Appendix I: Travel Demand Forecasting Report

TRAVEL DEMAND FORECASTING REPORT

Prepared for: Sonoma-Marin Area Rail Transit District

Prepared by:

Parsons Brinckerhoff Quade & Douglas, Inc.

September 2005 Appendix I: Travel Demand Forecasting Report

Appendix I: Travel Demand Forecasting Report

TABLE OF CONTENTS

1.0 INTRODUCTION ------1

1.1 Study Corridor------1

2.0 MODEL BACKGROUND------3

2.1 Modeling Process ------3

2.2 System-Wide Flow of Trips ------4

2.3 Traffic Analysis Zones ------7

2.4 Highway Network------9

2.5 Transit Network------9 2.5.1 Transit Network Development ------9 2.5.2 Transit Network Path-Building ------10

2.6 Modifications to the MTC/VTA Model ------11 2.6.1 Home-Based Work Modifications ------11 2.6.2 Non-Home-Based Work Modifications------12 2.6.3 Walk Access Link Modifications------12

3.0 DEMOGRAPHICS ------13

3.1 Population------13

3.2 Employment ------15

4.0 STUDY ALTERNATIVES ------17

4.1 No-Build Alternative ------17

4.2 Express Bus Alternative ------18

4.3 SMART Passenger Rail Alternative: Cloverdale to Larkspur------22 4.3.1 Local Shuttle System ------24

4.4 SMART Passenger Rail Alternative: Windsor to San Rafael Minimum Operable Segment (MOS) ------25

5.0 RESULTS ------26

5.1 Transit Travel Times------26

5.2 System-Wide Transit Summary------29 5.2.1 Daily Transit Trips------29 5.2.2 Home-Based Work Transit Trips------29

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5.3 Express Bus Ridership ------30

5.4 Passenger Rail Ridership ------32 5.4.1 Daily Ridership ------32 5.4.2 Home-Based Work Ridership ------33 5.4.3 Peak Period Ridership ------35 5.4.4 Shuttle Bus Ridership ------38 5.4.5 Parking Demand------39

5.5 Transit Trip Length ------40

5.6 Vehicle Miles Traveled and Vehicle Hours Traveled ------41

LIST OF FIGURES Figure 1.1-1 Smart Corridor Study Area------2 Figure 2.2-1 Year 2025 Home Based Work Desire Lines – Sonoma County ------5 Figure 2.2-2 Year 2025 Home Based Work Desire Lines Desire Lines – Marin County ------6 Figure 2.3-1 Study Area Traffic Analysis Zones------8 Figure 2.5-1 Transit Support Node and Access Link Structure ------10 Figure 3.1-1 Forecast Growth in Population by TAZ, 2000-2025 ------14 Figure 3.2-1 Forecast Growth in Employment by TAZ, 2000-2025------16 Figure 4.2-1 Express Bus Alternative - Location of Express Bus Service Stops ------20 Figure 4.2-2 Express Bus Alternative - Location of Super Express Bus Service Stops ------21 Figure 5.1-1 Location of Traffic Analysis Zones with High Population and Employment------28 Figure 5.4-1 2025 Peak Period Ridership for Cloverdale to Larkspur Alternative------36 Figure 5.4-2 2025 Peak Period Ridership for Windsor to San Rafael Alternative------37

LIST OF TABLES Table 2.2-1 Flow of Home Based Work Trips from County to Super Districts in Year 2025------7 Table 3.1-1 Forecast Growth in Population, 2000-2025------13 Table 3.1-2 Forecast Growth in Number of Households, 2000-2025 ------13 Table 3.2-1 Forecast Growth in Employment, 2000-2025 ------15 Table 4.2-1 Frequency Improvements to Bus Routes------18 Table 4.3-1 Passenger Rail Alternative - Passenger Rail Stations ------22 Table 4.3-2 Passenger Rail Alternative - Station-to-Station Distance (Miles)------23 Table 4.3-3 Passenger Rail Alternative - Station-to-Station Travel Time (Minutes)------23 Table 4.3-4 Traffic Analysis Zones with Access to Parking at Stations------24 Table 5.1-1 High Population and Employment Traffic Analysis Zones ------26 Table 5.1-2 Future Peak Period Transit Travel Times in Minutes------27

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Table 5.2-1 Forecast 2025 System-Wide Total Daily Transit Trips Comparison ------29 Table 5.2-2 Forecast 2025 System-Wide Total Home-Based Work Transit Trips Comparison------30 Table 5.3-1 2025 Total Daily Ridership for Express Bus Routes ------31 Table 5.3-2 2025 Total Home-Based Work Ridership for Express Bus Routes ------31 Table 5.4-1 2025 Total Daily Ridership for SMART Passenger Rail: Cloverdale to Larkspur ------32 Table 5.4-2 2025 Total Daily Ridership for SMART Passenger Rail: Windsor to San Rafael ------33 Table 5.4-3 2025 Total Home-Base Work Ridership for SMART Passenger Rail: Cloverdale to Larkspur------34 Table 5.4-4 2025 Total Home-Base Work Ridership for SMART Passenger Rail: Windsor to San Rafael------35 Table 5.4-5 Daily 2025 Shuttle Bus Boarding for Cloverdale to Larkspur Alternative ------38 Table 5.4-6 Daily 2025 Shuttle Bus Boarding for Windsor to Rafael Alternative ------38 Table 5.4-7 2025 Parking Demand for Cloverdale to Larkspur Alternative------39 Table 5.4-8 2025 Parking Demand for Windsor to San Rafael Alternative------40 Table 5.5-1 Forecast Transit Trip Length for Build Alternatives ------41 Table 5.6-1 2025 VMT and VHT for Sonoma County and Marin County by Study Alternative------42

APPENDIX A – 2025 HOME BASED WORK TRIPS SONOMA COUNTY

APPENDIX B – 2025 HOME BASED WORK TRIPS MARIN COUNTY

APPENDIX C – STATION-TO-STATION FARE MATRIX

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Appendix I: Travel Demand Forecasting Report

1.0 INTRODUCTION

The Sonoma Marin Area Rail Transit (SMART) Rail District is evaluating transportation improvements along the approximately 70-mile corridor extending from Cloverdale in Sonoma County, California to a ferry terminal located in Larkspur, Marin County, California. The corridor generally parallels Highway 101 running north-south in Sonoma and Marin counties along an existing railroad right-of-way.

The objective of this SMART Travel Demand Forecasting report is to present travel demand modeling results for the alternatives analyzed as a part of the Draft Environmental Impact Report (DEIR) for the SMART project. A Draft Environmental Impact Statement (DEIS) will be prepared at a later date. The report presents the results of each alternative developed for the study based on anticipated demands for year 2025. The contents of this report include a description of the travel demand model used for the study, demographics of the study area, an overview of the study alternatives, and the travel demand forecast results for each alternative.

1.1 Study Corridor

The Highway 101/SMART corridor encompasses Sonoma and Marin counties. Sonoma County is the northernmost county of the nine county San Francisco Bay Area region, and it is bordered by Napa County to the east, Mendocino County to the north, the San Pablo Bay and Marin County to the south, and the Pacific Ocean to the west. Marin County is located north of San Francisco County and is bordered by the San Francisco Bay to the east and the Pacific Ocean to the west. Highway 101, a four- lane facility serves as the lifeline for local and regional traffic and transit in the two counties as it is the only continuous north-south roadway.

Figure 1.1-1 illustrates the study corridor. The corridor extends from Asti Road in Cloverdale through central Sonoma County to the ferry terminal at Larkspur in east Marin County. This report defines the SMART Study Area as the area inclusive of Sonoma and Marin counties in their entirety and distinguishes the Highway 101/SMART corridor as the transit corridor adjacent to Highway 101 encompassed by the following incorporated local jurisdictions: Cloverdale, Healdsburg, Windsor, Santa Rosa, Rohnert Park, Cotati, Petaluma, Novato, San Rafael, and Larkspur.

Ridership forecasts will be presented for other places in the study area served by the existing transit network. The Highway 101/SMART corridor is served by a network of bus routes operated by various public agencies. They include: • Golden Gate Bridge, Highway and Transportation District (GGBHTD) • Sonoma County Transit District • Marin County Transit District (Transit funding agency only) • Santa Rosa CityBus • Petaluma Transit • Healdsburg In-City

Travel times and delays on Highway 101 are expected to increase as a result of continuing population and employment growth in the region. High Occupancy Vehicle (HOV) lanes that were recently constructed provide some relief to certain high density segments of the highway. They include segments between San Rafael and Novato, and Wilfred Avenue (Rohnert Park) and Santa Rosa. As a part of future enhancements, new segments are identified for widening between Corte Madera and Windsor resulting in a seamless corridor of HOV lanes. In conjunction with these highway enhancements, the study analyzes alternate means of travel such as passenger rail and express-bus service between strategically located transit centers in the corridor.

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FIGURE 1.1-1 SMART CORRIDOR STUDY AREA

Source: Parsons Brinckerhoff

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2.0 MODEL BACKGROUND

The model chosen for the SMART project was the Santa Clara Valley Transportation Authority (VTA) regional model, which is an enhanced version of the Metropolitan Transportation Commission (MTC) regional model in TP+/Viper software. BAYCAST-90, the MTC regional model, encompasses the nine- county San Francisco Bay Area and is the model used to develop the Regional Transportation Plan (RTP) and prepare travel forecasts for major regional corridor studies. The MTC model was calibrated to the 1990 regional household survey and was re-validated by MTC to 1998 traffic counts and transit operator boardings as part of the 2001 update of the RTP.

VTA enhanced the MTC regional model by estimating transit submode ridership in the home-based work mode choice models, recalibrating to a more recent year 2000 baseline and adding in an external transit mode choice model to estimate transit trips from outside the nine county region into the region. The nine counties are Sonoma, San Mateo, Contra Costa, Marin, Santa Clara, Solano, San Francisco, Alameda, and Napa.

This model was chosen for the SMART project because it was recently recalibrated to base year 2000 conditions under guidance provided by the Federal Transit Administration (FTA) and it was the best model available in the region at the time. The FTA model recalibration was a condition for using the VTA regional models for the FTA New Starts project planning efforts.

To utilize the model for the SMART project only minor changes were necessary. The main changes were to the transit assumptions to reflect the differing transit levels of service by alternative. The remainder of this chapter briefly describes the general modeling process, the flow of work trips into and out of Sonoma and Marin counties based on the travel demand forecasting model, and the modifications and the major inputs to the travel forecasting model in terms of traffic analysis zones, highway network, and transit network. This section begins to set the stage for travel in the SMART corridor.

2.1 Modeling Process

The VTA model estimates travel in four basic steps: • Trip generation, • Trip distribution, • Mode choice, and • Trip assignment

The initial step, trip generation, geographically determines the amount of travel activity that the socio- economic data will generate; i.e., employment centers versus residential neighborhoods. The second step, trip distribution, links and disperses the generated travel by identifying origin and destination pairs. Mode choice then evaluates the various transportation options available and disaggregates the total demand by travel mode. The final step, trip assignment, is where demand is assigned to the transportation system facilities and modes.

The results of the trip generation and trip distribution steps (person trip tables) were obtained from a year 2025 model run, and were held constant for this project. The mode choice model is the integral link in the travel demand chain. Mode choice models are mathematical expressions used to estimate the share of travel on each available mode given its time and cost characteristics, and the demographic and socio- economic characteristics of trip makers.

The development of future year 2025 forecasts for the proposed transit improvements in the SMART Corridor relies primarily upon a nested logit mode choice model. The mathematics behind the mode

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choice model considers projected levels in 2025 for all key variables that influence travel demand. These variable considerations include population, households, employment, income, and auto ownership, as well as highway network characteristics (i.e. link capacities and speeds, centroid characteristics, and HOV facilities) and transit system characteristics (i.e. bus and rail routes, stations, and frequency). These major inputs into the travel demand model are discussed in the following sections and chapters.

2.2 System-Wide Flow of Trips

The Year 2025 trip tables for the study area were held constant; therefore the origins and destinations of the trips remain constant across alternatives. This section describes the major trip movements for the home-based work (HBW) trips related to the SMART study area. As mentioned, the model is comprised of nine counties. These counties are further divided into 34 superdistricts. The six superdistricts corresponding to Sonoma and Marin were combined to represent each county. To understand system- wide HBW trip movement, desire lines were created between each county in the SMART study area to every super-district in the remaining counties.

Figures 2.2-1 and 2.2-2 display Year 2025 desire lines representing two-way flow of HBW person trips for Sonoma County and Marin County, respectively. The blue lines indicate trip productions while the green lines indicate trip attractions. The tables of total home-based work person trips between super- districts, which were used to create these desire lines for each SMART county, are displayed in Appendix A and Appendix B. Figure 2.2-1 shows the flows to and from Sonoma County (Superdistricts 29) in 2025. The main flow of HBW trips is to/from Marin County, followed by flows to San Francisco (Superdistrict 1), and from Napa (Superdistrict 27). Figure 2.2-2 shows the 2025 flows to and from Marin County (Superdistrict 32) in 2025. The major flow of trips is to San Francisco (Superdistrict 1), followed by major flows to and from Sonoma County (Superdistricts 29 and 30).

Table 2.2-1 is a subset of the super-district to super-district table which focuses on 2025 trips associated with the SMART corridor going to/from the other super-districts. As shown in Table 2.2-1, 446,000 work trips originate in Sonoma County of which over 365,000 trips (or 82 percent) remain inside the county, the next highest area for Sonoma County work trip destinations is Marin County (Superdistricts 30-32) with nearly 40,000 daily trips, followed by San Francisco (Superdistrict 1) with approximately 12,000 daily trips. The super district with the most work trips destined to Sonoma County is from Napa County (Superdistrict 27), with over 14,000 daily trips. It is followed by Marin County, Superdistricts 30 and 31, which produces a combined flow of about 17,000 daily trips destined to Sonoma County.

As observed in Table 2.2-1, like Sonoma County the majority of work trips remain inside the county of origin, Marin, which generates over 125,000 daily trips. However, from Marin approximately 55,000 (22 percent) of work trips are attracted into San Francisco Superdistrict 1, and approximately nine percent travel to Sonoma County Superdistricts 29-31.

It is evident from the desire lines that the majority of the HBW trips in the study area remains within the origin County or travel to the other County. This, coupled with the congestion on Highway 101, suggest a need for travel within and between the counties.

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FIGURE 2.2-1 YEAR 2025 HOME-BASED WORK TRIP DESIRE LINES – SONOMA COUNTY

Source: Parsons Brinckerhoff

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FIGURE 2.2-2 YEAR 2025 HOME-BASED WORK TRIP DESIRE LINES – MARIN COUNTY

Source: Parsons Brinckerhoff

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TABLE 2.2-1 FLOW OF HOME-BASED WORK TRIPS FROM COUNTY TO SUPER DISTRICTS IN YEAR 2025 County District From Sonoma To Sonoma County District From Marin To Marin 1 12,326 730 1 55,098 1,710 San 2 2,805 1,888San 2 6,404 4,315 Francisco 3 2,731 951Francisco 3 8,478 3,117 4 485 688 4 1,767 1,468 5 2,594 618 5 5,383 3,455 San Mateo 6 1,087 217San Mateo 6 1,139 1,066 7 1,157 75 7 1,265 810 8 212 83 8 361 483 9 276 26 9 686 423 10 81 168 10 182 229 Santa Clara 11 113 84Santa Clara 11 254 168 12 67 98 12 375 134 13 75 67 13 63 89 14 79 49 14 45 46 15 633 679 15 749 556 16 511 169 16 706 1,096 Alameda 17 810 901Alameda 17 1,808 1,432 18 1,974 2,444 18 3,917 6,706 19 965 1,881 19 2,325 4,883 20 1,627 2,841 20 3,111 11,426 21 870 1,250 21 791 1,562 Contra Contra 22 390 585 22 1,263 1,000 Costa Costa 23 278 381 23 1,190 501 24 187 1,094 24 607 1,046 25 943 4,296 25 784 5,325 Solano Solano 26 1,139 3,730 26 381 4,331 27 3,550 14,034 27 835 2,143 Napa Napa 28 3,006 2,962 28 157 112 Sonoma 29365,111 29 12,286 25,410 30 18,042 9,061Sonoma 30 8,449 11,792 Marin 31 13,720 8,161 31 395 2,768 32 8,208 3,909 Marin 32 125,147 Total Sonoma Trips 446,050 429,229Total Marin Trips 246,400 224,749 Source: MTC Model, Parsons Brinckerhoff

2.3 Traffic Analysis Zones

Traffic Analysis Zones (TAZs) are building blocks of travel demand models. They represent geographic areas in the model from which and to which trips are allocated.

A particular level of geography can be designated as a TAZ and is typically based on using Census geography. Census geography is classified into blocks, block groups, tracts, and counties. The model was based on 1990 Census geography and the level of geography used was Census tracts. The same level of geography is retained in the SMART model to maintain consistency with the original structure. The entire model is comprised of 1,199 internal TAZs and 21 external TAZs. However, the study area is comprised of 108 internal traffic analysis zones. Figure 2.3-1 illustrates the TAZs in each study county.

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FIGURE 2.3-1 STUDY AREA TRAFFIC ANALYSIS ZONES

Source: MTC, 2003

The zonal data include a number of attributes that represent different characteristics of the geographic area. The main attributes defined are: • Population • Households • Auto Ownership • Area in Acres • Retail Employment • Non-Retail Employment • Mean Household Income

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2.4 Highway Network

Highway supply characteristics required by the travel forecasting procedures include estimation of the highway network facilities, highway level of service (i.e., travel speed or time), HOV and toll designations, and auto operating costs.

The model provided the highway networks for use on the SMART project. The networks were checked for connectivity and enhanced as necessary to provide slightly more detail in the study area. Minor enhancements were made which included adding new streets and reconnecting centroid connectors. HOV lanes were added in some portions of Sonoma and Marin counties resulting in a continuous set of HOV lanes on Highway 101 from Corte Madera to Windsor.

The future year 2025 highway network was used as an underlying network to develop transit networks for alternatives in this study. This highway network remained constant for all alternatives.

2.5 Transit Network

A reflection of the level of service experienced by a potential transit user is constructed through development of a computerized network representation of the system of routes and service levels existing in the region. This computer-coded transit network must be an accurate representation of the individual bus routes, fixed guide-way lines, headways, and travel times that define transit service. Consistency in representation methods across all alternatives is essential to ensure that differences in travel times between those alternatives are accurate portrayals of service level differences and not simply differences in coding conventions. Since level of service varies throughout the day, transit networks are constructed for both a peak period and a base or off-peak period. This allows the networks to capture such nuances as ‘express’ or ‘commuter’ routes that do not provide off-peak service or routes that offer different service frequencies at different times of the day.

An extensive network of bus routes, light rail, and passenger rail exists in the Bay area. The model incorporates the entire transit system that is expected to be in place by 2025 in the RTP network, including the route systems in Sonoma and Marin counties. This network was the starting point for developing the transit networks for the SMART project. These transit networks were developed based on using the future highway network as the underlying highway network. Four transit networks were created. They are defined in detail in the alternatives definition chapter but in general are as follows: 1. No-Build 2. Express Bus 3. SMART Passenger Rail Alternative: Cloverdale to Larkspur 4. SMART Passenger Rail Alternative: Windsor to San Rafael (Minimum Operable Segment)

2.5.1 Transit Network Development

Transit networks were developed for each alternative based on procedures from the BAYCAST model. For example, Figure 2.3-1 illustrates the different types of access links and transit support nodes created by the SMART model for a passenger rail station. The different geometric shapes represent transit support nodes and the dashed lines represent transit access links generated by the model. The access links are distinguished by origin and destination ends and are classified as: Mode 1 – Walk Access Connector (Traffic Analysis Zone to Funnel Node) Mode 2 – Drive Access Connector (Traffic Analysis Zone to Park-and-Ride Facility) Mode 3 – Transfer Connector (Bus Stop to Rail Station) Mode 4 – Drive Access Walk Funnel Link (Park-and-Ride Facility to Rail Station) Mode 5 – Walk Access Walk Funnel Link (Funnel Node to Rail Station)

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FIGURE 2.5-1 TRANSIT SUPPORT NODE AND ACCESS LINK STRUCTURE

Rail Tracks

Rail Station

MODE 3 MODE 4 MODE 5 Park ‘N’ Ride Lot Bus Stop Funnel Node MODE 2

Local Street MODE 1

Traffic Analysis Zone

Highway

Source: Parsons Brinckerhoff

The access links are generated for every transit route in the transit system. Each transit route is a computerized representation of the transit route through nodes that traverse the highway network specifying where the route stops allowing travelers to get on or off the route. Additionally, the route coding includes the frequency by time of day. The model creates an AM peak period network and a Midday off-peak period network.

The transit network development process also involved developing station-to-station fares, locating park- and-ride facilities near station stops, and designating traffic analysis zones that fall in the catchment area of these park-and-ride facilities. The catchment area for each park-and-ride facility encompassed zones that are within a maximum distance of seven miles.

Transit station-to-station fares for the SMART model were estimated based on assuming a maximum fare of $5.00 in 1990 US dollars for the 70-mile long passenger rail. A fare matrix was created based on distance between stations. Appendix C presents the fare matrix prepared for the full length passenger rail alternative.

2.5.2 Transit Network Path-Building

Transit paths were built and checked for accuracy using the transit networks developed following the procedures discussed in the preceding section. The paths were checked by producing interzonal transit paths on a select set of traffic analysis zones. The inputs to path-building included background highway network, transit route files, transit station-to-station fares, mode-to-mode transfer fares, supplementary link files, and access information.

Three sets of transit paths were produced by the model: 1. AM Peak Period “Best” Paths 2. AM Peak Period “Walk-only” Paths 3. Midday “Walk-only” paths.

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In the AM peak period best paths, walk access to transit competes with auto access to transit to produce the best paths. AM peak walk-only paths and midday walk-only paths produces walk access paths to transit.

2.6 Modifications to the MTC/VTA Model

This section presents modifications made to the MTC/VTA travel demand model for the SMART EIR. Specific changes were made to the mode choice portion of the model to improve its ability to estimate rail travel. Each modification was made with the intent of improving the model’s ability to replicate data observed in the region of interest (the San Francisco Bay Area). Observed data/behavior was obtained from the Caltrain On-Board Survey used to calibrate the model (Caltrain, 2003).The approach first introduced a new variable to the mode choice model, and the coefficient acting on the new variable was then calibrated using observed data. The changes are discussed in two sections below: for the home- based work trip purpose and the other trip purposes.

2.6.1 Home-Based Work Modifications

The home-based work mode choice model includes walk-to-transit modes segmented by service type (i.e. walk to passenger rail) and generic auto access modes (i.e. drive-to-transit; where transit could be passenger rail, light rail, local bus, and so on). The modifications to the model are discussed separately for each of these access types below.

Walk-access to Passenger Rail: The segmentation of transit modes in the walk access nest allowed for the introduction of passenger-rail specific coefficients. One shortcoming of the mode choice model is the lack of a penalty applied to bus-to-rail or rail-to-bus transfers. In the calibration year, this shortcoming caused an overestimation of transfer trips (a Caltrain on-board survey observed a transfer rate near 50% versus an estimated rate near 86%). To alleviate this problem, a variable to capture the number of transfers was introduced to the model and a coefficient was calibrated to allow the estimated transfer rate to more closely match the observed transfer rate. The final calibrated value for this coefficient was - 3.400, which corresponds to 70 equivalent minutes of in-vehicle travel time.

Drive-access to Transit: Transit modes in the drive access nest (park and ride and kiss and ride) are treated as generic. As such, variables specific to the passenger rail choice are introduced conditionally only if a passenger rail in-vehicle time is present in the input skim matrices (new drive access to passenger rail skims were produced for the SMART project and the mode choice source code was modified to accept the new skims). Three variables specific to the drive-to-passenger rail mode were introduced, namely: transfers (same as the walk access), a ratio of the drive access to passenger rail in- vehicle time, and an alternative specific constant.

The transfer variable behaves similar to the walk-access mode, discussed previously. Again, this variable was calibrated to match the observed transfer rate. The final calibrated coefficient is -4.200, which translates to 86 equivalent in-vehicle minutes.

The travel time ratio variable computes the ratio of the drive access time to the passenger rail in- vehicle time. Such a variable has been shown to be an important determinant of passenger rail choice in places such as San Diego. The coefficient on this variable was calibrated to approximately match the observed ratio in the San Diego Region. The final coefficient is -1.000 (20 minutes of in-vehicle time).

The introduction of negative utilities based on transfers and the travel time ratio causes the passenger rail portion of the drive-access to transit mode to lose market share. To regain this share, an alternative specific constant is introduced specific to the drive to passenger rail mode (again, the input skim is used to determine when this constant should be applied). The final value of this coefficient is 0.9732, which translates to 20 equivalent in-vehicle minutes.

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2.6.2 Non-Home-Based Work Modifications

Modifications made to the non-home-based work trip purposes include only a transfer penalty, similar to the home-based work modifications. Due to the difficulty of compiling and modifying the mode choice source code for these purposes, the penalty was introduced as a time penalty in the input skim matrices instead of coefficients in the source code. The resulting impact on the choice of mode is identical. The penalties were only introduced when a passenger rail travel time was present. The final calibrated penalty for the walk access transfer trips was 60 minutes and 75 minutes for the drive access trips.

2.6.3 Walk Access Link Modifications

In addition to the above noted modifications to the mode choice model, the project team also made some modifications to the walk access links. The walk links were recoded to better reflect the location of actual development relative to proposed rail stations. The modifications included shortening walk distances between several TAZ centroids and the associated rail stations and adding additional walk access links to connect additional TAZs to the rail stations. The main focus was at the Marin County Civic Center Station and Larkspur Station. At the Civic Center station three walk links were modified, TAZ 1063 was shortened from 0.8 of a mile to 0.4 of a mile, and TAZs 1061 and 1062 were added with a 0.6 mile access link and 0.35 mile access link respectively. Neither TAZ 1061 nor 1062 were originally included in the model, both TAZ centroids were over a mile from the rail station. At the Larkspur station the walk access link from TAZ 1081 was also shortened from over one mile to a half of a mile. Additionally, another walk link was added to the North Novato station from TAZ 1049. All walk links have an average speed of three miles per hour in the travel forecasting model.

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3.0 DEMOGRAPHICS

Population and employment are two major components in forecasting travel demand. Fluctuation in these components over a period of time and across geographic areas invariably impact transportation facilities giving rise to increased congestion, traffic delays, and higher transit ridership. This chapter highlights the changes in demographics and employment estimates in the study area for the base year (2000) and the future year (2025).

3.1 Population

Population data was obtained from the MTC regional model, which was based on information from the Association of Bay Area Governments (ABAG). Although this information was developed before the 2000 US Census data were released, the estimates are very close to each other. ABAG did a special set of forecasts that extended the horizon year of Projections 2000 from 2020 to 2025.

Based on MTC forecasts, the 2025 population for Sonoma County is projected to increase to approximately 591,600 persons, reflecting a growth of almost 30 percent. Marin County is projected to increase to approximately 278,400 persons, showing a nominal growth of 11.2 percent. The growth is expected to increase overcrowding in residential areas in the study area causing increased congestion on Highway 101 and affecting other transportation facilities. Tables 3.1-1 and 3.1-2 present the change in population and the number of households between the study years.

TABLE 3.1-1 FORECAST GROWTH IN POPULATION, 2000-2025 County 2000 2025 Growth % Growth Sonoma 455,305 591,597 136,292 29.9% Marin 250,402 278,401 27,299 11.2% Study Area 705,707 869,998 164,291 23.3% Source: ABAG Projections 2000 and MTC

TABLE 3.1-2 FORECAST GROWTH IN NUMBER OF HOUSEHOLDS, 2000-2025 County 2000 2025 Growth % Growth Sonoma 171,524 222,789 51,265 29.9% Marin 99,504 113,631 14,127 14.2% Study Area 271,028 336,420 65,392 24.1% Source: ABAG Projections 2000 and MTC

Figure 3.1-1 presents graphical illustrations of growth in population in Sonoma and Marin counties from 2000 to 2025. It is observed from the figure that areas located adjacent to the corridor report a higher growth in population than the areas further from the corridor. The higher population growth zones near the corridor are mainly comprised of cities and towns such as Windsor, Santa Rosa, Rohnert Park, Cotati, Petaluma, and Novato. Novato is projected to have the highest population growth of 95.8 percent. The dark shades in the figure represent zones with population growth ranging from approximately 61 percent to 100 percent and are located primarily to the east of the SMART corridor.

As expected, the growth in households is similar to the growth in population. The study area is projected to grow by over 65,000 additional households by 2025. Sonoma County is projected to increase by approximately 51,000 households, or nearly 30 percent, and Marin County is projected to increase by approximately 14,000 households, or about 14 percent.

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FIGURE 3.1-1 FORECAST GROWTH IN POPULATION BY TAZ, 2000-2025

Source: ABAG/MTC & Parsons Brinckerhoff, 2000

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3.2 Employment

Table 3.2-1 reports employment estimates for Sonoma and Marin counties by retail and non-retail categories. Between 2000 and 2025, Sonoma County is projected to have significant growth in non- retail employment of 63 percent compared with a growth of 28.2 percent in Marin County. The number of jobs in retail employment is expected to increase at a lower rate of 33 percent and 18 percent in Sonoma and Marin County respectively. Overall employment growth, however, is estimated to grow considerably at 47.6 percent for the entire study area.

TABLE 3.2-1 FORECAST GROWTH IN EMPLOYMENT, 2000-2025 County 2000 2025 Growth % Growth Non-Retail Employment Sonoma 366,980 598,079 231,099 63.0% Marin 220,350 282,488 62,138 28.2% Study Area 587,330 880,567 293,237 49.9% Retail Employment Sonoma 40,080 53,301 13,221 33.0% Marin 26,670 31,498 4,828 18.1% Study Area 66,750 84,799 18,049 27.0% Total Employment Sonoma 407,060 651,380 244,320 60.0% Marin 247,020 313,986 66,966 27.1% Study Area 654,080 965,366 311,286 47.6% Source: ABAG Projections 2000 and MTC

Figure 3.2-1 illustrates growth in total employment for the zones in the study area. It is observed from the figure that employment will continue to grow near the corridor especially in areas such as Healdsburg, Windsor, Petaluma, and Novato. The growth of employment near the corridor is higher compared with the growth of population.

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FIGURE 3.2-1 FORECAST GROWTH IN EMPLOYMENT BY TAZ, 2000-2025

Source: ABAG/MTC & Parsons Brinckerhoff, 2000

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4.0 STUDY ALTERNATIVES

As a part of the environmental analysis process for the Highway 101/SMART corridor, four alternatives were developed. The Draft Environmental Impact Statement (DEIS)/Draft Environmental Impact Report (DEIR) can be referred to for a detailed description of each alternative. This chapter provides a general description of the alternatives and a more detailed review of how the alternatives were created for forecasting travel demand.

4.1 No-Build Alternative

The No-Build Alternative provided an initial platform for applying the SMART model and analyzing the transportation impacts of other alternatives. The alternative consists of physical characteristics of roadway that existed in 2000 and additional projects as identified in the MTC 2025 Regional Transportation Plan (RTP) for the San Francisco Bay Area, and amended in November 2002. In the study area, these future projects mainly include HOV widening projects on Highway 101 at the following locations: • Marin County Gap Closure: Lucky Drive to North San Pedro Road • Marin-Sonoma Narrows: Route 37 to Petaluma • Old Redwood Highway to Rohnert Park Expressway • Rohnert Park Expressway to Wilfred Highway • Highway 12 to Steele Lane • Steele Lane to Windsor River Road

In the existing condition, transit stops or bus pads are located along Highway 101 in the general purpose lanes. These bus pads are accessible only to bus routes operating in the corridor. In the model, the routes using HOV lanes are coded to change lanes to the general purpose lanes to stop at the bus pad. A total of fifteen bus pads currently exist on Highway 101. They include: • Rohnert Park Expressway (Rohnert • Tiburon Blvd and Blythdale Blvd (Mill Park) Valley) • San Marin Drive/Atherton Avenue • Lucky Drive (Larkspur) (Novato) • Spencer Avenue (Sausalito) • Alameda del Prado (Novato)

• Ignacio Blvd (Novato)

• Rowland Blvd (Novato) • DeLong Avenue (Novato) • Miller Creek Road (Marinwood) • Freitas Parkway “Terra Linda” (San Rafael)

• North San Pedro Road (San Rafael) • Lucas Valley Road (San Rafael) • Paradise Drive and Tamalpais Drive (Corte Madera) • Seminary Drive (Mill Valley)

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The No-Build Alternative future scenario was designed to reflect 2001 bus service levels in the study area. The following express routes are included in the No-Build Alternative (refer to Appendix D for a complete list of all routes in the corridor):

80_GG2 80_GG18 80_GG24B 80_GG34 80_GG50A 80_GG70A 80_GG80A 80_GG4 80_GG20A 80_GG26 80_GG38 80_GG50B 80_GG72 80_GG80B 80_GG8 80_GG20B 80_GG28 80_GG44 80_GG54 80_GG74 80_GG93 80_GG10 80_GG24A 80_GG32 80_GG48 80_GG56 80_GG76 80_GG97

4.2 Express Bus Alternative

The Express Bus Alternative includes two main components, increased frequencies and additional routes. A 15 percent increase in frequency was incorporated in the model by modifying the headways on several bus routes. Table 4.2.1 presents peak and off-peak frequencies on these routes. The No-Build frequencies are indicated in parentheses.

TABLE 4.2-1 FREQUENCY IMPROVEMENTS TO BUS ROUTES Peak Off-Peak Peak Off-Peak Bus Route Bus Route Headway Headway Headway Headway Sonoma Local_14RPL 30 (70) 60 (90) Sonoma Intercity_48NBL 60 (80) 90 (100) Sonoma Intercity_20MRL 30 (60) 90 (90) Sonoma Intercity_60HXS 45 (100) - Sonoma Intercity_20MRL- 30 (60) 90 (90) Santa Rosa CityBus_4 30 (60) 60 (60) Sonoma Intercity_26WB 60 (100) 90 (100) Golden Gate_GG24A 45 (100) - Sonoma Intercity_30NBX 30 (100) - Golden Gate_GG72 12 (15) - Sonoma Intercity_30SBL 60 (80) 90 (100) Golden Gate_GG74 12 (18) - Sonoma Intercity_34SNV- 60 (100) - Golden Gate _GG80A 30 (30) 24 (30) Sonoma Intercity_40WBL 60 (90) 90 (100) Golden Gate _GG80B 20 (30) 24 (30) Sonoma Intercity_44NBL 30 (75) 40 (100) Golden Gate _GG1 15 (30) 30 (30) Sonoma Intercity_44SBL 30 (60) 40 (100) Golden Gate _GG1- 15 (30) 30 (30) Sonoma Intercity_46SSUX 60 (100) 90 (100) Golden Gate _GG75 24 (40) - Source: MTC Model, Parsons Brinckerhoff

The Express Bus Alternative also included several key improvements to inter-county bus services. Fourteen new bus routes were defined as a part of this alternative – 12 area-to-area passenger lines and two express bus lines. In the travel forecasting model these routes were coded as Golden Gate Transit for convenience as it is acknowledged that a decision on the transit operator has not been made. They are designated GG_80_101 through GG_80_114 and are listed below:

1. North Santa Rosa to Novato: GG_80_101 2. East Santa Rosa to Novato: GG_80_102 3. North Santa Rosa to Terra Linda: GG_80_103 4. East Santa Rosa to Terra Linda: GG_80_104 5. North Santa Rosa to San Rafael: GG_80_105

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6. East Santa Rosa to San Rafael: GG_80_106 7. Rohnert Park-Cotati-Petaluma to Novato (via Highway 101): GG_80_107 8. Rohnert Park-Cotati-Petaluma to Novato (via Sonoma Mountain Parkway): GG_80_108 9. Rohnert Park-Cotati-Petaluma to Terra Linda (via Highway 101): GG_80_109 10. Rohnert Park-Cotati-Petaluma to Terra Linda (via Sonoma Mountain Parkway): GG_80_110 11. Rohnert Park-Cotati-Petaluma to San Rafael (via Highway 101) : GG_80_111 12. Rohnert Park-Cotati-Petaluma to San Rafael (via Sonoma Mountain Parkway): GG_80_112 13. Express Bus: GG_80_113 14. Super Express Bus: GG_80_114

The twelve area-to-area passenger routes provide direct connection between residential areas and employment centers in the peak direction. These point-to-point long distance lines utilize the continuous set of HOV lanes on Highway 101 and supplement San Francisco bound bus services operated by Golden Gate Transit (GGT). The passenger routes have 60 minute headways per peak period in the peak direction (southbound in the morning and northbound in the afternoon), for a total of 24 round trips per weekday.

The Express Bus Route service (a modification of the existing Golden Gate Transit Route 80), stops at many freeway bus pads and off-freeway transit centers along Highway 101 between Cloverdale and the Larkspur water transit terminal. To accommodate stops at most of the freeway bus pads on Highway 101, the express bus service travels primarily in mixed flow lanes rather than in the HOV lanes. This route runs in the peak period and has a frequency of 120 minutes. Figure 4.2-1 illustrates the Express Bus stops along Highway-101.

The Super Express Bus Route service, between Cloverdale and the Larkspur water transit terminal, stops at four bus pads and four off-freeway transit centers effectively utilizing the Highway 101 HOV lanes to reduced travel times. The frequency on this route is 120 minutes during the peak period. Figure 4.2-2 illustrates the Super Express Bus stops along Highway-101.

The Express Bus alternative also includes physical and service improvements. Two new freeway bus pads are proposed near Highway 101/Steele Lane interchange in Santa Rosa and Highway 101/State Route 116 (Gravenstein Highway) interchange in Cotati.

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FIGURE 4.2-1 EXPRESS BUS ALTERNATIVE – LOCATION OF EXPRESS BUS SERVICE STOPS

Source: Parsons Brinckerhoff

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FIGURE 4.2-2 EXPRESS BUS ALTERNATIVE – LOCATION OF SUPER-EXPRESS BUS SERVICE STOPS

Source: Parsons Brinckerhoff

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4.3 SMART Passenger Rail Alternative: Cloverdale to Larkspur

This alternative provides passenger rail service along approximately 70 miles of the SMART corridor from Cloverdale in Sonoma County to the Larkspur water transit terminal in Marin County. In addition a 15 percent increase in frequency on several bus routes as mentioned in Section 4.2 was also incorporated in this alternative. The passenger rail serves 14 stations at the locations shown in Table 4.3-1. The rail service has a frequency of approximately 30 minutes in both southbound and northbound directions in the peak period and two trains during mid-day. The end to end travel time on the rail line is approximately 93 minutes, with an average speed of about 46 mph. Table 4.3-2 displays station-to- station distance in miles and Table 4.3-3 displays station-to-station travel times in minutes. Ridership forecasts for this particular rail alternative were developed for the Year 2025.

With the exception of Downtown Santa Rosa, Downtown San Rafael, and Larkspur stations parking is provided at all the remaining rail stations. A limited number of park-and-ride (PNR) spaces are accommodated at the Downtown Petaluma station. Table 4.3-4 lists the traffic analysis zones input to the model which have the most likelihood of using a PNR facility available at a station.

TABLE 4.3-1 PASSENGER RAIL ALTERNATIVE - PASSENGER RAIL STATIONS Rail Station Location

1. Cloverdale Asti Road south of Citrus Fair Drive 2. Healdsburg Historic Depot at Harmon Street 3. Windsor Windsor Road and Windsor River Road 4. Santa Rosa / Jennings Ave Jennings Avenue and Range Avenue 5. Downtown Santa Rosa Historic Depot at Railroad Square 6. Rohnert Park North of Golf Course Drive at Roberts Lake Road 7. Cotati Cotati Avenue and Industrial Road 8. Petaluma / Corona Road Corona Road and McDowell Boulevard Historic Depot at Lakeville Highway and E. 9. Downtown Petaluma Washington Street 10. North Novato Redwood Boulevard and Atherton Avenue 11. South Novato Ignacio Avenue and Highway 101 Interchange 12. Marin County Civic Center Civic Center Drive and McInnis Parkway 13. Downtown San Rafael Tamalpais Avenue between Third and Fourth Streets 14. Larkspur NWP Right-of-way west of Marin Airporter Source: Parsons Brinckerhoff, Community Design + Architecture, 2004.

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TABLE 4.3-2 PASSENGER RAIL ALTERNATIVE - STATION-TO-STATION DISTANCE (MILES)

Station Park Cotati Rohnert Windsor Larkspur Petaluma S. Novato N. Novato Downtown Downtown Cloverdale Petaluma - San Rafael Healdsburg Santa Rosa Santa Rosa Civic Center Jennings Av. Marin County Corona Road

Cloverdale 0.0 16.6 21.6 28.3 30.8 35.9 38.6 46.1 47.1 55.9 60.0 65.0 67.6 72.3

Healdsburg 16.6 0.0 5.0 11.7 14.2 19.3 22.0 29.5 30.5 39.3 43.4 48.4 51.0 55.7

Windsor 21.6 5.0 0.0 6.7 9.2 14.3 17.0 24.5 25.5 34.3 38.4 43.4 46.0 50.7

Santa Rosa - Jennings Av. 28.3 11.7 6.7 0.0 2.5 7.6 10.3 17.8 18.8 27.6 31.7 36.7 39.3 44.0

Downtown Santa Rosa 30.8 14.2 9.2 2.5 0.0 5.1 7.8 15.3 16.3 25.1 29.2 34.2 36.8 41.5

Rohnert Park 35.9 19.3 14.3 7.6 5.1 0.0 2.7 10.2 11.2 20.0 24.1 29.1 31.7 36.4

Cotati 38.6 22.0 17.0 10.3 7.8 2.7 0.0 7.5 8.5 17.3 21.4 26.4 29.0 33.7

Petaluma - Corona Road 46.1 29.5 24.5 17.8 15.3 10.2 7.5 0.0 1.0 9.8 13.9 18.9 21.5 26.2

Downtown Petaluma 47.1 30.5 25.5 18.8 16.3 11.2 8.5 1.0 0.0 8.8 12.9 17.9 20.5 25.2

N. Novato 55.9 39.3 34.3 27.6 25.1 20.0 17.3 9.8 8.8 0.0 4.1 9.1 11.7 16.4

S. Novato 60.0 43.4 38.4 31.7 29.2 24.1 21.4 13.9 12.9 4.1 0.0 5.0 7.6 12.3

Marin County Civic Center 65.0 48.4 43.4 36.7 34.2 29.1 26.4 18.9 17.9 9.1 5.0 0.0 2.6 7.3

San Rafael 67.6 51.0 46.0 39.3 36.8 31.7 29.0 21.5 20.5 11.7 7.6 2.6 0.0 4.7

Larkspur 72.3 55.7 50.7 44.0 41.5 36.4 33.7 26.2 25.2 16.4 12.3 7.3 4.7 0.0 Source: Parsons Brinckerhoff

TABLE 4.3-3 PASSENGER RAIL ALTERNATIVE - STATION-TO-STATION TRAVEL TIMES (MINUTES)

Station Park Cotati Rohnert Windsor Larkspur Petaluma S. Novato N. Novato Downtown Downtown Cloverdale Petaluma - San Rafael Healdsburg Santa Rosa Santa Rosa Civic Center Jennings Av. Marin County Corona Road

Cloverdale016233134404450546673798493

Healdsburg160 7 1518242834385057636877

Windsor 23 7 0 8 11 17 21 27 31 43 50 56 61 70

Santa Rosa - Jennings Av. 31 15 8 0 3 9 13 19 23 35 42 48 53 62

Downtown Santa Rosa 34 18 11 3 0 6 10 16 20 32 39 45 50 59

Rohnert Park4024179 6 0 4 10142633394453

Cotati44282113104 0 6 102229354049

Petaluma - Corona Road 50 34 27 19 16 10 6 0 4 16 23 29 34 43

Downtown Petaluma 54 38 31 23 20 14 10 4 0 12 19 25 30 39

N. Novato 66 50 43 35 32 26 22 16 12 0 7 13 18 27

S. Novato 73 57 50 42 39 33 29 23 19 7 0 6 11 20

Marin County Civic Center 79 63 56 48 45 39 35 29 25 13 6 0 5 14

San Rafael 84 68 61 53 50 44 40 34 30 18 11 5 0 9

Larkspur 93 77 70 62 59 53 49 43 39 27 20 14 9 0

Source: Parsons Brinckerhoff

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TABLE 4.3-4 TRAFFIC ANALYSIS ZONES WITH ACCESS TO STATION PARKING Rail Station Traffic Analysis Zones

1. Cloverdale 1046, 1047 2. Healdsburg 1044. 1045 3. Windsor 1040, 1041, 1042 4. Santa Rosa / Jennings Ave 1014, 1017-1022, 1026-1030, 1034-1039 5. Downtown Santa Rosa - 6. Rohnert Park 1006, 1009, 1010, 1012, 1013, 1023-1025, 1031 7. Cotati 1007, 1008, 1011 8. Petaluma / Corona Road 997-999, 1000, 1004, 1005 9. Downtown Petaluma 1001-1003 10. North Novato 1050-1054 11. South Novato 1055-1059 12. Marin County Civic Center 1060, 1061, 1063-1066, 1069 13. Downtown San Rafael - 14. Larkspur - Source: Parsons Brinckerhoff

4.3.1 Local Shuttle System

A local shuttle bus system is designed to distribute passengers at the work-end (i.e., non-home end) of their trip. However, the shuttles are also used as a means of access to the rail stations. A total of nine shuttle routes are proposed to serve the passenger rail stations in Downtown San Rafael, North Novato, South Novato, and Larkspur. These shuttles cater to the local populace living near a station but are primarily designed to serve the work end of the trip. The shuttles are free to passengers, and operate during the same hours as the passenger rail in the morning and afternoon peak commute periods. During the morning peak period the shuttles operate at six minutes headway and during the afternoon peak period they operate at 10 minutes headway.

A key feature of the shuttle system is to provide dedicated service to the passenger rail, allowing for a shorter timed-transfer connection between rail and bus services. For example, once all passengers from a given train have completed transferring to the bus, the bus departs the station. This allows an average transfer time of three minutes between passenger rail and shuttle. If a train is delayed, the shuttle waits for passengers from its subsequent arrival. This is an important benefit because it removes the uncertainty of waiting time associated with traditional bus-rail transfers.

Shuttles are scheduled to coincide with passenger rail timings traveling in the peak direction: southbound trains in the morning peak and northbound trains in the evening peak. Passengers traveling in the reverse peak direction may use shuttles but will experience a longer wait for a train. The routes are designed to permit a complete one-way loop in less than the headway of the train (i.e., less than 30 minutes). This maximizes the efficiency of the service and minimizes out-of-direction travel for passengers.

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4.4 SMART Passenger Rail Alternative: Windsor to San Rafael Minimum Operable Segment (MOS)

This passenger rail alternative referred to as the Minimum Operable Segment (MOS) provides passenger rail service in the SMART corridor from Windsor Station to the San Rafael Downtown Station. It has a similar operating plan as the Cloverdale to Larkspur passenger rail alternative including the 15 percent increase in frequency on several bus routes indicated in Section 4.2. However, the alignment is shorter, extending approximately 49 miles rather than 70 miles, and is less expensive to implement due to its shorter length. The end to end travel time on this rail line is approximately 61 minutes, with an average speed of about 48 mph. The rail stations on this segment are identical to the full passenger rail alternative except it only includes those stations between Windsor and San Rafael with the same park- and-ride facilities.

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5.0 RESULTS

This section discusses the travel forecasting results for the Year 2025. Specifically, this section examines sample transit travel times for each alternative, system-wide transit summaries for daily and home-based work (HBW) trips, ridership for express bus and local shuttle routes, as well as station by station rail boardings.

5.1 Transit Travel Times

Transit travel times were estimated between strategically located traffic analysis zones (TAZs) in the Highway 101/SMART corridor for each alternative. The zones were selected based on having the highest population and employment concentrations in the corridor. Table 5.1-1 presents total population and total employment for these TAZs.

TABLE 5.1-1 HIGH POPULATION AND EMPLOYMENT TRAFFIC ANALYSIS ZONES IN 2025 TAZ City/Town Population Employment 997 Petaluma 20,901 27,362 1011 Cotati 28,421 30,064 1025 Santa Rosa 17,622 30,644 1041 Windsor 45,413 9,874 1052 Novato 11,574 21,718 1081 San Rafael 10,124 23,362

1009 Rohnert Park 10,063 31,440 1019 Santa Rosa 14,257 36,938 1023 Santa Rosa 2,256 36,992 1036 Santa Rosa 3,570 39,554 1037 Santa Rosa 12,219 30,872 1052 Novato 11,574 21,718 1077 San Rafael 5,331 20,820 1081 San Rafael 10,124 23,362 Source: ABAG/MTC, 2000

In the above table, the first six zones represent high population zones while the remaining eight zones represent high employment zones. Travel times between these two sets of zone-interchanges were estimated for each transit alternative and are shown in Table 5.1-2. The estimated travel times are the total travel time from TAZ to TAZ, including initial wait times at a bus stop or a rail station, all transfer times from one mode to another mode, the in-vehicle travel time (IVTT), and the access and egress time. In addition, the travel times indicate the best available transit paths between zones and are representative of a combination of different modes of travel. Figure 5.1-1 illustrates locations of the TAZs shown in the above table.

The estimates indicate that travel times between zone-interchanges located at a longer distance are lower in each alternative compared to the No-Build Alternative. As an example, the distance between TAZ 1041 in Windsor and TAZ 1052 in Novato is approximately 38 miles and it takes 30 minutes less to travel by express bus or passenger rail than in the No-Build transit services. The Express Bus and the rail alternatives primarily provide point-to-point service to long distance travel and require fewer stops and transfers. These alternatives result in faster travel times compared to the No-Build, with possible savings in travel times of up to an hour.

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TABLE 5.1-2 FUTURE PEAK PERIOD TRANSIT TRAVEL TIMES IN MINUTES No-Build TAZ 1009 1019 1023 1036 1037 1052 1077 1081 CITY Rohnert ParkSanta Rosa Novato San Rafael 997 Petaluma 61 99 84 89 103 69 93 101 1011 Cotati 38 75 61 65 88 88 112 119 1025 Santa Rosa 34 40 33 40 83 88 99 111 1041 Windsor 82 52 55 53 72 122 146 167 1052 Novato 69 103 90 94 108 - 62 75 1081 San Rafael 103 137 124 128 141 72 24 - Express Bus TAZ 1009 1019 1023 1036 1037 1052 1077 1081 CITY Rohnert ParkSanta Rosa Novato San Rafael 997 Petaluma 61 99 84 89 103 69 66 74 1011 Cotati 38 75 61 65 88 88 72 81 1025 Santa Rosa 34 50 33 40 83 88 99 111 1041 Windsor 71 52 55 53 56 93 105 111 1052 Novato 69 103 90 94 108 - 61 75 1081 San Rafael 103 137 124 127 141 72 24 - Commuter Rail from Cloverdale to Larkspur TAZ 1009 1019 1023 1036 1037 1052 1077 1081 CITY Rohnert ParkSanta Rosa Novato San Rafael 997 Petaluma 40 83 44 54 87 56 61 73 1011 Cotati 34 75 38 65 75 62 67 79 1025 Santa Rosa 33 50 25 40 78 74 79 91 1041 Windsor 45 52 37 53 67 81 86 98 1052 Novato 56 100 60 91 104 - 45 57 1081 San Rafael 98 132 92 122 136 72 24 - Commuter Rail from Windsor to San Rafael (MOS) TAZ 1009 1019 1023 1036 1037 1052 1077 1081 CITY Rohnert ParkSanta Rosa Novato San Rafael 997 Petaluma 40 83 44 54 87 56 61 72 1011 Cotati 34 75 38 65 75 62 67 78 1025 Santa Rosa 33 40 25 34 78 74 79 108 1041 Windsor 45 52 37 53 67 81 86 97 1052 Novato 56 100 60 91 105 - 45 56 1081 San Rafael 99 134 95 124 138 74 25 - Source: MTC Model, Parsons Brinckerhoff

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FIGURE 5.1-1 LOCATION OF TRAFFIC ANALYSIS ZONES WITH HIGH POPULATION AND EMPLOYMENT

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5.2 System-Wide Transit Summary

5.2.1 Daily Transit Trips

Table 5.2-1 presents a summary of system-wide daily transit trips for each alternative and compares to the No-Build transit trips in the study area. In addition to the new SMART services, the daily transit trips include transit trips by various sub-modes operating in the Bay Area including bus routes (local, express), light rail transit (VTA, MUNI), heavy rail (BART), commuter rail (AMTRAK, Caltrain), and water transit services.

TABLE 5.2-1 FORECAST 2025 SYSTEM-WIDE TOTAL DAILY TRANSIT TRIP COMPARISON

Trips between Sonoma Trips within and and Marin Counties and Alternative between Sonoma and other 7 Bay Area Marin Counties counties

No-Build Daily Trips 46,699 55,119 Daily Trips 46,965 56,896 Express Bus Difference from No-Build 266 1,777 % Change 0.57% 3.22% Daily Trips 52,534 63,483 SMART Passenger Rail: Difference from No-Build 5,835 8,364 Cloverdale to Larkspur % Change 12.49% 15.17% Daily Trips 52,702 63,395 SMART Passenger Rail: Difference from No-Build 6,003 8,276 Windsor to San Rafael MOS % Change 12.85% 15.01% Source: MTC Model, Parsons Brinckerhoff

On a daily basis by 2025, it is estimated there will be over 55,000 trips within and between Sonoma and Marin counties. In addition, it is estimated there will be another 46,000 or more daily transit trips, which either begin or end in Sonoma or Marin counties. As existing services are improved or new service is added to the corridor, transit travel within the corridor is projected to increase. As seen in the table, the passenger rail alternatives are projected to attract more transit trips within the study area than the Express Bus Alternative. The two passenger rail alternatives are forecast to attract more than 8,000 daily trips within and between Sonoma and Marin counties, projecting an increase of 15 percent over the No-Build Alternative.

In comparison to the No-Build transit forecasts, each of the three Build alternatives is projected to attract a considerable number of trips traveling in the Highway 101/SMART corridor, ranging from approximately three percent to 15 percent. The transit trip movement between the study area and the remainder of the Bay Area is projected to increase by less than one percent for the Express Bus alternative and nearly 13 percent for the passenger rail alternatives

5.2.2 Home-Based Work Transit Trips

Table 5.2-2 displays system-wide home-based work (HBW) transit trips for each of the alternatives, and compares them to the No-Build HBW transit trips. HBW transit trips constitute an average of approximately 31 percent of the total system-wide transit trips in each alternative (Total 9-County Trips in

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Table 5.2-1 vs. Table 5.2-2). However, when comparing the system-wide versus HBW trips occurring between Sonoma and Marin counties and the other seven Bay Area counties the percentage is much greater - approximately 75 percent. This indicates the majority of transit trips with one end in the study area are work trips.

It is estimated there will be over 13,000 daily work trips within and between Sonoma and Marin counties in 2025, and approximately 41,000 work trips between the study area counties and the seven Bay Area counties in 2025. The number of transit trips increases as more transit service is added to the corridor.

The system-wide change in 2025 home-based work trips compared to the No-Build trips is projected to range from an increase of 970 trips to approximately 4,000 trips within and between Sonoma and Marin counties. The SMART passenger rail service between Cloverdale and Larkspur, combined with other transit services in the Highway 101/SMART corridor, is projected to carry approximately 4,000 additional trips compared to the No-Build Alternative transit services. The movement of work trips between Sonoma and Marin and other counties in the Bay Area is expected to increase by approximately two percent to 4.5 percent.

TABLE 5.2-2 FORECAST 2025 SYSTEM-WIDE TOTAL HOME-BASED WORK TRANSIT TRIP COMPARISON Trips between Sonoma Trips within and and Marin Counties and Alternative between Sonoma and other 7 Bay Area Marin Counties counties

No-Build HBW Trips 13,040 41,709 HBW Trips 13,477 41,938 Express Bus Difference from No-Build 437 229 % Change 3.35% 0.55% HBW Trips 18,372 47,440 SMART Passenger Rail: Difference from No-Build 5,332 5,731 Cloverdale to Larkspur % Change 40.89% 13.74% HBW Trips 18,419 47,599 SMART Passenger Rail: Difference from No-Build 5,379 5,890 Windsor to San Rafael MOS % Change 41.25% 14.12% Source: MTC Model, Parsons Brinckerhoff

5.3 Express Bus Ridership

Table 5.3-1 displays the total daily ridership for the 14 Express Bus routes by mode of access. The total ridership is projected to be over 2,300 daily riders who either drive or walk to the bus stop. It is observed that approximately 85 percent of the total ridership is by walk access to bus during the peak commuter period. The Express Bus (GG_80_113) attracts the highest ridership of 558 riders while the 12 area-to- area commuter routes attract a combined ridership of over 1,500 daily riders. A total of 230 riders are expected to travel daily by the Super Express Bus route.

Table 5.3-2 reports the total home-based work ridership for the Express Bus routes for drive access and walk access. During peak commute period, a total of 1,341 riders are projected to use the express bus routes for home-based work related trips. A majority of these trips are walk-access boardings with a share of approximately 85 percent of the total trips. The area-to-area commuter routes reflect a combined ridership of 881 riders, followed by Express Bus with 156 riders, and Super Express with 108 riders.

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TABLE 5.3-1 2025 TOTAL DAILY RIDERSHIP FOR EXPRESS BUS ROUTES

Express Bus Route Drive Peak Walk Total

North Santa Rosa to Novato: GG_80_101 0 1 1 East Santa Rosa to Novato: GG_80_102 3 60 63 North Santa Rosa to Terra Linda: GG_80_103 8 71 79 East Santa Rosa to Terra Linda: GG_80_104 18 134 152 North Santa Rosa to San Rafael: GG_80_105 3 42 45 East Santa Rosa to San Rafael: GG_80_106 10 107 117 Rohnert Park-Cotati-Petaluma to Novato: GG_80_107 7 115 122 Rohnert Park-Cotati-Petaluma to Novato: GG_80_108 10 129 139 Rohnert Park-Cotati-Petaluma to Terra Linda: GG_80_109 13 195 208 Rohnert Park-Cotati-Petaluma to Terra Linda: GG_80_110 16 216 232 Rohnert Park-Cotati-Petaluma to San Rafael: GG_80_111 10 194 204 Rohnert Park-Cotati-Petaluma to San Rafael: GG_80_112 12 218 230 Express Bus: GG_80_113 150 408 558 Super Express Bus: GG_80_114 55 175 230 Total Daily Ridership 315 2,065 2,380 Source: MTC Model, Parsons Brinckerhoff

TABLE 5.3-2 2025 TOTAL HOME-BASED WORK RIDERSHIP FOR EXPRESS BUS ROUTES

Express Bus Route Drive Peak Walk Total

North Santa Rosa to Novato: GG_80_101 0 1 1 East Santa Rosa to Novato: GG_80_102 0 32 32 North Santa Rosa to Terra Linda: GG_80_103 4 45 49 East Santa Rosa to Terra Linda: GG_80_104 11 82 93 North Santa Rosa to San Rafael: GG_80_105 1 23 24 East Santa Rosa to San Rafael: GG_80_106 5 63 68 Rohnert Park-Cotati-Petaluma to Novato: GG_80_107 0 60 60 Rohnert Park-Cotati-Petaluma to Novato: GG_80_108 0 69 69 Rohnert Park-Cotati-Petaluma to Terra Linda: GG_80_109 2 115 117 Rohnert Park-Cotati-Petaluma to Terra Linda: GG_80_110 1 131 132 Rohnert Park-Cotati-Petaluma to San Rafael: GG_80_111 1 120 121 Rohnert Park-Cotati-Petaluma to San Rafael: GG_80_112 0 140 140 Express Bus: GG_80_113 127 156 283 Super Express Bus: GG_80_114 44 108 152 Total Daily Ridership 196 1,145 1,341 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 31 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

5.4 Passenger Rail Ridership

5.4.1 Daily Ridership

Table 5.4-1 displays the balanced daily boardings and alightings for SMART passenger rail service between Cloverdale and Larkspur by mode of access. Table 5.4-2 displays the balanced daily boardings for the MOS between Windsor and San Rafael. An estimated 4,756 riders are projected to use the rail service on a daily basis in 2025 between Cloverdale and Larkspur and an estimated 3,464 riders are projected to use the MOS.

TABLE 5.4-1 2025 TOTAL DAILY RIDERSHIP FOR SMART PASSENGER RAIL: CLOVERDALE TO LARKSPUR Peak Off-Peak Total Commuter Rail Station Stop Drive Walk Walk Ridership Boardings 88 2 0 89 Cloverdale Alightings 88 2 0 89 Boardings 78 244 79 401 Healdsburg Alightings 78 244 79 401 Boardings 223 337 121 681 Windsor Alightings 223 337 121 681 Boardings 325 92 78 494 Santa Rosa - Jennings Ave. Alightings 325 92 78 494 Boardings 465 140 118 722 Downtown Santa Rosa Alightings 465 140 118 722 Boardings 273 90 37 400 Rohnert Park Alightings 273 90 37 400 Boardings 171 54 25 250 Cotati Alightings 171 54 25 250 Boardings 159 34 3 195 Petaluma - Corona Road Alightings 159 34 3 195 Boardings 200 110 53 362 Downtown Petaluma Alightings 200 110 53 362 Boardings 83 65 7 155 North Novato Alightings 83 65 7 155 Boardings 67 16 40 122 South Novato Alightings 67 16 40 122 Boardings 113 137 138 388 Marin County Civic Center Alightings 113 137 138 388 Boardings 83 49 176 307 Downtown San Rafael Alightings 83 49 176 307 Boardings 74 86 33 192 Larkspur Alightings 74 86 33 192 Boardings 2,398 1,454 905 4,756 GRAND TOTAL Alightings 2,398 1,454 905 4,756 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 32 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

TABLE 5.4-2 2025 TOTAL DAILY RIDERSHIP FOR SMART PASSENGER RAIL: WINDSOR TO SAN RAFAEL Peak Off-Peak Total Commuter Rail Station Stop Drive Walk Walk Ridership Boardings 201 180 82 463 Windsor Alightings 201 180 82 463 Boardings 304 72 71 447 Santa Rosa - Jennings Ave. Alightings 304 72 71 447 Boardings 407 129 98 634 Downtown Santa Rosa Alightings 407 129 98 634 Boardings 249 64 29 342 Rohnert Park Alightings 249 64 29 342 Boardings 166 47 24 236 Cotati Alightings 166 47 24 236 Boardings 151 30 2 183 Petaluma - Corona Road Alightings 151 30 2 183 Boardings 161 80 52 292 Downtown Petaluma Alightings 161 80 52 292 Boardings 71 62 7 140 North Novato Alightings 71 62 7 140 Boardings 52 15 38 105 South Novato Alightings 52 15 38 105 Boardings 94 86 116 296 Marin County Civic Center Alightings 94 86 116 296 Boardings 88 62 180 329 Downtown San Rafael Alightings 88 62 180 329 Boardings 1,942 826 696 3,464 GRAND TOTAL Alightings 1,942 826 696 3,464 Source: MTC Model, Parsons Brinckerhoff

Drive access boardings are approximately the same as the walk access boardings in the rail alternatives, reflecting 50 percent of all rail boardings for the Cloverdale to Larkspur Alternative and 56 percent of all rail boardings for the MOS Alternative. The model results indicate that the three most heavily utilized stations are Windsor, Santa Rosa at Jennings Avenue, and Downtown Santa Rosa. The Downtown Santa Rosa station is estimated to attract the highest number of boardings and alightings, with a total of approximately 722 riders for the Cloverdale to Larkspur Alternative and 634 riders for the MOS Alternative. The elimination of Cloverdale, Healdsburg, and Larkspur stations in the MOS Alternative results in a decrease of approximately 1,300 riders compared to the Cloverdale to Larkspur Alternative. In addition to the loss in ridership from the three eliminated stations, the remaining stations also have a small decrease in ridership.

In the two rail alternatives, the Novato stations have the fewest boardings and alightings with each attracting about 150 daily boardings and alightings across alternatives.

5.4.2 Home-Based Work Ridership

Table 5.4-3 presents home-based work balanced ridership for the Cloverdale to Larkspur Alternative by mode of access. The balanced ridership for the MOS Alternative is shown in Table 5.4-4.

Sonoma-Marin Area Rail Transit 33 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

In the year 2025 it is estimated that the passenger rail service between Cloverdale and Larkspur carries approximately 3,860 riders, reflecting approximately 89 percent of the total daily ridership. In the MOS Alternative, 3,092 riders are projected to travel between Windsor and San Rafael, reflecting approximately 75 percent of total daily trips. The drive access boardings constitute approximately 58 percent of all boardings for each of the two rail alternatives.

TABLE 5.4-3 2025 TOTAL HOME-BASED WORK RIDERSHIP FOR SMART PASSENGER RAIL: CLOVERDALE TO LARKSPUR Peak Off-Peak Total Commuter Rail Station Stop Drive Walk Walk Ridership Boardings 82 2 0 83 Cloverdale Alightings 82 2 0 83 Boardings 65 77 31 172 Healdsburg Alightings 65 77 31 172 Boardings 196 174 58 427 Windsor Alightings 196 174 58 427 Boardings 297 74 52 423 Santa Rosa - Jennings Ave. Alightings 297 74 52 423 Boardings 429 126 82 636 Downtown Santa Rosa Alightings 429 126 82 636 Boardings 252 78 27 356 Rohnert Park Alightings 252 78 27 356 Boardings 164 48 21 233 Cotati Alightings 164 48 21 233 Boardings 153 33 3 189 Petaluma - Corona Road Alightings 153 33 3 189 Boardings 197 107 48 351 Downtown Petaluma Alightings 197 107 48 351 Boardings 81 59 7 146 North Novato Alightings 81 59 7 146 Boardings 60 11 33 104 South Novato Alightings 60 11 33 104 Boardings 101 108 108 317 Marin County Civic Center Alightings 101 108 108 317 Boardings 76 42 153 271 Downtown San Rafael Alightings 76 42 153 271 Boardings 70 63 23 156 Larkspur Alightings 70 63 23 156 Boardings 2,220 999 642 3,860 GRAND TOTAL Alightings 2,220 999 642 3,860 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 34 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

TABLE 5.4-4 2025 TOTAL HOME-BASE WORK RIDERSHIP FOR SMART PASSENGER RAIL: WINDSOR TO SAN RAFAEL Peak Off-Peak Total Commuter Rail Station Stop Drive Walk Walk Ridership Boardings 183 161 54 397 Windsor Alightings 183 161 54 397 Boardings 278 64 48 389 Santa Rosa - Jennings Ave. Alightings 278 64 48 389 Boardings 376 117 68 561 Downtown Santa Rosa Alightings 376 117 68 561 Boardings 229 59 21 308 Rohnert Park Alightings 229 59 21 308 Boardings 159 43 20 221 Cotati Alightings 159 43 20 221 Boardings 145 29 2 176 Petaluma - Corona Road Alightings 145 29 2 176 Boardings 157 78 47 281 Downtown Petaluma Alightings 157 78 47 281 Boardings 69 56 6 130 North Novato Alightings 69 56 6 130 Boardings 46 11 32 89 South Novato Alightings 46 11 32 89 Boardings 84 76 94 253 Marin County Civic Center Alightings 84 76 94 253 Boardings 80 52 157 288 Downtown San Rafael Alightings 80 52 157 288 Boardings 1,804 742 546 3,092 GRAND TOTAL Alightings 1,804 742 546 3,092 Source: MTC Model, Parsons Brinckerhoff

5.4.3 Peak Period Ridership

Figures 5.4-1 and 5.4-2 display schematic representations of AM peak period boardings and alightings for each SMART passenger rail alternative. Peak boardings and peak alightings represent the sum of peak drive access and peak walk access ridership at each rail station during the morning (AM) commute peak period. In the figures, on and off indicate boardings and alightings respectively, at each station stop. The numbers between station stops indicate total segment volumes (or loads) in the direction of travel. As seen from the figures, the ridership is heavier in the southbound direction of travel than in the northbound direction of travel during the morning peak period; the reverse takes place in the PM peak period.

In the Cloverdale to Larkspur Alternative, illustrated in Figure 5.4-1, the peak period load point is in the southbound direction between the Santa Rosa-Jennings Avenue Station and the Downtown Santa Rosa Station with a load of 750 riders. In the southbound direction at both Windsor and Santa Rosa-Jennings Avenue stations it is estimated that there will be over 250 boardings during the AM peak period. In the northbound direction the AM peak period load point is about 300 and occurs between Rohnert Park and Downtown Santa Rosa stations.

Similar to the Cloverdale to Larkspur Alternative, the MOS Alternative’s peak load point in the southbound direction is between the Santa Rosa stations; however the load is less with approximately

Sonoma-Marin Area Rail Transit 35 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

570 riders (Figure 5.4-2). In the northbound direction, the peak period load point is between Cotati and Rohnert Park stations and is estimated to have approximately 300 AM peak period riders.

FIGURE 5.4-1 2025 PEAK PERIOD RIDERSHIP FOR CLOVERDALE TO LARKSPUR ALTERNATIVE

SOUTHBOUND NORTHBOUND On Off On Off 89 0Cloverdale 0 0

89 0

On Off On Off 156 6 0 160 Healdsburg

239 161 On Off On Off 356 49 126 30 Windsor

546 65

On Off On Off 259 56Santa Rosa - 33 70 Jennings Avenue

750 102

On Off On Off 9 358Downtown 11 228 Santa Rosa

400 320

On Off On Off 29 151 96 88 Rohnert Park

278 311

On Off On Off 66 28 115 18 Cotati

316 215 On Off On Off 62 5Petaluma - 121 5 Corona Road

373 99

On Off On Off 41 223Dowtown 31 16 Petaluma

191 84

On Off On Off 59 36 34 20 North Novato

213 70

On Off On Off 55 12 11 6 South Novato

257 66 On Off On Off 60 98Marin County 43 50 Civic Center

219 72 On Off On Off 0 111Downtown 21 0 San Rafael

108 51

On Off On Off 0 108Larkspur 51 0 TOTAL TOTAL 1,241 1,241 693 691

Sonoma-Marin Area Rail Transit 36 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

FIGURE 5.4-2 2025 PEAK PERIOD RIDERSHIP FOR WINDSOR TO SAN RAFAEL ALTERNATIVE SOUTHBOUND NORTHBOUND On Off On Off 351 0Windsor 0 30

351 30

On Off On Off 253 39Santa Rosa - 16 69 Jennings Avenue

566 84 On Off On Off 8300Downtown 6223 Santa Rosa

274 300 On Off On Off 25 118 85 87 Rohnert Park

181 302

On Off On Off 62 22 112 17 Cotati

221 208 On Off On Off 54 4Petaluma - 120 4 Corona Road

271 92 On Off On Off 37 159Downtown 31 15 Petaluma

148 77

On Off On Off 46 35 34 19 North Novato

159 62 On Off On Off 40 11 11 6 South Novato

188 57 On Off On Off 25 96Marin County 43 17 Civic Center

118 32

On Off On Off 0 118Downtown San Rafael 32 0 TOTAL TOTAL 901 902 490 487

Sonoma-Marin Area Rail Transit 37 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

5.4.4 Shuttle Bus Ridership

Table 5.4-5 and Table 5.4-6 report shuttle bus boardings by mode of access for each passenger rail alternative. An estimated 6,652 riders are projected to use the shuttle bus system in the Cloverdale to Larkspur Alternative and an estimated 4,756 riders in the MOS Alternative. It is observed that the total walk access boardings constitute over 90 percent of the total boardings in each alternative. For the full length alternative, the shuttle routes in Larkspur attract the highest number of daily riders with 2,000 boardings followed by the routes in San Rafael with over 1,700 boardings. For the MOS Alternative, the shuttle routes in San Rafael report the highest boardings of 1,800 boardings followed by the routes in Petaluma with 1,200 boardings. Ridership on the free shuttles is higher than rail ridership for both alternatives due to the model assignment of non-rail riders to the coded shuttle system.

TABLE 5.4-5 DAILY 2025 SHUTTLE BUS BOARDINGS FOR CLOVERDALE TO LARKSPUR ALTERNATIVE No. Shuttle Route City/Station Peak Drive Peak Walk Off-Peak Walk Total 1 80_Route_A San Rafael 0 23 65 88 2 80_Route_B San Rafael 48 271 101 420 3 80_Route_C San Rafael 90 435 417 942 4 80_Route_D San Rafael 19 122 123 264 5 80_Route_E Petaluma 28 292 112 432 6 80_Route_F Petaluma 87 477 269 833 80_Route_G-A Novato 7 88 147 242 7 80_Route_G-B Novato 20 133 350 503 80_Route_H-A Marin CCC 8 40 87 135 8 80_Route_H-B Marin CCC 65 510 128 703 80_Route_L-A Larkspur 195 605 803 1,603 9 80_Route_L-B Larkspur 46 322 119 487 Total Boardings 613 3,318 2,721 6,652 Source: MTC Model, Parsons Brinckerhoff

TABLE 5.4-6 DAILY 2025 SHUTTLE BUS BOARDINGS FOR WINDSOR TO SAN RAFAEL ALTERNATIVE No. Shuttle Route City/Station Peak Drive Peak Walk Off-Peak Walk Total

1 80_Route_A San Rafael 0 23 65 88 2 80_Route_B San Rafael 49 274 102 425 3 80_Route_C San Rafael 98 538 453 1,089 4 80_Route_D San Rafael 19 123 124 266 5 80_Route_E Petaluma 28 285 112 425 6 80_Route_F Petaluma 88 476 273 837 80_Route_G-A Novato 7 89 153 249 7 80_Route_G-B Novato 19 136 363 518 80_Route_H-A Marin CCC 9 44 87 140 8 80_Route_H-B Marin CCC 73 527 128 728 Total Boardings 390 2,515 1,860 4,756 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 38 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

5.4.5 Parking Demand

Table 5.4-5 shows the estimated daily parking required at each station based on the projected drive-to- station boardings for the full length passenger rail alternative during peak periods. It was assumed that about ten percent of the total drive access boardings occur by kiss-and-ride (KNR) type of boarding. It is estimated that approximately 1,110 parking spaces will be needed to meet the overall demand for station parking. The Santa Rosa – Jennings Ave. Station has the highest parking demand at 225 spaces while Downtown Petaluma has the lowest demand at 30 spaces. Table 5.5-5 reports the daily parking required at each station for the MOS alternative. It is projected that a total of 985 parking spaces will be required to meet parking needs with Santa Rosa and Downtown Petaluma stations showing similar parking demand as in the full length alternative.

TABLE 5.4-7 2025 PARKING DEMAND FOR CLOVERDALE TO LARKSPUR ALTERNATIVE Parking Rounded to Commuter Rail Drive Access Assume Spaces Nearest Five Station Boardings 10% Carpool Needed Spaces Cloverdale 175 157.5 78.8 80 Healdsburg 97 87.3 43.7 45 Windsor 401 360.9 180.5 185 Santa Rosa - Jennings Ave. 496 446.4 223.2 225 Downtown Santa Rosa 3No Parking Provided 0 Rohnert Park 204 183.6 91.8 95 Cotati 294 264.6 132.3 135 Petaluma 313 281.7 140.9 145 Downtown Petaluma 58 52.2 26.1 30 North Novato 140 126.0 63.0 65 South Novato 112 100.8 50.4 55 Marin County Civic Center 104 93.6 46.8 50 Downtown San Rafael 0No Parking Provided 0 Larkspur 2No Parking Provided 0 Total 2,399 2,154.6 1,077.3 1,110 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 39 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

TABLE 5.4-8 2025 PARKING DEMAND FOR WINDSOR TO SAN RAFAEL ALTERNATIVE Parking Rounded to Commuter Rail Drive Access Assume Spaces Nearest Five Station Boardings 10% Carpool Needed Spaces Windsor 370 333.0 166.5 185 Santa Rosa - Jennings Ave. 471 423.9 212.0 225 Downtown Santa Rosa 2No Parking Provided 0 Rohnert Park 189 170.1 85.1 95 Cotati 287 258.3 129.2 135 Petaluma 298 268.2 134.1 145 Downtown Petaluma 57 51.3 25.7 30 North Novato 117 105.3 52.7 65 South Novato 84 75.6 37.8 55 Marin County Civic Center 67 60.3 30.2 50 Downtown San Rafael 1No Parking Provided 0 Total 1,943 1,746.0 873.0 985 Source: MTC Model, Parsons Brinckerhoff

5.5 Transit Trip Length

Transit trip length for each build alternative was developed based on the transit person-miles-traveled (PMT) reported by the model. Table 5.4-9 presents total PMT and the average person trip length for each alternative by mode of access. In the Express Bus Alternative, the trip lengths were computed only for the long distance point-to-point express routes i.e. Express Bus and Super Express Bus.

From the table, it is observed that the Super Express Bus reports the highest trip length of 57 miles for drive access boardings and 29 miles for the peak walk access boardings. The long trip lengths could be attributed to fewer bus pads along its route and for effectively utilizing the HOV lanes on Highway-101. The Express Bus has shorter trip lengths of 15 miles and 11 miles for drive access and walk access boardings, respectively.

In the case of passenger rail alternatives, a higher trip length of approximately 17 miles is reported in the southbound direction for peak walk access boardings. For the drive access boardings, the southbound trip length is higher at 15 miles in the Cloverdale to Larkspur Alternative than the MOS Alternative which reports a trip length of 11 miles. However, in the northbound direction both rail alternatives have an average trip length of approximately 11 miles for drive access boardings. The MOS Alternative shows a higher trip length of approximately 14 miles for peak walk boardings in the northbound direction while the Cloverdale to Larkspur Alternative shows a shorter trip length of 10 miles in the same direction.

Sonoma-Marin Area Rail Transit 40 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

TABLE 5.5-1 FORECAST TRANSIT TRIP LENGTH FOR BUILD ALTERNATIVES Total Person-Miles- Average Person Express Bus Alternative Boardings Traveled (PMT) Trip Length (Miles) Express Bus Drive 150 2,251 15.01 Peak Walk 408 4,477 10.97 Off-Peak Walk--- Super Express Bus Drive 55 3,136 57.02 Peak Walk 175 5,083 29.05 Off-Peak Walk--- Total Person-Miles- Average Person Commuter Rail Alternative Boardings Traveled (PMT) Trip Length (Miles) Cloverdale to Larkspur (Northbound) Drive 756 8,189 10.83 Peak Walk 622 6,403 10.29 Off-Peak Walk 235 2,106 8.96 Cloverdale to Larkspur (Southbound) Drive 1,642 24,913 15.17 Peak Walk 832 14,275 17.16 Off-Peak Walk 671 6,901 10.28 Windsor to San Rafael (Northbound) Drive 701 7,560 10.78 Peak Walk 268 3,710 13.84 Off-Peak Walk 139 1,371 9.86 Windsor to San Rafael (Southbound) Drive 1,240 13,979 11.27 Peak Walk 557 9,237 16.58 Off-Peak Walk 555 5,465 9.85 Source: MTC Model, Parsons Brinckerhoff

5.6 Vehicle Miles Traveled and Vehicle Hours Traveled

Vehicle miles traveled (VMT) and vehicle hours traveled (VHT) for each future alternative were estimated using loaded highway networks from the model. VMT represents the product of highway traffic volumes and the vehicle distance traveled after trip assignment. Similarly, VHT represents the product of highway traffic volumes and highway congested travel time after trip assignment. VMT and VHT for the study area were estimated for morning four-hour peak period, morning peak hour and evening peak hour. Table 5.6-1 presents Year 2000 and forecast VMT and VHT by alternative for Sonoma and Marin Counties.

Sonoma-Marin Area Rail Transit 41 Travel Demand Forecasting Report September 2005 Appendix I: Travel Demand Forecasting Report

TABLE 5.6-1 2025 VMT AND VHT FOR SONOMA COUNTY AND MARIN COUNTY BY STUDY ALTERNATIVE Four-Hour Peak Period 4-Hour Peak 4-Hour Peak Average Roadway Scenario Year Period VMT Period VHT Speed (Mph)

No Build (Base) 2000 3,861,210 127,501 30.3 No Build (RTP) 2025 4,829,900 171,557 28.2 Express Bus 2025 4,832,840 171,401 28.2 Cloverdale to Larkspur Rail 2025 4,789,470 168,435 28.4 Windsor to San Rafael Rail (MOS) 2025 4,803,910 171,112 28.1 Morning (AM) Peak Hour AM Peak AM Peak Average Roadway Scenario Year Hour VMT Hour VHT Speed (Mph)

No Build (Base) 2000 1,197,530 42,833 28.0 No Build (RTP) 2025 1,607,490 80,006 20.1 Express Bus 2025 1,605,410 79,649 20.2 Cloverdale to Larkspur Rail 2025 1,599,780 78,197 20.5 Windsor to San Rafael Rail (MOS) 2025 1,593,270 77,879 20.5 Evening (PM) Peak Hour PM Peak PM Peak Average Roadway Scenario Year Hour VMT Hour VHT Speed (Mph)

No Build (Base) 2000 1,202,500 42,014 28.6 No Build (RTP) 2025 1,554,780 65,873 23.6 Express Bus 2025 1,563,810 66,937 23.4 Cloverdale to Larkspur Rail 2025 1,547,520 64,582 24.0 Windsor to San Rafael Rail (MOS) 2025 1,551,510 65,059 23.8 Source: MTC Model, Parsons Brinckerhoff

Sonoma-Marin Area Rail Transit 42 Travel Demand Forecasting Report September 2005

APPENDIX A

2025 HOME-BASED WORK TRIPS SONOMA COUNTY

Sonoma-Marin Area Rail Transit Travel Demand Forecasting Report September 2005

2025 TOTAL HBW TRIPS FROM SONOMA COUNTY TO SUPER-DISTRICTS IN BAY AREA (PART I) PART I San Francisco San Mateo Santa Clara Alameda

County SD 12345678910111213141516 1 74,391 11,119 10,162 1,850 3,057 2,252 1,622 1,230 1,997 868 642 313 58 240 878 245 2 91,541 44,429 24,412 6,616 8,021 4,876 4,480 2,823 3,188 1,483 1,577 626 553 250 1,318 1,868 San 3 112,883 22,575 66,398 9,541 19,404 6,652 7,881 4,574 4,289 2,374 1,861 881 381 342 2,558 2,556 Francisco 4 45,274 11,716 22,543 7,481 6,292 2,073 2,368 642 2,392 454 882 437 460 91.6 535 606 5 49,025 16,992 36,265 7,324 97,144 30,468 16,770 4,570 4,256 1,527 1,264 821 556 562 1,827 2,455 6 19,167 3,449 7,845 1,349 45,695 71,284 33,691 9,669 12,146 3,640 2,294 1,906 869 722 2,298 2,185 San Mateo 7 11,737 3,569 5,814 1,821 29,985 21,280 81,729 35,460 17,388 7,281 5,434 3,163 1,504 2,649 1,342 5,234 8 3,668 472 523 147 2,930 4,754 18,349 60,782 52,880 8,010 11,353 7,285 2,991 2,912 661 3,368 9 3,595 486 1,326 144 5,564 4,589 14,537 47,568 135,756 23,594 23,641 23,783 7,897 7,825 1,475 7,343 10 2,202 503 750 129 3,692 3,391 11,632 26,864 98,799 65,656 57,893 19,938 18,119 9,939 1,371 6,673 11 3,069 750 730 103 2,919 1,604 6,568 14,759 82,621 46,909 83,766 54,485 31,868 10,011 1,291 10,592 12 2,491 553 2,417 195 3,315 2,067 10,120 26,200 96,061 39,557 70,363 76,351 28,009 19,855 4,792 18,064 13 772 137 310 73.3 1,220 912 3,361 8,635 63,759 23,618 57,629 26,398 30,316 13,251 1,006 3,776 Santa Clara 14 1,040 25.7 159 8.5 97.7 135 642 1,916 13,199 8,276 15,674 6,998 11,876 51,764 321 992 15 10,102 614 1,597 77.8 3,324 3,681 3,445 2,564 20,053 2,613 5,189 9,606 1,755 548 102,778 13,383 16 12,296 917 5,782 1,325 9,862 8,780 14,158 11,684 50,574 8,380 12,797 17,348 4,849 1,846 15,073 96,951 17 19,316 3,356 4,763 1,648 10,062 13,343 10,023 3,189 9,230 2,447 3,651 3,150 777 802 26,886 41,676 18 58,263 11,710 13,896 3,219 9,995 5,898 4,102 2,282 4,666 1,559 2,595 2,044 758 644 14,929 22,511 Alameda 19 18,013 3,810 4,531 683 2,501 1,047 1,239 942 1,370 459 1,563 534 257 132 3,132 4,977 20 31,762 3,427 11,623 1,559 5,163 1,550 1,922 497 1,080 578 661 296 481 171 4,703 3,360 21 26,257 4,890 9,665 1,333 4,683 2,166 1,490 334 1,526 468 978 658 132 132 9,360 2,182 22 20,691 2,576 5,192 684 2,466 1,486 869 296 472 187 328 359 148 133 5,322 1,532 Contra 23 9,791 1,610 4,139 463 3,664 2,422 1,357 730 3,186 1,036 1,770 1,884 390 601 35,240 7,257 Costa 24 7,153 2,779 4,050 656 2,404 1,194 1,189 464 2,393 373 789 1,024 235 394 16,402 3,074 25 10,041 2,040 3,147 658 6,689 657 923 191 689 193 223 396 233 125 1,514 1,122 Solano 26 6,149 1,940 2,601 460 6,012 667 617 493 990 315 663 533 200 336 2,706 1,830 27 2,574 185 414 79.5 460 263 140 20.1 58.4 6.3 23.9 8.7 3.3 30.1 371 883 Napa 28 117 77.9 85 36.5 208 56.1 16.4 9.2 49.6 39.1 35 4.9 2.9 2.7 26.1 47.1 Sonoma 29 12,326 2,805 2,731 485 2,594 1,087 1,157 212 276 81.1 113 67.1 75 78.9 633 511 30 8,653 796 1,237 365 981 200 341 42.6 142 7 31.6 106 17.1 3.1 249 274 31 18,208 1,844 2,733 471 1,629 425 452 171 351 31.4 61.9 93.3 36.7 18.3 231 231 Marin 32 28,236 3,764 4,509 931 2,773 515 473 148 193 144 160 177 9.4 24 268 201 TOTAL 720,802 165,915 262,347 51,914 304,807 201,772 257,660 269,961 686,029 252,163 365,906 261,671 145,816 126,434 261,495 267,958

Sonoma-Marin Area Rail Transit A-1 Travel Demand Forecasting Report September 2005

2025 TOTAL HBW TRIPS FROM SONOMA COUNTY TO SUPER-DISTRICTS IN BAY AREA (PART II) PART II Alameda Contra Costa Solano Napa Sonoma Marin TOTAL CountySD17181920212223242526272829303132 1 735 4,248 1,389 347 441 752 545 159 161 88.3 130 17 730 529 565 616 122,376 2 2,539 7,287 3,288 830 1,343 855 788 484 386 155 330 40.4 1,888 1,224 1,521 1,569 222,587 San 3 3,551 8,072 4,880 1,238 1,858 853 799 700 224 154 159 34.4 951 513 1,021 1,584 291,740 Francisco 4 952 3,897 1,294 623 1,375 197 287 224 63.2 53.4 79.5 11.1 688 206 443 819 115,457 5 4,625 5,691 2,524 1,622 1,126 717 1,242 429 294 82.5 37.7 14.9 618 806 1,275 1,374 294,303 6 8,221 3,383 1,304 606 730 552 1,517 204 73.5 20.9 9 5.5 217 134 665 267 236,117 San Mateo 7 3,529 1,860 1,283 569 551 253 777 37 11.3 42.5 5.7 3.9 74.8 180 443 188 245,196 8 1,368 683 473 84.8 303 94.1 358 42 5.2 5.8 2 14.9 82.7 144 144 196 185,086 9 1,612 817 400 106 748 238 484 95.3 114 11.3 16.5 2.2 26 91.6 34.6 297 314,215 10 2,105 658 280 69.7 112 157 508 41.2 35.2 45.8 5.3 24 168 126 25 78.3 331,990 11 3,147 878 216 140 147 428 897 63 39.4 53.2 48 4.9 83.8 46.3 86 36.1 358,357 12 4,392 1,695 530 150 274 351 1,714 60.9 51.9 78.9 13.1 6.8 98.4 14.4 60.8 58.6 409,959 13 1,088 479 149 61.7 154 71.5 341 34.1 11 19.7 4.8 2.7 66.6 18.1 43.4 27.9 237,743 Santa Clara 14 261 117 27.7 10.8 36.9 81.1 281 64.5 4.3 17.8 1.8 1.8 48.8 2.6 6.7 36.3 114,125 15 21,976 17,250 2,719 1,863 4,104 4,388 19,157 1,157 159 168 80 46.8 679 231 187 138 255,631 16 40,998 20,049 6,938 1,205 2,044 1,432 4,562 426 71.5 78.8 168 11.4 169 394 422 280 351,868 17 90,929 62,076 10,959 3,568 3,230 2,386 6,457 1,146 352 256 90.6 26.9 901 294 738 401 338,127 18 44,395 145,168 31,854 11,334 7,770 7,633 5,338 1,969 1,302 547 459 203 2,444 899 3,480 2,327 426,192 Alameda 19 8,468 24,260 52,230 7,423 3,028 2,948 1,253 796 836 439 305 77.8 1,881 715 2,530 1,639 154,017 20 5,986 24,904 25,594 74,056 11,274 5,223 2,852 3,678 2,605 1,391 636 202 2,841 1,787 5,746 3,892 241,500 21 6,100 19,768 7,170 9,954 79,574 40,482 15,400 12,581 3,215 2,081 659 174 1,250 489 686 388 266,225 22 4,394 15,114 7,004 5,435 19,565 33,140 9,125 4,578 1,584 438 147 52.5 585 239 440 321 144,900 Contra 23 15,024 12,026 3,211 2,852 8,992 13,169 31,128 2,487 413 375 178 60.6 381 108 279 114 166,337 Costa 24 5,598 12,541 2,604 5,576 42,492 15,444 7,164 89,844 2,044 2,177 457 150 1,094 275 448 324 232,802 25 2,121 9,201 3,388 8,591 15,190 5,399 3,251 1,670 38,850 5,950 10,787 1,770 4,296 1,925 2,504 896 144,630 Solano 26 2,121 8,605 1,580 13,165 17,247 5,994 2,817 4,781 38,446 129,481 15,968 1,814 3,730 1,781 1,780 769 276,587 27 537 1,410 525 2,209 1,493 972 295 213 8,033 2,627 43,446 6,551 14,034 696 1,089 358 90,005 Napa 28 27.8 108 186 407 354 114 22.2 9.2 911 686 10,351 15,494 2,962 27.7 66.5 17.9 32,560 Sonoma 29 810 1,974 965 1,627 870 390 278 187 943 1,139 3,550 3,006 365,111 18,042 13,720 8,208 446,050 30 456 693 445 562 240 331 446 139 345 131 199 41.4 9,061 16,293 11,941 4,445 59,212 31 633 1,631 672 1,448 240 292 395 61.6 242 133 298 37.9 8,161 10,528 34,086 12,340 98,183 Marin 32 719 1,592 1,208 1,102 311 640 349 406 197 117 338 77.4 3,909 3,758 8,358 23,398 89,005 TOTAL 289,415 418,136 177,289 158,832 227,217 145,975 120,824 128,765 102,022 149,041 88,958 29,981 429,229 62,515 94,833 67,400 7,293,082

Sonoma-Marin Area Rail Transit A-2 Travel Demand Forecasting Report September 2005

APPENDIX B

2025 HOME-BASED WORK TRIPS MARIN COUNTY

Sonoma-Marin Area Rail Transit Travel Demand Forecasting Report September 2005

2025 TOTAL HBW TRIPS FROM MARIN COUNTY TO SUPER-DISTRICTS IN BAY AREA (PART I) PART I San Francisco San Mateo Santa Clara Alameda

County SD 12345678910111213141516 1 74,391 11,119 10,162 1,850 3,057 2,252 1,622 1,230 1,997 868 642 313 58 240 878 245 2 91,541 44,429 24,412 6,616 8,021 4,876 4,480 2,823 3,188 1,483 1,577 626 553 250 1,318 1,868 San 3 112,883 22,575 66,398 9,541 19,404 6,652 7,881 4,574 4,289 2,374 1,861 881 381 342 2,558 2,556 Francisco 4 45,274 11,716 22,543 7,481 6,292 2,073 2,368 642 2,392 454 882 437 460 91.6 535 606 5 49,025 16,992 36,265 7,324 97,144 30,468 16,770 4,570 4,256 1,527 1,264 821 556 562 1,827 2,455 6 19,167 3,449 7,845 1,349 45,695 71,284 33,691 9,669 12,146 3,640 2,294 1,906 869 722 2,298 2,185 San Mateo 7 11,737 3,569 5,814 1,821 29,985 21,280 81,729 35,460 17,388 7,281 5,434 3,163 1,504 2,649 1,342 5,234 8 3,668 472 523 147 2,930 4,754 18,349 60,782 52,880 8,010 11,353 7,285 2,991 2,912 661 3,368 9 3,595 486 1,326 144 5,564 4,589 14,537 47,568 135,756 23,594 23,641 23,783 7,897 7,825 1,475 7,343 10 2,202 503 750 129 3,692 3,391 11,632 26,864 98,799 65,656 57,893 19,938 18,119 9,939 1,371 6,673 11 3,069 750 730 103 2,919 1,604 6,568 14,759 82,621 46,909 83,766 54,485 31,868 10,011 1,291 10,592 12 2,491 553 2,417 195 3,315 2,067 10,120 26,200 96,061 39,557 70,363 76,351 28,009 19,855 4,792 18,064 13 772 137 310 73.3 1,220 912 3,361 8,635 63,759 23,618 57,629 26,398 30,316 13,251 1,006 3,776 Santa Clara 14 1,040 25.7 159 8.5 97.7 135 642 1,916 13,199 8,276 15,674 6,998 11,876 51,764 321 992 15 10,102 614 1,597 77.8 3,324 3,681 3,445 2,564 20,053 2,613 5,189 9,606 1,755 548 102,778 13,383 16 12,296 917 5,782 1,325 9,862 8,780 14,158 11,684 50,574 8,380 12,797 17,348 4,849 1,846 15,073 96,951 17 19,316 3,356 4,763 1,648 10,062 13,343 10,023 3,189 9,230 2,447 3,651 3,150 777 802 26,886 41,676 18 58,263 11,710 13,896 3,219 9,995 5,898 4,102 2,282 4,666 1,559 2,595 2,044 758 644 14,929 22,511 Alameda 19 18,013 3,810 4,531 683 2,501 1,047 1,239 942 1,370 459 1,563 534 257 132 3,132 4,977 20 31,762 3,427 11,623 1,559 5,163 1,550 1,922 497 1,080 578 661 296 481 171 4,703 3,360 21 26,257 4,890 9,665 1,333 4,683 2,166 1,490 334 1,526 468 978 658 132 132 9,360 2,182 22 20,691 2,576 5,192 684 2,466 1,486 869 296 472 187 328 359 148 133 5,322 1,532 Contra 23 9,791 1,610 4,139 463 3,664 2,422 1,357 730 3,186 1,036 1,770 1,884 390 601 35,240 7,257 Costa 24 7,153 2,779 4,050 656 2,404 1,194 1,189 464 2,393 373 789 1,024 235 394 16,402 3,074 25 10,041 2,040 3,147 658 6,689 657 923 191 689 193 223 396 233 125 1,514 1,122 Solano 26 6,149 1,940 2,601 460 6,012 667 617 493 990 315 663 533 200 336 2,706 1,830 27 2,574 185 414 79.5 460 263 140 20.1 58.4 6.3 23.9 8.7 3.3 30.1 371 883 Napa 28 117 77.9 85 36.5 208 56.1 16.4 9.2 49.6 39.1 35 4.9 2.9 2.7 26.1 47.1 29 9,410 1,646 1,806 247 827 181 172 58 97 38.7 57 29.7 20 42.5 266 249 30 1,736 642 355 221 692 504 244 99.7 105 36.8 44.3 33 22.4 33.2 300 170 Sonoma 31 1,180 517 571 17 1,076 402 742 54 74 5.6 11.6 4.8 32.6 3.2 67 93 Marin 32 55,098 6,404 8,478 1,767 5,383 1,139 1,265 361 686 182 254 375 63.2 45.4 749 706 TOTAL 720,802 165,915 262,347 51,914 304,807 201,772 257,660 269,961 686,029 252,163 365,906 261,671 145,816 126,434 261,495 267,958

Sonoma-Marin Area Rail Transit B-1 Travel Demand Forecasting Report September 2005

2025 TOTAL HBW TRIPS FROM MARIN COUNTY TO SUPER-DISTRICTS IN BAY AREA (PART II) PART II Alameda Contra Costa Solano Napa Sonoma Marin TOTAL County SD 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 1 735 4,248 1,389 347 441 752 545 159 161 88.3 130 17 152 521 56 1,710 122,376 2 2,539 7,287 3,288 830 1,343 855 788 484 386 155 330 40.4 648 1,074 165 4,315 222,587 San 3 3,551 8,072 4,880 1,238 1,858 853 799 700 224 154 159 34.4 340 466 145 3,117 291,740 Francisco 4 952 3,897 1,294 623 1,375 197 287 224 63.2 53.4 79.5 11.1 292 324 72 1,468 115,457 5 4,625 5,691 2,524 1,622 1,126 717 1,242 429 294 82.5 37.7 14.9 230 354 35 3,455 294,303 6 8,221 3,383 1,304 606 730 552 1,517 204 73.5 20.9 9 5.5 81 128 9 1,066 236,117 San Mateo 7 3,529 1,860 1,283 569 551 253 777 37 11.3 42.5 5.7 3.9 27.6 40 7 810 245,196 8 1,368 683 473 84.8 303 94.1 358 42 5.2 5.8 2 14.9 60.2 14 8 483 185,086 9 1,612 817 400 106 748 238 484 95.3 114 11.3 16.5 2.2 9.1 14.3 2.6 423 314,215 10 2,105 658 280 69.7 112 157 508 41.2 35.2 45.8 5.3 24 125 40 3.5 229 331,990 11 3,147 878 216 140 147 428 897 63 39.4 53.2 48 4.9 17.2 58.5 8.1 168 358,357 12 4,392 1,695 530 150 274 351 1,714 60.9 51.9 78.9 13.1 6.8 46.3 45.2 6.9 134 409,959 13 1,088 479 149 61.7 154 71.5 341 34.1 11 19.7 4.8 2.7 10.4 52.8 3.4 89.4 237,743 Santa Clara 14 261 117 27.7 10.8 36.9 81.1 281 64.5 4.3 17.8 1.8 1.8 3.8 41 4 45.6 114,125 15 21,976 17,250 2,719 1,863 4,104 4,388 19,157 1,157 159 168 80 46.8 128 537 14 556 255,631 16 40,998 20,049 6,938 1,205 2,044 1,432 4,562 426 71.5 78.8 168 11.4 71 84 15 1,096 351,868 17 90,929 62,076 10,959 3,568 3,230 2,386 6,457 1,146 352 256 90.6 26.9 368 417 116 1,432 338,127 18 44,395 145,168 31,854 11,334 7,770 7,633 5,338 1,969 1,302 547 459 203 1,081 1,135 229 6,706 426,192 Alameda 19 8,468 24,260 52,230 7,423 3,028 2,948 1,253 796 836 439 305 77.8 943 808 131 4,883 154,017 20 5,986 24,904 25,594 74,056 11,274 5,223 2,852 3,678 2,605 1,391 636 202 1,209 1,443 188 11,426 241,500 21 6,100 19,768 7,170 9,954 79,574 40,482 15,400 12,581 3,215 2,081 659 174 497 494 259 1,562 266,225 22 4,394 15,114 7,004 5,435 19,565 33,140 9,125 4,578 1,584 438 147 52.5 185 350 50 1,000 144,900 Contra 23 15,024 12,026 3,211 2,852 8,992 13,169 31,128 2,487 413 375 178 60.6 99 164 117 501 166,337 Costa 24 5,598 12,541 2,604 5,576 42,492 15,444 7,164 89,844 2,044 2,177 457 150 414 566 114 1,046 232,802 25 2,121 9,201 3,388 8,591 15,190 5,399 3,251 1,670 38,850 5,950 10,787 1,770 2,039 2,115 142 5,325 144,630 Solano 26 2,121 8,605 1,580 13,165 17,247 5,994 2,817 4,781 38,446 129,481 15,968 1,814 1,634 1,894 202 4,331 276,587 27 537 1,410 525 2,209 1,493 972 295 213 8,033 2,627 43,446 6,551 9,016 4,919 100 2,143 90,005 Napa 28 27.8 108 186 407 354 114 22.2 9.2 911 686 10,351 15,494 854 1,931 177 112 32560 29 451 1,377 690 1,136 516 261 147 133 647 871 2,726 1,431 60,623 41,458 2,431 25,410 155,451 30 104 439 197 466 237 120 120 49 265 251 681 1,408 26,556 158,061 11,971 11,792 217,953 Sonoma 31 255 158 77 25 116 10 10 4.1 32 17 144 167 8,756 35,119 20,137 2,768 72,646 Marin 32 1,808 3,917 2,325 3,111 791 1,263 1,190 607 784 381 835 157 12,286 8,449 395 125,147 246,400 TOTAL 289,415 418,136 177,289 158,832 227,217 145,975 120,824 128,765 102,022 149,041 88,958 29,981 128,799 263,118 37,312 224,749 7,293,082

Sonoma-Marin Area Rail Transit B-2 Travel Demand Forecasting Report September 2005

APPENDIX C

STATION-TO-STATION FARE MATRIX

Sonoma-Marin Area Rail Transit Travel Demand Forecasting Report September 2005

STATION TO STATION FARE* MATRIX

Station Park Cotati Rohnert Rohnert Windsor Larkspur Petaluma S. Novato N. Novato Downtown Downtown Cloverdale Petaluma - San Rafael Healdsburg Santa Rosa Santa Rosa Civic Center Jennings Av. Marin County Corona Road Corona

Cloverdale $0.00 $1.92 $2.20 $2.57 $2.70 $2.99 $3.14 $3.55 $3.61 $4.09 $4.32 $4.60 $4.74 $5.00

Healdsburg $1.92 $0.00 $1.28 $1.65 $1.79 $2.07 $2.22 $2.63 $2.69 $3.17 $3.40 $3.68 $3.82 $4.08

Windsor $2.20 $1.28 $0.00 $1.37 $1.51 $1.79 $1.94 $2.36 $2.41 $2.90 $3.12 $3.40 $3.54 $3.80

Santa Rosa - Jennings Av. $2.57 $1.65 $1.37 $0.00 $1.14 $1.42 $1.57 $1.98 $2.04 $2.53 $2.75 $3.03 $3.17 $3.43

Downtown Santa Rosa $2.70 $1.79 $1.51 $1.14 $0.00 $1.28 $1.43 $1.85 $1.90 $2.39 $2.62 $2.89 $3.04 $3.30

Rohnert Park $2.99 $2.07 $1.79 $1.42 $1.28 $0.00 $1.15 $1.56 $1.62 $2.11 $2.33 $2.61 $2.75 $3.01

Cotati $3.14 $2.22 $1.94 $1.57 $1.43 $1.15 $0.00 $1.41 $1.47 $1.96 $2.18 $2.46 $2.60 $2.86

Petaluma - Corona Road $3.55 $2.63 $2.36 $1.98 $1.85 $1.56 $1.41 $0.00 $1.06 $1.54 $1.77 $2.05 $2.19 $2.45

Downtown Petaluma $3.61 $2.69 $2.41 $2.04 $1.90 $1.62 $1.47 $1.06 $0.00 $1.49 $1.71 $1.99 $2.13 $2.39

N. Novato $4.09 $3.17 $2.90 $2.53 $2.39 $2.11 $1.96 $1.54 $1.49 $0.00 $1.23 $1.50 $1.65 $1.91

S. Novato $4.32 $3.40 $3.12 $2.75 $2.62 $2.33 $2.18 $1.77 $1.71 $1.23 $0.00 $1.28 $1.42 $1.68

Marin County Civic Center $4.60 $3.68 $3.40 $3.03 $2.89 $2.61 $2.46 $2.05 $1.99 $1.50 $1.28 $0.00 $1.14 $1.40

San Rafael $4.74 $3.82 $3.54 $3.17 $3.04 $2.75 $2.60 $2.19 $2.13 $1.65 $1.42 $1.14 $0.00 $1.26

Larkspur $5.00 $4.08 $3.80 $3.43 $3.30 $3.01 $2.86 $2.45 $2.39 $1.91 $1.68 $1.40 $1.26 $0.00

* In year 1990 US dollars based on distance in miles between stations

Sonoma-Marin Area Rail Transit C-1 Travel Demand Forecasting Report September 2005