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Page 17 of 23 Attachments 1. Committee Membership David J. Forkenbrock (Chair), Director, Public Policy Center, and Professor, University of Iowa, Iowa City, holds appointments in Urban and Regional Planning and in Civil and Environmental Engineering. His research and teaching interests include analytic methods in planning and transportation policy and planning. He recently completed work as the principal investigator for National Cooperative Highway Research Program projects on Evaluation of Methods, Tools, and Techniques to Assess the Social and Economic Effects of Transportation Projects, and Effective Methods for Environmental Justice Assessment. He is a member of the College of Fellows, American Institute of Certified Planners, and a Lifetime National Associate of the National Academy of Sciences. Chandra R. Bhat, Associate Professor, Department of Civil Engineering, University of Texas, Austin, is also the Associate Chairman of the Civil Engineering Department and the Fluor Centennial Teaching Fellow in Engineering. His research interests include land use and travel demand modeling, evaluation of the impact of transportation control measures on mobile emissions, activity pattern analysis, and use of nonmotorized transportation. He has authored or coauthored more than 40 papers on topics relating to travel demand forecasting published in peer-reviewed journals and has done work on improvements to travel modeling procedures for a number of MPOs, including Boston, DallasâFort Worth, HoustonâGalveston, and Seattle. He chairs the TRB Committee on Passenger Travel Demand Forecasting. William A. Davidson, Principal Consultant, PBConsult, San Francisco, California, directs the technical activities of the Systems Analysis Group. He has 31 years of experience in the field of travel demand model development and forecasting. He has developed complete travel demand model sets for many large metropolitan areas, including Los Angeles, Chicago, San Francisco, Houston, Cleveland, Las Vegas, Phoenix, St. Louis, Buffalo, Austin, and DallasâFort Worth. He is particularly known for his work in mode choice model development and has developed advanced-practice tour-based models in Houston and Columbus, Ohio. He worked for the Federal Transit Administration and the National Transit Institute to develop and teach a course on multimodal travel demand forecasting. Ronald William Eash, Visiting Scholar, Transportation Center, Northwestern University, Evanston, Illinois, was a senior Technical Manager at the Chicago Area Transportation Study (CATS), the MPO for metropolitan Chicago, where he was responsible for the implementation of a regional travel forecasting model for northeastern Illinois. Features of this model included simulation of individual travel and mode choice decisions, incorporation of nonmotorized alternatives, and time-of-day traffic assignments for air quality conformity. He also developed the current CATS household trip generation model and has conducted numerous travel forecasting studies of transportation corridor alternatives. Keith L. Killough, Principal, KLK Consulting, Los Angeles, California, has served on travel model improvement peer review panels in Los Angeles, Sacramento, Santa Cruz, San Diego, and Colorado Springs, and he is currently on the review panel for the federal
Page 18 of 23 TRANSIMS project. He was the Manager of Planning and Development for the Los Angeles County Metropolitan Transportation Authority (MTA), which serves as transportation planner, coordinator, designer, builder, and operator for Los Angeles County. In this capacity, Mr. Killough was responsible for travel simulation modeling, geographic information systems, and strategic transportation planning and led the MTA Long-Range Plan updates in 1995 and 2001. He previously was Planning Manager at the Southern California Rapid Transit District and was responsible for implementation of the travel forecasting models used for the development of the Metro Red Line Project. Debbie A. Niemeier, Professor, Civil and Environmental Engineering, University of California, Davis, is Chancellorâs Fellow at UC Davis and Director of the UC Davisâ Caltrans Air Quality Project, where she conducts research to assist the state and MPOs with speed correction factors, hot-spot modeling, and conformity. She has authored or coauthored more than 40 papers on transportation and air quality modeling published in peer-reviewed journals and is the author of the chapter âMobile Source Emissions: An Overview of the Regulatory and Modeling Frameworksâ in Transportation Engineering Handbook: Planning Methods and Applications. She is a licensed Professional Engineer. Prior to her tenure at UC Davis, she worked as an engineer for the Texas Department of Transportation and the City of San Marcos, Texas, and as a transportation project manager for T.Y. Lin International. Mark L. Schlappi, Systems Analysis Program Manager, Maricopa Association of Governments, Arizona, is responsible for refining the MPOâs forecasting models and producing travel forecasts for highways, transit, and bikeways. He was previously the transportation planner for Scottsdale, Arizona. He has worked on corridor improvement studies and goods movement studies, and he served on travel model peer-review panels for Las Vegas and Salt Lake City. 2. Statement of Task This project will perform review of the state of the practice of travel demand modeling by the Transportation Planning Board (TPB) of the Metropolitan Washington Council of Governments. The review panel will provide guidance on: 1. The performance of the TPBâs latest travel model (version 2) in forecasting regional travel; 2. The proposed process for merging the latest travel model outputs to produce mobile source emissions; 3. The TPBâs proposed direction of future travel demand model upgrades; 4. Travel survey and other data needed to accomplish future model upgrades; and 5. The detail (grain) of travel analysis zones that should be developed for future upgrades. Sponsors: Metropolitan Washington Council of Governments
Page 19 of 23 3. Comparison of Period-Specific Link Volumes Projected by the Travel Model and Postprocessing Procedure To gain greater insight into the degree to which TPBâs postprocessing procedure hourly traffic volume estimates are consistent with the period-specific link volumes projected by the four- step model, the committee compared the two sets of estimates. 1. Using the travel demand link-volume estimates (provided by MWCOG in file AMPMOP051.ASC), we calculated the following for freeways and arterials: Daily volumelink = PM volumelink + AM volumelink + off-peak volumelink Percentage of daily volume in each peak period:19 % AM volumelink = (AM volumelink / daily volumelink ) * 100 % PM volumelink = (PM volumelink / daily volumelink ) * 100 2. We computed the equivalent percentages of daily volume in each period that would be estimated by using the postprocessing link profile method (e.g., from Table 4 in the postprocessing report20): AM Freeway AM Arterial PM Freeway PM Arterial Even Freeway Even Arterial AM period21 28.3% 31.0% 11.7% 12.0% 18.9% 20.4% PM period22 13.9% 15.8% 27.3% 28.5% 19.5% 20.7% 3. We plotted histograms of the %AM and %PM found in Step 1 by facility type and peaking profile. These histograms (Figures 4-1 through 4-6) show the frequencies of the percentages of daily volumes falling in each period using the travel demand estimates. The vertical bold line on each histogram represents table results of Step 2, the percentage of daily volume that would be assigned to the peak period for each link on the basis of the postprocessing method. The numbers of links falling into each category are shown in Table 4-1. 19 The same steps would be used for the off-peak period. 20 Metropolitan Washington Council of Governments, Description and Validation of the Version 2.1/TP+/MOBILE6 Emissions Post-Processor, March 21, 2003. 21 AM period: hours 7, 8, 9 (Table 4). 22 PM period: hours 17, 18, 19 (Table 4).
Page 20 of 23 Table 4-1 Number of links in the TPB network (FACCODE = 1 for freeways, 2 and 3 for arterials, 4 for collectors, 5 for expressways, and 6 for freeway ramps; profiles start at 1 in Table 4 of the postprocessor document, starting from the left). Figure 4-1 Freewaysâclassified as AM link. Figure 4-2 Freewaysâclassified as PM link. PROFILE * FACCODE Cross-tabulation 728 114 204 1046 1904 1073 2977 1122 1122 485 64 231 780 2219 1608 3827 2041 2041 1034 299 248 1581 2525 1312 3837 977 977 2247 6648 3993 4140 477 683 18188 1 2 3 4 5 6 7 8 9 PROFILE Total 1 2 3 4 5 6 FACCODE Total TDM_PAM 54.0 50.0 46.0 42.0 38.0 34.0 30.0 26.0 22.0 18.0 14.0 300 200 100 0 Std. Dev = 7.84 Mean = 26.5 N = 728.00 28.3% is what would be assigned to all links classified as AM (Table 4) TDM_PPM 35.0 33.0 31.0 29.0 27.0 25.0 23.0 21.0 19.0 17.0 15.0 13.0 11.0 9.0 160 140 120 100 80 60 40 20 0 Std. Dev = 3.03 Mean = 20.7 N = 728.00 13.9% is what would be assigned to all links classified as AM (Table 4) TDM_PAM 20.0 18.0 16.0 14.0 12.0 10.0 8.06.04.02.00.0 70 60 50 40 30 20 10 0 Std. Dev = 4.11 Mean = 10.6 N = 485.00 11.7% is what would be assigned to all links classified as PM (Table 4) TDM_PPM 100.0 95.0 90.0 85.0 80.0 75.0 70.0 65.0 60.0 55.0 50.0 45.0 40.0 35.0 30.0 25.0 20.0 15.0 120 100 80 60 40 20 0 Std. Dev = 12.18 Mean = 38.3 N = 485.00 27.3% is what would be assigned to all links classified as PM (Table 4) Percentage of Daily Volume in AM Percentage of Daily Volume in PM Percentage of Daily Volume in AM Percentage of Daily Volume in PM N um be r of L in ks N um be r of L in ks N um be r of L in ks N um be r of L in ks
Page 21 of 23 Figure 4-3 Freewaysâclassified as âevenâ link. Figure 4-4 Major/minor arterialsâclassified as AM link. Figure 4-5 Major/minor arterialsâclassified as PM link. TDM_PAM 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 200 100 0 Std. Dev = 2.33 Mean = 18.0 N = 1034.00 18.9% is what would be assigned to all links classified as EVEN (Table 4) TDM_PPM 36.0 34.0 32.0 30.0 28.0 26.0 24.0 22.0 20.0 18.0 16.0 14.0 12.0 10.0 200 100 0 Std. Dev = 2.63 Mean = 24.5 N = 1034.00 19.5% is what would be assigned to all links classified as EVEN (Table 4) TDM_PAM 100.0 95.0 90.0 85.0 80.0 75.0 70.0 65.0 60.0 55.0 50.0 45.0 40.0 35.0 30.0 25.0 20.0 15.0 1000 800 600 400 200 0 Std. Dev = 8.43 Mean = 28.3 N = 2977.00 TDM_PPM 56.0 52.0 48.0 44.0 40.0 36.0 32.0 28.0 24.0 20.0 16.0 12.0 8.04.00.0 1000 800 600 400 200 0 Std. Dev = 4.24 Mean = 22.9 N = 2977.00 TDM_PAM 38.0 36.0 34.0 32.0 30.0 28.0 26.0 24.0 22.0 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 1000 800 600 400 200 0 Std. Dev = 3.79 Mean = 12.3 N = 3827.00 TDM_PPM 97.5 92.5 87.5 82.5 77.5 72.5 67.5 62.5 57.5 52.5 47.5 42.5 37.5 32.5 27.5 22.5 800 600 400 200 0 Std. Dev = 11.95 Mean = 38.6 N = 3827.00 Percentage of Daily Volume in AM Percentage of Daily Volume in PM Percentage of Daily Volume in AM Percentage of Daily Volume in PM Percentage of Daily Volume in AM Percentage of Daily Volume in PM N um be r of L in ks N um be r of L in ks N um be r of L in ks N um be r of L in ks N um be r of L in ks N um be r of L in ks 31.0% is what would be assigned to all links classified as AM (Table 4) 15.8% is what would be assigned to all links classified as AM (Table 4) 12.0% is what would be assigned to all links classified as PM (Table 4) 28.5% is what would be assigned to all links classified as PM (Table 4)
Page 22 of 23 Figure 4-6 Major/minor arterialsâclassified as âevenâ link. TDM_PAM 43.0 41.0 39.0 37.0 35.0 33.0 31.0 29.0 27.0 25.0 23.0 21.0 19.0 17.0 15.0 13.0 11.0 9.0 600 500 400 300 200 100 0 Std. Dev = 2.95 Mean = 19.4 N = 3837.00 TDM_PPM 56.0 52.0 48.0 44.0 40.0 36.0 32.0 28.0 24.0 20.0 16.0 1200 1000 800 600 400 200 0 Std. Dev = 3.57 Mean = 27.3 N = 3837.00 Percentage of Daily Volume in AM Percentage of Daily Volume in PM N um be r of L in ks N um be r of L in ks 20.4% is what would be assigned to all links classified as EVEN (Table 4) 20.7% is what would be assigned to all links classified as EVEN (Table 4)
Page 23 of 23 4. Work Program Document Descriptions of Proposed Work Elements for the TPB Models Development Program to (a) Address Concerns Raised by the TRB Committee's First Letter Report and (b) Advance the State of Modeling Practice in the Metropolitan Washington Region, National Capital Region Transportation Planning Board, Washington, D.C.: Metropolitan Washington Council of Governments, December 24, 2003 (with appendices). Appendices will be available at http://trb.org/publications/reports/mwcogapril04app.pdf.
