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! 1 Appendix 1 MPO Survey: Questionnaire and Summary of Results

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Jack Faucett Associates, Inc. Final Report March 1997 MPO TRANSPORTATION SURVEY RESULTS As part of the NCHRP research project on transportation data collection, MPOs were surveyed with respect to their data collection needs and collection activities. This appendix describes the survey instrument, outlines the sample development, summarizes the survey responses, and draws several conclusions regarding MPO data activities. Survey Instrument A copy of the survey questionnaire is provided at the end of this appendix. The survey instrument was designed to provide information in a variety of areas: current modelling activities. data used to support modelling, data collected to monitor growth and transportation system use, organization/storage of data, hardware and software support, and gaps in data availability. The survey fonn was designed to be self-a~ninistered. It was mailed to the sample. Follow-up calls were conducted for those recipients that did not respond within two weeks. In most instances, the calls became phone interviews. NCHRP Multimodal Transportation Planning Data Al-l Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report . Survey Sample March 1997 The sample included twenty-f~ve MPOs. The sample was selected to provide broad geographic coverage and diversity in size of the area represented. A total of sixteen of the survey recipients responded to the survey form either by return mail or through a phone interview. No attempt was made to augment the responses since the survey was designed to identify general trends and activity patterns rather than establishing Weir statistical validity. The respondents are categorized in Exhibit 18 of Section 2.2 by size of weir urban area. Survey Responses The survey responses are summarized below in the order of the questions. Question No. 1: Principal Forecasting Models for Travel Demand, Demand Management and Air Quality Analysis-Most of Me respondents identified a specific modelling package for travel demand forecasting. Tranplan was the most widely used package, primarily by Me medium-sized MPO's. A modified version of Tranplan (FSTUMS) is the standard modelling package in the State of Florida. The larger MPOs did not have a typical forecasting package. Two of the MPOs use their own mainframe models which are partially based upon UTPS or emme2. Over large MPOs use the standard emme2 package' TMODEL2' or minutp. Very few of the respondents currently simulate travel demand management approaches in the model stream. Only one cited use of an actual model. Two of the MPOs re-adjust the trip table in an attempt to forecast TDM impacts on travel levels. Several of the respondents are anticipating modifications to their modelling system for sensitivity to TDM options. NCHRP-Multimodal Transportation Al-2 Planning Data Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report March 1997 _ Most of the MPOs conduct air quality modelling because of federal requirements. MOBILES and MOBILSa are the primary air quality models used by the respondents. Several other models were mentioned by individual respondents, including PPAQ, CAL3QHC, EMIS, and DTIM. Question No. 2: Principal Data Sources-This question has considerable overlap with question No. 1 1 dealing with transportation system surveillance data sources. Much of the surveillance data is used as the base for forecasting future year demographic characteristics and for calibrating the forecasting models. With respect to the key data for forecasting, most respondents begin with U.S. Census data for population characteristics, and state statistics for employment. The population data is frequently updated using building permits, utility hook-ups, aerial photography, field surveys, and meetings with representatives of the various local jurisdictions. The employment data characteristically ties employment to central offices rather than the actual physical location. Therefore, the state employment data requires extensive field survey or phone interviews to check accuracy. Four of the large MPOs have either completed a recent household survey, or have one scheduled within the next two years. A few of the respondents had conducted recent origin/destination travel surveys. The Florida Application for Development Approval (ADA) provides an extremely rich data base for MPOs in that state. In addition to identifying development plans, the application provides detailed information and land characteristics such as soil type, as well as current aerial photography for the site. These data, collected at private expense, significantly enhance the ability of the MPOs to forecast the type, intensity, and location of future development. Data sources for forecasting the impacts of various Travel Demand Management (TDM) techniques are not nearly as extensive. Most of the spreadsheet models used to evaluate these NCHRP-Multimodal Transportation . A1-3 Planning Data Project 8-32(5)

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Jack Faucett; Associates, Inc. Final Report March 1997 strategies are based upon a limited supply of published data collected in a handful of cities. The Institute of Transportation Engineers has published the most extensive documentation of TDM analysis, but it does not appear to be used extensively at this time. Most of the data used to drive the air quality models are derived from the travel forecasts. This includes the percent of hot and cold starts, travel speeds, and travel volumes. As me models are becoming more sophisticated, however, they are requiring more finite data than the models can predict with reliable accuracy. Question No. 3: Anticipated Changes to Modelling Procedures - Over three quarters of the respondents identified impending changes they would be making to the modelling process. The most frequently cited changes were increased sensitivity to time-of-day and incorporation of trip-chaining. Other changes identified by individual respondents are listed below: increased market segmentation, peak spreading, o trip distribution sensitivity to peak hour impedances, trip generation sensitivity to modal availability, and incorporation of new Highway Capacity Manual. Question No. 4: Sources of Key Data This question was found to be redundant with question No. 2. Information reported here that had not already been reported under question No. 2 was reported as a No. 2 response. Question No. 5: Organization of Data This appeared to be the most challenging question on the survey. A number of respondents that were contacted by phone appeared to be confused by the question. They typically asked for an explanation or more detailed example. Some NCHRP Multimodal Transportation A14 Planning Data Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report - March 1997 respondents would then agree that Hey followed the example cited in He question, but would then explain how they were different. Half of the respondents indicated that they followed the data framework outlined in the question (i.e., model development, model calibration, and TIP development), while the other half indicated that they followed another format. To some extent, the larger MPOs appeared to be more likely to have organized the data in a particular format. Of the respondents that said Hey organized data differently from the example, the general theme was to separate the data into two categories: 1) model inputs and 2) system monitoring. Air quality was identified as another possible category by which to organize data. Question No. 6: Use of a Centralized Data Base-As with question No. 5, this question resulted in an even split between the respondents. Eight of the agencies have a centralized database, while eight do not. Those that have the central data base typically maintain the data themselves. The data base is usually accessible by the state-DOT, local counties, and local cities. One of the respondents make the data available Trough the Internet. Most of He agencies did not think there was redundancy in the data collected or stored. About half of the respondents outlined concerns regarding ~nter-organ~zational data sharing. These concerns are outlined below: . uncertainty regarding He responsibility for the data or collection techniques and fear of a shift of data gathering and maintenance responsibilities to the MPO, difficulty converting others' data to a readable format, consistency in the level of detail, differences in software packages used by the various agencies, and access to data collected by others. NCHRP-Multimodal Transportation Al-S Planning Data Project 8-32~5J

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Jack Faucett Associates, Inc. Final Report March 1997 Question No. 7: type of Hardware Platform-Eleven of the sixteen respondents use personal computers for modelling activities. The pc's are typically networked. Two of the large MPOs use a mainframe. Another two use Sun work-stations. One of the mid-sized MPOs uses a minicomputer. Each of the agencies uses the same hardware platform for modelling and data storage. Question No. 8: Database Software-There was kale consistency in the database programs used by the respondents. The most commonly used software is dBase, but this is used by only six respondents. Four of the agencies identified ARCINFO as their database software. A number of agencies listed several software packages. The remaining programs identified in the survey include: Access' Atlas GIS' Rapid File, Paradox' STATA, Foxpro' SAS, and SPSS. Question No. 9: Data Storage Upgrades-Over half of the respondents have short-term plans to improve their data storage capabilities. Most in this group intend to increase storage capacity. One is switching to a relational database while another is adding GIS capabilities. The smaller MPOs appear to be in a "catch-up" mode, one adding a network, and another attempting just to keep up with technology. Question No. 10: Use of GIS-Fourteen of the sixteen agencies already use GIS in some form in their planning process. Over half of the respondents have integrated their travel demand models with GIS. The remaining agencies use GIS for data storage or mapping of information. Surprisingly, two of the three small agencies are already using GIS. Of the two agencies that are not using GIS, one is small and one is large. Both are planning on implementing GIS in the near future. Question No. 11: Surveillance Data Sources-This question covered data sources for seven areas: demoaraphic/socio-economic. vehicle volumes, public transit, intermodal, construction monitoring, travel mode information, and travel time/trip length. NCHRP Multimodal Transportation A1-6 Planning Data Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report March 1997 - Most of the respondents listed the U.S. Census as a key source for demographic data. This information is typically updated and checked through a variety of sources including building permits, utility hook-ups, aerial photography, field survey, and meetings with individual jurisdictions. Employment data is generally based upon state statistics. While this source is reasonably comprehensive, it frequently assigns branch office or remote employees to the central office or payroll location. This significantly distorts the actual geographic distribution of employees, requiring extensive cross-checking and field work by the MPO. The state-DOT was the most commonly cited source of data on traffic counts. While there was some variation in the functional classes of roadways which they monitored, almost all of the respondents depend on the state for some traffic data. Cities and counties also contribute count data in a number of areas. About one third of the MPOs collect count data themselves. Public transit data is typically provided by the transit operator. In most instances, this is an independent transit authority. In a few cases, the core city operates the bus system. Transit data provided by the transit operator typically include standard Section 15 information. Occasionally, onboard surveys are conducted to be used for model updates. The MPO is sometimes responsible for the administration of the survey. Intermodal data is difficult to obtain in most cities. Total freight volumes are available Trough public port authorities, or interviews with shippers. Detailed information on specific commodities or shipping patterns is not readily available. Due to the competitive nature between private shippers, it appears that such information may always be difficult to obtain. Construction status infonnation is typically provided by the state-DOT for its projects. The MPOs contact appropriate local agencies to update the status of their projects. NCHRP Multimodal Transportation A1-7 Planning Data Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report March 1997 - Travel mode information varies by location. Bicycle and pedestrian data are not collected regularly in most areas. Auto occupancy information is typically regional in nature, unless a special study has been conducted along a specific facility. About one-third of the respondents had conducted some type of Gavel survey over the last several years that provided some information on travel modes. Two of the three small MPOs were included in this group. Travel time data is not being collected comprehensively on a regular basis. Six respondents indicated that they had conducted origin/destination surveys which provided travel time information. Two respondents noted speed and delay studies. Question No. 12: Data Gaps-Most of the respondents identified gaps in data resources. Most of the problems fell in one of three data areas: population/employment, travel characteristics, and traffic counts. Accurate employment information by place of work was the most frequently mentioned problem. As mentioned earlier, the state employment information Epically aggregates employees by central office or payroll locations. This requires extensive effort on the part of the MPO to disaggregate the data to actual work location. On the population side, one respondent desired more information on household income. A wide variety of needs were identified for travel data. Medical and recreational trips were mentioned as areas needing more research. Better identification of external to external trips was also mentioned. Finally, trip route information was also identified as a need. Traffic counts are needed more often, in more locations, and for shorter periods of time. In one instance, the accuracy of the state counts for freeway links was cited as unreliable. In general, there was a desire to have more opportunity to check the validity of existing data. NCHRP Multimodal Transportatwn Al-8 Planning Data Project 8-32~5J

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Jack Faucett Associates, Inc. Final Report _ March 1997 Other general areas of need included better concurrence between population, dwelling units, and auto registration databases, current information on transportation funding, detailed freight movements, and roadway inventories. Question No. 13: Recommended State Data Collection Acidities-Although several respondents suggested more~state activity in collection of traffic counts, there were no recommendations that received broad support. The Florida respondent suggested that the state standardize GIS use for MPOs within its jurisdiction. This would be comparable to Florida DOT's approval of a specific forecasting software. Other suggestions included: goods movement for Intermodal Management Systems (IMS), better employment data, speed and delay studies, and broader roadway inventory. Summary of Conclusions The survey results appear to support two general conclusions. Many MPOs do not have a long-term vision with respect to organization of data. Data needs are increasing, which will place further demands on data gathering, storage, and maintenance activities. As indicated above, many respondents appeared to be confused by question No. 5 regarding their data organization framework. This suggests that the current data organization is likely to be more a reaction to short-term needs than a thoughtful long-term strategy. This is reinforced by the significant absence of a centralized database in half of the MPOs. The lack of the database was evenly split for small, medium, and large area agencies. It does not seem to be related to the size or complexity of the organization, or funding availability. Again, it seems to be more a lack of long-range vision. NCHRP- Mulfimodal Transportation Al-9 Planning Data Project 8-32~5)

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Jack Faucett Associates, Inc. Final Report . , . _March 1997 Most of the agencies desire to increase the sophistication of their models. As air quality models become more complex, more time-specific data will be required to support their operation. Limited transportation intending is beginning to necessitate more accurate forecasting and analysis of congested roadways. A greater emphasis will be placed on peak hour forecasts. This will require a shift from a 24-hour or weighted peak/off-peak analysis format in many cities. Better representation of peak spreading will be required in all models. Effective modelling of TDMs will also grow in importance as low-cost solutions become necessary. Finally, better representation of medical and recreational trips will become more critical as the number of these trips grows with an aging society. The significant shift to two-worker households has created a need to undersuand and represent Hip chaining in the models, if they are to represent reality. With the flood of information and information technology, the natural reaction has been to focus on immediate opportunities to apply both. While this may have improved our responsiveness in the short teen, it exacerbates the long-tenn condition. The complexity of our travel behavior and transportation funding needs are eclipsing both information and technology. If we are to keep pace with our needs, we must take the time to fully evaluate the resources available, and consciously develop a plan to use those resources to the fullest. NCHRP Multimodal Transportation A1-10 Planning Data Project 8-32~5)

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Jack FaucettAssoci~es, Inc. Final Report March 1997 Metropolitan Planning Organizations Multimodal Transportation Planning Data Needs Survey Instrument 1. Please identify principal models that are used for: A.) Travel modeling and forecasting (trip generation, trip distribution, mode choice, and network assignment) . B.) Transportation demand management C.) Measurement of emissions affecting air quality 2. Please list principal data sources for input to models listed above: A.) B.) C.) - NCHRP-Multimodal Transportalvion Al-ll Project 8-32(5) Planning Data

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Jack Faucett Associates, lac. Final Report March 1997 3. Is your agency considering implementation of new models (e.g., time-of-day, trip chaining, non-motorized transportation, etc.) in the transportation planning system? If so, which ones, and what are the major issues driving the decision? 4. What are Me sources of the key data used to derive the models? (Please list primary and secondary data sources by model.) 5. Do you currently organize your data collection activities along the lines of model development, model calibration, and TIP development? Yes No If "no", how would you characterize your data organization framework? NCHRP-Mu~imo~Transportation A1-12 Project8-32(5) Planning Data

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Jack Faucett Associates, Inc. Final Report March 1997 6. Do you maintain a centralized database for the input data listed in 2 and 4 above? Yes No A.) If "yes", which organizations access the database? B.) Which organizations maintain the data? C.) . If "no", do you believe there is redundancy in the types of data collected or stored? D.) Are there any inter-organ~zational data sharing issues? (These problems could be hardware/soiftware related, data scale related, or related to proprietary nature of the clata.) NCHRP - Multimodal Transportation Al-13 Project 8-32~5) Planning Data

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Jack Faucett Associates, Inc. _ Final Report March 1997 I . 7 What type of computer hardware platform do you use for A.) modeling? B.) data storage? S. What database software packages are currently in use? 9. Are you planning to update your data storage capabilities in the near term? Yes No A.) If "yes", what are you planning to change? NCHRP-Multimodal Transportation Al-14 Project 8-32(5) Planning Data

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Jack Faucett Associates, Inc. Final Report March 1997 10. Do you currently use a GIS system to support transportation planning? Yes No A.) If "yes", please briefly describe how the system is used, the software package that is used, and the types of data which support any analytic capability. B.) If ``no`~' are you planning on using a GIS system in the near future? (Please explain.) NCHRP-Multimo~Transportation Al-lS Project8-32(5J Planning Data

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Jack Faucett Associates, Inc. Final Report March 1997 _ 11. What are your transportation system surveillance data sources? A. ~ Demographic/Socioeconomic Characteristics B.) Vehicle Travel Volumes (Peak Period and ADT Counts) C.) Public Transit System Characteristics D.) Intermodal System Characteristics (Rail, Truck, Air, Waterway, Pipeline, Other) E.) Construction Project Monitoring Information F.) Travel Mode Information (SOY, HOV, Transit, Bicycle, Pedestrian) G.) Travel Time and Trip Length Information NCHRP-Multimodal Transportation A1-16 Project 8-32~5) Planning Data

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Jack Faucett Associates, Inc. Final Report March 1997 12. What are the major gaps between the data you have and the data that you need? 13. Can you suggest data you need (and not available to you) that could be collected (or otherwise developed) more efficiently by the state DOT and made available to you? NCHRP Multimodal Transportation A1-17 Project 8-32~5) Planning Data

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