Gateway Cities Transit Assessment Final Draft Date: February 28, 2014

Prepared for: Gateway Cities Council of Governments Los Angeles County Metropolitan Transportation Authority

Prepared by: 445 S. Figueroa Street, Suite 2700 Los Angeles, CA 90071

Table of Contents

Executive Summary ...... ES-1 2013 Existing Transit Service ...... ES-2 2035 No Build ...... ES-2 2035 Build ...... ES-3 Summary ...... ES-7

1.0 Purpose and Approach ...... 1-1 1.1 Approach ...... 1-2 1.2 Diversion Rate Assumptions ...... 1-4

2.0 Assessment Content ...... 2-1 2.1 Existing Services ...... 2-1 2.2 Planned Services ...... 2-5 2.3 The Transit Database ...... 2-9

3.0 Data Sources ...... 3-1

4.0 Database Summary ...... 4-1

5.0 Findings ...... 5-1 5.1 2013 Existing ...... 5-1 5.2 2035 No Build ...... 5-2 5.3 2035 Build...... 5-3 5.4 Summary of Analysis ...... 5-13

A. Personal Vehicle Trip Reduction ...... A-1

B. Diverted Personal Vehicle Trips Roadway Allocation ...... B-1

C. Intercity and Commuter Rail Travel Market Assumptions ...... C-1

List of Tables

Table ES.1 Year 2013 Average Weekday Ridership by Transit Mode ...... ES-2 Table ES.2 Summary of Planned Transit Service Improvements in Gateway Cities ...... ES-3 Table ES.3 2035 Build Daily Personal Vehicle Trip Reduction ...... ES-6 Table 1.1 Transit Trip Mode Diversion Assumptions ...... 1-5 Table 1.2 Commuter and Intercity Rail Trip Mode Diversion Assumptions ...... 1-6 Table 3.1 Prior Studies Used to Develop the Transit Assessment ...... 3-1 Table 3.2 Agencies Interviewed to Develop the Transit Assessment ...... 3-2 Table 3.3 Agencies that Did Not Respond to Request for Comment ...... 3-3 Table 4.1 Capacity, Ridership and Diversion from Other Modes, by Major Transit Project ...... 4-3 Table 5.1 Summary of Existing Transit Services in the Gateway Cities ...... 5-1 Table 5.2 Peak-Hour Capacity by Mode – Existing ...... 5-2 Table 5.3 Average Weekday Ridership by Mode – Existing ...... 5-2 Table 5.4 Summary of Planned Improvements to Transit Services in Gateway Cities ...... 5-3 Table 5.5 Forecasted Weekday Ridership Growth in the Gateway Cities ...... 5-4 Table 5.6 Peak-Hour Capacity Growth ...... 5-5 Table 5.7 Prior Mode for All New Average Weekday Ridership ...... 5-9 Table 5.8 2035 Weekday Personal Vehicle Trip Reduction ...... 5-9 Table 5.9 2035 Build Scenario Average Weekday Automobile Trips Removed by Roadway ...... 5-11 Table A.1 Daily Personal Vehicle Trips Reduced Due to Transit Services ...... A-1 Table B.1 2035 Build Daily Personal Vehicle Trips Reduced by Roadway ...... B-3 Table C.1 High-Speed Rail Travel Markets – Share of Total Trips ...... C-2

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List of Tables, continued

Table C.2 2035 Population Forecast – Los Angeles County Population ...... C-2 Table C.3 2035 Population Forecast – Gateway Cities Population ...... C-2 Table C.4 Intercity Markets Forecasted Total Trips and Diversion Assumptions ...... C-3 Table C.5 Intercity Markets Calculated Diverted Trips by Purpose and Mode ...... C-4 Table C.6 Intercity Markets Calculated Total Trips All Trip Purposes ...... C-5 Table C.7 Intercity Markets Calculated Average Diversion Rates ...... C-5 Table C.8 Final Rail Market Diversion Rates Used for Ridership Analysis ..... C-6

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List of Figures

Figure ES.1 2035 Build Major Transit Route Capacity Utilization ...... ES-4 Figure ES.2 Daily Personal Vehicle Trips Diverted by Major Roadway ...... ES-6 Figure 2.1 Existing Transit Services ...... 2-4 Figure 5.1 2035 Average Weekday Ridership by Transit Mode ...... 5-5 Figure 5.2 2035 Seated Peak-Hour Capacity by Mode ...... 5-6 Figure 5.3 2035 Build Major Transit Route Capacity Utilization ...... 5-7 Figure 5.4 2035 Build Total Weekday Personal Vehicle Trips Removed, by Major Roadway ...... 5-10

Executive Summary

The Gateway Cities Transit Assessment consists of an inventory of existing transit services and a sketch-level analysis of the potential effects of planned and proposed rapid transit projects considered in the Gateway Cities Strategic Transportation Plan, based on trends and industry factors. The assessment illustrates how existing, approved, planned, and proposed transit projects may affect transit ridership, personal vehicle travel, and other travel modes in the Gateway Cities. The analysis addresses local services, regional services such as Metrolink, and interregional services such as the Amtrak Pacific Surfliner and proposed statewide high-speed rail system. Current and historic data were collected from existing public documents, transit provider interviews, and our estimates using widely accepted transit factors. Upon completion of data collection, we estimated the effect of existing transit services on other travel modes, assembled future transit ridership forecasts, and analyzed the potential effect of future transit service levels on transportation performance. The future analysis considered two scenarios: 1. 2035 No Build. Continuation of 2013 transit service levels, but increased population and employment consistent with regional and statewide growth forecasts; and 2. 2035 Build. Planned and proposed speed and service level improvements for existing transit, new transit route and service offerings, and increased population and employment consistent with regional and statewide growth forecasts. The 2035 forecasts reflect application of multiple assumptions based on readily available data and trends. For example, transit ridership forecasts are based on a synthesis of prior statewide, regional, and corridor forecasts, and generalized ridership trends for cases where specific forecasts were not available. The results indicate a range of possible future transit system performance and multimodal effects. Sections 1.0 and 5.0 in the main report provide further information on analysis data, assumptions, and results. This technical memorandum is accompanied by a spreadsheet transit database containing detailed data collection and analysis results. A separate report, the Gateway Cities Maximum Transit Scenario Assessment, builds upon this analysis to estimate the additional impact of greatly enhancing regional bus services in the Gateway Cities. A third report, the Gateway Cities Park-and-Ride Assessment,

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discusses the potential effect of existing and planned park-and-ride facilities in the Gateway Cities subregion.

2013 EXISTING TRANSIT SERVICE Table ES.1 describes existing average weekday transit ridership by mode in the subregion. Existing transit services, including local bus, express bus, light rail, and heavy rail, provide about 318,790 trips each weekday. We estimate that existing transit services currently remove 125,880 personal vehicle trips1 from the Gateway Cities roadway system each weekday. This represents about 2.3 percent of the total average weekday personal vehicle trips in the Gateway Cities.

Table ES.1 Year 2013 Average Weekday Ridership by Transit Mode

Mode Average Weekday Ridership Commuter and Intercity Rail 7,660 Light Rail 102,800 Rapid and Express Buses 17,250 Local and Other Buses 191,080 Total 318,790

2035 NO BUILD If forecasted socioeconomic growth occurs between 2013 and 2035 but no additional transit improvements are made, average weekday transit ridership in the subregion is projected to increase by 34,150 (11 percent) to about 352,940. Of these total future trips, 342,280 are projected to board or alight in the subregion, and 10,670 are projected to pass through the subregion. By 2035, about 5.8 million personal vehicle trips are forecasted to take place within the Gateway Cities each weekday. This scenario diverts about 139,850 total daily personal vehicle trips from subregional roadways, or a 2.4-percent reduction in personal vehicle travel attributable to transit usage.

1 These 125,880 personal vehicle trips is less than total transit passenger trips because a “typical” personal vehicle carries 1.59 people, on average.

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2035 BUILD Several major rapid transit improvements to the Gateway Cities transit system have been proposed or planned by the year 2035 (see Table ES.2). Projects considered in the 2035 Build scenario include California High-Speed Rail Phase 1 Blended service, the Metro Gold Line extension, Eco Rapid Transit, and several bus rapid transit (BRT) projects. We also assumed conservative increases in local transit service levels where no other information was available. Project information was collected from a wide range of local and regional sources as shown in Table ES.2.

Table ES.2 Summary of Planned Rapid Transit Service Improvements in Gateway Cities

System Improvement High-Speed Rail (Phase 1 Blended) New interregional rail service between San Francisco/San Jose, Merced, and Los Angeles/Anaheim. Amtrak Pacific Surfliner Various operational improvements, service enhancement Metrolink Various operational improvements, service enhancement Metro Blue 16 percent service level increase Metro Green 16 percent service level increase Metro Gold Eastside extension (Washington Blvd alignment) Eco Rapid Transit New transit service from Los Angeles Union Station to Cerritos Huntington Park Downtown Shopper New trolley service on Pacific Boulevard linking Downtown with Shuttle Northwest area-specific plan Atlantic Boulevard Bus Rapid Transit New bus rapid transit (BRT) service along Atlantic Boulevard New express bus service from Santa Ana to California State OCTA Route 722a University Long Beach Six new BRT lines (Artesia, Del Amo, Willow, Lakewood, Long Beach Transit Bus Rapid Transita Norwalk, and 7th Street)

a Long Beach Transit BRT and OCTA Route 722 projects would influence regional transit in the 2035 Build scenario, but both were excluded from quantitative evaluation in this report due to limited available data..

Ridership Under year 2035 Build conditions, average weekday transit ridership is expected to increase by about 38,860 over 2035 No Build conditions, to 391,800 weekday trips. Of these, approximately 363,120 (93 percent) connect to locations in the Gateway Cities, while 28,670 (7 percent) are forecasted to pass through. A significant portion of those new trips are the result of travelers switching from conventional buses to new, more reliable transit modes. The 2035 Build scenario represents a 23-percent growth (73,010 trips) compared to existing conditions.

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Capacity and Utilization Together, planned and proposed transit improvements are expected to increase seated peak-hour transit capacity in the Gateway Cities by 42 percent, from 13,860 in 2013 to 19,740 in 2035 Build conditions. According to these forecasts, demand for new services exceeds peak-hour capacity on several lines in the 2035 Build scenario, most notably on the enhanced Metro Blue, Green and Gold Line light-rail services. Figure ES.1 illustrates the peak-period capacity utilization for major transit projects or project categories.

Figure ES.1 2035 Build Major Transit Route Capacity Utilization

Amtrak Pacific Surfliner

Metrolink Orange, 91, Riverside

HSR (Phase 1 Blended)

Eco Transit

Metro Blue Line

Metro Green Line

Metro Gold Line

Atlantic Boulevard Corridor

Metro Route 760

Other Express Routes

Metro Route 60

Montebello Bus Lines

Norwalk Transit

LADOT

Other Metro Local and Shuttle

Long Beach Transit

Small Transit Operators

0% 25% 50% 75% 100% 125% 150% 175%

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Source of New Transit Ridership Under 2035 Build conditions, new transit options attract riders from several prior modes of travel:  Other Transit. About 36,540 transit trips are projected to shift from local bus or other transit to more frequent or higher-speed transit options, such as light rail and express bus. Prior users of bus transit often comprise a large proportion of ridership on new light-rail or rapid bus transit systems. This explains why ridership on local and other buses declines under 2035 Build conditions.  Personal Vehicles. As a result of the new transit enhancements in the 2035 Build scenario, approximately 26,700 new daily transit riders are estimated to have previously made their trip in a personal vehicle such as a car or truck. Note that the actual number of vehicles removed from area roadways is significantly smaller since personal vehicles often carry more than one passenger. The impact of transit on the number of vehicles on area roadways is presented later in this section.  Air. The 2035 Build scenario assumes high-speed rail will be operational by 2035. High-speed rail is expected to attract 2,490 former airline passengers, in particular for the very long distance trips between southern and northern California.  Biking and Walking. Under 2035 Build conditions, about 5,950 new riders are projected to have previously walked or cycled from their origin to their destination. This figure does not take into account short-distance bike or walk trips used to access bus stops or transit stations, which would likely increase under 2035 Build conditions as a result of higher transit capacity and demand.  Induced Trips. The improvement of transit access can allow a small number of potential riders to take transit trips where they would otherwise have taken no trip at all. About 3,690 new trips are projected to be induced as a result of new transit opportunities under 2035 Build conditions.

Personal Vehicle Trip Reduction Under year 2035 Build conditions, transit services are projected to remove about 155,670 personal vehicle trips from subregion roadways. This figure represents a 24-percent increase compared to existing conditions and an 11-percent increase over 2035 No Build conditions. Table ES.3 shows the projected personal vehicle trip reduction under year 2035 No Build and Build conditions.

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Table ES.3 2035 Build Daily Personal Vehicle Trip Reduction

Mode No Build Build Change Commuter and Intercity Rail 6,160 13,470 7,310 Light Rail 44,170 52,300 8,130 Rapid and Express Buses 7,410 7,790 380 Local and Other Buses 82,100 82,100 Total 139,840 155,660 15,820

Travel demand modeling suggests there will be approximately 5.8 million daily vehicle trips in the Gateway Cities by 2035. The 2035 Build scenario’s complete set of transit options accounts for a 2.7-percent reduction in personal vehicle travel in the Gateway Cities, of which the proposed new transit services account for about 0.3 percent. Figure ES.2 illustrates the forecasted reduction in daily personal vehicle trips by major roadway in the Gateway Cities.

Figure ES.2 Daily Personal Vehicle Trips Diverted by Major Roadway

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SUMMARY This analysis is intended to provide a forecast of the potential ridership and multimodal impacts of planned and proposed rapid and express transit investments in the Gateway Cities. The study concludes the following:  Rapid transit enhancements produce ridership gains. Expanding and enhancing rapid and express transit opportunities in the Gateway Cities would have a significant, positive effect on ridership, particularly on new light-rail transit systems.  Transit ridership growth is not forecasted to keep pace with aggressive capacity expansion. The slate of transit enhancements in the Build scenario contribute to a 42-percent increase in peak-hour seated transit capacity within the Gateway Cities compared to existing conditions. This produces a 23- percent increase in ridership, about 11 percent of which can be described by socioeconomic growth alone.  Prior bus users constitute over one-half of new rapid transit ridership. New light rail and BRT services offer more reliable, direct access for current bus users, which can lure away many would-be bus passengers. As passengers shift from bus to these new types of transit, only modest gains in ridership on local buses result, despite significant capacity improvements. This analysis assumed regionwide increases in bus service levels, but transit providers may want to consider targeting potential bus service enhancements to avoid inefficient overlap between such services. Transit providers may also look for cost-effective ways to distinguish the unique role of local bus service by improving speed and frequency of the routes as well as customer service and technology improvements.  Less than one-half of new ridership results in reductions in light vehicle travel. Only about 38 percent of new transit trips were previously taken by personal vehicle, compared to 52 percent who switched from buses, and 8 percent who were former pedestrians and bicyclists. About 5 percent are new travelers entirely.  Planned rapid transit improvements have greatest effect on I-5 vehicle travel. Of the 15,820 weekday vehicle trips removed from area roadways as a result of new transit improvements, 10,600 are removed from I-5 (67 percent of total change), due largely to high-speed rail, Eco Rapid Transit, and Amtrak Pacific Surfliner corridor improvements.  Several rapid transit lines face capacity issues. As a result of forecasted new demand for transit, several transit lines may be over capacity by 2035, in particular Metro light-rail systems in the Gateway Cities.  Reduced personal vehicle trips due to rapid transit usage constitute a very small share of overall regional vehicle travel. While expanding transit options is expected to reduce personal vehicle travel in the Gateway Cities,

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the reduction attributable to expanded transit services amounts to less than one-half percent of total forecasted vehicle travel in the subregion in 2035.  Local bus improvements are not addressed, and no data was available for some proposed improvements. Local transit providers have noted that the improvements proposed in this report pertain specifically to rapid and express transit options, whereas local bus service constitutes a sizeable majority of ridership in the subregion today. Furthermore, several proposed improvements submitted by agencies (e.g. Long Beach Transit BRT projects and OCTA Route 722) did not yet have data necessary for inclusion in the quantitative assessment, and are therefore omitted from results presented here. A separate report, the Gateway Cities Maximum Transit Assessment, explores the potential effects of significantly increasing local bus service in addition to rapid and express transit improvements.  Sketch-level, regional analysis. This analysis presents a best estimate of future conditions based on readily available data, trends, and planning factors. It is therefore limited in scope and analytical precision. For instance, this study assumes consistent socioeconomic growth based on prior trends, and that passengers respond similarly to capacity changes on each local bus line. Actual passenger behavior will differ from service to service, depending on many specific factors not considered in this analysis. Therefore, this analysis is intended to provide only a general overview of regional trends rather than actionable data on any one transit line. Future analysis conducted as part of the Gateway Cities Strategic Transportation Plan will utilize a new multiresolution model to forecast more complex forecasts of transit impacts and the interaction between travel modes. Those more rigorous forecasts may differ significantly from the forecasts presented here, which are based solely on preexisting data and trends. Future land use planning and unforeseeable socioeconomic trends could impact actual travel behavior significantly as well. Coordination of transportation planning with these other important factors should always be considered.

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1.0 Purpose and Approach

The purposes of the transit assessment are as follows:  Develop a comprehensive inventory of existing transit services in the Gateway Cities subregion, as well as proposed and planned rapid and express transit projects and improvements; and  Understand how existing, planned, and proposed transit services affect other modes, in particular, personal vehicle travel. Transit service in the subregion is provided by a number of operators, including Amtrak, Metrolink, the Los Angeles County Metropolitan Transportation Authority (Metro), Long Beach Transit, and a number of small operators. These agencies provide commuter and intercity passenger rail, light rail, and rapid and express bus service, as well as local bus service. The assessment provides the following information for existing transit services, which also includes the year 2035 No Build scenario:  Running time within the subregion (peak and off-peak);  Headway (peak and off-peak);  Peak-hour seated capacity;  Average weekday ridership in subregion, including: – Boardings and/or alightings in the subregion, and – Passengers passing through the subregion.  Peak-hour ridership within the subregion; and  Peak-hour seated capacity utilization. In addition to the above, the following information is provided for planned and proposed transit projects and improvements:  Project cost;  Change in running time within the subregion (peak and off-peak);  Change in headway (peak and off-peak);  Change in peak-hour seated capacity;

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 Change in average weekday ridership in the subregion, including: – Boardings and/or alightings in the subregion, and – Passengers passing through the subregion.  Change in peak-hour ridership in the subregion;  Reduction in personal vehicle trips;  Trips diverted from nonmotorized (walk or bike) travel; and  Trips diverted from other transit.

1.1 APPROACH Transit condition data for the subregion were developed using a three-step approach, as follows: 1. Gather information from existing documents and data sources; 2. Interview staff at Metro and other transit agencies; and 3. Estimate remaining information, as needed, using widely accepted factors. All data sources and agency respondents are listed in Section 3.0. Wherever possible, we used information from existing documents, data sources and staff interviews.2 In cases where we were unable to obtain route-specific data, we used the following methods and assumptions:  Running time under future No Build conditions. Assumed to be the same as under existing conditions.  Peak-hour capacity. Calculated by combining information on peak-hour service frequency, capacity per vehicle, and vehicles per train (for rail).  Peak-hour seated capacity. Calculated by combining information on peak- hour service frequency, seated capacity per vehicle, and vehicles per train (for rail). When necessary, we assumed 38 seats per standard 40-foot bus.  Gateway Cities Weekday ridership. Equal to subregion area trips plus pass- through trips (see Section 2.0 for definition of these terms).  Peak-hour trips. Apply a typical industry factor to weekday ridership. We used 18 percent for commuter rail and 10 percent for other transit.

2 We used ridership forecasts and diversion rates from different modes found in previous studies of major transit projects. As shown in Section 3.0, studies included statewide and regional plans, environmental assessments, and strategic plans.

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 Gateway Cities Ridership under future No Build conditions. Apply a 10- percent growth rate to ridership under existing conditions where no ridership forecasts were available.  Gateway Cities Ridership under future Build conditions. Where no other studies and forecasts were available, we applied an industry typical ridership elasticity to service improvements implemented under Build conditions. For example, we assumed a 16-percent increase in service results in a 4.5-percent increase in ridership. We also assumed a 30-percent decrease in travel time results in an 18-percent increase in ridership.  Annual ridership. Apply a typical industry factor to weekday ridership. We used 300.  Monthly ridership. Annual ridership divided by 12.  Weekly ridership. Annual ridership divided by 52.  Maximum peak-hour load.3 Apply a typical industry factor to ridership. We assumed a factor of 1.8 percent.4  Peak-hour capacity utilization. Equal to the maximum peak-hour load divided by peak-hour capacity.  Peak-hour seated capacity utilization. Equal to the maximum peak-hour load divided by peak-hour seated capacity.  Personal vehicle trip reductions for Build conditions. Apply a typical industry factor to the increase between future Build and No Build ridership. We assumed a factor of 24 percent.5 For more information see Section 1.2.  Trips diverted from other transit for Build conditions. Apply a typical industry factor to the difference between future Build and No Build ridership. We assumed a factor of 62 percent.4 For more information, see Section 1.2.  Automobile trip reductions for existing conditions and future No Build conditions. Apply a typical industry factor to ridership. The diversion from

3 Load should not be confused with ridership. Ridership equals the total number of on- boardings during any period of time (e.g., hour, day, week). Load equals the total numbers of passengers on board in a snapshot moment (on-boardings minus off- boardings through that moment). A higher factor would be used if calculating maximum peak-hour ridership. 4 An 18-percent figure was used for Metrolink routes (Orange, 91, Riverside) because most service on these routes occurs during peak periods only. 5 For commuter and intercity rail, we used route-specific diversion rates from existing intercity rail, commuter rail, and light-rail transit project forecasts and studies.

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personal vehicle under the existing and No Build scenarios would be higher than for the Build scenario because other transit service would not be available. We assumed a factor of 62.5 percent. For more information, see Section 1.2.

Note on Commuter and Intercity Rail Intercity and commuter rail trips connecting to or traveling through the Gateway Cities required specialized assumptions to account for trip distances and destinations. For example, Amtrak Pacific Surfliner connects destinations between San Luis Obispo and San Diego, so only a portion of the total route trips pass through the Gateway Cities. To account for this, we factored commuter and intercity rail trips using multiple data sources. For more information on factoring commuter and intercity rail trips to reflect the effects on the Gateway Cities, please see Appendix C.

1.2 DIVERSION RATE ASSUMPTIONS When new transit systems are introduced, new transit trips come from a variety of prior transportation modes, including those who previously traveled by personal vehicle; by other transit modes (e.g., those who previously traveled by bus, but now have access to more reliable transit); and by walking or bicycling. In addition, new transit services may induce a small proportion of new trips. We refer to this collective phenomenon as “diversion” from other modes. This section explains the assumptions used to estimate modal diversion in this report. Note that these rates represent broad assumptions based on readily available data and widely used planning factors. More thorough analysis using travel demand and mesoscopic modeling will likely produce differing results.

General Diversion Rate Assumptions We developed default diversion rates based on methods used in prior studies for cases where route specific data were not available.6 For Existing or No Build conditions, no diversion is possible from other transit. We allocated transit diversion from the Build scenario to the other modes to account for the change.

6 Diversion rates represent a summary of rates from the following sources: 1) Evans, Jay et al., 2004, Transit Cooperative Research Program Report 95 – Chapter 9, Transit Cooperative Research Board; 2) Tann, Helen, 2006, The San Pablo Rapid – BRT Project Evaluation, Federal Transit Administration (FTA); 3) Alameda-Contra Costa Transit District, 2012, AC Transit East Bay Bus Rapid Transit Project Final Environmental Impact Statement (EIS)/Environmental Impact Report (EIR); and 4) Iteris, Inc., 2013, technical support materials for I-605 Congestion Hot Spots for Gateway Cities Transportation Strategic Plan.

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To calculate weekday personal vehicle trip reductions on subregion roadways, we first calculated the number of travelers who chose transit rather than using a personal vehicle. Each such traveler is known as an “automobile person-trip”, which refers to a trip made by an individual in a personal vehicle. This trip could be made as either the vehicle driver or a passenger. To calculate the personal vehicle trip reduction, we divided the number of personal vehicle person-trips by an average vehicle occupancy rate of 1.59, which is based on the U.S. Department of Energy’s 2009 estimate.7 Table 1.1 illustrates the default diversion rates by mode.

Table 1.1 Transit Trip Mode Diversion Assumptions

Transit Scenario/Conditions Auto Other Transit Walk or Bike Induced Build (new service) 24% 62% 9.5% 4.5% Existing or No Build 62.5% 0% 25% 12.5%

Sources: Evans, Jay et al. (2004); Tann, Helen (2006), AC Transit (2012); and Iteris, Inc. (2013).

Commuter and Intercity Rail Diversion Rate Assumptions While these diversion rates are reasonable for typical light-rail or other trip modes, longer-distance trips require a separate set of assumptions. For example, because intercity passenger rail trips are much longer in length, we would not expect many travelers to make these trips by walking or bicycling today. Furthermore, prior analysis by the California High-Speed Rail Authority has provided detailed high-speed rail (HSR) diversion rates by market pairs, reflecting the wide differences in diversion rates associated with travel distance and destination. Table 1.2 illustrates the route-specific diversion rates for HSR, Amtrak Pacific Surfliner, Metrolink, and some intraregional express routes where additional market and mode diversion data were available from previous studies. For detailed information on commuter and intercity rail trip mode diversion assumptions, please see Appendix C.

7 U.S. Department of Energy: http://www1.eere.energy.gov/vehiclesandfuels/ facts/2010_fotw613.html, accessed July 2013.

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Table 1.2 Commuter and Intercity Rail Trip Mode Diversion Assumptions

Personal Other Transit, Transit Type Vehicle Walk/Bike Air Induced High-Speed Rail San Francisco (SF) to LA 55% 0% 42% 4% San Joaquin Valley to LA 93% 0% 5% 2% LA to San Diego 98% 0% 0% 2% SF/Sacramento to San Diego 38% 0% 61% 0% Within LA Basin (Metrolink) 90% 0% 0% 10%

Source: 2012 California HSR Revised Business Plan, Ridership and Revenue Forecasting Technical Appendix, modeling assumptions for Phase 1 Blended (model run 12-043d).

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2.0 Assessment Content

This section describes the content of the existing and proposed services evaluated in the transit assessment database, and includes instructions for navigating and using the database.

2.1 EXISTING SERVICES The database includes information for the following existing transit services:  Commuter and Intercity Rail: – Amtrak Pacific Surfliner; – Metrolink Orange Line; – Metrolink 91 Line; and – Metrolink Riverside Line;  Light Rail: – Metro Blue Line; – Metro Green Line;  Rapid and Express Buses: – Metro Rapid Bus Route 760; – Metro Rapid Bus Route 762; and, – Metro Other Rapid or Express Bus Routes;  Local and Other Buses: – Metro Local Route 60; – Metro Local Route 108; – Metro Local Route 110; – Metro Local Route 115; – Metro Local Route 251; – Metro Local Route 260; – Metro Other Local or Shuttle Routes; – Long Beach Transit Route 1 – Easy Ave;

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– Long Beach Transit Route 21 – Cherry; – Long Beach Transit Route 22 – Cherry Ave/Downey Ave; – Long Beach Transit Route 37 – Pine Ave/Downtown Long Beach/Queen Mary; – Long Beach Transit Route 45 – Anaheim St to Santa Fe; – Long Beach Transit Route 46 – Anaheim St to downtown; – Long Beach Transit Route 51 – Long Beach Blvd to Artesia Station; – Long Beach Transit Route 61 – Atlantic Ave to Artesia Station; – Long Beach Transit Route 71 – Orange Ave; – Long Beach Transit Route 72 – Orange Ave; – Long Beach Transit Route 81 – 10th St to CSULB; – Long Beach Transit Route 91 – 7th St/Bellflower Blvd; – Long Beach Transit Route 92 – 7th St/Woodruff Ave; – Long Beach Transit Route 93 – 7th St/Clark Ave; – Long Beach Transit Route 94 – 7th St to Los Altos Only; – Long Beach Transit Route 96 – Zap – 7th St; – Long Beach Transit Route 101 – Carson St/Centralia; – Long Beach Transit Route 102 – Willow/Spring; – Long Beach Transit Route 103 – Carson St to Lakewood Mall; – Long Beach Transit Route 104 – Willow/Spring; – Long Beach Transit Route 111 – Broadway/Lakewood Blvd; – Long Beach Transit Route 112 – Broadway/Clark Ave; – Long Beach Transit Route 121 – Ocean/Belmont Shore/CSULB/PCH at Ximeno; – Long Beach Transit Route 131 – Redondo Ave to Alamitos Bay Landing; – Long Beach Transit Route 151 – 4th St; – Long Beach Transit Route 171 – PCH to Market Place; – Long Beach Transit Route 172 – PCH/Palo Verde; – Long Beach Transit Route 173 – PCH/Studebaker; – Long Beach Transit Route 174 – PCH/Ximeno Ave Only; – Long Beach Transit Route 176 – ZAP – PCH; – Long Beach Transit Route 181 – Magnolia Ave;

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– Long Beach Transit Route 182 – Pacific; – Long Beach Transit Route 191 – Santa Fe/Del Amo Blvd; – Long Beach Transit Route 192 – Santa Fe/South St; – Bell Gardens Transit; – Bellflower Bus; – Cerritos on Wheels; – City of South Gate; – Commerce Municipal Bus Lines; – Compton Renaissance Transit System; – Cudahy Area Rapid Transit; – DowneyLink; – El Sol Shuttle (Los Angeles County Department of Public Works); – Huntington Park Local Transit Bus; – Los Angeles Department of Transportation (Commuter Express; Community Connection, DASH Southeast Route); – Lynwood Breeze; – Montebello Bus Lines; – Norwalk Transit; – Orange County Transportation Authority; – Paramount Easy Rider; – Sunshine Shuttle (Los Angeles County Department of Public Works); and – Willowbrook Shuttle. See Figure 2.1 for a map of these existing transit services.

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Figure 2.1 Existing Transit Services

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2.2 PLANNED SERVICES The database includes information for the following planned improvements to transit service in the Gateway Cities subregion:  California High-Speed Rail Phase 1 Blended Service;  LOSSAN corridor track improvements and Amtrak Pacific Surfliner service expansion;  Metrolink Orange County Line operational improvements and service enhancement;  Metrolink 91 Line operational improvements and service enhancement;  Metrolink Riverside Line operational improvements and service enhancement;  Metro Blue Line 16 percent increase in service;  Metro Green Line 16 percent increase in service;  Metro Gold Line Eastside extension;  Metro Gold Line Eastern extension to Orange;  Eco Rapid Transit8;  Huntington Park Downtown Shopper Shuttle;  Orange County Transportation Authority Route 722;  Atlantic Blvd BRT;  Long Beach BRT – Artesia Line;  Long Beach BRT – Del Amo Line;  Long Beach BRT – Willow Line;  Long Beach BRT – Lakewood Line;  Long Beach BRT – Norwalk Line; and  Long Beach BRT – 7th St Line. Figure 2.2 illustrates the location of new planned commuter, intercity light rail, and BRT routes. Figure 2.3 illustrates the combined existing and new transit services.

8 Also referred to as Orangeline Development Authority (OLDA) or Pacific-Electric Right-of-Way West Santa Ana Branch project.

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Figure 2.2 2035 Build Scenario New Transit Services

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Figure 2.3 Future Transit Services (Combined Existing and New)

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Notes on Planned Improvements

Commuter and Intercity Rail The California High-Speed Rail Authority is building an HSR system running from San Francisco to Los Angeles/Anaheim via the Central Valley, and later to Sacramento and San Diego. The California High-Speed Rail Program Revised 2012 Business Plan (2012 Business Plan) provides an implementation strategy of early investments in intercity, regional, and commuter rail systems and phased HSR system delivery (Phase 1 Blended scenario). The blended approach, which integrates HSR service with existing systems allowing for coordinated scheduling, ticketing, and transfers, is a key element to HSR implementation. Our synthesis of ridership forecasts follows the California State Rail Plan methodology, in which HSR trips that connect to Metrolink, Pacific Surfliner, and other transit routes are accounted for only as HSR ridership, not ridership on the other services. Similarly, Amtrak Pacific Surfliner trips that connect to Metrolink or other subregional transit routes are accounted for only as Amtrak Pacific Surfliner ridership. Similar methods are followed for Metrolink trips that connect to subregional transit routes. The 2012 California State Rail Plan and the 2012 Business Plan do not show HSR stations within the subregion for the Phase 1 Blended scenario; therefore, we forecast only HSR trips passing through the subregion.

Metro Gold Line Extension The Metro Gold Line Eastside extension is considering two possible alternatives: to Whittier along Washington Blvd, or to South El Monte along SR 60. This analysis assumed the Washington Blvd alignment, as only one of these two alternatives will be implemented.9 The Gold Line eastern extension to Orange County is a possible further extension of the Gold Line, which would be implemented after completion of the Eastside extension.

Eco Rapid Transit The alternatives analysis for Eco Rapid Transit includes several alternatives, from systemwide local transit improvements, to a light-maglev system. We averaged the results for the three light-rail alternatives to use as inputs for this transit assessment. The inputs included 2035 average daily ridership to/from and through the subregion, diversion rates for personal vehicle and transit trips, and descriptive data such as running time, frequency, and capacity.

9 Los Angeles County Metropolitan Transportation Authority, Eastside Transit Corridor Phase 2 Alternatives Analysis Report, pages 3-6.

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Atlantic BRT The Atlantic Boulevard high-capacity transit alternatives have included light-rail and BRT. We assumed BRT transit service (capacity, speed, etc.) for this analysis. We also assumed that the Atlantic BRT would replace existing Metro Bus Routes 260 and 762; therefore, these routes have no ridership forecasts for the 2035 Build scenario.

Long Beach BRT Six Long Beach BRT routes have been proposed. While listed here and illustrated in the maps, insufficient data existed at the time of publication to include these routes in quantitative analysis.

2.3 THE TRANSIT DATABASE A spreadsheet-based database of all existing and proposed transit services and projects was developed to supplement this report. The database provides the following information for each service:  Overview;  Description of Existing Service;  Description of Planned/Proposed Changes;  Existing Service; and  Proposed Service and Utilization Levels.

Overview The Overview section contains the following data fields for each service or planned improvement:  System,  Improvement Type,  Location, and  Name.

Description of Existing Service The Description of existing service section contains the following data fields for each existing transit service:  Existing Owner/Operator;  Scale. Whether the service is regional, subregional, or local; and  Description – Existing Service. A description of the existing service.

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Description of Planned/Proposed Changes The Description of planned/proposed changes section contains the following data fields for each planned improvement:  Description – Planned/Proposed. Description of the planned improvement;  From, To. Endpoints of the planned improvement;  Jurisdictions or Lead Agency;  Project Completion Date;  Project Cost; and  OM Cost – Annual. Projected annual operating and maintenance costs.

Existing Service The existing service section contains the following data fields for each existing transit service:  Peak running time in GCCOG. End-to-end time within the Gateway Cities for the transit service during peak periods under existing conditions;  Off-peak running time in GCCOG. End-to-end time within the subregion for the transit service during off-peak periods under existing conditions;  Headway (peak);  Headway (off-peak);  Peak-hour capacity – one direction. The capacity of transit vehicles on the transit service in one direction during the peak hour under existing conditions;  Peak-hour seated capacity – one direction. The seated capacity of transit vehicles on the transit service in one direction during the peak hour under existing conditions;  Weekday trips in GCCOG. Number of transit trips using the transit service in the subregion under existing conditions;  Weekday trips to/from GCCOG. Number of transit trips boarding and/or alighting in the subregion under existing conditions;  Weekday trips through GCCOG. Number of transit trips using the transit service in the subregion under existing conditions, but not boarding or alighting in the subregion;  Peak-period trips to/from GCCOG. Number of transit trips using the transit service in the subregion in the peak hour under existing conditions; and

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 Peak-period trips through GCCOG. Number of transit trips using the transit service in the subregion in the peak hour under existing conditions, but not boarding or alighting in the subregion.

Planned/Proposed Service and Utilization Levels This section contains the following data fields for each planned or proposed transit change:  Running time in GCCOG (peak). End-to-end time in the subregion for the transit service during peak periods under future Build conditions;  Running time (off-peak). End-to-end time in the subregion for the transit service during off-peak periods under future Build conditions;  Headway (peak);  Headway (off-peak);  Peak-hour capacity – one direction. The capacity of transit vehicles on the transit service in one direction during the peak hour under future Build conditions;  Peak-hour seated capacity – one direction. The seated capacity of transit vehicles on the transit service in one direction during the peak hour under future Build conditions;  Monthly ridership in GCCOG – 2035 Build. Number of transit trips using the transit service in the subregion under future Build conditions per month;  Weekly ridership in GCCOG – 2035 Build. Number of transit trips using the transit service in the subregion under future Build conditions per week;  Total Route Weekday Ridership – 2035 No Build. Average weekday ridership for the entire route (end-to-end) under future No Build conditions;  Total Route Weekday Ridership – 2035 Build. Average weekday ridership for the entire route (end-to-end) under future Build conditions;  Weekday trips in GCCOG – 2035 No Build. Number of transit trips using the transit service in the subregion under future No Build conditions;  Weekday trips in GCCOG – 2035 Build. Number of transit trips boarding or alighting (to/from), plus the number of transit trips traveling though the subregion using the transit service under future Build conditions;  Weekday trips to/from GCCOG – 2035 No Build. Number of transit trips boarding or alighting (to/from), plus the number of transit trips traveling though the subregion using the transit service under future No Build conditions;  Weekday trips to/from GCCOG – 2035 Build. Number of transit trips boarding or alighting in the subregion under future Build conditions;

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 Weekday Trips through GCCOG – 2035 No Build. Number of transit trips using the transit service in the subregion under future No Build conditions, but not boarding or alighting in the subregion;  Weekday Trips through GCCOG – 2035 Build. Number of transit trips using the transit service in the subregion under future Build conditions, but not boarding or alighting in the subregion;  Diverted weekday automobile person-trips to/from GCCOG. Number of personal vehicle person-trips removed by the increase in transit trips boarding or alighting in the Gateway Cities, under Build conditions;  Diverted weekday automobile person-trips through GCCOG. Number of automobile person-trips removed by the increase in transit trips passing through the Gateway Cities, under Build conditions;  Diverted weekday automobile person-trips in GCCOG. Total automobile person-trips removed by the increase in weekday transit ridership, including the change in both to/from and pass-through trips;  Weekday other transit trips to/from GCCOG diverted. Number of trips diverted from other transit by the increase in Gateway Cities area transit trips;  Weekday other transit trips through GCCOG diverted. Number of trips diverted from other transit by the increase in pass through transit trips;  Weekday other transit trips in GCCOG diverted. Total number of trips diverted from other transit by the increase in weekday transit ridership, including both to/from and pass-through trips;  Weekday walk/bike trips in GCCOG diverted. Number of trips diverted from nonmotorized (walk or bike) modes by the increase in total transit trips;  Weekday induced trips in GCCOG. Total number of trips that would have otherwise not occurred had the improved transit service not been available;  Peak-period trips in GCCOG – 2035 Build. Number of transit trips using the transit service in the subregion in the peak hour under future Build conditions;  Peak-period capacity utilization in GCCOG. Percent of transit vehicle capacity utilized during the peak hour under future Build conditions; and  Peak-period seated capacity utilization in GCCOG. Percent of transit vehicle seated capacity utilized during the peak hour under future Build conditions.

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3.0 Data Sources

Table 3.1 lists documents referenced in development of the transit assessment. Table 3.2 lists the agencies interviewed to develop information for the transit assessment. Table 3.3 lists those agencies that were contacted, but did not respond.

Table 3.1 Prior Studies Used to Develop the Transit Assessment

I-710 Major Corridor Study I-710 EIR/EIS (Various Studies):  2008 SCAG RTP Traffic Model  Railroad Goods Movement Study  Alternative Goods Movement Technology Study  Multimodal Review  I-710 Geometric Studies at the SR 91 Freeway I-605/SR 91/I- 405 Hot Spots Feasibility Study  Gateway Cities Strategic Transportation Plan – Phase I (prepared by Infraconsult, 2012)  SR 91/I-605/I-405 Project– Final Multimodal Analysis Report  Freeway Congestion Analysis Report  Arterial Intersection Congestion Analysis Report  Feasibility Report I-5 EIR/EIS (SR 91 to I-605) – Carminita Road, Alondra Boulevard, Imperial Highway, Rosecrans Avenue, Valley View Avenue, and Florence Avenue I-5 EIR/EIS (I-605 to I-710) Metro Eastside Transit Corridor Phase 2 SR 60 Carpool Addition Comprehensive Regional Goods Movement Plan and Implementation Strategy Orange and Los Angeles Intercounty Transportation Study Orange Line Development Authority (OLDA) Studies ITS Integration Plan for Goods Movement

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Table 3.1 Prior Studies Used to Develop the Transit Assessment (continued)

SR 91 Lane Additions in Orange County (OCTA) SR 91 Toll Lane Potential (OCTA) I-605/I-405/SR 22 Carpool Lane Connector Ramps (OCTA) Route 722 Summary Page (OCTA) Tierra Luna EIR Air Quality Plans  I-710 EIR/EIS AQ/HRA  GCCOG AQAP SCAG 2008-2035 Regional Transportation Plan (RTP) SCAG 2012-2035 Regional Transportation Plan (RTP) SCAG 2013 Federal Transportation Improvement Program (FTIP) 2012 California State Rail Plan 2012 California High-Speed Rail Revised Business Plan 2012 LOSSAN Strategic Implementation Plan

Table 3.2 Agencies Interviewed to Develop the Transit Assessment

Bell Gardens Transit Bellflower Bus City of Cerritos – Cerritos on Wheels10 Compton Renaissance Transit System Cudahy Area Rapid Transit East Los Angeles Shuttle Long Beach Transit Los Angeles County Metropolitan Transportation Authority (Metro) Paramount Easy Rider Sunshine Shuttle

10 The City of Cerritos provided information on Cerritos on Wheels ridership and service for the bidirectional loop they operate. Due to the relatively low ridership and limited service area, the quantitative data was not included in the database. The route was considered in overall analysis of transit needs in Gateway Cities.

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Table 3.3 Agencies that Did Not Respond to Request for Comment

City of Bell Huntington Park Local Transit Bus Lynwood Breeze

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4.0 Database Summary

The full transit database is contained in a separate Microsoft Excel document. A summary of the information in the database is provided in Table 4.1. This table summarizes peak-hour seated transit capacity, average weekday ridership, and the estimated sources of new transit trips under the 2035 Build scenario. This table presents major transit routes based on annual ridership estimates collected for this study, as these routes illustrate significant transit services for Gateway Cities. For definitions of the summary table fields, see Section 2.0. For further detail on diversion to transit from other modes, see Section 5.0 and Appendices A and B.

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Table 4.1 Capacity, Ridership and Diversion from Other Modes, by Major Transit Project

Peak-Hour Seated Capacity Average Weekday Ridership in the Gateway Citiesa Source of New Transit Ridership in 2035 Build (compared to 2035 No Build) 2035 Peak 2035 Change Existing 2035 No Build 2035 Build Auto Air Other Transit Walk Bike Induced Trips Project c Existing 2035 Build Utilization (Build – NB) Commuter and Intercity Rail Amtrak Pacific Surfliner 430 650 46% 3,040 4,380 5,390 1,010 960 50 Metrolink Orange, 91, Riverside 2,900 3,100 88% 4,620 6,350 11,010 4,660 4,190 470 High-Speed Rail (Phase 1 Blended) 650 88% 9,410 9,410 6,540 2,490 360 Subtotal 3,330 4,400 74% 7,660 10,730 25,810 15,080 11,690 2,490 880 Light Rail Eco Rapid Transit 2,740 56% 28,330 28,330 6,800 17,560 2,690 1,270 Metro Blue 1,970 2,280 140% 76,050 83,650 87,420 3,760 900 2,330 360 170 Metro Green 1,050 1,220 156% 26,750 29,420 30,750 1,320 320 820 130 60 Metro Gold 1,820 135% 20,800 20,800 4,990 12,900 1,980 940 Subtotal 3,020 8,060 128% 102,800 113,070 167,300 54,210 13,010 33,610 5,160 2,440 Rapid and Express Buses Atlantic Boulevard BRT 230 118% 8,310 8,310 2,000 5,150 790 370 Metro Route 760 230 230 118% 5,120 5,630 5,630 Metro Route 762 80 0% 2,020 2,220 -2,220 -2,220 All Other Metro and Express Routes 460 460 90% 10,110 11,120 11,120 Subtotal 770 920 99% 17,250 18,970 25,060 6,090 2,000 2,930 790 370 Local and Other Buses Metro Route 60 230 230 118% 10,260 11,280 9,540 -1,740 Montebello Bus Lines 760 760 114% 16,640 18,300 15,470 -2,830 Norwalk Transit 380 380 44% 8,500 9,350 7,910 -1,440 LADOT DASH 180 180 118% 7,080 7,790 6,590 -1,200 All Other Metro Local and Shuttle 1,070 1,070 103% 46,550 51,200 39,210 -11,990 Long Beach Transit 3,030 3,030 188% 91,050 100,150 84,680 -15,470 All Other Small Operators 1,090 680 94% 11,000 12,100 10,230 -1,870 Subtotal 6,740 6,330 87% 191,080 210,170 173,630 -36,540 Total 13,860 19,710 318,790 352,940 391,800 38,840 26,700 2,490 36,540 5,950 3,690 a Average weekday; includes pass-through trips. b Net of ridership diverted from other transit. c Table specifies major transit services based on ridership estimates. Services not displayed are included in categories labeled as “other”.

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5.0 Findings

This section presents the findings of the transit assessment analysis. For details on analysis data and underlying assumptions, see Section 1.0.

5.1 2013 EXISTING Table 5.1 summarizes existing services by mode in the Gateway Cities subregion.

Table 5.1 Summary of Existing Transit Services in the Gateway Cities

Commuter & Intercity Rapid and Express Rail Light Rail Buses Local and Other Buses  Amtrak Pacific Surfliner  Metro Blue  Metro Route 760  Metro Route 60  Metrolink Orange  Metro Green  Metro Route 762  Montebello Bus Lines  Metrolink 91  Other Metro Rapid and  Norwalk Transit  Metrolink Riverside Express Routes  LADOT DASH  Other Metro Local and Shuttle Routes  Long Beach Transit  Other Small Operators

Table 5.2 presents total existing peak-hour seated transit capacity by mode. In the peak hour, transit services provide a total seated capacity of about 13,860 in one direction. The largest share of seated capacity is provided by local and other buses (49 percent), followed by commuter and intercity rail (24 percent), light rail (22 percent), and rapid and express buses (5 percent). Small bus operators are those that provide less capacity than larger operators such as Metro and Long Beach Transit. The largest small operator is Montebello Bus Lines, which provides 764 seats of one-directional capacity during the peak hour. Existing capacity issues reported by owners and operators include:  El Sol Shuttle is experiencing capacity issues on their Union Pacific/Salazar Park and City Terrace/East Los Angeles College routes.

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 Cudahy Area Rapid Transit is experiencing capacity issues at the senior center (Clara Park). Also, narrow streets and shared stops with existing Metro stops are hampering bus travel speed and reliability.  City of South Gate reports that their buses are almost always full. Narrow streets and difficulty locating bus stops are hampering bus travel speed and reliability.

Table 5.2 Peak-Hour Capacity by Mode – Existing

Mode Total Capacity Commuter and Intercity Rail 3,330 Light Rail 3,010 Rapid and Express Buses 760 Local and Other Buses 6,740 Total 13,840

Table 5.3 indicates average weekday ridership by mode under existing conditions. Today, transit serves an estimated 318,790 riders in the Gateway Cities each weekday, of which an estimated 311,000 board or alight in the subregion, and 7,770 pass through. The largest share of estimated ridership takes place on local and other buses (60 percent), followed by light rail (32 percent), rapid and express buses (5.5 percent), and commuter and intercity rail (2.5 percent).

Table 5.3 Average Weekday Ridership by Mode – Existing

Mode Average Weekday Ridership Commuter and Intercity Rail 7,660 Light Rail 102,800 Rapid and Express Buses 17,250 Local and Other Buses 191,080 Total 318,790

These existing transit services remove an estimated 125,880 personal vehicle trips from area roadways each weekday. This represents about 2.3 percent of total estimated weekday vehicle trips in the Gateway Cities.

5.2 2035 NO BUILD If forecasted socioeconomic growth occurs between 2013 and 2035 but no additional transit improvements are made, average weekday transit ridership in

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the subregion is projected to increase by 34,150 (11 percent) to about 352,940. Of these total future trips, 342,280 are projected to board or alight in the subregion, and 10,670 are projected to pass through the subregion. By 2035, about 5.8 million personal vehicle trips are forecasted to take place within the Gateway Cities each weekday. This scenario diverts about 139,850 personal vehicle trips from subregional roadways, which amounts to about a 2.4- percent cumulative reduction in personal vehicle travel attributable to transit.

5.3 2035 BUILD Table 5.4 indicates all major improvements to the Gateway Cities transit system assumed in the 2035 Build scenario.

Table 5.4 Summary of Planned Improvements to Rapid Transit Services in Gateway Cities

System Improvement High-Speed Rail (Phase 1 Blended) New blended interregional rail service between San Francisco / San Jose, Merced, and Los Angeles / Anaheim Amtrak Surfliner Various operational improvements, service enhancement Metrolink Various operational improvements, service enhancement Metro Blue 16 percent increase in service Metro Green 16 percent increase in service Metro Gold Eastside extension (Washington Blvd alignment) Eco Rapid Transit New transit service from Los Angeles Union Station to Cerritos Huntington Park Downtown Shopper New trolley service on Pacific Boulevard linking Downtown with Shuttle Northwest area-specific plan Atlantic Boulevard Bus Rapid Transit New bus rapid transit (BRT) service along Atlantic Boulevard New express bus service from Santa Ana to California State OCTA Route 722a University Long Beach Six new BRT lines (Artesia, Del Amo, Willow, Lakewood, Long Beach Transit Bus Rapid Transita Norwalk, and 7th Street)

Ridership Table 5.5 shows forecasted growth in transit ridership under Existing, 2035 No Build, and 2035 Build conditions. Under year 2035 Build conditions, average weekday transit ridership is expected to increase by about 73,010 over existing conditions (23-percent increase) to 391,800 trips. Of these, approximately 363,120 (93 percent) connect to locations in the Gateway Cities, while 28,670 (7 percent) are forecasted to pass through. A significant portion of those new trips are the result of travelers switching from local buses or other transit to new rapid and

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express transit modes. The net growth in transit ridership compared to 2035 No Build conditions is approximately 38,840, or an 11-percent increase.

Table 5.5 Forecasted Weekday Ridership Growth in the Gateway Cities

Ridership Growth vs. 2035 No 2035 Mode Existing Build Build Existing No Build Commuter and Intercity 7,660 10,730 25,810 237% 141% Rail Light Rail 102,800 113,070 167,300 63% 48% Rapid and Express Buses 17,250 18,970 25,060 45% 32% Local and Other Buses 191,080 210,170 173,630 -9% -17% Total 318,790 352,940 391,800 23% 11%

Notes: Figures represent average weekday ridership. Ridership on local and other buses declines marginally due to diversion to new rail options and to Metro Local Routes 260 and 762 being replaced by Atlantic Corridor BRT service. Figure 5.1 shows average weekday ridership by mode under 2035 No Build and 2035 Build conditions. Under Build conditions, the largest share of total riders is expected to use local and other buses (44 percent), followed by light rail (43 percent), commuter and intercity rail (7 percent), and rapid and express buses (6 percent). Of the 38,840 additional weekday transit trips attributable to planned and proposed transit enhancements, light-rail services account for the majority of new riders (53 percent), followed by commuter and intercity rail (39 percent) and rapid and express buses (8 percent). Eco Rapid Transit is responsible for a plurality of new ridership (28 percent), followed by HSR (24 percent), the Gold Line extension (20 percent), and Metrolink (12 percent).

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Figure 5.1 2035 Average Weekday Ridership by Transit Mode

Capacity and Utilization Table 5.6 shows the change in seated peak-hour transit capacity as a result of new transit improvements. Together, planned and proposed transit improvements are expected to increase seated peak-hour transit capacity in the Gateway Cities by 42 percent from 13,860 to 19,710.

Table 5.6 Peak-Hour Capacity Growth

Existing Mode and No Build 2035 Build Capacity Growth Commuter and Intercity Rail 3,330 4,400 32% Light Rail 3,020 8,060 168% Rapid and Express Buses 770 920 20% Local and Other Buses 6,740 6,330 -6% Total 13,860 19,710 42%

Source: Figures represent peak-hour seated capacity in one direction. Ridership on local and other buses declines marginally due to Metro Local Routes 260 and 762 being replaced by Atlantic Corridor BRT service. Figure 5.2 shows seated capacity by mode in Existing and 2035 Build scenarios. In the 2035 Build scenario, the largest share of transit seated capacity in the subregion would be provided by light rail (41 percent), followed by local and

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other buses (32 percent), commuter and intercity rail (22 percent), and rapid and express buses (5 percent). Light-rail seated capacity is expected to increase by 168 percent over existing conditions due to service enhancements on the Metro Blue and Green lines, and the new Metro Gold Line extension and Eco Rapid Transit routes. Local and other buses provide the next greatest share of transit capacity, although available seats decline slightly because the Atlantic Boulevard BRT is expected to replace two local bus routes.

Figure 5.2 2035 Seated Peak-Hour Capacity by Mode

Under year 2035 Build conditions, a number of transit routes are expected to experience peak-hour demand in excess of seated capacity.11 The following routes are forecasted to face utilization over 125 percent, and may not achieve their full ridership potential unless capacity issues are addressed:  El Sol Shuttle (165 percent);  Metro Green Line (155 percent);  Metro Blue Line (140 percent);  Metro Gold Line (135 percent);  Metro Bus Route 760 (120 percent);

11 Most Metro bus lines have seated capacity utilization over 100 percent, but less than 125 percent. Metro manages the capacity of its bus lines to achieve this level of utilization.

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 Metrolink Riverside/Perris Valley Line (120 percent);  Metrolink Orange Line (110 percent);  Metro Bus Routes 60, 110, 115, 251 (102 to 120 percent); and  Long Beach Transit Routes 61, 92, 93, 94, 171, 173, 192 (107 to 170 percent). Figure 5.3 illustrates 2035 Build transit capacity for each major transit project or project category. Red shading indicates where peak-period ridership demand is forecasted to exceed 100 percent utilization.

Figure 5.3 2035 Build Major Transit Route Capacity Utilization

Amtrak Pacific Surfliner

Metrolink Orange, 91, Riverside

HSR (Phase 1 Blended)

Eco Transit

Metro Blue Line

Metro Green Line

Metro Gold Line

Atlantic Boulevard Corridor

Metro Route 760

Other Express Routes

Metro Route 60

Montebello Bus Lines

Norwalk Transit

LADOT

Other Metro Local and Shuttle

Long Beach Transit

Small Transit Operators

0% 25% 50% 75% 100% 125% 150% 175%

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Source of New Ridership Each new passenger attracted to transit due to new service improvements can be thought of as shifting from one of a number of “prior” travel modes:  Personal vehicle (driver or passenger);  Commercial airline;  Other transit modes (e.g., those who switch from bus to new light rail);  Walking or bicycling; or  Induced travel (i.e., new trips that would not have been taken otherwise). New shorter-distance transit enhancements such as light rail or rapid buses typically draw most of their new ridership from those who previously took other less reliable modes of transit, followed by those who drove, biked or walked. By contrast, longer-distance enhancements such as commuter and intercity rail typically draw most new riders from personal vehicle travel and few if any from bicycling or walking, which are more suited to short-distance trips. Very long trips on intercity rail, such as on HSR, will also draw former air passengers due to competitive travel times and services. Table 5.7 shows the estimated prior travel mode for new transit trips under 2035 Build conditions.  Other Transit. About 36,540 transit trips are projected to shift from local bus or other transit to more reliable, faster transit options such as light rail and express bus. Prior users of local buses often comprise a large proportion of ridership on new light rail or rapid bus transit systems. This explains why ridership on local and other buses declines under 2035 Build conditions.  Personal Vehicles. As a result of the new transit enhancements in the 2035 Build scenario, approximately 26,700 new daily transit riders would have otherwise made their trip in a personal vehicle such as a car or truck. Note that the actual number of vehicles removed from area roadways is significantly smaller since personal vehicles often carry more than one passenger. The impact of transit on the number of vehicles on area roadways is presented later in this section.  Air. The 2035 Build scenario assumes HSR will be operational by 2035. HSR is expected to attract 2,490 former airline passengers, in particular for the long distance trips between southern and northern California.  Biking and Walking. Under 2035 Build conditions, about 5,950 new riders are projected to have previously walked or cycled from their origin to their destination. This figure does not take into account short-distance bike or walk trips used to access bus stops or transit stations, which would likely increase under 2035 Build conditions as a result of higher transit capacity and demand.

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 Induced Trips. The improvement of transit access can allow a small number of potential riders to take transit trips where they would otherwise have taken no trip at all. About 3,690 new trips are projected to be induced as a result of new transit opportunities under 2035 Build conditions.

Table 5.7 Prior Mode for All New Average Weekday Ridership

Other Personal Induced Mode Transit Vehicles Air Walk Bike Trips Commuter and Intercity Rail – 11,690 2,490 – 880 Light Rail 33,610 13,010 – 5,160 2,440 Rapid and Express Buses 2,930 2,000 – 790 370 Local and Other Buses – – – – – Total 36,540 26,700 2,490 5,950 3,690

Personal Vehicle Trip Reduction Under year 2035 Build conditions, transit services are projected to remove about 155,660 personal vehicle trips from Gateway Cities roadways. This represents a 24-percent increase over existing conditions and an 11-percent increase over 2035 No Build conditions. Table 5.8 shows the projected personal vehicle trip reduction under No Build and Build conditions. For more information on personal vehicle trip reduction by transit improvement, see Appendix A.

Table 5.8 2035 Weekday Personal Vehicle Trip Reduction

Travel demand modeling forecasts suggest there will be approximately 5.8 million vehicle trips taking place in the Gateway Cities each weekday by 2035. The total compliment of existing and planned transit services in the 2035 Build scenario would account for a 2.7-percent reduction in total daily personal vehicle travel, of which proposed new transit services would account for about 0.3 percent.

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Personal Vehicle Trip Reduction by Major Roadway To assess the effects of the forecasted reductions in personal vehicle travel on roadway congestion, we developed planning-level forecasts of travel reductions by major roadway. Based on the proximity of each major transit project to major roadways, we allocated personal vehicle trips to SR 60, I-5, I-710, I-105, or arterials. Results of this analysis are illustrated in Table 5.9. For complete Existing and 2035 No Build results, see Appendix B. Figure 5.4 illustrates the total forecasted personal vehicle trips diverted in the 2035 Build scenario (relative to existing conditions), by major roadway. These figures represent the total impact of all existing, planned and proposed transit services by 2035.

Figure 5.4 2035 Build Total Weekday Personal Vehicle Trips Removed, by Major Roadway

Of total vehicle trips removed in 2035 Build, a majority (61 percent) are forecasted to be removed from arterial streets, due to local bus and other shorter- distance transit services. Approximately 20 percent of trip removals occur from I-710, followed by I-5 (10 percent), I-105 (7 percent), and SR 60 (2 percent). Compared to 2035 No Build, 15,820 vehicle trips are removed from area roadways. These are the trips specifically removed by new transit improvements and routes. The greatest cumulative effect on travel occurs on I-5, where about 10,600 vehicles per weekday are removed due to rapid transit improvements (67 percent of total change). About 2,820 vehicle trips are removed from arterial roadways due to rapid transit improvements (18 percent); followed by 1,800 from SR 60 (11 percent); and just under 1,000 weekday trips are removed from I-710 and I-105 combined. A plurality of trip removals on I-5 is attributed to the California HSR system (4,090), followed by Eco Rapid Transit (3,610).

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Table 5.9 2035 Build Scenario Average Weekday Automobile Trips Removed by Roadway

2035 Build Affected Roadwaysb 2035 Build Weekday Personal Vehicle Trips Reductionc Weekday Personal Service Vehicle Tripsa SR 60 I-5 I-710 I-105 Arterials SR 60 I-5 I-710 I-105 Arterials Commuter and Intercity Rail Amtrak Pacific Surfliner 3,190 100% 3,190 0 Metrolink Orange Line 3,080 95% 5% 2,930 150 Metrolink 91 Line 830 15% 80% 5% 120 660 40 Metrolink Riverside Line 2,280 100% 5% 2,280 110 California HSR 4,090 100% 4,090 0 Subtotal 13,470 2,400 10,870 310 Light Rail Eco Rapid Transit 4,250 85% 5% 10% 3,610 210 420 Metro Blue 33,240 90% 10% 29,920 3,320 Metro Green 11,690 90% 10% 10,520 1,170 Metro Gold 3,120 25% 25% 50% 780 780 1,560 Subtotal 52,300 780 4,390 29,920 10,730 6,480 Rapid and Express Buses Atlantic Boulevard BRT 1,250 50% 50% 620 620 Metro Route 760 2,200 50% 50% 1,100 1,100 Metro Route 762 100% Other Metro Rapid/Express 4,340 100% 4,340 Subtotal 7,790 1,720 6,070

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2035 Build Affected Roadwaysb 2035 Build Weekday Personal Vehicle Trips Reductionc Weekday Personal Service Vehicle Tripsa SR 60 I-5 I-710 I-105 Arterials SR 60 I-5 I-710 I-105 Arterials Local and Other Buses Metro Route 60 4,410 100% 4,410 Montebello Bus Lines 7,150 100% 7,150 Norwalk Transit 3,650 100% 3,650 LADOT DASH 3,040 100% 3,040 Other Metro Local/Shuttle 20,000 100% 20,000 Long Beach Transit 39,130 100% 39,130 All Other Small Operators 4,730 100% 4,730 Subtotal 82,100 82,100 Total 155,670 3,180 15,260 31,640 10,730 94,960 a Personal vehicle trip reduction assumes an average personal vehicle occupancy rate of 1.59 persons per vehicle. b Allocation by Cambridge Systematics, 2013.

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5.4 SUMMARY OF ANALYSIS This analysis is intended to provide a forecast of the potential ridership and multimodal impacts of planned and proposed rapid transit investments in the Gateway Cities. The study concludes the following:  Rapid transit enhancements produce ridership gains. Expanding and enhancing rapid and express transit opportunities in the Gateway Cities would have a significant, positive effect on ridership, particularly on new light-rail transit systems.  Transit ridership growth is not forecasted to keep pace with aggressive capacity expansion. The slate of transit enhancements in the Build scenario contribute to a 42-percent increase in peak-hour seated transit capacity within the Gateway Cities compared to existing conditions. This produces a 23- percent increase in ridership, about 11 percent of which can be described by socioeconomic growth alone.  Prior bus users constitute over one-half of new rapid transit ridership. New light rail and BRT services offer more reliable, direct access for current bus users, which can lure away many would-be bus passengers. As passengers shift from bus to these new types of transit, only modest gains in ridership on local buses result, despite significant capacity improvements. This analysis assumed regionwide increases in bus service levels, but transit providers may want to consider targeting potential bus service enhancements to avoid inefficient overlap between such services. Transit providers may also look for cost-effective ways to distinguish the unique role of local bus service by improving speed and frequency of the routes as well as customer service and technology improvements.  Less than one-half of new ridership results in reductions in light vehicle travel. Only about 38 percent of new transit trips were previously taken by personal vehicle, compared to 52 percent who switched from buses, and 8 percent who were former pedestrians and bicyclists. About 5 percent are new travelers entirely.  Planned rapid transit improvements have greatest effect on I-5 vehicle travel. Of the 15,820 weekday vehicle trips removed from area roadways as a result of new transit improvements, 10,600 are removed from I-5 (67 percent of total change), due largely to high-speed rail, Eco Rapid Transit, and Amtrak Pacific Surfliner corridor improvements.  Several rapid transit lines face capacity issues. As a result of forecasted new demand for transit, several transit lines may be over capacity by 2035, in particular Metro light-rail systems in the Gateway Cities.  Reduced personal vehicle trips due to rapid transit usage constitute a very small share of overall regional vehicle travel. While expanding transit

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options is expected to reduce personal vehicle travel in the Gateway Cities, the reduction attributable to expanded transit services amounts to less than one-half percent of total forecasted vehicle travel in the subregion in 2035.  Local bus improvements are not addressed, and no data was available for some proposed improvements. Local transit providers have noted that the improvements proposed in this report pertain specifically to rapid and express transit options, whereas local bus service constitutes a sizeable majority of ridership in the subregion today. Furthermore, several proposed improvements submitted by agencies (e.g. Long Beach Transit BRT projects and OCTA Route 722) did not yet have data necessary for inclusion in the quantitative assessment, and are therefore omitted from results presented here. A separate report, the Gateway Cities Maximum Transit Assessment, explores the potential effects of significantly increasing local bus service in addition to rapid and express transit improvements.  Sketch-level, regional analysis. This analysis presents a best estimate of future conditions based on readily available data, trends, and planning factors. It is therefore limited in scope and analytical precision. For instance, this study assumes consistent socioeconomic growth based on prior trends, and that passengers respond similarly to capacity changes on each local bus line. Actual passenger behavior will differ from service to service, depending on many specific factors not considered in this analysis. Therefore, this analysis is intended to provide only a general overview of regional trends rather than actionable data on any one transit line. Future analysis conducted as part of the Gateway Cities Strategic Transportation Plan will utilize a new multiresolution model to forecast more complex forecasts of transit impacts and the interaction between travel modes. Those more rigorous forecasts may differ significantly from the forecasts presented here, which are based solely on preexisting data and trends. Future land use planning and unforeseeable socioeconomic trends could also impact actual travel behavior significantly. Coordination of transportation planning with these other important factors should always be considered.

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A. Personal Vehicle Trip Reduction

Table A.1 illustrates major transit routes and transit categories in the Gateway Cities and the number of personal vehicle trips they reduce under the Existing, 2035 No Build, and 2035 Build scenarios. The last column illustrates the forecasted change between the No Build and Build scenarios.

Table A.1 Daily Personal Vehicle Trips Reduced Due to Transit Services

2035 Transit Projects Existing 2035 No Build 2035 Build (Build – NB) Intercity & Commuter Rail

Amtrak Pacific Surfliner 1,751 2,592 3,193 600 Metrolink Orange, 91, Riverside 2,600 3,571 6,192 2,621 High-Speed Rail (Phase 1 Blended) – – 4,086 4,086 Subtotal 4,352 6,163 13,471 7,308 Light Rail

Eco Rapid Transit – – 4,250 4,250 Metro Blue 29,706 32,676 33,241 565 Metro Green 10,448 11,493 11,692 199 Metro Gold – – 3,120 3,120 Subtotal 40,154 44,169 52,302 8,133 Rapid and Express Buses

Atlantic Boulevard BRTa – – 1,247 1,247 Metro Route 760 1,999 2,199 2,199 – Metro Route 762 a 788 867 – (867) All Other Metro and Express Routes a 3,949 4,344 4,344 – Subtotal 6,736 7,409 7,790 380

A-1 Gateway Cities Transit Assessment Appendix

2035 Transit Projects Existing 2035 No Build 2035 Build (Build – NB) Local and Other Buses

Metro Route 60 4,007 4,408 4,408 – Montebello Bus Lines 6,499 7,149 7,149 – Norwalk Transit 3,320 3,652 3,652 – LADOT DASH 2,766 3,043 3,043 – All Other Metro Local and Shuttlea 18,183 20,002 20,002 – Long Beach Transit 35,567 39,123 39,123 - All Other Small Operators 4,296 4,726 4,726 – Subtotal 74,639 82,103 82,103 – Total 125,880 139,845 155,666 15,821b

a 2035 Build values represent Atlantic Blvd BRT replacing existing Metro Routes 260 and 762. b Note that other planned services such as Long Beach BRT and OCTA 722 are missing from this table due to unavailability of data at the time of publication on which to perform analysis. These new services could add to this sum.

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B. Diverted Personal Vehicle Trips Roadway Allocation

To assess the effects of the forecasted reductions in personal vehicle travel on roadway congestion, we developed planning-level forecasts of travel reductions by major roadway. Based on the proximity of each major transit project to major roadways, we allocated personal vehicle trips to SR 60, I-5, I-710, I-105, or arterials. For example, the Metro Blue Line light-rail runs parallel to I-710, so 90 percent of personal vehicle trips attracted to the Blue Line were assumed to otherwise take place on the I-710, with the remaining 10 percent taking place on arterial roadways. Table B.1 illustrates each of these allocation assumptions, and the resulting personal vehicle trip reduction by roadway in the Existing, 2035 No Build, and 2035 Build scenarios.

B-1 Gateway Cities Transit Assessment Appendix

Table B.1 2035 Build Daily Personal Vehicle Trips Reduced by Roadway

Personal Vehicle Trips Removed Affected Roadways Existing Auto Trips Removed by Roadway 2035 No Build Auto Trips Removed by Roadway 2035 Build Auto Trips Removed by Roadway Future – Future – Service Existing NB Build SR 60 I-5 I-710 I-105 Arterials SR 60 I-5 I-710 I-105 Arterials SR 60 I-5 I-710 I-105 Arterials SR 60 I-5 I-710 I-105 Arterials Commuter & Intercity Rail

Amtrak Pacific Surfliner 1,751 2,592 3,193 100% – 1,751 – – – – 2,592 – – – – 3,193 – – –

Metrolink Orange Line 1,295 1,779 3,085 95% 5% – 1,231 – – 65 – 1,690 – – 89 -– 2,930 – – 154

Metrolink 91 Line 348 478 828 15% 80% 5% 52 278 – – 17 72 382 – – 24 124 663 – – 41

Metrolink Riverside Line 957 1,315 2,279 100% 5% 957 – – – 48 1,315 -– – – 66 2,279 - – – 114

California HSR – – 4,086 100% – – – – – – – – – – – 4,086 – – –

Subtotal 4,352 6,163 13,471 1,009 3,260 – – 130 1,386 4,664 – – 179 2,404 10,872 – – 310

Light Rail

Eco Rapid Transit – – 4,250 85% 5% 10% – – – – – – – – – – – 3,612 – 212 425

Metro Blue 29,706 32,676 33,241 90% 10% – – 26,735 - 2,971 – – 29,409 – 3,268 – – 29,917 – 3,324

Metro Green 10,448 11,493 11,692 90% 10% – – - 9,403 1,045 – – – 10,344 1,149 – – – 10,522 1,169

Metro Gold – – 3,120 25% 25% 50% – – - - - – – – -– -– 780 780 – – 1,560

Subtotal 40,154 44,169 52,302 – – 26,735 9,403 4,015 – – 29,409 10,344 4,417 780 4,392 29,917 10,735 6,478

Rapid and Express Buses

Atlantic Boulevard BRT – – 1,247 50% 50% – – – – – – – – – – – – 624 – 624

Metro Route 760 1,999 2,199 2,199 50% 50% – – 999 – 999 – – 1,099 – 1,099 – – 1,099 – 1,099

Metro Route 762 788 867 – 100% – – 788 – – – – 867 – - – – – – –

Other Metro Rapid/Express 3,949 4,344 4,344 100% – – – – 3,949 – – - – 4,344 – – – – 4,344

Subtotal 6,736 7,409 7,790 – – 1,787 – 4,948 – – 1,966 – 5,443 – – 1,723 – 6,067

Local and Other Buses

Metro Route 60 4,007 4,408 4,408 100% – – – – 4,007 – – – – 4,408 – – – – 4,408

Montebello Bus Lines 6,499 7,149 7,149 100% – – – – 6,499 – – – – 7,149 – – – – 7,149

Norwalk Transit 3,320 3,652 3,652 100% – – – – 3,320 – – – – 3,652 – – – – 3,652

LADOT DASH 2,766 3,043 3,043 100% – – – – 2,766 – – – – 3,043 – – – – 3,043

Other Metro Local/Shuttle 18,183 20,002 20,002 100% – – – – 18,183 – – – – 20,002 – – – – 20,002

Long Beach Transit (not 39,272 43,198 43,198 100% 39,272 43,198 43,198 including planned BRT) All Other Small Operators 4,296 4,726 4,726 100% – – – – 4,296 – – – – 4,726 – – – – 4,726

Subtotal 74,639 82,103 82,103 – – – – 74,639 – – – – 82,103 – – – – 82,103

Totals 125,880 139,845 155,666 1,009 3,260 28,522 9,403 83,733 1,386 4,664 31,375 10,344 92,142 3,184 15,264 31,640 10,735 94,958

Source: Cambridge Systematics analysis and estimation.

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C. Intercity and Commuter Rail Travel Market Assumptions

Long distance intercity transit trips required a unique set of assumptions to support the trip diversion analysis. For example, because intercity passenger rail trips are much longer in length, we would not expect many travelers to make these trips by walking or bicycling. Prior analysis by the California High-Speed Rail Authority has provided detailed high-speed rail (HSR) diversion rates by market pairs, reflecting the wide differences in diversion rates associated with travel distance and destination. This appendix details how HSR diversion assumptions and other readily available data were used to calculate trip diversion for commuter and intercity rail. The first step was to estimate the share of trips that occurred in each of the intercity travel markets that are most relevant to rail services serving or passing through the Gateway Cities. These shares could then be applied to the transit ridership planning-level forecasts. Note that diversion from Amtrak Pacific Surfliner and Metrolink to HSR is imbedded in these assumptions. Table C.1 presents HSR ridership forecasts by market pair for 2030. We adjusted the 2030 values using a 0.5-percent annual growth rate applied in the HSR Business Plan12, then calculated the share of total trips within each market pair. The market areas or pairs included greater Los Angeles (LA) (approximately the six-county Southern California Association of Governments [SCAG] area), North to South greater Los Angeles, San Francisco (SF) to LA, San Joaquin Valley (SJV) to LA, LA to San Diego, and SF and Sacramento to San Diego. Next, we used population to factor statewide commuter and intercity route ridership to reflect the number of trips likely to affect the Gateway Cities. For interregional trips we applied the Gateway Cities population share relative to the LA County population. Tables C.2 and C.3 illustrate the data used for these calculations.

12 California High-Speed Rail Authority, 2012 Revised High-Speed Rail Business Plan, 2012.

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Table C.1 High-Speed Rail Travel Markets – Share of Total Trips

2030 Year 2035 2035 Percent Share of Total Blended 2030 Low High Low High Low High Average Total HSR Ridership 19.1 31.0 19.6 31.8 In LA Basin 0 3.1 0.0 3.2 0.0% 10.0% 5% North-South LA 0.4 0.5 0.4 0.5 2.1% 1.6% 2% San Francisco – LA 5.4 8.2 5.5 8.4 28.3% 26.5% 27% San Joaquin Valley – LA 3.7 5.1 3.8 5.2 19.4% 16.5% 18% LA – San Diego 0.4 0.1 0.4 0.1 2.1% 0.3% 1% SF & Sacramento – San Diego 0.8 1.0 0.8 1.0 4.2% 3.2% 4%

Source: 2012 High-Speed Rail Business Plan, Tables 5.15 and 5.16. Year 2035 values calculated based on a 0.5-percent growth rate from Year 2030 forecast.

Table C.2 2035 Population Forecast – Los Angeles County Population

Region Year 2035 Population Share of SCAG Population SCAG 18,200,000 Los Angeles County 11,353,000 62.4%

Source: Southern California Association of Governments, Regional Transportation Plan and Sustainable Communities Strategy, 2012 County Fact Sheets.

Table C.3 2035 Population Forecast – Gateway Cities Population

Region Year 2035 Population Share of LA County Population Gateway Cities 2,222,000 19.6%

Source: Southern California Association of Governments, Regional Transportation Plan and Sustainable Communities Strategy, 2012 County Fact Sheets. Finally, we calculated average diversion based on diversion rates developed in the HSR Business Plan. These rates were unique to market pairs and trip purpose. The markets were identified as Metropolitan Planning Organization (MPO) areas, including SCAG (Greater Los Angeles), the Metropolitan Transportation Commission (Bay Area) and San Diego Association of Governments (San Diego). The trip purposes included business, commercial, recreational and other trips. The modes from which transit trips were diverted included personal vehicle, conventional rail, air, and induced trips. For our analysis, conventional rail was categorized as “other transit.” Tables C.4, through C.8 illustrate the calculations used to derive the diversion rate assumptions we used in our analysis. The summary results of our analysis are detailed in Section 5.0.

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Table C.4 Intercity Markets Forecasted Total Trips and Diversion Assumptions

Scenario 12-043d, Phase 1 Blended (Low) Business/Commercial Recreational/Other Diverted Diverted Diverted from Diverted from from from Business/ Recreational/ Personal Conventional Diverted Induced Personal Conventional Diverted Induced Commercial Other Total Vehicle Rail from Air Trips Vehicle Rail from Air Trips Greater LA to: Bay Area 802,000 1,902,000 2,705,000 54% 0% 43% 3% 55% 0% 41% 4% San Joaquin Valley 485,000 1,385,000 1,870,000 91% 0% 7% 2% 94% 0% 4% 2% San Diego area 3,000 216,000 219,000 0% 100% 0% 0% 99% 1% 0% 0% San Diego to Greater LA 3,000 216,000 219,000 0% 100% 0% 0% 99% 1% 0% 0% Bay Area 39,000 374,000 413,000 9% 0% 89% 2% 41% 0% 58% 0%

Source: 2012 California HSR Revised Business Plan, Ridership and Revenue Forecasting Technical Appendix, modeling assumptions for Phase 1 Blended (model run 12-043d).

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Table C.5 Intercity Markets Calculated Diverted Trips by Purpose and Mode

Business/Commercial Recreational/Other Diverted Diverted Diverted from Diverted from from Personal Conventional Diverted Induced from Personal Conventional Diverted Induced Vehicle Rail from Air Trips Vehicle Rail from Air Trips Greater LA to Bay Area 433,080 – 344,860 24,060 1,046,100 – 779,820 76,080 San Joaquin Valley 441,350 – 33,950 9,700 1,301,900 – 55,400 27,700 San Diego area – 3,000 – – 213,840 2,160 – – San Diego to Greater LA – 3,000 – – 213,840 2,160 – – Bay Area 3,510 – 34,710 780 153,340 – 216,920 –

Source: 2012 California HSR Revised Business Plan, Ridership and Revenue Forecasting Technical Appendix, modeling assumptions for Phase 1 Blended (model run 12-043d).

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Table C.6 Intercity Markets Calculated Total Trips All Trip Purposes

Diverted Diverted from Personal from Diverted Induced Vehicle Conventional Rail from Air Trips Greater LA to Bay Area 1,479,180 – 1,124,680 100,140 San Joaquin Valley 1,743,250 – 89,350 37,400 San Diego area 213,840 5,160 – – San Diego to Greater LA 213,840 5,160 – – Bay Area 156,850 – 251,630 780

Table C.7 Intercity Markets Calculated Average Diversion Rates

Diverted Diverted from Personal from Diverted Induced Vehicle Conventional Rail from Air Trips Greater LA to Bay Area 55% 0% 42% 4% San Joaquin Valley 93% 0% 5% 2% San Diego area 98% 2% 0% 0% San Diego to Greater LA 98% 2% 0% 0% Bay Area 38% 0% 61% 0%

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Table C.8 Final Rail Market Diversion Rates Used for Ridership Analysis

Diverted Diverted from from Personal Conventional Diverted Induced Vehicle Rail from Air Trips Interregional SCAG Intercity Trips San Francisco – LA 55% 0% 42% 4% San Joaquin Valley - LA 93% 0% 5% 2% LA - San Diego 98% 0% 0% 2% SF& Sacramento - San Diego 38% 0% 61% 0% Intraregional Greater LA Trips In LA Basin 90% 0% 0% 10% North-South LA 90% 0% 0% 10%

Note: Intraregional trip diversion rates based on generalized results from preceding analysis.

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