12 2 14 Item 14 All Door Boarding Report

Transcript

1 - All Door Boarding Evaluation Final Report 2014 December Technology and Performance 1 Page FINANCE AND INFORMATION TECHNOLOGY

2 Table of Contents Executive Summary ... ... 1 ... Introduction ... ... ... ... 2 Implementation ... ... ... ... 5 Methodology Evaluation ... ... ... 9 Results ... ... ... ... 11 Conclusion ... ... ... ... 21 Appendix ... ... ... ... 22

3 EXECUTIVE SUMMARY ith For generations, the transit industry has had to balance the desire for faster service w most bus Today - door boarding and fare , the need to collect fares. systems require front verification by the operator - in order to increase fare compliance. The tradeoff is that front extends dwell times at stops, lengthens overall travel times and uses door boarding also iciently . scarce resources less eff O n July 1, 2012, the San Francisco Municipal Transportation Agency (SFMTA) bec ame North America implement All - Door Boarding the first multimodal transit operator in to . Ex pandin g a policy already applicable to light rail vehicles, the SFMTA systemwide - customers with valid proof - of began permitting payme nt to enter through any door of Muni buses . In doing so, the agency legaliz ed an informal practice that had and streetcars oped organically in response to front - door queues, crowding and slow service. devel - of - Payment systems, the SFMTA allows Unlike other transit operators with Proof customers to pay cash on - board vehicles at surface stops, thus avoiding the expenses of ticket ven ding machines. Serving the nation’s second - densest major city with crowded transit vehicles largely operating in mixed traffic , the SFMTA must make efficient use of every minute in revenue service. T wo years after implementation, a comprehensive evaluation of All - Door Boarding finds that the policy has contributed to : Legalizing All boarding Door Boarding has encouraged customers  Shorter Stops – - to distribute themselves more evenly , thereby between the front and rear doors Pre at busy Muni and post - implementation surveys reducing average dwell times. - stops average reductions of 1 .5 seconds ( 38% ) per customer entry or exit. found All - Door Boarding also has improved dwell time consistency and lowered variability, factor in helping reduc e vehicle bunches and gaps and an important making service more reliabl e and predictable . 2011 through FY 2013  Faster Trips – From FY 2010 - system - 2014, average bus speed s (including stops) improved modestly from 8.41 to 8.56 mph (2%) . All - Door Boarding has helped keep Muni moving during a period of rapid growth in San Francisco and increasing demand on the . All - Door Boarding transportation system just one of many tools such as exclusive transit lanes, transit signal priority and is parking management that together can help reduce travel time.  Improved Fare Compliance – A series of four fare surveys between 2009 and 2014 indicate th at fare compliance continues to improve. The fare evasion rate has d ecreased from 9.5% to 7.9% over five year s and the estimated uncaptured revenue due to fare evasion has dropped from $19.2 million to $17.1 million. The success of All - Door Boarding in San Francisco’s operating environment - cost exploring demonstrates the potential benefits of this policy for other cities that are effective opportunities to speed up transit. Technology and Performance 1 Page FINANCE AND INFORMATION TECHNOLOGY

4 INTRODUCTION On July 1, 2012, the San Francisco Municipal Transportation Agency (SFMTA) became the first multimodal transit provider in North America to permit systemwide All - Door As the operator of Muni, the eighth , the SFMTA largest U.S. transit system Boarding. - manages a diverse fleet of buses (motor coaches and electric trolley coaches), light rail vehicles, historic streetcars and cable cars with an annual ridership of 22 6 million. This report summarizes the operational and financial results of All - Door Boarding two years after implementation. - Previously available on the six Muni light rail lines only, the SFMTA expanded All Door Boarding to enco mpass all vehicles. The rules are simple: customers with valid transfers/fare receipts, Clipper® Cards or other fare media may enter through any door of any vehicle at any time. Clipper® users must validate their cards by tapping readers which are adjace nt to every door. The historic open - air cable cars remain a special case where conductors handle fare collection . All - Door Boarding in San Francisco evolved from various official policies and unofficial policy allowing - payment practices over the past two decades. On light rail , a proof - of - No such in the 1990s. took effect paid fares to enter through any door customers with pre policy existed on buses, however. , cu stomers organically developed a culture of Instead rear - door boarding at certain busy stops – with or without proof - of - payment – in response illegal practice and its to long front door queues, crowding, and slow service. T he then - - inconsistent application increase d perceptions of fare evasion even though it reduced delays and demonstrated the potential of sanctioned All - Door Boarding. Dwe ll Times and Fare Collection: A Historical Perspective Shortening dwell time – when a vehicle stops for customers to board an d alight – can alanc ing make transit a more attractive choice and optimize scarce fiscal resources. B the desire for faster service with the need to collect fares has challenged the transit industry for generations. Historically, rail rapid transit lines such as the New York Subway or - Chicago ‘L’ evolved to have off board ticket vending machines and faregates, thus minimizing dwell times at stations but increasing fare collection costs. er “surface” transit The situation has been more difficult for buses, streetcars and oth - modes due to relatively lower ridership volumes and the physical configurations of at grade and open boarding locations. A century ago, streetcar companies employed an customers paid. operator and a conductor, which enabled the vehicle to move while Fighting for its economic survival, the industry transitioned to one person operation. - Although this change reduced deficits, it increased boarding delays since everyone now . (Figure 1) needed to file through the front door Technology and Performance 2 Page FINANCE AND INFORMATION TECHNOLOGY

5 Brooklyn, NY (1937) Akron, OH (1945) FIGURE 1 Front - Door Boarding (Images from the publications Transit Hails the Historical (1937) and Trolley Coaches Modern Car Why People Like Them (1945)) – Building off successful European models, the transit industry in North America took an important step towards reducing dwell times with the first modern light rail systems in Edmonton (1978) , Calgary (1981) and San Diego (1981). Under those and most - - Payment" (POP) systems, customers may enter through any door subsequent "Proof of fare media with prepaid or tickets pre - purchased from station vending machines. F are inspectors may issue citations to those without valid proof - of - payment. - of - payment Now standard on new light rail lines, transit systems are extending the proof model to many bus rapid transit operations such as Select Bus Service in New Yor k, the Health Line in Cleveland and the Orange Line in Los Angeles. As of 2014, h owever, San Francisco remains the only large urban bus and rail transit system in North America with - . A ll throughout the entire transit network D oor B oarding The Need for All Door Boarding - - Door San Francisco’s operating environment provides an ideal testing ground for All United States . Boarding in the - densest major city with Serving the nation’s second crowded transit vehicles largely operating in mixed traffic, the SFMTA must make efficient use of every minute in revenue service. All - Door Boarding is part of a larger effort to improve travel times through transit priority lanes, signal preemp tion, stop consolidation, new vehicles and increased limited - stop service. Service s top s account for about 20% of Muni’s travel time. Muni buses average approximately , the highest in the country along with New York. 70 boardings per hour This rate incr 100 boardings during the peak hour in the peak direction, about eases to hampers the ability to deliver on - time service. which further way, - of - all or Unlike systems with exclusive rights part of every Muni line operates in mixed traffic. Muni buses ave rage only 8.6 mph. Boarding delays exacerbate the difficulty of meeting demand with an insufficient fleet – at least 8% of peak - hour buses are currently full. The challenges of the recent past will only intensify in the future: San Francisco’s populatio n increased from 805,235 to 837,442 (+4.0%) between 2010 and 2013 and is projected to reach 1 million by 2032. Technology and Performance 3 Page FINANCE AND INFORMATION TECHNOLOGY

6 A Different Implementation Approach implement systemwide All - Door Boarding, the SFMTA overcame two significant To hurdles that historically have precluded similar policies elsewhere: (1) extending fare enforcement cost - - dispersed transit network; and (2) effectively over a geographically placing ticket vending mach ines at every stop with associated installation, s ervicing and maintenance costs. During the past five years, the SFMTA has strengthened its Proof - of - Payment P rogram incrementally fare inspections from and fare compliance. In 2010, it expanded improve d 60 bus lines and one historic streetcar line , representing an over six light rail lines to Door increase in ridership coverage from 145,000 to 680,000 weekday trips. In 2012, All - Boarding brought a modest increase in Transit Fare Inspect ors . Ac tive full - time grew equivalent positions from 41 to 54 over two years . With staffing constrained by the budget , the SFMTA developed new deployment strategies to protect fare revenues as expanded to . Rotating fare inspectors daily to the entire network P roof - of - P ayment has geographical coverage. different police districts has been particularly helpful in increasing implementation Front - (a) Pre Door Boarding - (b) - Implementation All - Post Door Boarding implementation (a) Queuing at the front door Muni Boarding Procedures 2 FIGURE before after implementation and (b) Entering through both doors implementation about stops. Rather than installing ticket vending ,500 surface rail and bus Muni serves 3 - A allows cash , the SFMT everywhere machines paying customers to enter through the obtain a 90 - minute transfer/fare receipt from the operator. front door, use the farebox and service ticket vending machines at light rail subway stations, electronic fare With full - surveys indicate products on Clipper®, and an extensive Clipper® retail vendor network, a little over 10% of intends The SFMTA boarding customers pay cash at busy stops. that reduce cash fares. to pilot mobile ticketing to increase customer convenience and further oor Boarding, the SFMTA hoped to achieve several and financial operational With All D - stops , (b) faster trips and (b) maintain ed or improve d fare compliance. goals : (a) shorter assign fewer In certain circumstances, faster service may permit a transit operator to FINANCE AND INFORMATION TECHNOLOGY Technology and Performance 4 Page

7 vehicles to a route and still maintain headways. Given existing crowding and pre - is was not a program objective. however, th schedule adherence issues, IMPLEMENTATION At the end of 2011, the SFMTA decided to formal systemwide All - Door implement within six months. Without a peer transit system model to follow, the agency Boarding faced uncertainty about revenue losses and other risks. On the other hand, the SFMTA already had unofficial All Door Boarding and would only be formalizing the policy across - the system. To determine the program’s outcome, preparations included a robust valuation plan . e Fare Survey on understanding Indirect preparation actually began several years , focus ing rlier ea systemwide fare payment patterns and identifying ways to improve the effectiveness of fare enforcement. In 2009, the SFMTA conducted its f irst comprehensive Proof - of - Payment Study in response to growing concerns about revenue losses from then - illegal rear door boarding in an environment of significant budget shortfalls. - Besides reviewing the practices of the agency’s Proof - of - Payment Program, the study included a comprehensive survey to determine the times, routes and locations where fare sample of fare compliance issues were most prevalent. To obtain a representative Inspectors and survey recorders rode payment patterns, teams of Transit Fare house in - the entire system for several months. employed two methodologies to determine fare payment: (a) a “spot check”, The survey where teams checked customers and then immediately exited, and (b) a “ride along”, - where teams customers. The remained on board for multiple stops to check boarding ride along” all owed the team to observe farebox payments and through which door “ customers entered. Examples of invalid proof of - payment included underpaying the cash - fare, showing nothing or improperly using fare media. With 41,239 customer observations , the fare surve y found a fare evasion rate of 9.5%. A smaller 2010 follow - up survey of over 12,000 customers revealed a fare evasion rate of 8. 6 %. Fare Enforcement The primary purpose of Transit Fare Inspectors is not to recover costs through their citation fines but to improve fare compliance. Rather than involving the court system, the SFMTA treats citations for adults as infractions and collects fines, which are just over one criminalize percent of fare revenues. E fforts are also underway at the state level to de youth citations at the state level. As important ly, Transit Fare Inspectors increase safety . ormed staff presence and s ecurity by providing a unif on that fare The SFMTA’s fare enforcement strategy is designed to create the expectati - Informed by the 2009 Proof inspections can happen anywhere at any time. Payment - of Technology and Performance 5 Page FINANCE AND INFORMATION TECHNOLOGY

8 Study, agency has undert a k en changes to improve its fare inspection program, the including: Expanding enforcement from light rail to buses and streetcars  Rotating Transit Fare Inspectors to a different police district everyday where they  an check any Muni vehicle, rather tha n focusing on one specific line c  Rescheduling shifts to improve weekend coverage so that all inspectors work i either Saturday or Sunday nstead of only Monday to Friday In  “enhanced fare enforcement”, where a large team of fare inspectors troducing quickly checks all customers on a vehicle, sometimes accompanied by police  Centralizing the Transit Fare Inspector reporting location at SFMTA headquarters to increase inspection time and reduce travel time to the system’s core - Month Preparation Process Six - Given the multi the SFMTA convened disciplinary nature of the implementation process, an internal working group consisting of virtually all organizational divisions: Finance & Information Technology, Transit (including Transit Management and Operations Planning & Schedules), Sustainable Streets (including Security, Investigat ions and Enforcement), Commu nications, System Safety and Taxi & Accessible Services . The group collaborated to accomplish the following:  Transit Fare Inspector Staffing Increase – The working group justified the hiring of approximately additional Transit Fare Inspectors, ultimately netting - 13 new full time equivalent positions over two fiscal years. As a result, estimated inspection rates have increased from 1.1% to 1.3% of bus, streetcar and light rail customers. The ed citation revenue would cover a portion of the budget assumed that increas incremental salaries and benefits, but that the net labor cost would be approximately $47,000 per employee. In May 2012, at the request of the SFMTA –  Transportation Code Amendments San Francisco Board of Supervisors amended the city’s Board of Directors, the Transportation Code to accommodate the new policy. The updated regulations - door boarding and clarified that Clipper® users must eliminated restrictions on rear tag their cards on readers to validate t heir fare upon . boarding – Methodologically  0 Fare Survey fare surveys, consistent with the 2009 and 201 SFMTA staff conducted an abbreviated survey in spring 2012 to benchmark fare compliance prior to implementation. The survey covered all times of day and virtually every Muni route. With 9,162 customer observations, it found a systemwide 8. 4% fare evasion rate. -  – Staff verified the functionality of previously - installed rear Vehicle Preparation door Clipper® readers , removed signs warning “Stop: Enter T hrough Front Door O nly” and added language - neutral decals illustrating the policy.  Public Outreach – The SFMTA installed informational car cards in English, Spanish and Chinese in shelters and on bus and streetcar overhead panels . Staff outreached to community groups to explain the boarding policy and emphasize safety when boarding and exiting vehicles. SFMTA’s Director of Transportation and Director of Transit held a press event four days prior to implementation. ou Y hearted house - videos in ube T - Finally, the SFMTA produced several light Technology and Performance 6 Page FINANCE AND INFORMATION TECHNOLOGY

9 featuring “Professor Muni” explaining All Door Boarding’ s “do’s” and “don’ts”. - P ublic outreach efforts , combined with signage on vehicles and shelters, may have contributed to a high public acceptance of the policy. In the month following implementation, the SFMTA received fewer than 50 complaints from unique individuals about All - Door Boarding .  W Internal Communications – ith the anticipated influx of rear - door customers , the SFM internally . TA made special efforts to communicate safety procedures Operators received a bulletin containing guidelines on positioning buses to maintain visibility and activating the rear doors. (a) Rear - Clipper® Door Card Reader All (b) - Door Boarding Decals on Streetcars, Light Rail and Buses Door Boarding - (d) New Decals Authorizing All (c) Former Decals Prohibiting All - Door Boarding Door Boarding FIGURE 3 Vehicle Preparation for All - (a) Verified functionality of - neutral decals Clipper® readers, (b) Designed language door - rear installed - previously explaining that customers with Clipper® Cards and other valid fare media could enter - door signs through the rear door, but not with cash, (c) Removed prohibiting rear door boarding. boarding and (d) Added the decals permitting rear - Page 7 Technology and Performance FINANCE AND INFORMATION TECHNOLOGY

10 (a) English Car Card explaining All Door Boarding - (b) Spanish and Chinese Car Card explaining All - Door Boarding (d) Transit Operator Bulletin (c) “Professor Muni” YouTube Video (a) and (b) English, Spanish and FIGURE External and Internal Communications 4 - ube video Chinese car cards placed on bus and streetcar overhead panels, (c) a Y ou T Transit Operator Instruction Bulletin for a Training & featuring “Professor Muni” and (d) s FINANCE AND INFORMATION TECHNOLOGY 8 Page Technology and Performance

11 EVALUATION METHODOLOGY During implementation, SFMTA staff developed a rigorous methodology to evaluate the - Door Boarding’s operational and financial impacts. Data included direct observations All of ridershi p and dwell times at busy stops and along entire routes, travel speeds from - approximately one third of buses and another comprehensive fare survey. Stationary Dwell Time Survey To correlate ridership volumes and dwell times, staff timed how long it too k for customers to enter and exit vehicles. Recognizing that limited personnel constrained the quantity of collected samples, the SFMTA chose this approach to achieve ridership accuracy that replicate. While APC s Automatic Passenger Counter (APC) reports could not necessarily provide reliable timing and geo - locational data, crowding at doors can interfere with registering customer entries and exits by existing laterally - mounted sensors. Stationary Dwell Time Surveys at fixed locations took place in spring 2012, just prior to implementation, and two years later in spring 2014. To control for as many variables as possible, the two sets of surveys took place on the identical day of the week. To gauge - ’s impacts in various contexts, st aff observed over 2,000 boardings and All Door Boarding - alightings at nine high - volume stops served by 29 routes of differing types (local, limited stop and express lines) and vehicles (two - door buses, three - door buses and streetcars). Additionally, the nine locations repr esented four diverse typ es and ridership markets, including the Downtown shopping area, the commuter oriented Financial District, - neighborhood commercial intersections in Chinatown and the Mission District, and tourist destinations in Fisherman’s Wharf and along the Embarcadero . to maximize the chances of observing S urveying focused on the afternoon peak period - - . The roughly 4 concentrated boardings to 1 ratio of boardings to alightings helped reduce g customers, although most the interference effects between entering and existin to leave before boarding. others people exercise the common courtesy of allowing S taff recorded the total boardings and alightings by door , the time d uration of customer no activity and farebox use . Dwell times exclud ed when the doors remained open but or customer activity took place , such as when the vehicle was stationary at a red light during a wheelchair lift deployment. Ride - Along Dwell Time Survey While the stationary methodology captured high - ridership stops, it did not measure the Door Boarding All - ’s impacts as vehicles traversed the city and served stops with varying - ridership. As a supplement, R ide - A long Dwell the SFMTA conducted Time Surveys. Consisting of riding buses for over 20 hours, t hese obse rvations helped estimate a “sweet to minimize dwell times. These surveys spot” for distributing boardings between doors door buses at different times of the day. With covered seven routes and two - and three - Due to oor openings and closings. one surveyor per door, teams observed over 840 d implementation. - staffing constraints, the SFMTA employed this methodology only post Technology and Performance 9 Page FINANCE AND INFORMATION TECHNOLOGY

12 Speed Analysis - The SFMTA relied on APC travel time data to measure whether All Door Boarding could third of motor and electric impact overall speed including stops. Installed on about one - APC level samples annually, enough to s trolley coaches, - provide 200,000 to 500,000 trip a draw general conclusions about potential speed impacts. Using deployment plan approved by the Federal Transit Administration for National Transit Database reporting , APC equipped vehicles on different routes to ensure sufficient and - the SFMTA rotate s weighted sampling. y Fare Surve Following three pre implementation fare surveys in 2009, 2010, and 2012, the SFMTA - undertook a nother fare survey in 2014 to determine how All - Door Boarding had affected fare compliance. All surveys included observations spread across nearly every route during all times of the day, with the 2009 and 2014 comprehensive surveys having several times more samples to provide greater statistical confidence at the route level. implementation surveys, the SFMTA hired a market research firm to r - Unlike the pre ecord observations for the post implementation survey. SFMTA staff worked with the contractor - to replicate the methodology and train its employees to partner with Transit Fare Inspectors. The 2014 survey also included customer observations at the nine Muni Metro subway stations, whereas the previous studies only observed those on board light rail and widespread geographical coverage survey’s illustrates the vehicles . Figure 5 boarding location. customer volumes at each Technology and Performance 10 Page FINANCE AND INFORMATION TECHNOLOGY

13 FIGURE 5 2014 Fare Survey Observations RESULTS Door Boarding began, Two years after official All - transit operations have improved without adverse financial impacts . Table 1 highlights the principal findings: themselves between  Boarding customers are distribut ing the front and rear doors more evenly than before entry and exit. well times per d , lowering average despite Systemwide bus speeds (including stops ) modestly improved  growth in population, employment, ridership and motor vehicle registrations . fare compliance Systemwide ncreased . slightly i  Technology and Performance 11 Page FINANCE AND INFORMATION TECHNOLOGY

14 TABLE 1 Principal Findings Implementation Post - Pre Data Source - Evaluation Metrics Implementation Operational Impacts Average 3.9 s Stationary Dwell Time Survey Average 2.5 s imes Per Dwell T Std. Dev. 3.5 s 2.0 (major stops) Std. Dev. s Boarding and Alighting 1 1 : - door vehicles 2 : 2 - door vehicles Average 4.3 s Average 2.7 s s Std. Dev. 3.6 s Std. Dev. 2.1 1 1 - vehicles door : : 3 door vehicles - 3 6 s Average 1. Average 1.3 s Std. Dev. 0.9 s Std. Dev. 0.5 s Stationary Dwell Time Survey 5 - Door Boarding 5 Rear % 1 . 28. 4 % 1 1 (major stops) : 48.3% door vehicles - 2 2 door vehicles - : 21.5% 1 1 : 77.7% door vehicles - 3 3 door vehicles : 55.0% - Rear - Door Boarding N/A % Ride - Along Dwell Time Survey 51.5 3 2 - door vehicles (all stops) : 42.1% 1 - door vehicles : 61.1% 3 Bus System Speed Automatic Passenger Counter FY 2013: 8.52 mph FY 2011: 8.41 mph FY 2012: 8.48 mph Data FY 2014: 8.56 mph Farebox Usage 0.4 % 13.7 % 1 Stationary Dwell Time Survey (major stops) Financial Impacts 2 2 Fare Evasion Fare Surveys 2009: 9.5% ±0.3% 2014: 7.9% ±0.2% customers) 635 (41,239 customers) (52, 2 2010: 8.6% ±0.5% (11,939 customers) 2 2012: 8.4% ±0.6% (9,162 customers) 4 Fare Revenue m Operating Budget FY 2010 - 11: $1 64. 3 m - FY 2012 179.1 13: $ 4 (excluding cable cars) FY 2011 - 12: $171.6 m FY 2013 : $178.1 m - 14 - of - Payment - Operating Budget FY 2010 Proof 11: $5.2 m 13: $6.1 m - FY 2012 FY 2013 - FY 2011 12: $5.3 m - 14: $7.0 m Program Expenses 12: 2,375,101 Proof - of - Payment Program : 2,817,740 FY 2011 - 1 FY 201 2 - Fare Inspections 3 FY 201 3 - 1 4 : 2,801,061 Records Fare Citations Issued Proof - of - Payment Program 13: 71,028 FY 2011 - 12: 42,867 FY 2012 - FY 2013 - 14: 72,426 Records 10 - 1 1 : $927,681 FY 20 Operating Budget Fare Citation Revenue - FY 2012 13: $2,423,514 12: $1,488,615 - FY 2011 FY 2013 14: $2,556,779 - Background Statistics Population 2010: 805,235 2012: 827,420 U.S. Census Bureau 2013: 837,442 2011: 814,233 Employment Bureau of Labor Statistics 2010 Q4: 555,742 2012 Q4: 601,101 2011 Q4: 570,094 2013 Q4: 626,230 - Weekday Bus and 518,747 13: SFMTA Estimates FY 2010 - 11: 500,213 FY 2012 - FY 2011 Ridership Streetcar FY 2013 - 14: 5 26,781 12: 513,964 California Department Of 2010: 470,481 Motor Vehicle 2012: 471,298 Registrations 2011: 466,448 Motor Vehicles 2013: 485,471 1 floor bus High - floor buses and streetcars . Low - Notes: es excluded due to limited sampling. 2 Ma rgin of error at a 95% confidence level . 3 . - Low floor buses 4 - Excludes $2.2 million ($0.75 million pro - 13) in funding to offset Free Muni for Youth fare rated for FY 2012 revenue impacts, as estimated by the SF Board of Supervisors Budget and Legislative Analyst’s Office Technology and Performance 12 Page FINANCE AND INFORMATION TECHNOLOGY

15 Dwell Times The Stationary Dwell Time Survey - door boardings and showed significant shifts to rear - floor vehicles corresponding decreases in dwell times. Most observations were of high growing fleet of low SFMTA’s floor buses, which pre - but also covered some of - implementation comprised less than 10% of vehicles. Due to the small sample size of lo - floor buses at th at time and the desire to compare identical vehicle types, the w Stationary Dwell Time Survey on high - floor models. results focus ear - door boardings increased from 29 % to 54 % at nine of Muni’s busiest stops. R Correspondingly, the average dwell time per boarding and alighting decreased 3 8 % from 3.9 3 to 2. 4 5 seconds. While seemingly small, t hese incremental savings can accumulate signal and be the difference between making a green light and waiting for another traffic cycle. - door buses and streetcars showed greater reductions in dwell times per boarding Two and alighting (1.6 seconds ) than three - door artic ulated buses (0.3 seconds ) . With an - extra door providing 50% greater and high levels of pre - existing All throughput Door B oarding, articulated buses already had relatively short dwell times. door buses, Figure 6 illustrates several key points: Focusing on two - more  . A The boarding distribution through each door affects dwell times “ even ” (arbitrarily defined as 25% to 75% rear distribution is - door usage) boarding significantly faster than a n “uneven” one (less than 25% or more than 75% rear - door usage). This was a consistent finding both before and after implementation. “Even” boarding distributions resulted in p er - person dwell times around two seconds ; “uneven” boarding distributions averaged four to five seconds .  - Door Boarding shifted more customers to the rear doors, thereby Legalizing All . “ E ven” boarding distributions are now occurring reducing average dwell times frequently than before and more customers are using the rear door much more on s two - door buses (48% instead of 22%) . Correspondingly, per - person dwell times have dropped from 4.3 to 2. 7 seconds . reduced  Legalizing All - Door Boarding also increased dwell time consistency and variability implementation dwell As measured by their standard deviation, post - . . times across observations became more consistent and less variable than before le bunches and gaps and is This can help reduce vehic an important factor in making service more reliable and predictable. Technology and Performance 13 Page FINANCE AND INFORMATION TECHNOLOGY

16 FIGURE 6 Distribution of Dwell Times per Boarding and Alighting on Two - Door High - Buses and Historic Streetcars Floor Findings by Stop Type The SFMTA serves many ridership markets, ranging from first - time visitors to seasoned commuters. As shown in Figures 7 and 8 and Table 2, the policy’s impacts have varied - with the most pronounced impacts occurring where pre existing All based on stop typ e - Door Boarding was less prevalent. In particular, the greatest absolute and percentage reduction in dwell times per boarding and alighting (3. 3 seconds, or 49%) occurred at tourist - oriented stops. Despite less readily adapted to All At Door Boarding. - familiarity with riding Muni, it appears v isitors pre Financial District commuter express bus stops, the - implementation boarding process was already efficient with a relatively low dwell time of 2.4 seconds per person even with . Aft erwards, commuters also nearly evenly distributed themselves - front door entries 85% 4 %). The least through each door, decreasing average dwell times by 1.0 second (4 change came at neighborhood commercial intersections in the Mission District and Chinatown, where unofficial rear door boarding was already commonplace. - Technology and Performance 14 Page FINANCE AND INFORMATION TECHNOLOGY

17 - FIGURE 7 Percentage of Rear Door Boardings by Stop Type 8 FIGURE e Average Dwell Times by Stop Typ Technology and Performance 15 Page FINANCE AND INFORMATION TECHNOLOGY

18 TABLE 2 Pre and Post - Implementation Stationary Dwell Time Survey Results - Dwell Time - Door Rear Survey per Vehicle Boardings Stop Type Alightings Boarding Observations Boarding & Period Percentage Alighting Before 49 547 115 19.7% 3.3 s Central Business District 26 324 98 38.3% 2.4 s After Central Business District 2.4 s Before 17 314 0 13.4% Financial District Financial District After 16 298 3 50.3% 1.4 s Neighborhood Commercial 180 Before 21 280 2.2 s 47.9% Door Buses) (2 - Neighborhood Commercial 1.6 s 63.1% After 20 225 119 - (2 Door Buses) Neighborhood Commercial 1.6 s 55.0% Before 19 389 125 Door Buses) - (3 Neighborhood Commercial 1.3 s 77.7% After 22 336 157 Door Buses) - (3 63 335 6.8 s 10.1% Tourist Destinations Before 48 Tourist Destinations 61 515 95 47.0% 3.5 s After - Door Vehicles Before 135 1,476 358 21.5% 4.3 s Subtotal, 2 2 1,362 - Door Vehicles After 123 Subtotal, 315 48.3% 2.7 s Subtotal, 3 Door Vehicles - Before 19 125 55.0% 1.6 s 389 Subtotal, 3 - Door Vehicles After 22 336 157 77.7% 1.3 s Grand Total 3.9 s Before 154 1,865 483 28.5% 472 Grand Total 145 1,698 After 54.1% 2.5 s th – Market & Powell and Market & 5 Stops and Routes for each Stop Type include: Central Business District (Muni Lines F, 5, 6, 9, 9L, 21, 31, 71L); Tourist Destinations Ferry Building, Fisherman’s Wharf and Market & Drumm (Muni Lines – th ighborhood Commercial & Mission and Stockton & Jackson (Muni Lines: 8AX, 8BX, 8X, 14, 16 F, 2, 6, 21, 31); Ne – 14L, 22, 30, 33, 45, 49); Commuter – Pine & Davis and Sacramento & Davis (Muni Lines: 1, 1AX, 1BX, 30X, 31AX, 31BX, 38AX, 38BX, 41) Optimal Distribution of Customers The Ride - Along Dwell Time Survey found that dwell times over entire routes could be minimized when approximately 60 - 70% and 80 - 90% of customers entered through the rear on two door and three - door buses, respectively. - half through two doors 9 shows that a com pletely even boarding distribution (one - Figure - third through three doors) did not minimize dwell times . One reason may be that or one the front door has lower throughput than the rear door(s) . The front door accommodates imited customers who may mobility or who pay require extra time, such as those with l As indicated by the mark sizes, higher boarding volumes are occurring near the cash. optimal dwell time points, suggesting that customers are naturally distributing themselves at each door to shorten their travel times. Technology and Performance 16 Page FINANCE AND INFORMATION TECHNOLOGY

19 Dwell Times vs. Boarding Distribution by Door 9 FIGURE Trip Speeds - 2011 through FY 2013 - 2014, the average APC - measured bus system From FY 2010 (including stops) increased slightly from 8.41 to 8.56 mph, or 2%. Several factors speed limited overall spe may have ed gains despite significant time savings at a stop level:  Population – According to the U.S. Census Bureau, San Francisco’s population grew by over 32,000 (+4.0%) between April 2010 and July 2013, increasing demand on the transportation system and adding to traffic congestion.  Employment – According to the Bureau of Labor Statistics, employment within San Francisco increased by over 70,000 (+12.6%), one of the largest job gains of any city in the United States. 2011 and FY - and 2014, average weekday bus - 2013  2010 Ridership – Between FY streetcar 6 ,000 (+ 5 . 3 %). ridership grew by over 2  Motor Vehicle Registrations – According to the California Department of Motor Vehicles, vehicles registered in San Francisco increased by approximately 15,000 (+3.2%). M uni vehicles spend four - fifths of their time traveling between stops, waiting at traffic lights or being stuck in traffic . Thus, a combination of exclusive transit lanes, transit Door signal priority , parking management and other strategies that supplement Al l - Boarding can contribute to significant travel time reductions. With even modest speed - All improvements, appears to have helped keep Muni moving during a Door Boarding of increasing demand on the city’s transportation system. period Technology and Performance 17 Page FINANCE AND INFORMATION TECHNOLOGY

20 Fare Compliance implementation fare survey c ounter ed concerns that All - Door Boarding - 2014 post The Of the 52,635 customer observations, 42,539 occurred on would spike fare evasion. light rail and streetcars and were factored into the overall fare evasion rate, which buses, was weighted by weekly line ridership. The remaining 10,096 observations took place at the nine Muni Metro underground ical light rail stations. To maintain methodolog and to av oid double - counting with light rail vehicle consistency across surveys the weighted fare evasion rate these station surveys . observations, excludes TABLE 3 Comparison of 2009 and 2014 Comprehensive Fare Surveys 2009 2014 2014 2009 Customers Fare Fare Customers Fare Analysis Category Evasion Surveyed Surveyed Evasion Rate (%) Rate (%) 1 Systemwide 38,672 52,635 7.9 9.5 Transit Mode 32,648 37,201 10.5 Bus & Historic Streetcar 8.0 Light Rail 6,024 4.7 5,338 7.5 2 Muni Metro Underground Stations N/A 10,096 3.5 N/A (top 10 bus corridors and all rail Route lines) 893 4.5 638 1 California (TC) 4.4 5 Fulton & 5L Fulton Ltd (TC) 740 9.7 738 7.3 6 Parnassus & 71 Haight - Noriega (MC/TC) 1,760 9.0 1,564 9.3 8X, 8AX, 8BX Bayshore Exp (MC) 1,882 14.0 1,682 8.5 14 Mission & 14L Mission Ltd (MC/TC) 1,760 19.9 2,230 11.3 22 Fillmore (TC) 1,074 9.7 751 9.3 29 Sunset (MC) 750 9.2 1,166 9.4 30 Stockton (TC) 8.4 4.0 1,295 1,316 38 Geary & 2,739 9.5 Ltd (MC) 1,361 6.9 eary 38L G - Mission (TC) 1,258 12.2 1,299 8.5 49 Van Ness 887 Market and Wharves (HS) 12.0 1,546 6.4 F 734 5.6 456 7.9 J Church (LR) K Ingleside (LR) 870 3.8 785 6.1 L Taraval (LR) 1,023 2.4 830 5.2 M Ocean View (LR) 1,216 3.8 1,107 5.1 N Judah (LR) 1,469 2.5 1,031 8.1 T Third (LR) 666 15.2 1,129 15.1 Period Time - 9,056 Weekday AM peak (7 6.2 9 a.m.) 8,286 5.6 Weekday Midday (9 a.m. - 2 p.m.) 7,655 9.5 10,599 6.5 9.8 Weekday School (2 4 p.m.) 7,170 - 3,244 9.8 10.5 Weekday PM peak (4 - 7 p.m.) 9,249 9,987 8.9 Weekday Evening (7 2,923 14.5 10 p.m.) 4,525 11.3 - Weekend (all day) 2,619 12.3 5,898 7.2 Successful or Attempted Rear Door - 11.2 857 55.3 4,451 Entries (Buses and Streetcars) NOTES: HS = historic streetcar; LR = light rail; MC = motor coach; TC = electric trolley coach. 1 Consists of base survey data prior to the July 1, 2009, fare increase, and excludes 2,567 supplementary observations afterwards. 2 - counting To maintain methodolog ical consistency between the 2009 and 2014 surveys and to avoid double subway station observations, Muni Metro observations are excluded when calculating with light rail vehicle the weighted fare evasion rate systemwide and by time period. Technology and Performance 18 Page FINANCE AND INFORMATION TECHNOLOGY

21 - FIGURE 10 Proof - of Payment Patterns, 2014 Fare Survey As shown in Table 3, the 2014 survey found that fare evasion has declined 1.6 percentage points over five years to 7.9%. Specifically, Expanding fare enforcement to buses and historic streetcars has increased  compliance by 2.4 percentage points on these modes. Perhaps due to this , vehicles evasion appears to have increased on light rail coverage shift, fare although it remains low at underground stations. Door Boarding has encouraged more fare payers to enter through  Legalizing All - the rear. At 11.2%, rear - door fare evasion was higher than the 7.9% systemwide average, but significantly lower than the 55.3% found in 2009. illustrates the percentage and absolute number of customers observed without Figure 10 valid proof of - payment at each survey location. - Technology and Performance 19 Page FINANCE AND INFORMATION TECHNOLOGY

22 Fare Revenues Fare revenue data suggest that All Door Boarding has not impacted SFMTA’s finances - Preliminary figures for SFMTA’s FY negatively. - 2014 operating budget indicate that 2013 transit fare revenue totaled $2 06.2 million. Bus, streetcar and light rail revenue cable car cash fares account comprise approximately $ 178.1 million of this amount and d for the remainder. In the unlikely scenario that every bus, streetcar and light rail customer had a valid fare, the SFMTA might be able to ca pture about $1 7.1 million annually based on s pring 2014 fares and the methodology outlined in Table 4 . Since some customers would probably ing fare payment, it is unrealistic to expect that the SFMTA could continue to avoid recuperate all $17.1 million even with greatly expanded e nforcement resources. Reflecting the decline in the overall fare evasion rate from 9.5 to 7.9 percent, the $17.1 million estimate is also down from the $19.2 million figure from the original 2009 study. The uncaptured revenue decline has not been proportional to the decrease in the fare evasion rate, however, largely because inflation - indexed fare increases have occurred in the intervening years per SFMTA Board policy. TABLE 4 Estimated Uncaptured Fare Revenue Uncaptured Major Types of Fare Violations Revenue* evenues Uncaptured R Estimating M ethodology No Ticket, Transfer or Pass, Invalid Transfers/Fare Receipts, Walk Away 1 $14 . million % paid cash and displayed a paid pass, 83 mers without a pre Of custo - proof - of - payment, transfer/fare receipt while the remaining 17 % lacked any n invalid transfer/fare receipt, had an invalid Clipper walked showed a ® Card or . Assumption: These customers away upon seeing a Transit Fare Inspector would have paid the applicable cash fare, and therefore total cash fare evenues would increase proportionately . r Underpayment $2.8 million When watching farebox payments, the survey team observed that 6.8% of customers did not pay the appropriate fare. Assumption: Customers paid only half the applicable base fare. Misused Youth Pass $0.2 million Compared to the total number of youths with a valid Youth Pass on Clipper ® , 5% of customers surveyed had an invalid Paid Youth Pass and 5% had a Free Muni for Youth Pass that belonged to someone else. Assumption: These s would otherwise purchase a Muni customer Only Pass, resulting in an - additional $43 and $66, respectively, in revenue per month per pass. Total $17.1 million * Estimated uncaptured revenue is based on fare rates during the survey (Spring 2014) While uncaptured fare revenue estimates have declined, actual fare revenues collected 2012 2012 and FY 2013, immediately before and - - have increased. Between FY 2011 cable car fare revenues grew by $7.5 million (+4.4%). - after implementation, non During - the last four months of FY 2012 2013, the SFMTA also launched the Free Muni for Youth Program to provide students from low income households with - and moderate - complimentary transit passes. Adjusting for funding received to defray the cost of these passes, the fare revenue change would be $8.2 million (+4.8%) based on Budget and Technology and Performance 20 Page FINANCE AND INFORMATION TECHNOLOGY

23 Non Legislative Analyst’s Office estimates. cable car fare revenues have increased faster - - ash than the combination of inflation indexed fare increases and ridership changes. C adult monthly passes increased by 3.1% fares stayed the same, grew by and ridership 0.6%. CONCLUSION With a growing interest in sustainability and urban living, many metropolitan areas are looking for innovative ways to improve transit. Since most transit lines in the United States operate in mixed traffic and require front door boarding, minimizing excess dwell - times is a widespread challenge. San Francisco’s experience with systemwide All - Door Boarding can inform other cities as they explore cos t - effective strategies to speed up while preserving fare revenue. service - already Although the SFMTA had accrued some benefits under unofficial All Door operational and financial Boarding, the agency has experienced incremental once the policy became legal. Muni customers are taking less time to improvements board, buses are moving a bit faster and fare compliance continues to improve. All - Door faceted approach to make transit faster and more Boarding is just one piece of a multi - trategies such as and xclusive transit lanes, transit signal priority e reliable. Other s parking management can together make more significant reductions in transit travel times. Given that transit systems contemplating All - Door Boarding are not starting in the same plac e as the SFMTA, they may encounter additional challenges if they elect to transition to this model. As each region has unique transportation needs, the SFMTA - Door Boarding may not be appropriate everywhere but believes acknowledges that All ind it to be a worthwhile investment. others may f Technology and Performance 21 Page FINANCE AND INFORMATION TECHNOLOGY

24 APPENDIX Detailed F 2014 are Survey Results Bus and Rail Lines Fare Margin Weekday Transit Customers Evasion of Name Line Mode Surveyed Ridership Error Rate California 1 TC 25,653 638 4.4% ±1.6% MC 1,048 539 6.9% ±1.5% 1AX California A Exp California B Exp MC 1,601 616 5.7% ±1.4% 1BX 2 MC 5,425 373 3.2% ±1.7% Clement TC 4,136 373 4.0% ±1.9% 3 Jackson Fulton TC/MC 21,278 738 7.3% ±1.8% 5/5L 586 TC 7,693 Parnassus 9.4% ±2.3% 6 33,485 Bayshore Exp MC 8X/8AX/8BX 1,682 8.5% ±1.3% 9/9L MC 19,560 1,568 11.1% ±1.5% San Bruno MC 5,907 618 6.5% ±1.8% 10 Townsend Folsom - Pacific MC 5,328 12 536 5.6% ±1.8% 14/14L Mission TC/MC 44,668 2,230 11.3% ±1.3% 14X Mission Exp MC 2,727 713 5.2% ±1.4% 16X Exp MC 1,438 Noriega 526 1.7% ±0.9% 17 Parkmerced MC 1,252 237 8.9% ±3.3% th 46 18 Av MC 4,120 851 6.6% ±1.5% 19 Polk MC 8,244 635 16.1% ±2.7% 7,512 ±2.3% 7.6% 471 21 Hayes TC 22 TC 17,150 751 9.3% ±2.0% Fillmore MC 4,308 586 10.2% ±2.3% 23 Monterey Divisadero TC 11,556 24 6.9% ±1.5% 945 27 Bryant MC 6,808 5.2% ±1.9% 498 th 19 15,329 Av MC 28/28L 720 8.7% ±2.0% 29 MC 19,922 1,166 9.4% ±1.6% Sunset 1,295 30 TC 26,413 Stockton 4.0% ±1.0% 30X Marina Exp MC 2,738 508 1.2% ±0.8% 31 Balboa TC 10,138 861 9.6% ±1.9% 31AX Balboa A Exp MC 960 143 2.1% ±2.2% 31BX MC 900 192 4.7% ±2.7% Balboa B Exp TC 6,790 439 11.2% ±2.8% 33 Stanyan Eureka MC 827 160 3.1% ±2.4% 35 36 MC 1,626 370 6.2% ±2.2% Teresita 524 37 MC 2,355 Corbett 2.9% ±1.3% 38/38L Geary MC 51,653 1,361 6.9% ±1.3% 38AX MC 986 399 4.3% ±1.5% Geary A Exp 355 38BX MC 1,057 Geary B Exp 0.8% ±0.8% 39 Coit MC 565 207 1.4% ±1.3% 41 Union TC 3,395 391 2.0% ±1.3% 1,207 5.1% ±1.2% 43 Masonic MC 13,219 Technology and Performance 22 Page FINANCE AND INFORMATION TECHNOLOGY

25 Fare Margin Transit Weekday Customers Evasion of Line Mode Surveyed Rate Ridership Error Name 8.0% O’Shaughnessy 16,208 1,331 MC ±1.4% 44 Union - Stockton TC 11,489 45 2.7% ±1.0% 928 MC 12,533 592 Van Ness 11.3% ±2.5% 47 th Quintara - 24 48 St MC 8,520 835 11.5% ±2.1% 1,299 Mission TC 23,504 - 8.5% ±1.5% Van Ness 49 Excelsior MC 2,217 482 6.4% ±1.9% 52 54 MC 6,820 Felton 13.4% ±2.5% 664 56 Rutland MC 479 161 21.7% ±5.2% 66 MC 843 272 2.6% ±1.5% Quintara MC 1,655 329 67 7.9% ±2.6% Bernal Heights - Noriega MC 12,077 71/71L 978 9.2% ±1.7% Haight 76X Marin Headlands Exp MC Weekends 155 0.0% ±0.0% 57 81X MC 169 Caltrain Exp 3.5% ±3.9% 82X Levi Plaza Exp MC 710 107 7.5% ±4.6% 514 83X Mid - Market Exp MC 114 1.8% ±2.1% 88 BART Shuttle MC 455 120 5.8% ±3.6% 108 488 MC ±3.0% 16.6% Treasure Island 3,229 NX MC 1,502 394 10.4% ±2.6% Judah Exp 6.4% Market & Wharves 23,208 887 SC ±1.6% F Church LR 14,767 456 J 7.9% ±2.4% LR 16,876 Ingleside 6.1% ±1.6% K 785 28,816 Taraval LR L 830 5.2% ±1.5% M Ocean View LR 26,920 1,107 5.1% ±1.3% LR 41,439 N 1,031 8.1% ±1.6% Judah 1,129 T LR 16,876 Third 15.1% ±2.0% Grand Total All 671,596 42,539 ±0.2% 7.9% * LR = Light Rail; MC = Motor Coach; SC = Streetcar; TC = Electric Trolley Coach Cable Cars are not included in the fare survey. Margin of error is at the 95% confidence level. Weighted by Line Ridership * Light Rail Subway Stations Muni Metro Margin Weekday Fare Customers Faregate Evasion Station of Surveyed Entries Rate Error 521 Castro 2.1% ±1.2% 4,822 Church 3,155 722 5.8% ±1.5% Civic Center 6,746 977 6.8% ±1.5% Embarcadero 1,678 2.1% ±0.6% 11,297 2.7% 852 Forest Hill ±0.9% 2,388 Montgomery 8,498 1,727 1.5% ±0.5% Powell 12,200 1,613 3.0% ±0.8% Van Ness 7,085 1,325 6.0% ±1.2% 3,848 681 3.7% ±1.3% West Portal 10,096 3.5%* ±0.3% 60,038 Grand Total * Weighted by Station Ridership Technology and Performance 23 Page FINANCE AND INFORMATION TECHNOLOGY

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