Comparison Of Four-Step Versus Tour-Based Models In .
Comparison of Four-Step Versus Tour-BasedModels in Predicting Travel Behavior Beforeand After Transportation System Changes –Results Interpretation and RecommendationsNazneen Ferdous and Chandra Bhat, Center for Transportation Research,The University of Texas at AustinLakshmi Vana and David Schmitt, AECOM ConsultJohn L. Bowman, Bowman Research and ConsultingMark Bradley, Mark Bradley Research and ConsultingRam Pendyala, Arizona State Universityfor theOhio Department ofTransportationOffice of Research andDevelopmentState Job Number134368February 2011Prepared in cooperation with the Ohio Departmentof Transportation and the U.S. DepartmentTransportation, Federal Highway Administration.
2. Government Accession No.1. Report No.3. Recipient’s Catalog No.FHWA/OH-2011/44. Title and subtitle5. Report DateComparison of Four-Step Versus Tour-Based Models in PredictingTravel Behavior Before and After Transportation System Changes– Results Interpretation and RecommendationsFebruary 20116. Performing Organization Code7. Author(s)8. Performing Organization Report No.Nazneen Ferdous, Chandra Bhat, Lakshmi Vana, David Schmitt,John Bowman, Mark Bradley, Ram Pendyala10. Work Unit No. (TRAIS)9. Performing Organization Name and Address11. Contract or Grant No.134368The University of Texas at AustinCenter for Transportation Research1616 Guadalupe Street, Suite 4.202Austin, TX 7870113. Type of Report and Period Covered12. Sponsoring Agency Name and Address14. Sponsoring Agency CodeOhio Department of Transportation1980 West Broad StreetColumbus, OH 4322315. Supplementary NotesPrepared in cooperation with the Ohio Department of Transportation and the U.S. DepartmentTransportation, Federal Highway Administration.16. AbstractThe main objective of this study was to examine the performance of the Mid-Ohio Regional PlanningCommission’s (MORPC) trip-based and tour-based frameworks in the context of three specific projectsstarted and completed within the past 15 years in the Columbus metropolitan area. The three specificprojects included (1) Polaris project, (2) Hilliard-Rome project, and (3) Spring-Sandusky interchangeproject. The performance evaluation of the trip-based and tour-based models was pursued at two levels.The first level corresponded to a region-level analysis (independent of specific projects) that comparedselected model outputs from each of the trip-based and tour-based model systems with correspondingregion-level observed data. The second level corresponded to a local-level analysis (specific to each of thethree projects identified earlier) that compared the trip volume outputs on selected roadway links in andaround the project region with corresponding link counts. For both the region-level and local-level analysis,the research team considered three years for analysis: 1990, 2000, and 2005. The results indicate that thetour-based model performed better overall than the trip-based model in the region-level analysis, while thepredictive abilities from the trip and tour-based models were about equal in the local-level analysis. Thisproject is a significant first step toward a better understanding of the tangible benefits of disaggregate tourbased modeling methods. But it would be imprudent to judge all model systems strictly on the results of thisone project, since the transportation planning community has accumulated four decades of learning andexperience on trip-based models while this particular tour-based model represents only one attempt, andone of the earliest, at implementing the tour-based or activity-based approach for practical use.Regardless, this project should serve as an important reference in the assessment of the potential practicalbenefits of disaggregate tour-based modeling approaches vis-à-vis aggregate trip-based methods.17. Key Words18. Distribution StatementTour-based model, trip-based model, sensitivityanalysis, transportation system, evaluationNo restrictions. This document is available to thepublic through the National Technical InformationService, Springfield, Virginia 2216119. Security Classif. (of this report)20. Security Classif. (of this page)21. No. of PagesUnclassifiedUnclassified138Form DOT F 1700.7 (8-72)Reproduction of completed pages authorized22. Price
Comparison of Four-Step Versus Tour-Based Models in Predicting TravelBehavior Before and After Transportation System Changes –Results Interpretation and RecommendationsbyNazneen Ferdous and Chandra Bhat, Center for Transportation Research,The University of Texas at AustinLakshmi Vana and David Schmitt, AECOM ConsultJohn L. Bowman, Bowman Research and ConsultingMark Bradley, Mark Bradley Research and ConsultingRam Pendyala, Arizona State UniversityPrepared in cooperation with the Ohio Department of Transportation and the U.S. DepartmentTransportation, Federal Highway Administration.February 2011Project Title: Sensitivity of Four-Step Versus Tour-Based Models to Transportation SystemChangesAgreement Number: 21741State Job Number 134368Sponsor: Ohio Department of TransportationThe contents of this report reflect the views of the author(s) who is (are) responsible for the facts and the accuracyof the data presented herein. The contents do not necessarily reflect the official views or policies of the OhioDepartment of Transportation or the Federal Highway Administration. This report does not constitute a standard,specification, or regulation.
ACKNOWLEDGMENTSThe support of Rebekah Anderson and Greg Giaimo is greatly appreciated. The authors aregrateful to Lisa Macias for her help in formatting this document.iv
TABLE OF CONTENTS1. INTRODUCTION .12. AN OVERVIEW OF THE MORPC MODEL SYSTEMS .22.1 Tour-Based Model .22.2 Trip-Based Model.33. STUDY PROJECTS AND CONTROL AREA.44. DATA PREPARATION EFFORTS FOR STUDY AREAS .55. EMPIRICAL COMPARISON EXERCISE .65.1 Region-Level Comparison .85.1.1 Vehicle Ownership .105.1.2 Work Flow Distributions.205.1.3 Work Flow Distribution by Time-of-Day of Trip Start .355.1.4 Average (Person) Work Trip Travel Time .415.1.5 Average Trip Distance by County of Origin .465.2 Project-Level Comparison .476. CONCLUSION .56REFERENCES .57APPENDIX A: Vehicle Ownership .59APPENDIX A.1: Vehicle Ownership – Model Year 1990.60APPENDIX A.2: Vehicle Ownership – Model Year 2000.61APPENDIX A.3: Vehicle Ownership – Model Year 2005.63APPENDIX B: Work Flow Distributions .65APPENDIX B.1: Work Flow Distributions – Model Year 1990.66APPENDIX B.2: Work Flow Distributions – Model Year 2000.69APPENDIX B.3: Work Flow Distributions – Model Year 2005.72APPENDIX C: Work Trip Start Time Distribution .75APPENDIX C.1: Work Trip Start Time Distribution – Model 1990 .76APPENDIX C.2: Work Trip Start Time Distribution – Model 2000 .78APPENDIX C.3: Work Trip Start Time Distribution – Model 2005 .80APPENDIX D: Average Work Trip Travel Time .83APPENDIX D.1: Person Work Trip Travel Time – Model Year 1990 .84APPENDIX D.2: Person Work Trip Travel Time – Model Year 2000 .84APPENDIX D.3: Person Work Trip Travel Time – Model Year 2005 .86APPENDIX E: Link Flows .87APPENDIX E.1: Link Flows – Model Year 1990 .88APPENDIX E.2: Link Flows – Model Year 2000 .105APPENDIX E.3: Link Flows – Model Year 2005 .110v
LIST OF ILLUSTRATIONSFigure 1: Selected Study Projects and Control Area . 5Figure 2: Model Study Region . 9Figure 3a: Relative Weighted Mean Absolute Percentage Error (WMAPE) by County and the OverallWMAPE for the Study Region - Comparison with the Census Data (Year 1990) . 13Figure 3b: Relative Weighted Mean Absolute Percentage Error (WMAPE) by County and the OverallWMAPE for the Study Region - Comparison with the Census Data (Year 2000) . 15Figure 3c: Relative Weighted Mean Absolute Percentage Error (WMAPE) by County and the OverallWMAPE for the Study Region - Comparison with the HIS Data (Year 2000) . 17Figure 3d: Relative Weighted Mean Absolute Percentage Error (WMAPE) by County and the OverallWMAPE for the Study Region - Comparison with the ACS Data (Year 2005) . 19Figure 4: Network Links Considered in the Project-Level Attributes Analysis . 50Figure 5: Absolute Percentage Error Statistic Comparison with the Observed Link Counts . 54Table 1a.Table 1b.Table 1c.Table 1d.Table 2a.Table 2b.Table 2c.Table 2d.Table 2e.Vehicle Ownership Level by County – Comparison with the Census Data (Year 1990) . 12Vehicle Ownership Level by County – Comparison with the Census Data (Year 2000) . 14Vehicle Ownership Level by County – Comparison with the HIS Data (Year 2000) . 16Vehicle Ownership Level by County – Comparison with the ACS Data (Year 2005) . 18Work Flow Distribution by County – Comparison with the Census Data (Year 1990) . 24Work Flow Distribution by County – Comparison with the Census Data (Year 2000) . 25Work Trip Flow Distribution by County – Comparison with the HIS Data (Year 2000) . 26Work Flow Distribution by County – Comparison with the ACS Data (Year 2005) . 28Intra-County Work Trip Flow Distribution for Franklin County – Comparison with theCTPP Data (Year 2000) . 29Table 3a. Work Flow Distribution by Trip Start Time – Comparison with the Census Data(Year 1990) . 36Table 3b. Work Flow Distribution by Trip Start Time – Comparison with the Census Data(Year 2000) . 36Table 3c. Work Flow Distribution by Trip Start Time: Peak Period – Comparison with the HIS Data(Year 2000) . 37Table 3d. Work Flow Distribution by Trip Start Time: Off-Peak Period – Comparison with the HISData (Year 2000) . 39Table 3e. Work Flow Distribution by Trip Start Time– Comparison with the ACS Data(Year 2005) . 41Table 4a. Travel Time for Work Trips – Comparison with the Census Data (Year 1990) . 43Table 4b. Travel Time for Work Trips – Comparison with the Census Data (Year 2000) . 43Table 4c. Travel Time for Work Trips – Comparison with the HIS Data (Year 2000) . 44Table 4d. Travel Time for Work Trips – Comparison with the ACS Data (Year 2005) . 46Table 5a. Average Person Trip Length (in miles) by Trip Type (Year 2000) . 47Table 5b. Average Person Trip Length (in miles) by County (Year 2000) . 47Table 6. Project Level Link Volume Comparison by Roadway Functional Class . 52Table A.1a: Vehicle Ownership Level by County (Source: 1990 Census) . 60Table A.1b: Vehicle Ownership Level by County (Source: 1990 trip-based model) . 60Table A.1c: Vehicle Ownership Level by County (Source: 1990 tour-based model) . 60Table A.2a: Vehicle Ownership Level by County (Source: 2000 Census) . 61Table A.2b: Vehicle Ownership Level by County (Source: 1999 HIS). 61Table A.2c: Vehicle Ownership Level by County (Source: 2000 trip-based model) . 61Table A.2d: Vehicle Ownership Level by County (Source: 2000 tour-based model) . 62vi
Table A.3a: Vehicle Ownership Level by County (Source: 2005 ACS) . 63Table A.3b: Vehicle Ownership Level by County (Source: 2005 trip-based model) . 63Table A.3c: Vehicle Ownership Level by County (Source: 2005 tour-based model) . 63Table B.1a: County to County Flows to Work (in 1000s, source: 1990 Census) . 66Table B.1b: County to County Flows to Work (in 1000s, source: 1990 trip-based model). 67Table B.1c: County to County Flows to Work (in 1000s, source: 1990 tour-based model) . 68Table B.2a: County to County Flows to Work (in 1000s, source: 2000 Census) . 69Table B.2b: County to County Trip Flows to Work (in 1000s of trips, source: 1999 HIS survey) . 69Table B.2c: County to County Flows to Work (in 1000s, source: 2000 trip-based model) . 70Table B.2d: County to County Flows to Work (in 1000s, source: 2000 tour-based model) . 71Table B.3a: County to County Flows to Work (in 1000s, source: 2005 ACS) . 72Table B.3b: County to County Flows to Work (in 1000s, source: 2005 trip-based model). 72Table B.3c: County to County Flows to Work (in 1000s, source: 2005 tour-based model) . 73Table C.1a: Work Trip Start Time Distribution (in %) by Time of Day (Source: 1990 Census) . 76Table C.1b: County-to-County Work Trip Start Time Distribution (in %) by Time of Day(Source: 1990 trip-based model) . 76Table C.1c: County-to-County Work Trip Start Time Distribution (in %) by Time of Day(Source: 1990 tour-based model) . 77Table C.2a: Work Trip Start Time Distribution (in %) by Time of Day (Source: 2000 Census) . 78Table C.2b: County to County Work Trip Start Time Distribution (in %) by Time of Day(Source: 1999 HIS survey) . 78Table C.2c: County to County Work Trip Start Time Distribution (in %) by Time of Day(Source: 2000 trip-based model) . 79Table C.2d: County to County Work Trip Start Time Distribution (in %) by Time of Day(Source: 2000 tour-based model) . 79Table C.3a: Work Trip Start Time Distribution (in %) by Time of Day (Source: 2005 ACS) . 80Table C.3b: Work Trip Start Time Distribution (in %) by Time of Day (Source: 2005 trip-basedmodel). 80Table C.3c: Work Trip Start Time Distribution (in %) by Time of Day (Source: 2005 tour-basedmodel). 81Table D.1: Travel Time for Work Trips (in minutes, observed data source: Census 1990). 84Table D.2a: Travel Time for Work Trips (in minutes, observed data source: Census 2000) . 84Table D.2b: Travel Time for Work Trips (in minutes, observed data source: 1999 HIS) . 85Table D.3: Travel Time for Work Trips (in minutes, observed data source: ACS 2005) . 86Table E.1a: Link Flows – Polaris Project Study Area (Model Year 1990). 88Table E.1b: Link Flows – Hilliard-Rome Project Study Area (Model Year 1990) . 89Table E.1c: Link Flows – Spring-Sandusky Project Study Area (Model Year 1990) . 91Table E.1d: Link Flows – Control Area (Model Year 1990) . 103Table E.2a: Link Flows – Polaris Project Study Area (Model Year 2000). 105Table E.2b: Link Flows – Hilliard-Rome Project Study Area (Model Year 2000) . 106Table E.2c: Link Flows – Control Area (Model Year 2000) . 109Table E.3a: Link Flows – Polaris Project Study Area (Model Year 2005). 110Table E.3b: Link Flows – Hilliard-Rome Project Study Area (Model Year 2005) . 111Table E.3c: Link Flows – Spring-Sandusky Project Study Area (Model Year 2005) . 114Table E.3d: Link Flows – Control Area (Model Year 2005) . 128vii
viii
1. INTRODUCTIONOver the past three decades, there has been a realization that simply enhancing the capacity (orsupply) of transportati
tour-based model performed better overall than the trip-based model in the region-level analysis, while the predictive abilities from the trip and tour-based models were about equal in the local-level analysis. This project is a significant first step toward a better understanding of the tangible benefits of disaggregate tour-based modeling .
grade step 1 step 11 step 2 step 12 step 3 step 13 step 4 step 14 step 5 step 15 step 6 step 16 step 7 step 17 step 8 step 18 step 9 step 19 step 10 step 20 /muimn 17,635 18,737 19,840 20,942 22,014 22,926 23,808 24,689 325,57! 26,453 /2qsohrs steps 11-20 8.48 9.0! 9.54 10.07 10.60 11.02 11.45 11.87 12.29 12.72-
Special Rates 562-600 Station Number 564 Duty Sta Occupation 0083-00 City: FAYETTEVILL State: AR Grade Suppl Rate Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8 Step 9 Step 10 Min OPM Tab Eff Date Duty Sta Occupation 0601-13 City: FAYETTEVILL State: AR Grade Suppl Rate Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8 Step 9 Step 10 Min OPM Tab Eff Date
Grade Minimum Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Mid-Point Step 8 Step 9 Step 10 Step 11 Step 12 Step 13 Step 14 Maximum Step 15 12/31/2022 Accounting Services Coordinator O-19 45.20 55.15 65.10 Hourly 94,016 114,712 135,408 Appx Annual 12/31/2022 Accounting Services Manager O-20 47.45 57.90 68.34 Hourly
Shake the bag so that everything mixes together (at least 1 min.) Store in a dark, dry place for 5 days Primary Growing Process Steps one Step two Step three Step four Step five Final step 11 12 Step two Step three Step five Step four Step one Step three Step 7, 8, & 9 Step four Step ten Step 3 &am
Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8 Step 9 Step 2 Step 2 Request For Quotation (RFQ) If you're a hardball negotiator at heart, this next step should bring you some real enjoyment. On the other hand, if you are not a negotiator by trade, don't worry; this step can still be simple and painless. Now that you have a baseline of what
Save the Dates for Welcome Programs CHECKLIST Step 1: Step 2: Step 3: Step 4: Step 5: Step 6: Step 7: Step 8: Step 9: Step 10: Step 11: Step 12: Step 13: . nursing@umsl.edu umsl.edu/nursing School of Social Work 218 Bellerive Hall 314-516-7665 socialwork@umsl.edu umsl.edu/ socialwk/
Step 1: start Step 2:read n Step 3:assign sum 0,I m n,count 0 Step 4:if m 0 repeat Step 4.1:m m/10 Step 4.2:count Step 4.3:until the condition fail Step5: if I 0 repeat step 4 until condition fail Step 5.1:rem I%10 Step 5.2:sum sum pow(rem,count) Step 5.3:I I/10 Step 6:if n sum print Armstrong otherwise print not armstrong Step 7:stop
Step 1: Registration Step 2: Personal Information Step 3: Select a Job Step 4: Fill Application Step 5: Review Application Step 6: Submit Application Step 7: Check Application Status Step 8: Set up Job Alerts STEP-BY- STEP GUIDE TO APPLYING AT UNFPA
