Proposal for IMPROVEMENTS TO THE EIGHT SAN JOAQUIN VALLEY MPO TRAFFIC MODELS

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3 for IMPROVEMENTS TO THE EIGHT SAN JOAQUIN VALLEY MPO TRAFFIC MODELS Submitted on February 13, 2014 by: FEHR & PEERS Citilabs AirSage Inrix CoStar EDR Group P WC

4 Table of Contents OVERVIEW... 1 DETAILED WORK PLAN... 3 Task 1 Project Management and Information Sharing... 3 Task 1.1 Administrative Coordination Monthly Progress Reports... 3 Task 1.2 Technical Coordination Monthly Webinars... 3 Task 1.3 Training... 4 Task 1.4 On-Line Project Data Center... 4 Task 1.5 On-Line GIS Mapping... 4 Task 2 Data Acquisition, Review, and Summary... 5 Task 2.1 Origin-Destination Data... 6 Task 2.2 Traffic Speed Data... 6 Task Census/2012 ACS... 8 Task CHTS... 8 Task 2.5 Alternative Forecast Data... 8 Task 2.6 Housing Affordability, Employment and Jobs/Housing Balance... 8 Task 2.7 Other Data... 9 Task 3 Refine Model Input Data Task 3.1 Transportation Analysis Zones Task 3.2 Land Use Inputs Task 3.3 Speed Network Update Optional Task 3.4 Develop Merced Single County Model Task 4 Estimation, Calibration, Validation, and Evaluation of Model Improvements Task 4.1 Economic Land Use Forecasting Task 4.2 Travel Model Estimation Task 4.3 Interregional Coordination Task 4.4 Model Calibration Task 4.5 Model Static Validation Task 4.6 Model Dynamic Validation... 18

5 Task 4.7 Evaluation Task 4.8 Integrate Post-Processors Task 4.9 Documentation Deliverables Schedule MANAGEMENT APPROACH...24 Management Team Our Management Approach Technical Coordination Monthly Webinars Administrative Coordination Monthly Progress Reports On-Line File Transfer Site Our Track Record Project Personnel Organization Chart Staff Roles, Tasks, and Hours CommitTed Fehr & Peers Staff Bios Sub-Consultant Staff Bios BUDGET AND BILLING...35 INSURANCE...37 DBE CERTIFICATION...38 Disadvantaged Business Enterprise (DBE) Policy DBE Usage on this Project CONFLICTS OF INTEREST...40 SUMMARY OF QUALIFICATIONS...41 San Joaquin Valley Project Experience San Joaquin Valley Model Improvement Program, San Joaquin Valley Counties, CA TCAG Mode Choice Tools TCAG Truck O-D Study Model Development Project Experience Mountain Accord Travel Demand Model Development, Salt Lake City, UT... 43

6 SLOCOG Regional Traffic Model Improvement, San Luis Obispo County, CA AMBAG Model Update, Monterey County, CA Big Data Project Experience Fresno-Clovis Metropolitan Area Public Transportation Strategic Service Evaluation, Fresno County, CA US EPA Smart Location Performance Indicator, Nationwide Monterey Bay Origin-Destination Study, Monterey, Santa Cruz, and San Benito Counties, CA ATTACHMENTS...46 Title VI Assurance Appendices Appendix A: Resumes Appendix B: DBE/WBE Bidders Listing

7 OVERVIEW We understand the unique opportunity the project offers, and have developed a responsive approach to acquire new data and build on the Valley Model Improvement Plan (VMIP). We specifically intend to improve the travel models so they are not only valid, but also address on-going questions raised during the RTP/SCS process. Our most important goal is to improve the models so they can be used to better inform decisions, and to that end we have three main areas of focus: 1. Work in a collaborative and transparent manner, remain flexible and responsive to feedback from MPO staff and their consultants, and provide frequent coordination calls and hands-on training throughout the project. 2. Update data sources using recently available Census and household survey data, combined with innovative big data (such as cell phone origin-destination patterns and GPS speeds) to reestimate and update the model components. Revalidate the models both statically and dynamically, and update post-processers as needed. 3. Leverage previous and on-going projects in combination with new data to better account for jobs/housing and economic issues influencing local and regional travel. Summarize alternative interregional forecast data and provide tool to assist in consistent scenario development and accounting. The graphic on the following page illustrates the integration of our proposed tasks in relation to our objectives and the schedule. A description of each task is contained in the Detailed Work Plan section, including a schedule of tasks. 1

8 In addition to our experience outside the SJV, we will build on the VMIP and pilot projects during the VMIP and after to perform the following: 2

9 DETAILED WORK PLAN The detailed work plan comprehensively addresses tasks in the RFP as a starting point and incorporates the unique approaches and specialized tools to accomplish the goals of the San Joaquin Valley Model Improvement Plan Phase 2 (VMIP2) within the legislated funding schedule of 27 months. This will be possible thanks to Fehr & Peers decades of Valley-wide modeling experience, recent and on-going projects and coordination with MPO modeling staff, and our relationships with data providers and teaming partners. The project has been divided into four major tasks, described in detail immediately below and shown graphically on the preceding page. The detailed task descriptions include descriptions of key deliverables, and are also listed separately following the task descriptions. A schedule detailing the task timelines and showing concurrent tasks follows the listing of key deliverables. TASK 1 PROJECT MANAGEMENT AND INFORMATION SHARING Task 1.1 ADMINISTRATIVE COORDINATION MONTHLY PROGRESS REPORTS Monthly progress reports will be submitted to the Fresno COG project manager accompanied by conference calls as needed. Each report will itemize tasks completed, percentage of budget spent and achievement of overall study objectives. They will also contain a summary of obstacles and issues, recommended solution or course of action, and a timeline for resolution. Task 1.2 TECHNICAL COORDINATION MONTHLY WEBINARS Webinars offer a very efficient manner of conveying verbal, written and graphic communication, and will allow the team and clients to respond to new issues in a timely manner. Monthly webinars will be held to present overall study progress and status of Valley-wide modeling tasks such as data collection and analysis results, interregional forecasting and transferable scripts. These webinars will also provide opportunities to review and discuss progress on parallel projects and allow MPO staff to coordinate and share their screen with each other to collaborate on their experience with the data or models, and to have hands on training and application throughout the project. 3

10 Task 1.3 TRAINING Unlike the major structural changes that occurred at the beginning of the VMIP necessitating training on the use of the travel models beginning in the second half of the project the VMIP 2 will have fewer structural changes and will focus more on updating input data, calibration parameters, and expanding the pilot projects previously implemented for individual models to all SJV models. As a result, monthly meetings will be part information sharing and part hands on training. Building on the model user guides and step-by-step instruction material that has been developed to-date, we will develop sample data and examples using actual projects or questions asked by MPO staff and walk through how the data or improved models can be used to represent these situations. The material and examples developed and used during the monthly webinars will be compiled into a curriculum that can be used for reference and to train future modeling staff. Near the end of the project, additional in-person training will be provided at a day-long workshop. The day-long workshop will cover the training materials from start to finish and will assist modelers in the understanding and use of the application of the models, and the use of the curriculum as a resource. Task 1.4 ON-LINE PROJECT DATA CENTER Project coordination will be facilitated by a web-based project management center continually available to all project participants. The center will contain relevant project status and coordination information including schedules, progress reports, and other status-tracking information as well as copies of all memoranda and webinar material. It will also serve as a data sharing resource for data, model files, and documentation, accessible by both the consultant team and the MPO modelers. Task 1.5 ON-LINE GIS MAPPING Although some MPOs have GIS staff or their own GIS server, not all have these resources. Even when the resources are available, many times the model data are not included and member agencies or others wishing to view model data do not have the required software. To assist in sharing the valuable information contained within the models, GIS data can be made accessible for viewing and downloading through an interactive web mapping application hosted by Fehr & Peers. The GIS data can be password protected and displayed in a way to encourage collaboration while controlling access to what can be viewed or downloaded. By highlighting groups of TAZs, tables and charts of the data can quickly be created through the web interface. 4

11 The image below is an example of web mapping services we have created using SACOG model data. Deliverables Monthly Progress Reports Minutes of webinar meetings Training curriculum 1 day-long in-person training Access and updates to Data Center (as needed) Access and updates to ArcGIS Sever (as needed) TASK 2 DATA ACQUISITION, REVIEW, AND SUMMARY Due to the timing of the original VMIP, many data sources possessing great value to understand and model travel behavior were not available. As such, older sources were used to supplement data for the base year, making calibration and validation difficult due to the economic downturn after the 2001/2003 CHTS and 2000 Census were collected but before the calibration efforts began. VMIP 2 not only takes advantage of the most recent Census and CHTS data and the model structure enhancements developed 5

12 as part of the VMIP, but also years of experience with Big Data. The following tasks describe the data collection for model estimation, calibration, validation, and also comparisons to other sources for alternative future forecasts. TASK 2.1 ORIGIN-DESTINATION DATA The purpose of this task is to collect data on interregional travel associated with the SJV MPOs. Since interregional trips are very long and are more difficult to capture with a household travel survey, we will be building on the VMIP three-county OD study which used cellphone data as one source. The data will be used for validation at a county-to-county level and will include a majority of California to capture the travel and commute sheds experienced by the northern and southern Valley MPOs. We will investigate further geographic refinement such as the major cities within each county and the remainder of the county. Although travel within each county will be reported, the data will mostly focus on long distance trips, so very short trips will be excluded from the sample. Among the key classifications are: Average weekday (Tuesday-Thursday) Daily and peak periods that correspond to the model time periods The image to the left shows an example ranking the work place for residents from San Joaquin County. Similar maps will be created for each of the eight counties to show daily and peak period travel patterns. The data will be used to validate the interregional travel, and also to develop the interregional coordination and summary process described in Task 4.3. TASK 2.2 TRAFFIC SPEED DATA The VMIP added functionality to incorporate accessibility and cost throughout the modeling process, from vehicle availability through traffic assignment. Although the models were calibrated to relative speed and time to produce validated results for each step of the model, the congested speed that resulted was not calibrated. Since speeds influence safety, performance indicators, and emissions, we will calibrate the models to congested speeds as part of the VMIP 2. This will make it possible for the models to produce 6

13 reliable estimates of the extent to which new roadway projects improve travel speeds and reduce greenhouse gas and other emissions per VMT. This task will require roadway travel speed collected from in-vehicle GPS devices or smart phone applications from two sources. The first source (provided by Citilabs) will cover all model roadways at an aggregate level and will provide free-flow and congested travel speeds based on observed data. For congested areas, more refined Inrix data will be collected. In addition to speeds, Inrix data provide information on bottlenecks and other speed metrics, which will be used to acquire refined data only for those areas where it is most beneficial. This combined approach maximizes the coverage and usefulness of traffic data and minimizes the data cost. An additional data source, the National Performance Measurement Data provided by the Federal Highway Administration that covers only the National Highway System (NHS) will also be provided. This data set is free to MPOs and State Departments of Transportation and includes detailed speed data aggregated for all vehicles and speed data for large trucks. Since only NHS roadways are included, this information will be used to supplement the purchased data, providing the variation for all vehicles compared to trucks. With all the MIP models having a truck and goods movement component, this source provides a comparison at a scale and level of detail that was not previously possible. Inrix speed and bottleneck maps similar to the example on the left are very helpful in identifying hot spots that can then be visited in the field or studied further to determine possible improvements. Weather, collision, and construction notifications are also included so nonrecurring congestion locations are listed separately from recurring congestion. 7

14 TASK CENSUS/2012 ACS The newest Census and ACS data will be used to validate the household information, replacing the previous Census 2000 data. Not only are the data more recent and closer to the validation year, but the variables reported will be updated to reflect the implementation of the ACS and revised Census data questions. TASK CHTS The VMIP was completed before the 2012 CHTS data were available, and used the 2001/2003 CHTS for validation of the household variables. We will estimate the models using newer data, and also those cross-classifications that are available from the Census and ACS. In addition to cross-classifications similar to those in the current models, we will investigate the potential of estimation by variables that would allow for better job/housing and economic evaluations. TASK 2.5 ALTERNATIVE FORECAST DATA Although the primary focus of VMIP 2 is to update the data and base year models, the purpose of the model is to forecast the outcome of potential changes in the future. This task will identify and review multiple forecasting sources (DOF, Caltrans Planning, etc.) and approaches (more local growth, increased regional commuting, etc.) which we will summarize for discussion with the MPO staff. The information collected during this task and the interregional forecasting tool discussed in Task 4.3 can be used by MPO staff to develop consistent forecasting scenarios. With the expanded sensitivity to inputs, alternative forecast data in addition to regional population, housing, and employment will be summarized. Data relating to household size, fuel efficiency, fuel pricing, auto operation and maintenance will be compiled to inform future assumptions and scenario development. Alternative forecasts and trends for Vehicle Miles Traveled (VMT) will also be provided. TASK 2.6 HOUSING AFFORDABILITY, EMPLOYMENT AND JOBS/HOUSING BALANCE Demographic and employment data are critical components to any land use, transportation, or integrated land use-transportation modeling effort. An appropriately detailed description of the people that live and work in each geographic zone is essential to understanding their travel behavior and in predicting the region s evolution over time, especially the relationship between the locations of employers paying a given range of wages and the residence locations of workers with similar income levels. There are many sources for this data but no single source provides all the data needed; this necessitates the merging of data from multiple sources and verifying its compatibility with other datasets being used. 8

15 Rather than purchasing multiple expensive datasets, learning the benefits and limitations of each, and spending staff time summarizing the data, we have added CoStar to the team. CoStar employs over 1,200 surveyors that not only call and visit residential, office, and commercial buildings, they also combine multiple demographic and transportation databases into a single web-accessible dashboard. Not only does CoStar continuously update the data, they keep the historic data so we can evaluate changes in rents, vacancies, and other relevant variables. The image to the right is an example of the CoStar dashboard for multifamily developments with current and historic trends shown. These will be used to calibrate the bid/rent functions of the land use allocation/disaggregation model, and to assist in the estimation and calibration of trip generation and distribution, allowing additional functionality to better match jobs and household income. More detail on the implementation of this function within Cube Land can be found in Task 4.1. TASK 2.7 OTHER DATA The majority of updated and new data are identified specifically in Tasks 2.1 through 2.6, but other data may also be desired such as traffic counts, adopted RTP scenarios, or other studies and projects. During this task, we will evaluate potential data needs to supplement those collected in previous tasks, and will acquire data to aid in implementing Task 3 and Task 4. As we prepare for performance based planning, tighter budgets, and the potential of significant labor or transportation changes that could influence the overall regional economy, having data and methods to evaluate scenarios will be increasingly important. Together with EDR Group, we will coordinate with MPO staff to identify needs for economic assessment, existing and potential data sources, and output data provided from economic assessments. 9

16 Deliverables: Technical memo summarizing the data collection activities and results, including summary tables and charts for area policy makers Appropriate technical data to be included in the model systems and/or validation dataset TASK 3 REFINE MODEL INPUT DATA TASK 3.1 TRANSPORTATION ANALYSIS ZONES The transportation analysis zone (TAZ) system for each model was updated during the VMIP, but based on the new Census geography or areas of potential refinement encountered during model application, the TAZs will be reviewed. In consultation with the staff at each MPO, the TAZ boundary files will be updated. The appropriate GIS layers will be updated. TASK 3.2 LAND USE INPUTS During the VMIP, Census 2000 land use data were used in combination with the CHTS 2001/03 to estimate and calibrate the trip generation rates. After Census 2000, the Census Bureau not only developed the continuous sampling and reporting via the American Community Survey, but they also changed the format, variables, and detail of data being reported. In 2012 it was discovered that all of the variables used in the MIP models are not available at the same cross-classification detailed level as was reported in As such, we propose to update the residential demographic variables at the same time we re-estimate trip generation equations. In addition to the availability of data provided by the ACS and Census, updating the land use inputs at the same time trip information is estimated and calibrated allows for the opportunity to expand the capabilities to take advantage of the job salary and household mortgage/expense data. While the Census and ACS provide the information for the base year recalibration, we also propose to use Cube Land to disaggregate the base year land use to reflect the validation conditions, allowing future forecasts of residential demographics to vary based on land use and transportation system changes. Although the land use data and Cube Land model will be calibrated and implemented for each model, the application of Cube Land is not required. It can be used to disaggregate land use while keeping the totals by zone nearly identical, test brand new scenarios by allocating the control total for each land use type, or a middle scenario where some areas do not change and others are allowed to be allocated based on Cube Land. During the RTP/SCS process the land use scenario development and use of Cube Land in 10

17 combination with scenario planning tools was not as clear as we hoped. To minimize the confusion for future applications, MPO staff will be trained using hands-on examples on how to forecast and maintain the land use inputs, as discussed in Task 1.3. We will also coordinate with each MPO to develop future year land use scenario data based on their RTP/SCS scenarios. More details on the land use model estimation are described in Task 4.1. TASK 3.3 SPEED NETWORK UPDATE As part of the VMIP, integration of GIS for each of the models made a substantial step forward by utilizing a geodatabase for background data and for storing model outputs. However, the highway and transit networks remained stick networks. The speed data acquired in Task 2.2 will be delivered on a GIS network base that will replace the stick travel model network. The benefits of this are more accurate mapping and distances, easy linkage to and comparisons to speed data, and inclusion of local streets for sub-taz level analysis. In addition, the GIS network contains many variables to complement those already part of the travel model network, including auto, HOV, transit, truck, bike, and walk accessibility designations. Advanced models such as Activity Based Models (ABMs) and Dynamic Traffic Assignment (DTA) also greatly benefit from the network accuracy and detail. The current ABMs require a separate GIS centerline file for accessibility calculations, so an integrated GIS network would allow for maintenance of a single transportation system rather than two. 11

18 Although we strongly recommend converting from a partial GIS model with stick network to a full transportation system in GIS, the option will be left to each MPO. If an individual MPO wishes not to use a GIS network, the speed calibration comparisons will be made via visual comparison rather than direct automated comparisons. Since the stick network requires manual data transfer and comparisons, the cost and schedule are identical whether upgrading to a full GIS network or remaining with a stick network. OPTIONAL TASK 3.4 DEVELOP MERCED SINGLE COUNTY MODEL During the VMIP, the ABM was determined to be three-county and for simplicity the trip model followed the same structure. As a result, the overhead and run time for the MCAG model increased significantly. While it may be beneficial to have Merced County as part of the Three-County Model (TCM) for large regional planning studies like the RTP/SCS, smaller scale projects may not benefit from the large model area but still have the long run time. As an optional task, we will coordinate with MCAG to develop a single-county model that is derived from the Three-County Model and can provide inputs directly to the TCM. Each of the VMIP models were developed in a way to efficiently add or remove areas from the model from a structural perspective (network, TAZs, Cube Catalog, etc). Since the TCM was developed in such a way that MCAG could have a single county model, VMIP 2 would be an opportune time to do so since calibration and validation of the model is included either way. Alternately, the MCAG model could be calibrated as part of the TCM and then a single county model could be created after VMIP 2 under a separate scope. Deliverables: Updated TAZ system and GIS mapping for each of the MPO models Updated land use data by TAZ for the validation year and RTP forecast years for each of the MPO models Updated master road network and transit networks for the validation year and RTP forecast years for each of the MPO models 12

19 TASK 4 ESTIMATION, CALIBRATION, VALIDATION, AND EVALUATION OF MODEL IMPROVEMENTS TASK 4.1 ECONOMIC LAND USE FORECASTING The VMIP developed and implemented an integrated transportation and standard socioeconomic land use forecasting model structure by expanding the pilot project for KernCOG. This system supports the travel demand models by allocating study area forecast control totals of households and jobs by type to zones within the study area, based upon bid-rent economic principles. This approach to land use forecasting provides a way of recognizing the important effects that linkages between spatial distributions of housing costs, household incomes, and job industries have on intra- and interregional travel. It also provides a way to automate the otherwise tedious and error-prone process of disaggregating land use assumptions developed through scenario visioning exercises into more detailed household and job type stratifications for travel modeling. Although the Cube Land software needed in order to develop economic land use forecasts is available to all of the San Joaquin Valley regional planning agencies under the Valleywide licensing agreement, bidrent functions allowing for the evaluation of jobs/housing affordability balance or incentive policies were not estimated for all of these counties. With updated input data from Census 2010, 2012 CHTS, CoStar and other jobs/housing data, locally derived bid-rent functions will be estimated for the entire San Joaquin Valley, allowing all agencies to benefit from integrated economic land use forecasting. 13

20 Once calibrated to the base year, the Cube Land models can be used with DOF or Caltrans county forecasts, and the multi-year master networks to develop zonal-level estimates of population, households and employment for future years. Dynamic calibration techniques may also be applied to constrain future year socioeconomic land use forecasts to previously developed land use scenarios, while preserving the ability to test the sensitivity of these scenarios to network and regional control total changes. Deliverable Calibrated Cube Land model integrated with updated travel model Baseline socio-economic forecasts of jobs and households by TAZ TASK 4.2 TRAVEL MODEL ESTIMATION The trip generation, auto availability, mode choice, and related models will start with the estimation completed during the VMIP and will be estimated and calibrated using the region-specific data from the 2012/13 CHTS. The fairly limited sample size, particularly for transit and non-motorized trips, will likely preclude the estimation of county-specific mode choice model coefficients. For those particular parameters and any other key model parameters that cannot be accurately estimated on local data, parameters based on empirical evidence from models estimated using data from other regions such as Sacramento or Valley-analogous portions of the Bay Area will be used. The primary components of the travel model and the level of re-estimation for each is discussed below. 14

21 Task Trip Generation and Vehicle Availability The VMIP resulted in all models generating person trips by vehicle availability from a very consistent set of land uses, utilized cross-classified residential data to generate household trips, increased the number of purposes to include multiple non-home based trip purposes, added K-12 and College trip purposes, and generates small, medium and heavy truck trips. With the new CHTS data we will re-estimate the vehicle availability and trip generation rates. In addition to the cross-classifications currently used in the models, we will investigate classifications that relate jobs/housing, income and long distance commuting, and other factors that were not available in previous data sets. Since it is anticipated that some variables linking jobs and housing will result in statistically significant relationships, additional trip purposes will be added for use in trip distribution and mode choice. The primary source for the vehicle availability and trip purpose splits (other than the truck purposes) will be the 2012 CHTS. Due to sample size, aggregation of survey data may be needed to estimate a valley wide starting point for trip generation, and then calibration based on model specific data can refine trip rates. The revised trip generation rates will eventually be tested by comparing the resulting vehicle trips for the base year and future year (following the mode choice step) with prior estimates of vehicle trips. The rates will be calibrated to ensure that total vehicle trips fit within the established limits required for air quality conformity. Although the main benefit of new data relate to passenger vehicles, if additional truck counts are available we will also revisit the truck trip generation rates. As mentioned in the Post-2012 MIP Recommendations, vehicle classification counts are recommended to capture changes in the freight and goods movement, especially since the SJV shows signs of significant increase in truck related traffic. Deliverables: Table of revised vehicle availability coefficients Table of revised trip generation rates by vehicle availability for each MPO, comparison of trips for base and future years Task Trip Distribution The current gravity model trip distribution process and factors for each existing MPO model will be mostly maintained for consistency. The required revisions are: Add friction factors for additional trip purposes resulting in the jobs housing relationship 15

22 Ensure that friction factors for non-work trips do not screen out short trips which are likely candidates for non-motorized travel, particularly in models which have only used vehicle trip generation For models without mode choice components, the composite travel time will be estimated using walk time based on distance and an average of walk and drive time for origin-destination pairs where walk is competitive with auto. In addition, the sub-taz level of detail available in the GIS network will be used in combination with TAZ size. Deliverable Updated trip distribution including additional trip purposes and walk adjustments Task Mode Choice In general, the mode choice functionality will remain the same as the current model. We will investigate potential relationships of jobs/housing for mode choice, but since the current mode choice model takes many of these factors into account, we do not anticipate changing the variables, most likely re-estimating the coefficients based on CHTS 2012 data. The only exception is TCAG, who have a parallel project to implement transit networks and full mode choice model to replace the synthetic transit network in the current model. Fehr & Peers is implementing the changes in coordination with TCAG and will insure consistency and that parallel projects do not hinder the schedule of the VMIP 2. Deliverable Updated mode choice coefficients for each model Task Pricing Since there have been no significant changes in roadway or other pricing systems within the SJV between 2001 and 2012, we do not anticipate updating pricing mechanisms within the model. Information to assist in forecast scenarios for fuel price, auto operating cost, etc. will be provided as part of Task 2.5. Deliverable Updated price sensitivity, if applicable. Task Trip Assignment Trip assignment includes traffic assignments and transit assignments. 16

23 Traffic Assignment Using volumes and speed data we will review the current volume delay functions and determine if reestimation is needed. Using recent research we will evaluate the potential of changing assignment methods to account for new technologies such as GPS navigation to determine if stochastic or other methods should replace the current user equilibrium. As we begin to calibrate and use the congested speed data, we may revisit the assignment methods. Deliverable Updated highway networks and assignment parameters Transit Assignment We do not anticipate modifying current public transit (PT) assignment Feedback Loop Since overall congestion levels and overall VMT have gone down between the 2001 CHTS and the 2012 CHTS, we do not have data to use for changing the feedback loop methodology in general. TASK 4.3 INTERREGIONAL COORDINATION Each of the eight San Joaquin Valley counties currently uses its own estimates of travel growth at the county boundaries and the proportions of through traffic. These forecasts of growth and through trips may be very different, even for adjacent counties, making it difficult to consistently identify interregional travel and possibly consolidate travel forecasts from multiple MPOs. It is recommended to provide regionally consistent travel forecasts at the boundaries of each MPO. At the conclusion of the VMIP, both the Statewide model and the San Joaquin Valley 8 County model were potential sources for interregional trips, but neither are available for use as of February We will continue to coordinate with Caltrans and ARB to determine when/if the models can be used, and in the meantime will develop summary reports to easily compare results at the gateways, and utilize AirSage data to develop an allocation method for calculating interregional trips passing through an adjacent SJV MPO. If desired, we will add or replace the current calculation methods for VMT to provide alternative summaries (i.e. for SB 375 or Climate Action Plans), or develop a post-processer that can combine the outputs of each model to account for trips traveling through adjacent SJV MPOs. This process will also consider SB 743 implementation, which may require different methods for VMT estimates to be used in CEQA studies. 17

24 Deliverable Updated interregional forecast input method and forecast summary TASK 4.4 MODEL CALIBRATION In this task, each component of the updated model will be calibrated to ensure that it produces accurate forecasts. Calibration is an iterative process where model settings are adjusted so the output of the model matches observed travel patterns. TASK 4.5 MODEL STATIC VALIDATION In the static validation tests, we will run the model to ensure that the model output matches available traffic counts and roadway speeds. In addition, the model will be validated across screenlines composed of several roadways to ensure that overall traffic flows are captured. As part of the static validation procedure, elements of the trip generation, trip distribution, and traffic assignment modules may be adjusted. Our goal is to meet or exceed Caltrans and Federal Highway Administration static model validation guidelines. Examples of static tests may include evaluation of the following (bold indicates criteria new to VMIP 2): trip length frequency by purpose interregional distribution patterns average travel times by purpose mode split by purpose roadway segment model-to-count ratios screenline model-to-count ratios model congested speed versus observed congested speed spot checks of route assignment VMT within the county compared to HPMS transit system ridership TASK 4.6 MODEL DYNAMIC VALIDATION The static validation tests described above ensure that the model can replicate existing traffic counts and speeds. While these tests are useful at confirming that the model can replicate existing conditions, models are generally used to forecast change, which static tests say nothing about. To determine how 18

25 well the model responds to changes in land use and the transportation network, we will perform a set of dynamic validation tests. Dynamic tests may include testing the changes in the following: household location, density, diversity, and other household attributes (income, size, age, auto ownership) employment location, density, diversity, and type roadway network connections, link capacities and speeds transit service average system speeds and frequencies parking or other pricing programs TASK 4.7 EVALUATION Based on the one-on-one interviews and subsequent discussions with the San Joaquin Valley MPO modelers, conformity is a mega issue for each of the Valley MPOs. To address this issue and to provide options for future data collection and model enhancements, the following tasks will be performed. Using the adopted RTP/SCS, the transportation models will be evaluated with respect to their impact on positive conformity demonstrations, which are essential to the continued receipt of federal transportation funding, and current SB 375 baseline emissions and scenario analysis. A final step of the evaluation will be identifying what the next steps are in terms of data collection, model enhancement, and additional resources or coordination beyond the VMIP 2. TASK 4.8 INTEGRATE POST-PROCESSORS After the VMIP was completed, each MPO developed new post-processers to respond to ARB requests, provide performance measures, or summarize information for general use. If needed, we will integrate the post-processers into the Cube Catalog. In addition, many of the MPOs developed post-processers and quick-response tools to account for TDM and other measures not captured by the model. After the re-validation of the travel model these tools will be updated to account for the changes in calibration and associated sensitivities. TASK 4.9 DOCUMENTATION Individual model documentation will be updated to contain data collection results, estimation processes and parameters, calibration methodology, and static and dynamic validation results. A separate User 19

26 Guide and training curriculum will be compiled from the materials developed for the monthly meetings and in-person training workshops. Deliverables Models Post-processors, and Model Development Reports and User Guide. DELIVERABLES The following table summarizes the deliverables by task including deliverable date. Delivery date is approximate mid-point of each tasks delivery date, and may vary by MPO. 20

27 PROJECT DELIVERABLES Deliverable Delivery Date 1 Monthly Progress Reports Monthly from April 2014 Minutes of webinar meetings Monthly from April 2014 Task 1 Training Curriculum Monthly from April 2014 Day-long training May 2015/June 2016 Updates to Data Center As needed Updates to ArcGIS Server As needed Task 2 Technical memo summarizing the data collection activities and results November 2014 Data and updated model files December 2014 Updated TAZ system and GIS mapping September 2014 Task 3 Updated base and future road and transit networks for each model November 2014 Updated land use tables with subdivided TAZs for each MPO January 2015 Calibrated economic land use forecast with updated bid-rent functions April 2015 Revised vehicle availability coefficients for each MPO May 2015 Revised trip generation rates for each MPO November 2015 Updated trip distribution process for each MPO November 2015 Updated mode split/choice coefficients for each MPO November 2015 Task 4 Updated pricing sensitivity for each MPO November 2015 Updated highway networks and assignment parameters for each MPO November 2015 Updated interregional forecast input method and forecast summary December 2015 Static Validation Documentation March 2016 Dynamic Validation Documentation April 2016 Model Evaluation Documentation May 2016 Updated models, post-processors, and Model Development Reports June 2016 Note 1 Delivery date is approximate mid-point of the 8 models delivery date, and will vary by MPO. 21

28 SCHEDULE SAN JOAQUIN VALLEY MODEL IMPROVEMENT PLAN PHASE Task 1: Project Management and Information Sharing Task 1.1: Technical Coordination Task 1.2: Administrative Coordination April May June July August September October November December January Task 1.3: Training X X Task 1.4: Project Datacenter Task 1.5: Online Maps Task 2: Data Collection and Processing Task 2.1: Cell Phone Data Task 2.2: Traffic Speed Data Task 2.3: 2010 Census/2012 ACS Task 2.4: 2012 CHTS Task 2.5: Alternative Forecast Data Task 2.6: Housing affordability and jobs/housing balance Task 2.7: Other Data D M February March April May June July August September October November December January February March April May June 22

29 SAN JOAQUIN VALLEY MODEL IMPROVEMENT PLAN PHASE Task 3 Refine Model Input Data Task 3.1 Transportation Analysis Zones Task 3.2 Land Use Inputs Task 3.3 Speed Network Update Task 4 Model Estimation, Calibration, Validation, and Evaluation Task 4.1 Economic Land Use Forecasting Task 4.2 Travel Model Estimation Task 4.3 Interregional Coordination Task 4.4 Model Calibration Task 4.5 Model Static Validation Task 4.6 Model Dynamic Validation Task 4.7 Evaluation Task 4.8 Integrate Post- Processors April May June July August September D October November D December January M February March April May June D D July August September October November December January D D February March April May June D D M Task 4.9 Documentation Notes: X D M In-Person Training Deliverable Milestone and Deliverable M 23

30 MANAGEMENT APPROACH Managing the VMIP 2 requires a unique combination of technical understanding about model development (and application) plus the ability to direct people to complete assignments in a timeeffective manner. Directing people for key steps in the process will also require consideration of data acquisition and timing that could vary across a large number of interrelated efforts in all eight counties, leveraging the work completed as part of the original VMIP, and subsequent individual model refinements. The July 2016 sunset on availability of Proposition 84 funds will require highly effective management of the project schedule and effective interactions among the Valley modelers. We also recognize that Valley models have been under very close scrutiny as they were applied for the current RTP/SCS cycle. Many of the issues relate to economic development assumptions and interregional travel, which will be addressed as part of this project. Furthermore, the results of the VMIP 2 process will need to demonstrate to the Strategic Growth Council and the rest of the State of California that Proposition 84 funds have been spent in a productive manner that will lead to further evolutionary advances of modeling practices. For these reasons, we have assembled a team of experts, will acquire new and innovative data sources, and will combine our technical expertise with our deep familiarity with the VMIP models. We also have a management team, management approach, and management track record that will assure all of the above challenges are met. MANAGEMENT TEAM Building on the successful completion of the MIP and continued coordination with many of the MPOs since then, we are naming Mike Wallace, Fehr & Peers Director of Behavior Analysis & Forecasting, as overall Project Manager. In addition, Senior staff familiar with previous and on-going work with the SJV MPOs will serve as Principal in Charge and Senior Advisors. Project Manager Mike Wallace: Mike is a Senior Associate and the Director of Behavior Analysis & Forecasting with Fehr & Peers and has 10 years of in-depth modeling experience which includes substantial work with all of the MPO models in the San Joaquin Valley. Building upon his leadership role on Valley MIP study design and implementation and leveraging his recent experience with many of the MPOs as part of on-call model support or application for the RTP/SCS experience, Mike will serve as Project Manager for the overall study to ensure quality of tasks and deliverables. Mike also has extensive experience in applying innovative data collection and analysis techniques for use in travel demand models. Mike will coordinate closely with the 24

31 management team to aid in communication between the consultant team and the MPO staff, and to keep the project moving forward smoothly. Principal-in-Charge Ronald T. Milam, AICP, PTP: Ron is the Principal-in-Charge of technical development for Fehr & Peers. During his more than 20 years of professional work, he has successfully completed a wide variety of projects throughout the western U.S. ranging from federal and state guidance to local impact or circulation plans. His current focus involves the use of Big Data in transportation modeling and planning studies and has included working with a wide variety of data sources. Ron s recent work in the San Joaquin Valley includes providing technical expertise during the calibration and validation of the trip-based models for each county as part of the overall MIP and serving as the Principal-in-Charge for the Stanislaus County Regional Transportation Plan and City of Fresno General Plan updates. Senior Advisor Jerry Walters: Jerry is a founding Principal of Fehr & Peers, the firm s Chief Technical Officer and a member of Fehr & Peers Executive Committee. He has the experience and authority to assure full firm commitment and any needed resources are allocated to the project. He also has over 30 years of experience in travel forecasting and related policy issues. He has managed complex studies such as the US EPA Study of Mixed Use Trip Generation and Caltrans Statewide Modeling Tools, and was a member of the SB 375 Regional Targets Advisory Committee. Senior Advisor Richard Lee, Ph.D.: Richard has over 25 years of experience in regional transportation planning and modeling, much of it focused on the San Joaquin Valley. He will serve as the day-to-day team manager ensuring implementation of VMIP study design. He has in-depth familiarity with the Valley and its planning agencies, as well as expertise on SB 375 and RTP requirements and procedures. He is a specialist in off-line and in-line quick-response tools for augmenting the analytic capacity of travel demand forecasting models. 25

32 OUR MANAGEMENT APPROACH Our overall management approach will emphasize coordinated, direct interaction with each Valley MPO modeler and their MPO s associated planning staff. Each model improvement will have a dedicated consultant contact who will work directly with the model to perform the improvements in direct consultation with MPO staff. In cases where the MPO modeler prefers to play a hands-on role, the consultant will engage the MPO staff at that level. In cases where the MPO modeler prefers only to be kept informed and then familiarized and trained in the changes at the end of the effort, we will work in that manner. Mike Wallace, as Project Manager, will coordinate and oversee the individual tasks and conduct regular progress meetings with the Valley modelers group. TECHNICAL COORDINATION MONTHLY WEBINARS In addition to our continuous interaction with individual Valley modelers on their respective model improvements, we will conduct monthly webinars on the overall project progress and the status of Valleywide tasks such as interregional forecasting and transferable scripts. These webinars will also provide opportunities to review and discuss progress and help ensure the timely feedback relating to the political and planning context within which the models will be used. Many of the MPOs have on-call contracts and are undertaking parallel model enhancement activities, and these monthly meetings can be used to discuss coordination with multiple projects and schedules. ADMINISTRATIVE COORDINATION MONTHLY PROGRESS REPORTS We will submit monthly progress reports to the VMIP 2 project manager and will arrange and participate in conference calls as needed. Each report will itemize tasks completed, percentage of budget spent and achievement of overall study objectives. They will also contain a summary of key obstacles and issues encountered and recommended means and time-line for resolution. ON-LINE FILE TRANSFER SITE We will maintain a web-based project management center continuously available to all project participants. The center will contain all relevant project status and coordination information including schedules, progress reports and other status tracking information, as well as copies of all memoranda and webinar material. 26

33 OUR TRACK RECORD The Fehr & Peers staff responsible for management and oversight of the VMIP 2 project have broad and effective experience managing projects of this type, involving complex and multi-dimensional technical issues, with diverse groups of stakeholders and large consultant teams. We have consistently performed fully within project schedules and budgets and with highest levels of client satisfaction. The following table provides examples of successful similarly complex projects. EXPERIENCE MANAGING MULTI-JURISDICTION, MULTI-DISCIPLINARY STUDIES Study Number of Clients/ Jurisdictions Number of Sub- Consultants Time/ Budget Performance San Joaquin Valley Model Improvement Plan 8 Fresno COG, Kern COG, StanCOG, SJCOG, MCAG, TCAG, MCTC, KCAG 7 Accelerated schedule, onbudget San Joaquin Valley Model Improvement Study Design 8 Fresno COG, Kern COG, StanCOG, SJCOG, MCAG, TCAG, MCTC, KCAG 5 Accelerated schedule, onbudget National Study of Mixed-Use Trip Generation 2 US EPA, ITE (plus 6 major US metro regions) 4 On schedule, onbudget California Statewide MPO Transportation/Land Use Tools 8 representative California urban and rural MPOs 2 On-time and budget (through 40% of schedule) Quantifying Greenhouse Gas Mitigation Measures 35 (10 active) California Air Quality Management Districts 0 On-time, on budget San Diego Smart Growth Trip Generation Methods 20 SANDAG plus member jurisdictions 3 On-time, on budget Fresno Public Transit Infrastructure Study I 17 FresnoCOG plus member jurisdictions 8 On-time, on budget I-5 Corridor Strategic Transportation Plan 10 SJCOG, StanCOG, MCAG and representative cities 4 On-time, on budget Fehr & Peers is dedicated to client service and achieves exemplary levels of client satisfaction on all of its projects, large and small. We continuously survey all of our clients on the quality of our performance. Our client satisfaction levels have remained consistently high, as illustrated below. Over 98% of our clients rate us as meeting or exceeding their expectations, with 52% saying we exceeded expectations, and over 81% rating us better than our competitors. 27

34 In the critical areas of quality, value, and service, the following percentages of clients state that we met or exceeded their expectations: Quality 99% Value 97% Service 98% In summary, the Fehr & Peers team offers not only the full range and depth of expertise needed for VMIP 2 but also the management team, management approach and track record to produce a highly successful project. PROJECT PERSONNEL ORGANIZATION CHART The following organization chart illustrates our proposed management organization and the roles of other key members of our team. Resumes are included in Appendix A. 28

35 STAFF ROLES, TASKS, AND HOURS COMMITTED Project Manager, Mike Wallace, is responsible for overseeing the consultant team and will be the main point of contact for the MPO s and other modeling consultants. Mike will also ensure quality of tasks and deliverables. Estimated hours: 164. Principal in Charge, Ron Milam, will provide oversight and expertise. Hours: 47 Senior Advisors, Jerry Walters, Richard Lee and Bob Sicko, will provide specialized expertise and resources. Hours: 40 Senior Modelers/Statistician, Kevin Johnson, Mackenzie Watten and Jennifer Ziebarth, are responsible for QA/QC and implementation. Hours: 132 Modelers/Analysts, Leon Raykin, Kristin Carnarius, and Amy Smith are responsible for improving and calibrating models, and will work with survey and GIS data for estimates and modeling. Hours: