
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