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Analysis of Recent Public Transit Ridership Trends (2019)

Chapter: Chapter 5: Case Studies

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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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Suggested Citation:"Chapter 5: Case Studies." National Academies of Sciences, Engineering, and Medicine. 2019. Analysis of Recent Public Transit Ridership Trends. Washington, DC: The National Academies Press. doi: 10.17226/25635.
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47 Chapter 5: Case Studies To further explore strategies transit agencies are using along with the relationships between ridership and operations, ten case studies were chosen for further analysis. The ten case studies conducted represent a variety of conditions in terms of ridership change, other performance trends, and strategies attempted to encourage transit ridership and combat potential declines. The ten transit agencies include:  Connect Transit in Bloomington-Normal, IL  Greater Portland Transit District in Portland, ME  IndyGo in Indianapolis, IN  King County Metro in Seattle, WA  Maryland Transit Administration in Baltimore, MD  Massachusetts Bay Transportation Authority in Boston, MA  Metro Transit in Minneapolis-St. Paul, MN  Metropolitan Transit Authority of Harris County in Houston, TX  Pinellas Suncoast Transit Authority in St. Petersburg, FL  Spokane Transit Authority in Spokane, WA For each transit agency, an interview was conducted to obtain background information on ridership trends and strategies from the transit agency’s perspective. Data on unlinked passenger trips, vehicle revenue miles, vehicle speeds, and in some cases on-time performance were obtained from each transit agency and trends in each of these operating characteristics were graphed along with their relationship to transit ridership.

48 Case Study 1 – Connect Transit, Bloomington-Normal, IL Background Connect Transit operates fixed route bus service in the Bloomington-Normal, IL metro area providing around 8,600 trips per weekday. Connect Transit operates 15 fixed routes that converge on two transit centers. Illinois State University represents a sizable portion of both the region’s population and the transit agency’s ridership. The typical Connect Transit passenger is transit dependent and between 18-24 years old. Bloomington-Normal Public Transit System was established as a joint effort between the City of Bloomington and the Town of Normal in 1972. After rebranding as Connect Transit in 2012 and refocusing efforts on customer service, employee development, and technology, the fixed route bus system saw significant growth in transit ridership in 2012, 2013, and 2014. In 2015, Connect Transit received the American Public Transportation Association (APTA) Award for Outstanding Public Transportation System for transit agencies in North America providing fewer than 4 million passenger trips annually. In 2015, the transit agency switched from a flag system, where passengers could flag down a bus at any safe street corner, to a fixed system, where passengers can only be picked up and dropped off at predetermined bus stop locations and transfer centers. The Connect Transit fixed-network was comprehensively redesigned in 2016 with long and circuitous routes replaced with new route alignments on major corridors. The network redesign consisted in increasing frequency, adding Sunday service to the system, and providing customers with a real-time mobile app. Since the redesign, minor adjustments to the transit system were made, included cutting a route in 2017 and extending service hours for select routes in 2018. Key Performance Trends Key trends for bus service from 2012 to 2018 are shown in Figure 19 which displays a 12- month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), and average speed. Bus ridership since 2012 has followed a remarkable trend, peaking in 2015 at over 35% above 2012 levels, and recently settling near 15% above. This all came with almost no change in service levels and recently declining average speeds. The increasing ridership happened at the same time new technologies were rolled out under the new General Manager who joined the transit agency in 2011. A redesigned website, mobile bus tracking, a rebranding to Connect Transit, and better customer service all took place in the last several years. The increase in ridership may be partially due to a change in the method for estimating ridership, manual counts to automated passenger control counts (APC). However, new technology could also account for improvements in passenger information, which may also partially explain the ridership increase. Although the network was redesigned in 2016 to increase fixed route ridership, the number of passenger trips and average speed continued to drop until mid-2017, as seen in Figure 19. This

49 initial decrease of riders may be due to the public confusion of the new routes with reused names. The decrease in average speed may be explained by new route alignments on major corridors with congestion. After an initial adjustment period post-launch of the restructured system, fixed route ridership began to increase. An extra hour of service on four of Connect Transit’s main routes was added in late 2018. Figure 19: Connect Transit Bus Systemwide Trends  Ridership data for Figure 20 and Figure 21 was calculated as monthly average weekday boardings averaged over the fall period (September, October, November, and December) of 2013 and 2017. Both passenger counts and route frequencies were provided from the transit agency. While the route alignments and schedules changed between 2013 and 2017, their comparison provides insights on the effect of the network redesign. From 2013 to 2017, all bus routes increased frequency but did not increase in passenger boardings per trip as seen in Figure 20. Connect Transit saw a peak in ridership in 2015 and overall average weekday ridership has decreased between the end of 2013 and the end of 2018. On time performance increased overall from 2013 and 2018 after the introduction of fixed routes and restructured system as seen in Figure 21. Following the system restructure in 2016, overall on-time performance improved. This may be due to the new alignment on major corridors, which allowed buses to operate shorter routes on better-maintained streets. Dwell times were also added in 2016 to the schedule on all routes to allow room for error or delay. Future Plans to Encourage Ridership Connect Transit was recently awarded a grant for battery electric replacement buses. Connect Transit hopes the new-technology buses will allow improvements in on-time performance while decreasing operating expenses. There is additional discussion of improving bus stop infrastructure, increasing fares, and the discontinuation of low-performing routes.

50 Figure 20: Connect Transit Frequency and Ridership and Trends in 2013 and 2018  Figure 21: Connect Transit On‐time Performance and Ridership Trends in 2013 and 2018 

51 Case Study 2 – Greater Portland METRO, Portland, ME Background The Greater Portland Transit District (Greater Portland METRO) is Maine’s largest public transit agency and provides more than 1.8 million boardings per year. METRO operates 11 fixed route bus service in southern Maine including Brunswick, Falmouth, Freeport, Gorham, Portland, South Portland, Westbrook, and Yarmouth. In the past half-decade, METRO bus ridership has increased after implementing high school student transit passes and a commuter service. Founded in 1966, METRO went through several decades of declines in bus service area and ridership. In 2004, the transit agency began expanding again, and improvements have come quickly since then. After a 2013 bus priority study of recommended improvements to a street to increase speed of buses, two signals were modified to accommodate transit and an in-line bus stop was added by 2017. In 2015, free rides for high school students began, and Sunday service was increased. An express bus service, METRO Breez, was added in 2016 and expanded in 2017. A university program with University of Southern Maine (USM), started providing free transit for students, staff, and faculty in 2018. The Husky Line, a distinctively-branded bus route featuring more frequent connections for students and professionals, was introduced in 2018 as well. Key Performance Trends Key trends for bus service from 2012 to 2018 are shown in Figure 22 which displays a 12- month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), and average speed. Bus ridership since mid-2015 shows a remarkable trend of nearly 30% growth. A sizeable portion of this ridership may be attributed to incoming high schoolers following the elimination of yellow bus service in 2015, indicated on Figure 22. Fixed route ridership continues to grow in 2016 to 2018, and service levels and average speed have steadily grown as well. METRO Breez express bus service began operating in August 2016 connecting the downtowns of Portland, Freeport, and in mid-2017 Brunswick.

52 Figure 22: METRO Bus Systemwide Trends  Ridership data for Figure 23 was calculated on each route as average monthly ridership over a year from 2013 to 2018. Historic route frequencies were not available. METRO bus ridership has remained steady or increased on all routes. Unfortunately, on-time performance (OTP) data before February 2018 was not available. METRO defines a bus to be “on-time” if it is operating less than six minutes late at a timepoint. On-time data is calculated and tracked through an automatic vehicle location (AVL) system. Available on-time performance data, February 2018 to February 2019, is displayed in Figure 24. Low OTP on express bus may be due the longer route. Figure 23: METRO Bus Ridership Trends by Route 

53 Figure 24: METRO Bus On‐time Performance Trends by Route  Future Plans to Encourage Ridership Looking towards the future, transit officials of greater Portland have begun a study of the region’s bus, rail and ferry services to guide transportation planning for the next three decades. METRO will deploy a new fare structure and payment system in 2019 to modernize the system. Although mobile app and plastic card technology will be introduced, a cash box will remain. A fare increase has been proposed, from $1.50 to $2.00, and the current reduced fare for riders older than 65 will extend to riders between 6 and 18. METRO is planning to add zero- emissions vehicles to its fleet in 2020. The city of Portland is also undergoing a series of progressive enhancements, such as changes to zoning code that allows developers to pay a fee in lieu of meeting minimum parking requirements.

54 Case Study 3 – IndyGo, Indianapolis, IN Background The Indianapolis Public Transportation Corporation, branded as IndyGo, is the largest public transportation operator in Indiana. IndyGo provides and operates bus and paratransit services around the Indianapolis region with 31 fixed bus routes providing nearly 10 million passenger trips a year. IndyGo is improving resources and operations over the next five years to expand service frequency and hours of operation for its fixed route local network. The transit agency is also constructing three new rapid transit lines, and changing the orientation of their network from a hub-and-spoke network to a grid system. Fixed route transit ridership generally declined since the public agency took over operations in 1975. IndyGo has recently undertaken a series of active steps to reverse the trend. Free circulator routes and university-focused routes became popular in the mid-2000s with transit ridership peaking in 2003 at more than 10.9 million unlinked annual passenger trips. These routes fell out of use and were discontinued in 2009 with system transit ridership falling to 8 million annual riders. On-board surveys conducted by IndyGo in 2009 and 2016 indicate that the typical rider profile, a low-income adult traveling between home and work, has not changed significantly over the years. A similar distribution of activities is seen between 2016 and 2009 responses, but there are slightly fewer passenger activities per vehicle trip in 2016. Today, the typical IndyGo passenger is transit dependent and frequently uses services to a wide variety of destinations. Key Performance Trends Key performance trends of IndyGo from 2012 to 2018 are shown in Figure 25 which displays a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), and average speed. The system saw a leap in transit ridership between 2012 and 2015, followed by steady ridership declines despite a new downtown transit center opening in 2016. Improved frequency, extended hours, and additional stop amenities were implemented on existing fixed routes in mid-2013. Fixed route-level frequency has not dramatically changed since mid-2013, and route-level transit ridership has decreased from late 2013 to late 2017, as seen in Figure 26. From 2013 to 2017, routes with typically high ridership lost the most ridership proportionally. Transit ridership data for Figure 26 and Figure 27 is from monthly farebox data averaged over the period and stop and frequency data is from the transit agency’s General Transit Feed Specification (GTFS).

55 Figure 25: IndyGo Bus Systemwide Trends from 2012 to 2018 Figure 26: IndyGo Frequency and Ridership Trends in 2013 and 2017 

56 Figure 27: IndyGo On‐time Performance and Ridership Trends in 2013 and 2017  IndyGo has defined on-time performance as one minute early to 5 minutes late from scheduled arrival since 2009. IndyGo measures on-time performance with on-board Automatic Vehicle Location systems and is in the process of transitioning to a new platform. IndyGo tracks every Professional Coach Operator’s on-time performance each month and frequently recognizes drivers who meet or exceeds the goal of a 90% on-time monthly average. Although the average speed has dropped nearly 10% since 2012, the on-time performance (OTP) for each route has improved on all routes between 2013 and 2017 as seen in Figure 27. Improving OTP during this period has not resulted in ridership increase. OTP data for the winter periods in Figure 27 is calculated by averaging IndyGo’s self-reported data averaged over the months of November, December, and January. Winter storms in 2013 may partially account for low on-time performance. However, the long term trend of improved reliability is shown in Figure 28. Figure 28: IndyGo Systemwide On‐Time Performance 

57 Future Plans to Encourage Ridership To prepare for upcoming capital improvements, the strategic planning division at IndyGo has performed exploratory analysis of ridership trends. Changes in IndyGo ridership has generally mirrored national changes with a slight lag. At the local level, the IndyGo team has examined geospatial transit ridership trends as seen in Figure 29. While examining area stop-level boardings, they found a decrease of boardings on specific streets which were affected by street closures and resulting delay. Figure 29: IndyGo Area Year over Year Ridership Gains (Losses)  Past efforts to improve on-time performance and frequency have not resulted in ridership improvements. Looking to the future, IndyGo is hoping to combat decreasing ridership by:  Adding BRT lines,  Utilizing geospatial analysis tools,  Updating rolling stock,  Converting one-way streets to two-ways for more accessibility, and  Improving transit shelters downtown. Three bus rapid transit (BRT) lines will replace some of IndyGo’s most popular routes and include improved station infrastructure, dedicated lanes, transit-signal priority, level boarding, and off-board fare collection infrastructure starting in 2019, 2021, and 2022. Downtown transit shelters will be converted to “Super Stops” which include near-level boarding, real-time arrival information, and upgraded lighting and covered seating.

58 Case Study 4 – King County Metro, Seattle, WA Background King County Metro is the primary operator of bus service, vanpools, paratransit services, and community shuttles in the Seattle region. The transit agency also operates two streetcar lines, Seattle’s light rail, and commuter rail services. As the eighth-largest bus agency in the US, King County Metro operates 237 fixed route bus services and provides over 120 million passenger trips each year. Seattle has recently been featured in the press for its dramatic shift from driving to transit. Light rail openings have boosted these effects, but King County Metro has also managed to continually increase bus ridership over the past several years. Founded in 1973, King County Metro has played an increasingly important role in reducing congestion, protecting the environment, and getting people where they need to go in the Seattle area. King County Metro operated in the downtown Seattle fare-free zone for almost 40 years until the ride free area was eliminated in 2012. A network of high-frequency limited-stop bus routes, known as RapidRide, was introduced in 2010 and expanded in 2011, 2012, and 2014. RapidRide operates on six corridors and accounted for approximately 17% of bus ridership in 2017. After briefly reducing service in 2014, fixed route bus service has restructured and expanded fixed route bus hours and frequency service in 2015, 2016, 2017, and 2018. Over the past three years, King County Metro has significantly increased ridership, launched a reduced-fare program for lower income passengers, improved passenger and operator safety, and transitioned towards zero- emission bus fleets. “Transit GO Ticket” mobile app was launched at the end 2016 and allows riders to buy and redeem transit tickets for King County Metro buses, King County Water Taxi, Seattle Streetcar, Sound Transit’s Link light rail, and Sounder trains, on their mobile devices. Future large technology projects include bus lanes, signal priority, and re-timing, often on a corridor level, to help improve bus route performance. King County Metro’s also implements constant small spot improvements like adding parking restrictions to help buses access stops. Key Performance Trends Key performance trends for fixed route bus and streetcar service are shown in Figure 30 and Figure 31 which display a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), average speed, and on-time performance (OTP). As seen in Figure 30, despite a consistent decrease in average speed, fixed route bus ridership has followed an upward trend since 2012, and has remained roughly constant since mid- 2016. The decrease in bus average speed may be due to an increase in traffic within Seattle causing bus average speed to gradually slow. Increased ridership may also explain a portion of the decrease in average speed; increased ridership is associated with higher dwell times. King County Metro officials indicated during interviews that service frequency was increased in an attempt to address

59 this passenger crowding. A decrease in average fixed route bus speed may explain decreased on- time performance on certain routes as seen in Figure 33. Streetcar ridership trends, placed on a different scale due to dramatic increases following the opening of the First Hill Line, is seen in Figure 31. The First Hill Line nearly tripled the system’s length in 2016. Figure 30: King County Bus Systemwide Trends from 2012 to 2018  Figure 31: King County Streetcar Systemwide Trends from 2012 to 2018  Fixed route bus ridership data for Figure 32 and Figure 33 is from adjusted average weekday automated passenger counter (APC) data averaged monthly over the fall period (September, October, November, December, January, February, and March). The fall 2015 service period extends from September 2015 to March 2016 and the fall 2017 service period extends from September 2017 to March 2018. Frequency data is provided from the transit agency. Express bus service and “One-Way Peak-Only” routes are not displayed in Figure 32 and Figure 33. Service frequencies have generally increased between 2015 and 2017 but ridership trends have not increased on every route.

60 Figure 32: King County Bus Frequency and Ridership Trends in 2015 and 2017  King County defines on-time performance as an arrival time between 1.5 minutes ahead of to 5.5 minutes behind the posted schedule. On-time performance metric for each route is calculated as the number of on-time arrivals divided by the total number of arrivals at time stops. The average weekday on-time performance metric during the fall service period is displayed per route in Figure 33. Figure 33: King County Bus On‐time Performance and Ridership Trends in 2015 and 2017 

61 Future Plans to Encourage Ridership King County Metro continues to monitor ridership and system performance, and analyze crowding and reliability to encourage ridership. King County Metro has a large budget each year to address crowding, reliability and service expansion needs. Recent and future key projects include the following:  Third Avenue is largely considered the key transit spine in Seattle. Beneath it lies the transit tunnel, which serves light rail and bus vehicles in dedicated lanes. On the avenue itself, transit priority has been added for additional downtown capacity, and recent improvements include restricting left turns and extending transit priority hours, both taking place throughout 2018.  State Highway 99 is a downtown freeway in Seattle, which the group mentions receiving transit upgrades around 2016. The highway is also the focus of a major construction project, and due to anticipated traffic impacts, King County Metro has provided additional service along parallel routes to provide alternative transportation options. These projects are both ongoing, and therefore do not show up in the figures. Additionally, as planners mentioned, their goal is primarily to make incremental improvements along small segments of routes across several years.  Four new RapidRoute lines will be added by 2024 to create a grid of frequent bus lines connecting the major population centers in King County. There are additional plans to add seven new RapidRoute lines between 2025 and 2040.  After the successful test of three battery-electric buses and an in-depth feasibility analysis, King County Metro will purchase only zero-emission buses starting in 2020.

62 Case Study 5 – Maryland Transit Administration, Baltimore, MD Background The Maryland Transit Administration (MTA) provides bus, light rail, heavy rail, and commuter rail service in the Baltimore, MD region. Commuter trains also serve the Washington, DC region. MTA operates 80 fixed route bus lines, three light rail lines, three commuter rail lines, and one heavy rail line, providing around 300,000 trips per weekday. The MTA took over bus operations from the private Baltimore Transit Company in 1970. The fixed route bus network prior to BaltimoreLink had many routes that served outdated job locations and were too long to manage reliably; buses that served downtown Baltimore frequently compounded congestion. In June 2017, the fixed route bus network was redesigned. The transit agency spread out the routes within the downtown core and created a grid of high-frequency routes with the goal to be a more efficient and reliable bus network. BaltimoreLink is a complete overhaul and rebranding of the system, reworked to provide BRT-ready color-coded lines with 24-hour service and high frequencies radiating from the city center. Additionally, connecting local buses were planned to form rings around the city to bridge gaps in service, and peak-period express buses would create fast links to downtown. In the future, MTA is pursuing the addition of a new rail line and a new northbound corridor with bus rapid transit (BRT) treatments. The Metro Subway heavy rail line opened in 1983, serving northwest suburbs and downtown Baltimore. The commuter rail, known as Maryland Area Regional Commuter (MARC), began operation in 1984 between Baltimore and Washington DC. An unconnected light rail line opened in 1992, serving north suburbs, downtown, and the Baltimore airport. Most of MTA’s light rail operates on a dedicated right-of-way and as of 2007, the mixed traffic downtown portion of the route operates with a transit signal priority system. Key Performance Trends Key performance trends for fixed route bus, light rail, and streetcar service are shown in Figure 34, Figure 35, and Figure 36 which display a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), average speed, and on-time performance (OTP). MTA’s fixed route bus ridership trend grew from 2013 to 2015 as seen in Figure 34. However, ridership has begun to plummet, falling nearly 15% from its peak in 2015. VRM, average speed, and OTP have all remained steady or improved over the same period for both bus and rail modes. Unfortunately, OTP data is available only on a fiscal year basis, and only reliably until 2016. Rail ridership followed a similar downward trend following 2015 as seen in Figure 35. Commuter rail, MARC, ridership has increased from 2012 to 2014 and since remained fairly constant as seen in Figure 36.

63 Figure 34: MTA Bus Systemwide Trends from 2012 to 2018  Figure 35: MTA Light Rail and Heavy Rail Systemwide Trends from 2012 to 2018  Figure 36: MTA Commuter Rail Systemwide Trends from 2012 to 2018  Fixed route bus ridership data for Figure 37 is from adjusted average weekday automated passenger counter (APC) data averaged monthly over the fall period (Sept to Dec). Frequency data

64 is provided from GTFS (General Transit Feed Specification) archives. Because of the network redesign and complete overhaul of the fixed bus system, 2014 and 2017 data are not connected in the figure. It is not possible to relate 2014 routes to 2017 routes due to the substantial changes in the network. The new BaltimoreLink network includes new route alignments, frequencies, and spans on most routes. Route level OTP data is not available because of a recent shift from using Automatic Vehicle Location (AVL) to an Automated Passenger Counter (APC) system. MTA’s fixed bus routes have seen a decrease in passenger boardings per trip as seen in Figure 37. Service frequencies have generally increased between 2014 and 2017 but ridership trends have not increased on every route. Figure 37: MTA Frequency and Ridership Trends in 2014 and 2017  Future Plans to Encourage Ridership Although MTA’s fixed bus ridership did not increase after the launch of BaltimoreLink, the network redesign process has left MTA in a better position for future transit improvements:  The Purple Line will be a 16-mile light rail line in suburban Washington, DC that will extend from Bethesda, MD to New Carrollton, MD. It will provide a direct connection to the Metrorail Red, Green and Orange Lines, as well as MARC Train, Amtrak and local bus services. The line will mainly operate in dedicated lanes with twenty-one planned stations. Purple Line service is anticipated to begin in 2022.  MTA is in the process of designing dedicated bus lanes, transit signal priority, Light RailLink and Metro SubwayLink stations enhancements, bus stop improvements, streetscaping, and roadway repaving on a five-mile stretch of North Avenue in Baltimore with completion by the end of 2021.

65 Case Study 6 – Massachusetts Bay Transportation Authority, Boston, MA Background The Massachusetts Bay Transportation Authority (MBTA) operates bus, light rail, heavy rail, and commuter rail in the Boston metro area. The MBTA operates some of the oldest rail lines in the country, including the first subway in the U.S. The MBTA system revolves around three heavy rail lines and one branched light rail main line that meet in downtown Boston. There are 177 bus routes, five bus rapid transit (BRT) routes, and thirteen commuter rail routes filling out the rest of the system. A history of strong transit ridership in the Boston metro area is the result of a connected and comprehensive system. To address existing service issues including unreliable and slow service and overcrowding, MBTA is working on modernizing their fixed route bus system with the Better Bus Project. The MBTA was formed in 1964 as a replacement for Metropolitan Transit Authority. Cuts in service and track mileage occurred in the latter half of the 20th century, as routes lost ridership and were abandoned. The Silver Line BRT was opened in 2002, followed by a series of extensions and expansions of that system until the present day. Recent projects to improve fixed route bus ridership primarily focus on speeding up buses on select routes. In a partnership between the city and the MBTA, a temporary bus lane was created in the Roslindale neighborhood along Washington St., one of the city’s busiest routes, in May 2018. The temporary lane was originally set with orange cones blocking off a single inbound lane to cars between 5-9 AM on weekdays, allowing only buses and bikes to travel in the lane. The results were a decrease in travel time by 20 to 25% during rush periods. In response to overwhelming support from bike and transit riders, the city made the bus lane permanent after the end of the four-week implementation period. Key Performance Trends Key performance trends for fixed route bus, heavy rail and light rail, and commuter rail are shown in Figure 38, Figure 39, and Figure 40 which display a 12-month rolling average of unlinked passenger trips (UPT), vehicle revenue miles (VRM), and average speed normalized to January 2012. Prior to 2014, passenger trip counts were collected and processed from farebox data. Automated passenger counters (APC) were implemented in most buses after 2014 but possible counting software errors made ridership data unreliable in 2015. The MBTA reports highly detailed OTP data, aggregated by individual day and mode. Daily OTP data became public in 2016. Bus OTP data only goes back to 2015, and rail OTP data only became available in March 2016, and it is therefore excluded from the figures. Bus data includes the Silver Line BRT. Trends in fixed bus ridership include increased bus ridership in mid-2015 followed by steady declines as seen in Figure 38. The increases may be due to inconsistencies in passenger trip reporting; starting in 2014, MBTA switched from fare box data to APC data for ridership data. An increase in bus ridership may also be due to a steady increase in bus use as more people are moving

66 to bus accessible areas. MBTA fixed route buses did not experience the national trend of ridership declines until about 2015 possibly a benefit of a larger, more robust system. VRM and speed remained somewhat constant over the period for both bus and rail, indicating that any route-level bus lane or reliability pilots may be holding off general declines in system-wide ridership seen with other transit agencies. Heavy rail and light rail ridership has remained fairly constant from 2012 to 2018 as seen in Figure 39. The temporary closing of Government Center Station in March 2014 to Jun 2016 may explain a drop in light rail ridership. Commuter rail ridership has decreased since 2015 despite the opening of two new stations, as seen in Figure 40. MBTA believes the drop in commuter rail ridership is due to service interruptions in Winter of 2015. Figure 38: MBTA Bus Systemwide Trends  Figure 39: MBTA Heavy Rail and Light Rail Systemwide Trends 

67 Figure 40: MBTA Commuter Rail Systemwide Trends  Fixed route bus ridership data for Figure 41 and Figure 42 is weekday automated passenger counter (APC) data averaged monthly over the fall period (September, October, November, and December) provided by the transit agency. Frequency data were obtained from archived GTFS (General Transit Feed Specification). MBTA defined 15 key bus routes with high ridership, service frequency, and span of service hours. These key bus routes are displayed in Figure 41 and Figure 42. Key routes with increases in service frequencies between 2014 and 2017 did not see increases in ridership as seen in Figure 41. Figure 41: MBTA Bus Frequency and Ridership Trends in 2014 and 2017 

68 MBTA defines on-time performance for frequent bus service as a departure between 0 minutes before and 3 minutes after its scheduled departure. Infrequent bus service is defined as on-time if it arrives 1 minute ahead to 6 minutes behind the posted schedule. The on-time performance metric for each route is calculated as a percentage of the number of on-time arrivals divided by the total number of arrivals at time stops. The on-time performance metric averages weekday peak and off- peak service during the fall period is displayed per route in Figure 42. On-time performance has increased on all fixed bus key routes. Figure 42: On‐time Performance and Ridership Trends in 2014 and 2017  Regarding impacts from the bus lanes, in MBTA’s own analysis, the Washington Street AM peak bus lane in Roslindale neighborhood has seen an increase of 4% in boardings along the corridor comparing Fall 2017-18 to Fall 2018-19. However, this analysis does not address that some riders may be coming from other routes rather than being new to MBTA service and some may be due to growth in the neighborhood population rather than the bus lane specifically. MBTA continues to conduct analysis of their ridership impacts from these projects and across their system. Future Plans to Encourage Ridership MBTA continues to monitor ridership and system performance to encourage transit ridership. Utilizing metrics and analysis, MBTA is planning a number of projects including station

69 renovations, modernizing fare collection systems, and upgrading services across all modes. Current and future projects include the following:  The Better Bus Project will improve MBTA bus service by reinventing the bus network to reflect changing demographics, and replacing the fare collection system. Improvements will be completed with a continuous change focus which includes the implementation of pilot projects and the continuing practice of making regular, quarterly updates to scheduled service to better align schedules with rider demand. After the 2018 analysis period, the program has proposed consolidating duplicate routes, improving the space available at bus stops, and eliminating obsolete variants of some bus routes in 2019.  MBTA plans to replace subway fleets and upgrade tracks, signals, and switches. New subway cars will be added over the next five years to improve frequency of trains along the Orange and Red by 2022.  Green Line Extension (GLX) will extend the northern end of the Green Line light rail system by 2021 with seven new T stations.

70 Case Study 7 – Metro Transit, Minneapolis, MN Background Metro Transit operates bus, light rail, and commuter rail services in the Minneapolis-St. Paul metro area. As the largest transit operator in Minnesota, the transit agency provides over 250,000 daily riders and operates 127 fixed bus routes, two light rail lines, two bus rapid transit lines, and one commuter rail line. Metro Transit recently opened a bus rapid transit (BRT) line, the Red Line, in 2013, a light rail line, the Green Line, in 2014 and a rapid bus line, the A Line, in 2016. Looking towards the future, Metro transit will continue to constructing a number of rapid bus projects to improve mobility. Founded in 1967, Metro Transit originally provided bus service to the Minneapolis-St. Paul metro area. The growing Twin Cities region began studying light rail in 1972, but a line would not be implemented until 2004 with the opening of the Metro Blue Line. In 2009, a commuter rail line opened to the north suburbs. A BRT service began in 2013, and 2014 saw the opening of Metro’s current busiest light rail line, the Metro Green Line. In preparation for the opening of the Metro Green Line in June 2014, surrounding bus routes were routed and timed to facilitate bus and rail transfers. The process took around two years to plan and implement. In addition, a new rapid bus service with transit signal priority and near level boarding, the A Line, was planned and opened in 2016 with a direct connection to the Green Line. Key Performance Trends Key performance trends for fixed route bus, light rail, and commuter rail service are shown in Figure 43, Figure 44, and Figure 45 which display a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), average speed, and on-time performance (OTP). Since, Metro indicates OTP only in annual reports, OTP numbers represent an entire year of service. As seen in Figure 43, fixed route bus service riders has decreased despite the addition of the rapid A Line. Bus service has risen system-wide, average speed has been relatively constant, and on time performance has decreased. Light rail service has increased dramatically between 2012 and 2018. Figure 44 has a different scale than the others to show large passenger increases after the Green Line opening. Light rail average speed and OTP have remained generally constant, though the Green Line opening has brought both down for rail service slightly. Light rail service increases were followed closely by ridership increases as seen in Figure 44. After the opening of a new commuter rail station in 2012, commuter rail service has stayed relatively constant over the past five years as seen in Figure 45. Ridership trends associated with the recent fare increase in November 2018 have not been examined.

71 Figure 43: Metro Transit Bus Systemwide Trends from 2012 to 2018  Figure 44: Metro Transit Light Rail Systemwide Trends from 2012 to 2018  Figure 45: Metro Transit Commuter Rail Systemwide Trends from 2012 to 2018 

72 Interviews with planners at Metro Transit provided additional insight into some strategies being undertaken to combat ridership decline. As seen in Figure 43 and Figure 44, bus ridership decreases correspond to rail ridership increases, as corridors previously served by buses were phased out and replaced with rail service. Metro Transit also observed bus ridership continued to drop after rail service was established and stable. In June 2016, the introduction of a new rapid bus line immediately boosted corridor ridership by 30% simply by speeding up bus. Fixed route bus ridership data for Figure 46 is from adjusted average weekday automated passenger counter (APC) data averaged monthly over the 2012 and 2015 fall period (Sept to Nov). Frequency data is provided from the transit agency. Express bus service routes are not displayed in Figure 46. Service frequencies have generally increased between 2015 and 2012 but ridership trends have not increased on every route. Figure 46: Metro Bus Frequency and Ridership Trends in 2012 and 2017  Future Plans to Encourage Ridership Metro Transit continues to invest in transit projects and technology to encourage ridership. In early 2019, Metro Transit implemented NexTrip real-time bus departure information. Construction of two BRT projects, the C Line and METRO Orange Line, are currently underway and four additional BRT lines are in the planning process.

73 Case Study 8 – Metropolitan Transit Authority of Harris County, Houston, TX Background The Metropolitan Transit Authority of Harris County (known as METRO) runs bus, commuter bus, and light rail service in the Houston metropolitan area. METRO is the Houston region’s largest public transit provider operating 83 local bus routes, 31 commuter bus routes, 3 light rail lines, and 1 community connector to almost 85 million passenger trips per year. METRO has an expansive fixed transit bus system and the most transit ridership in Texas. After a large bus system redesign and addition of two light rail lines in 2015, overall transit system ridership grown about 0.8 percent from 2016 to 2017. Houston METRO was founded in 1979 with a one-cent sales tax to replace a smaller system, HouTran. The transit agency expanded fixed route bus service with park and ride, and high occupancy vehicle (HOV) lanes, to become one of the largest all-bus fleet in the United States in the 1990s. The transit agency’s first light rail line opened in 2004, ending a 14-year period during which Houston was the largest city in the country without a rail system. The most recent rail extension occurred in 2015 although METRO remains primarily a bus system. In August 2015, METRO redesigned its bus network, increasing the number of high- frequency bus routes, while reducing lower-frequency routes. The system was redesigned for the first time since the 1980s. Houston’s sprawling nature made downtown-oriented routes only useful for some trips while high-frequency gridded routes allow for faster travel, even if it requires a transfer. The transit agency’s goal was to simplify bus routes and improve access to frequent service, while still maintaining coverage service in low density areas. As part of the redesign, METRO set a goal for METRO’s system network of 80% high frequency routes and 20% coverage routes. The plan included upgrading bus stop signage and route maps with clearer information and adding trip planning apps and text-in next bus information. “Q Mobile Ticketing”, a smartphone app with the ability to purchase, store, and validate transit passes, was also introduced in August 2015. During the entire launch event, the call center doubled in size and buses with free fares roamed to pick up unknowing would-be passengers. A key aspect of the redesign was increased weekend service, with nearly all routes running the same baseline service all seven days. Reliability was a heavy motivator behind the redesign but no study has been completed on on-time performance since the implementation. Key Performance Trends Key performance trends of Houston METRO bus and light rail from 2012 to 2018 are shown in Figure 47 and Figure 48, which display a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), on-time performance (OTP), and average speed. Houston METRO fixed route bus ridership has remained unchanged since a system-wide overnight redesign, the opening of which is indicated on Figure 47. Steady increases

74 in transit service levels following the redesign appear to have little effect on ridership. Additionally, decline in average speed is most likely a product of routes being transitioned to serve denser, more congested areas of the city. Rail ridership trends are overwhelmed by the openings of two light rail lines in 2015, indicated on Figure 48 with an expanded scale to show the dramatic effects of rail openings. These new lines have steadied out at nearly 300% more service than was provided in 2012, however ridership sits only 70% above the 2012 level. Figure 47: Houston METRO Bus Systemwide Trends from 2012 to 2018  Figure 48: Houston METRO Light Rail Systemwide Trends from 2012 to 2018  While the route alignments and schedules changed between 2013 and 2017, their comparison provides insights on the effect of the network redesign as seen in Figure 49. Only a few of the routes remained similar enough to be able to relate 2013 and 2017 route data with an arrow in the figure. Ridership is calculated as average weekday boardings during the fall period in September, October, November, December, January, and February of 2013 and 2017. Both passenger counts

75 and route frequencies were provided from the transit agency. From 2013 to 2017, bus routes with increased frequency did not increase in passenger boardings per trip. Figure 49: Houston Metro Frequency and Ridership Trends in 2013 and 2017  On-time performance (OTP) transit data was not available for analysis. METRO defines fixed route bus on-time performance as leaving within the five-minute window after the scheduled departure time. OTP data is calculated based on automatic vehicle location (AVL) software. Future Plans to Encourage Ridership As Houston’s population grows, Houston METRO plans meet the region’s transportation needs by expanding its transit network. In January 2017, METRO began developing a new plan, METRONext, for transit services in the Houston/Harris County region with a focus on providing more transportation choices to more people. The goals of METRONext are to improve mobility, enhance connectivity, support vibrant communities, and ensure a return on investment. METRONext will develop a Regional Transit Plan, the Vision Plan, and a Moving Forward Plan. The Vision Plan will identify major capital investments and other improvements needed for METRO to meet the mobility challenges of the next 20 years. The Moving Forward Plan is the first step in implementation and includes major investments such as increased regional express service, extended light rail lines, a new bus rapid transit system and many improvements to the existing bus network including new Park & Rides, Community Connectors, an increase in bus service, and enhanced bus stops to address Universal Accessibility. Future bus rapid transit systems include the Uptown BRT project with frequent transit service from Westpark to the Northwest Transit Center in 2020, and the connecting Inner-Katy BRT project to downtown.

76 Case Study 9 – Pinellas Suncoast Transit Authority (PSTA), Pinellas County, FL Background The Pinellas Suncoast Transit Authority (PSTA) is the operator of bus, commuter bus, and demand response services in the St. Petersburg area. PSTA now operates 34 fixed routes providing 12.4 million passengers trips a year. PSTA was one of the first operator to provide subsidies to TNCs for connecting service to select bus stops in 2016 with their Direct Connect Program. After implementing all phases of Direct Connect in 2018, PSTA is looking to evaluate every bus route in the system, redesign their fixed route system, and implement an express bus rapid transit corridor. Formed in 1984 in the merger of two area transit agencies, the PSTA operates in the greater Tampa-St. Petersburg area. While PSTA serves St. Petersburg and some surrounding areas, a separate transit agency called Hillsborough Area Regional Transit (HART) serves Tampa and points east despite the downtown areas of Tampa and St. Petersburg being no more than 15 miles apart. The two systems began honoring each other’s fares and allowing free transfers in 2004. The transit agency recently made headlines as the first operator to provide subsidies to TNCs for connecting service to select bus stops. This partnership, which began in 2016, covers the first $5 of an Uber ride to designated bus stops, expanding their service area outside of walking distance. Lyft was added soon after, and in 2018, the number of designated stops doubled to 24. This program, called Direct Connect, was the first to integrate TNCs into a local bus system. The program was implemented in three phases from early 2016 to early 2018 with increasing operational coverage across the greater Tampa-St. Petersburg area. Key Performance Trends Key trends for bus service from 2012 to 2018 are shown in Figure 50 which displays a 12- month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), and average speed. Phases 1 and 2 of the TNC partnership start date is indicated on the figures. Phase 3 was fully implemented in April 2018. Bus ridership dropped throughout 2016 and 2017, while service, speed, and on-time performance remained roughly the same. Demand response ridership, which PSTA uses to categorize these TNC trips, is up nearly 10% since late 2016. In addition, the trend of speed dropping rapidly while VRM increases at a similar rate seems to indicate quite a large increase in Vehicle Revenue Hours. This likely corresponds to an increase in the number of “demand response” vehicles on the road at any given time. It appears that while the pilot has grown demand response ridership, buses are not seeing positive results of the pilot. This is perhaps due to the phenomenon of a preference for a one-seat ride. In other words, once passengers are already in the TNC vehicle, they would prefer to take it all the way to their destination than transfer to a bus along the way.

77 Figure 50: PSTA Bus Systemwide Trends from 2012 to 2018  While focusing on implementing the Direct Connect Program, frequency of PSTA fixed- routes has not dramatically shifted between 2015 and 2018 as seen in Figure 51, which shows fixed-route ridership and frequencies before and after Direct Connect’s full implementation. Ridership data for Figure 51 and Figure 52 is from average daily automated passenger counter (APC) data averaged monthly over the fall period (October, November, December, February) and frequency data is provided from the transit agency. Average daily ridership has decreased on all but four routes since fall 2015. Figure 51: PSTA Frequency and Ridership Trends in 2015 and 2018 

78 Figure 52: PSTA On‐time Performance and Ridership Trends in 2015 and 2018  PSTA defines on-time performance as 0 minutes early to 4.59 minutes late. This definition was modeled after the American Bus Benchmarking Group (ABBG) standard. On-time performance is collected using HASTUS transit scheduling software and recorded as monthly average on-time performance as seen in Figure 52. On-time performance increased on every bus route between fall 2015 and 2018 but this trend was not associated with an increase in ridership. Future Plans to Encourage Ridership PSTA is working towards increasing transit ridership, making transit more competitive with driving, and building financial stability. Current projects towards their goal of “safely connecting people and places” include:  Circulator Study in Downtown St. Petersburg,  Bus Rapid Transit,  Advantage Pinellas Transit Planning Effort, and  New mobile ticketing app and smartcard system. PSTA is currently conducting an analysis of transit circulation within downtown St. Petersburg to identify options for a modified or new network of circulator services. Express Bus Rapid Transit (BRT) service will be piloted in St. Petersburg’s Central Avenue corridor from downtown St. Petersburg to the Gulf beaches and open in 2021. Advantage Pinellas is a planning effort to evaluate every bus route in the system. On-board rider surveys and public outreach will result in recommendations for route and mobility service changes. PSTA and HART are currently beta testing “Flamingo Fares”, a regional mobile ticketing app and smartcard system.

79 Case Study 10 – Spokane Transit Authority, Spokane, WA Background The Spokane Transit Authority (STA) is the sole provider of bus and demand-response service in Spokane County, WA. Public takeover of Spokane’s bus routes took place in 1968 after years of declining revenues. A public transportation benefit area was established in 1980 to devote sales taxes to transit, and the Spokane Transit Authority was created alongside it. STA serves the cities of Spokane, Spokane Valley, Cheney, Liberty Lake, Airway Heights, Medical Lake, the Town of Millwood, and part of Eastern Washington University. Today, the transit agency operates 36 fixed routes, most of which run through a downtown transit center. Five routes provide frequent, fifteen- minute or less service all day. In addition to the fixed-route bus service, STA provides commuter express routes, paratransit, and vanpool services. During the early 2000s, fixed route bus service was expanded and the region experienced ridership growth as a result. Due to the recession, revenue from sales tax was lost and STA was forced to cut and restructure fixed route service frequency to concentrate on key routes. Productivity (as defined as riders per revenue mile) and ridership increased until 2015 following this consolidation and the implementation of a university pass program. By partnering with universities and local community colleges, the typical rider has shifted to a slightly younger demographic. Figure 53: Spokane Transit Authority Bus Systemwide Trends from 2012 to 2018  Key Performance Trends Key performance trends of STA from 2012 to 2018 are shown in Figure 53 which displays a 12-month rolling average normalized to January 2012 of the unlinked passenger trips (UPT), vehicle revenue miles (VRM), on-time performance (OTP), and average speed. Despite some growth early in the decade, transit ridership in Spokane dropped by nearly 10% between 2015 and 2017 because of the movement of business and construction delays. During this period, Spokane introduced real-time information and university bus pass programs. On-time performance tracks

80 similarly to ridership, gradually decreasing beginning in mid-2015. VRM and average speed have remained fairly constant until the end of 2017 when ridership trends appear to be pointing upward, perhaps due to the transit agency’s most recent strategic plan to increase service and ridership. Ballot measures increasing sales tax, passed in 2016 and 2018, have resulted in more funding and a focus on high performance transit. Service changes implemented in 2017 included extending Saturday night service, increasing weekend service, providing new routes, and improving bus stop facilities. The new routes and increased frequencies on some routes can be seen in Figure 54 and Figure 55 which compare transit ridership data, frequency, and on-time performance in 2016, before implementation, and 2018, after implementation. Ridership data is the average weekday farebox data during the fall period in September, October, November, December of 2016 and 2018. Stop and frequency data is from the transit agency’s General Transit Feed Specification (GTFS). On-time performance data has been collected with a CAD/AVL system since 2014. The fixed route service frequency and ridership trends associated with the 2017 shift in service are displayed in Figure 54. Although the increased frequency has resulted in more riders, transit ridership per trip has decreased so route productivities have declined. Figure 54: Spokane Transit Frequency and Ridership Trends in 2016 and 2018  On-time performance and transit ridership trends during the 2016 and 2018 period are also displayed in Figure 55. STA is committed to on-time performance and maintains a very high

81 systemwide standard. The 2017 service change included stop improvements associated with lower dwell times and higher on-time performance. Although on-time performance is highly valued by customers, there was no clear trend between on-time performance and ridership. Figure 55: Spokane Transit On‐time Performance and Ridership Trends in 2016 and 2018  Future Plans to Encourage Ridership The local community has recently invested in transit by voting to increase sales tax funding in 2016 and 2018, developing college bus pass programs, and providing bus passes to everyone who works or lives in a new urban neighborhood development. Future key projects include the addition of a six-mile bus rapid transit (BRT) route, Central City Line, which will connect Spokane’s downtown and colleges and improve service, speed, and reliability in 2021 with near- level platforms, off-board ticketing, and transit signal priority. There are also plans to extend the transit service area of STA to the nearby Coeur d’Alene metropolitan area in 2025. Summary Nearly every transit agency investigated in the case studies had ridership increases through 2015 followed by steady decreases in ridership. The exceptions to this are Houston, TX, Portland, ME, and Seattle, WA.

82  In Houston, transit ridership has remained relatively constant without the declines seen by most transit agencies, but this is amongst substantial increases in service that came with the network redesign.  In Portland, transit service has been increased, especially on routes that serve schools and universities, but these strategic improvements have really paid off as ridership has increased even more than the service.  In Seattle, transit service has also increased, but ridership has increased even more. Ridership on both bus and streetcar have increased steadily over time with substantial investments in dedicated right-of-way and rapid transit services as well as a focus on speed and reliability. In all other cases, among the transit agencies where ridership declined, the amount of service provided has remained relatively similar over this time or has only been slightly increased. In every transit agency reviewed, average speeds have decreased or have remained the same, indicating that more vehicles are frequently needed to offer the same or degraded service. Some transit agencies have fought hard to keep average speeds up using strategic improvements such as signal priority or improvements to boarding. Generally, on-time performance has been improving, although it is clearly not causing transit ridership to increase. If anything, the trend appears that on-time performance is easier to maintain as ridership has decreased. With regard to rail ridership, the results are more mixed. In some transit agencies, such as Maryland Transit Authority’s light rail, ridership decreased and in others, such as Boston’s heavy rail, ridership remained steady. Minneapolis and Houston had substantial increases in ridership on light rail, but only with even greater increases in service, including the opening of new lines. Commuter rail seems to be fairing better across the country and the transit agencies among the case studies are no different. Whatever is impacting bus transit ridership across the country does not have the same impact on the dedicated right-of-way longer distance commuter rail services. However, all of the transit agencies interviewed are working hard to retain their riders. Transit agencies such as Houston and Baltimore are restructuring their bus service in some way including network redesigns and simplification of routes and information. Oftentimes, such as in Boston, this is paired with substantial analysis, making use of new data and analytics tools. Pinellas County has implemented a substantial partnership with the TNCs. Multiple transit agencies are updating their rolling stock, especially to obtain lower emitting and faster boarding vehicles. Newer technology in fare media and real-time information is being considered or has been adopted by many of the transit agencies. Transit agencies such as Portland and Spokane are doing substantial work to attract high school and college students as well as strategic partnership with new developments. Finally, there is a concerted effort to use dedicated right-of-way such as BRT and

83 bus lanes as well as strategic speed and reliability improvements to maintain higher levels of service and better customer service for riders.

Next: Conclusions and Next Steps »
Analysis of Recent Public Transit Ridership Trends Get This Book
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Transit ridership across the United States has declined for six straight years. Bus ridership, which has declined more than other transit services, is now at the lowest point since 1965. Rail ridership, with the exception of commuter rail, has also declined, and commuter rail ridership has recently leveled off.

The TRB Transit Cooperative Research Program's TCRP Research Report 209: Analysis of Recent Public Transit Ridership Trends presents a current snapshot of public transit ridership trends in the U.S. on bus and rail services in urban and suburban areas, focusing on what has changed in the past several years. It also explores and presents strategies that transit agencies are considering and using for all transit modes in response to changes in ridership.

Ten case studies are included to better understand individual strategies transit agencies are using to mitigate ridership losses and increase ridership overall. Nearly every transit agency investigated in the case studies had ridership increases between 2012 and 2015 followed by steady decreases in ridership. Generally, on-time performance has been improving, although it is not causing transit ridership to increase.

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