DART Ridership Board Workshop January 5, 2018 0
Overview This presentation looks at many facets of DART s bus and rail ridership trends. No single factor can adequately explains the current trends Key topics covered: General bus and ridership trends Factors behind the trends including both increases and decreases in ridership: demographics, the economy and employment, geography and physical development, service characteristics, ridership counting, and others 1
GENERAL RIDERSHIP TRENDS 2
General Ridership Trends Overall ridership has trended upward since 2001 Bus ridership has generally declined since 2008, but has experienced more significant declines in 2016 and 2017 LRT ridership is flat or up slightly in 2016 and 2017 after expansion-driven growth since 2001 TRE ridership has been trending down since 2008, but had a small increase when the Arlington MAX was implemented in 2013 and 2014, and is improving with more frequent service (especially on Saturdays) 3
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 198,090 207,339 200,615 193,957 197,996 202,745 222,734 221,353 228,197 220,552 216,862 205,946 229,876 232,317 230,815 227,633 213,226 DART Fixed-Route Ridership Trends Average Weekday Ridership - Bus, LRT, TRE 240,000 230,000 220,000 210,000 200,000 190,000 180,000 170,000 160,000 150,000 140,000 4
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 45,230 38,696 56,767 55,301 61,994 60,592 65,752 64,592 59,810 59,293 71,606 90,221 96,272 96,380 97,846 96,346 97,242 DART LRT Ridership Trends Average Weekday Ridership - LRT 110,000 100,000 90,000 80,000 70,000 60,000 50,000 40,000 30,000 5
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 4,758 7,211 8,045 7,674 7,535 8,077 7,643 8,618 8,206 7,788 7,421 8,893 8,680 7,432 9,796 9,879 8,468 TRE Ridership Trends Average Weekday Ridership - TRE 10,500 9,500 8,500 7,500 6,500 5,500 4,500 3,500 6
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 113,095 135,803 130,983 129,506 131,577 128,511 126,229 121,999 108,079 145,649 163,886 135,809 152,122 151,869 152,650 146,081 125,873 DART Bus Ridership Trends Average Weekday Ridership - Bus 170,000 160,000 150,000 140,000 130,000 120,000 110,000 100,000 90,000 80,000 7
Route-Level Ridership Trends Staff has reviewed ridership trends at a route level to try to help determine some of the factors behind changes We looked at weekday ridership for each route operating FY14 through FY17 four years of data There were no fare increases or major rail openings during this period that could influence the results 142 bus routes operated during the entire four-year period We calculated the slope for each route the overall linear weekday ridership trend for that route over the four years Reflecting general bus ridership trends for the period, 21 routes had positive trends, and 121 routes had negative trends 8
Routes with the Best Ridership Trend Route Name Avg Weekday Riders FY14 Avg Weekday Riders FY17 Slope Notes 883 UT Dallas Shuttle 3,175 4,943 1.5774 549 Downtown Irving- Westmoreland Rapidly expanding ridership, service growth 919 1,099 0.1497 Midday frequency improvements 524 LoveLink 362 483 0.1135 Serves Love Field, with major growth 208 Northwest Plano Express 557 630 0.0878 Serves growing employment center 529 Inwood-Royal Lane 304 379 0.0729 Uncertain 463 Addison-Downtown Garland 385 Chaha-South Garland TC 170 214 0.0405 11 Jefferson-Malcolm X/Bexar 1,404 1,491 0.0692 Steady ridership growth, service added 4,236 4,299 0.0393 2 Hatcher 1,121 1,152 0.0191 Uncertain Route expanded to connect to Rowlett Station Route reorganized in 2010, more frequent service 841 Telecom Corridor FLEX 137 154 0.0166 Serves growing employment center 9
Location of Growing Routes 529 208 841 883 463 385 524 549 11 2 10
Oct-13 Dec-13 Feb-14 Apr-14 Jun-14 Aug-14 Oct-14 Dec-14 Feb-15 Apr-15 Jun-15 Aug-15 Oct-15 Dec-15 Feb-16 Apr-16 Jun-16 Aug-16 Oct-16 Dec-16 Feb-17 Apr-17 Jun-17 Aug-17 Route 883 UTD Trends Average Weekday Ridership 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 883 12 per. Mov. Avg. (883) 11
Oct-13 Dec-13 Feb-14 Apr-14 Jun-14 Aug-14 Oct-14 Dec-14 Feb-15 Apr-15 Jun-15 Aug-15 Oct-15 Dec-15 Feb-16 Apr-16 Jun-16 Aug-16 Oct-16 Dec-16 Feb-17 Apr-17 Jun-17 Aug-17 Route 549 Trends Average Weekday Ridership 1,200 1,100 1,000 900 800 700 600 549 12 per. Mov. Avg. (549) 12
Underlying Factors for Gains Most of the routes with the greatest improvements had one of several factors influencing their results: Employment growth Activity growth (e.g. Love Field) Service improvements, particularly frequency improvements 13
Routes with the Worst Ridership Trend Route Name Avg Weekday Riders FY14 Avg Weekday Riders FY17 Slope Notes 409 Illinois-Westmoreland 2,013 1,654-0.3127 Demographics 19 Ann Arbor-Lakewood 2,235 1,878-0.3204 Likely gentrification, demographics 161 Glen Oaks 1,850 1,484-0.3383 Demographics 362 Addison-Arapaho via Campbell 962 601-0.3405 Riders siphoned off by UTD Shuttle 467 Buckner-South Garland 2,678 2,278-0.3684 Demographics 24 Mockingbird- Capitol/McMillan 1,573 1,178-0.3787 Large-scale redevelopment, gentrification 466 SW Center Mall-Buckner 2,537 2,139-0.4212 Demographics 486 1 583 Downtown Garland- Royal Lane Wynnewood- Mockingbird Richland College-Lovers Lane 2,755 2,275-0.4338 1,872 1,362-0.4628 2,493 1,919-0.5745 Riders siphoned off by 987, demographics Large-scale redevelopment, gentrification Large-scale redevelopment, gentrification 14
Location of Declining Routes 362 486 583 24 1 19 467 409 466 161 15
Oct-13 Dec-13 Feb-14 Apr-14 Jun-14 Aug-14 Oct-14 Dec-14 Feb-15 Apr-15 Jun-15 Aug-15 Oct-15 Dec-15 Feb-16 Apr-16 Jun-16 Aug-16 Oct-16 Dec-16 Feb-17 Apr-17 Jun-17 Aug-17 Route 583 Trends Average Weekday Ridership 3,100 2,900 2,700 2,500 2,300 2,100 1,900 1,700 1,500 583 12 per. Mov. Avg. (583) 16
Oct-13 Dec-13 Feb-14 Apr-14 Jun-14 Aug-14 Oct-14 Dec-14 Feb-15 Apr-15 Jun-15 Aug-15 Oct-15 Dec-15 Feb-16 Apr-16 Jun-16 Aug-16 Oct-16 Dec-16 Feb-17 Apr-17 Jun-17 Aug-17 Route 1 Trends Average Weekday Ridership 2,200 2,000 1,800 1,600 1,400 1,200 1,000 1 12 per. Mov. Avg. (1) 17
Underlying Factors for Losses Routes with the biggest declines had several factors that influenced their results: Redevelopment and gentrification Potential competition from other services like Transportation Network Companies (TNC) in Uptown area and near downtown Underlying demographic changes 18
National Trends Recent DART ridership trends generally mirror national ridership trends Bus ridership is down throughout the country Rail ridership is down for some systems, up for others Recent trends for a number of cities with light rail and/or commuter rail operations follow 19
National Bus Trends Most peer bus systems are also experiencing declines Chart compares recent bus ridership for medium and large American systems with light/commuter rail operations City/System Change 2016-2017 Phoenix 6.6% Houston -1.5% Salt Lake -2.1% Pittsburgh -2.1% Minneapolis -2.8% Portland -2.9% San Diego -4.5% DART -4.7% St Louis -7.0% Denver -8.6% Charlotte -9.9% Source: Federal Transit Administration National Transit Database Monthly Module Adjusted Data Release 20
National Light Rail Trends Peer rail ridership has been less consistent, with more systems seeing growth Chart compares recent light rail ridership for medium and large American systems with light rail operations City/System Change 2016-2017 Minneapolis 3.7% Phoenix 2.0% DART 0.9% Denver 0.2% Houston -1.1% Pittsburgh -1.5% Charlotte -1.5% Portland -2.6% Salt Lake -2.8% San Diego -3.6% St Louis -6.5% Source: Federal Transit Administration National Transit Database Monthly Module Adjusted Data Release 21
Texas Trends The larger transit systems in Texas have been sharing ridership data for over a decade Trends for the largest four systems (DART, Houston Metro, San Antonio VIA, Austin Capital Metro) have been somewhat similar 22
Oct-07 Jan-08 Apr-08 Jul-08 Oct-08 Jan-09 Apr-09 Jul-09 Oct-09 Jan-10 Apr-10 Jul-10 Oct-10 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Apr-16 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 Large Texas System Trends Average Weekday Bus and Rail Riders 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000 DART Houston Metro Capital Metro VIA 12 per. Mov. Avg. (DART) 12 per. Mov. Avg. (Houston Metro) 12 per. Mov. Avg. (Capital Metro) 12 per. Mov. Avg. (VIA) 23
FACTORS BEHIND THE TRENDS 24
Factors Driving Ridership Change As we have tracked ridership and activity, we see some clear trends and correlations, yet it is not clear that any single factor is driving ridership Instead, ridership seems to be impacted by a number of key factors Some of them are systemic; others affect individual routes or areas Some are factors that DART cannot directly control, while others are within DART control 25
Factors DART Does Not Directly Control Demographic and rider usage: demographics, how riders use the system Economy, employment: employment trends, spatial location of population and employment, spatial location of economic development Geography and physical development: geography, residential teardowns, transit-oriented development Other factors: fuel prices, crime 26
Factors DART Controls Service characteristics: frequency, service levels, service quality Ridership counting impacts: changes in counting methodology 27
DEMOGRAPHICS AND RIDER USAGE 28
Demographics: Who Rides the System Gender of DART Riders Female 47.2% Male 52.8% Source: 2014 Regional Rider Survey 29
Who Rides the System 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 63.9% under 35 3.2% 6,569 26.9% 56,173 33.8% 70,410 Age of DART Riders 19.5% 40,583 9.9% 20,571 5.4% 11,184 1.4% 2,996 Under 18 18-24 25-34 35-44 45-54 55-64 Over 65 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Source: 2014 Regional Rider Survey 30
Who Rides the System 120,000 100,000 Ethnicity of DART Riders 52.7% 60.0% 50.0% 80,000 40.0% 60,000 24.6% 30.0% 40,000 18.4% 20.0% 20,000 0.6% 2.5% 0.3% 0.8% 10.0% 0 Amer Indian Asian Black/AA Hispanic Nat Hawaiian White Other 0.0% Source: 2014 Regional Rider Survey 31
0.65% 0.31% 2.53% 0.32% 0.04% 0.81% 1.55% 7.28% 17.82% 18.44% 24.60% 34.38% 38.62% 52.66% Who Rides the System 60.00% Ethnicity of DART Riders and Ethnicity of Service Area Population 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Amer Indian Asian Black/AA Hispanic Nat Hawaiian White Other Riders Population Source: 2014 Regional Rider Survey and U. S. Bureau of the Census 2010 Federal Census 32
Who Rides the System Income of DART Riders 50,000 45,000 40,000 Low Income 51.7% 20.0% 41,673 21.5% 44,834 25.0% 20.0% 35,000 30,000 25,000 14.6% 30,434 13.0% 27,189 15.0% 20,000 15,000 8.1% 16,879 9.0% 18,833 5.7% 8.1% 16,823 10.0% 10,000 11,821 5.0% 5,000 0 Less than $12,000 $12,000 - $19,999 $20,000 - $23,999 $25,000 - $34,999 $35,000 - $49,999 $50,000 - $74,999 $75,000 or more No answer 0.0% Source: 2014 Regional Rider Survey 33
How and Why Riders Use DART A mix of rail, bus, and bus/rail riders The proportion of bus-only riders has dropped over time as the rail network has grown About 54% of DART riders complete trips without transferring; the others must use 2 or more vehicles to complete their trips More people ride for work commutes than any other trip purpose A large plurality of riders use service five days per week 34
Modes Used The Modes DART Riders Use for Their Trips Rail Only 28.9% Bus and Rail 32.2% Bus Only 38.9% Source: 2014 Regional Rider Survey 35
Changes in Mode Over Time 2007 Survey 2014 Survey Rail Only 23.0% Bus and Rail 29.0% Rail Only 28.9% Bus and Rail 32.2% Bus Only 48.0% Bus Only 38.9% Source: 2007 Transit Rider Survey and 2014 Regional Rider Survey 36
Transfers How Many Vehicles DART Riders Use to Complete a Trip One 54.5% Two 28.4% Three 14.1% Five/Six 0.1% Four 2.9% 45.5% of DART Riders Transfer to complete their trip. 17.1% of DART Riders transfer more than once to complete their trip. Source: 2014 Regional Rider Survey 37
Why Riders Use the System NHB Work 4.4% NHB Other 4.9% HB Air 0.3% HB Accom 1.1% HB Eat 3.4% HB College 8.6% HB K-12 2.4% HB Other 0.4% HB Pers 9.6% HB Work 48.3% HB Social 12.3% HB Shop 4.3% Trip Purpose All Riders NB means Home Based NHB means Non Home Based Source: 2014 Regional Rider Survey 38
How Often Riders Use the System How Often DART Riders Ride 100,000 90,000 80,000 70,000 43.7% 91,037 50.0% 45.0% 40.0% 35.0% 60,000 50,000 40,000 30,000 19.6% 40,836 25.2 % 12.5% 30.0% 25.0% 20.0% 15.0% 20,000 10,000 0 5.5% 11,460 Every Day 5 days/week 2-4 times/week 6.1% 12,639 7.8% 16,207 Once a week 2-3 times/month 26,123 4.9% 10,172 Once a month < Once a month 10.0% 5.0% 0.0% Source: 2014 Regional Rider Survey 39
ECONOMY, EMPLOYMENT 40
Economy and DART Ridership It has not been consistent throughout DART s history, but there was an extended period of time where a strong economy as measured by low unemployment has corresponded to high bus ridership Yet in the 1990 s and in the past few years, this relationship seems to be broken bus ridership declines despite historically low unemployment figures 41
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Unemployment and DART Bus Ridership 50,000,000 9.0% 45,000,000 40,000,000 35,000,000 30,000,000 25,000,000 8.0% 7.0% 6.0% 5.0% 4.0% 3.0% 20,000,000 2.0% Bus Ridership Unemployment Rate 42
Impact of Employment Changes With so many riders using DART to go to work, ridership is profoundly affected by changes in the location and size of the employed population This is especially true for employed population shifts in areas that have a high proportion of transit-dependent riders people who do not have alternatives available 43
General Employment Trends Overall employment trends have varied with economic cycles, but have generally been improving in recent years This is important because employment and ridership trends have been closely linked historically, especially for bus ridership There are substantially more jobs in Dallas County now than 10+ years ago, but Fewer of these jobs are in the core Dallas CBD where so much transit service operates The decentralization of jobs can have a significant negative impact on a centrally-oriented transit system 44
91.2% 91.2% 92.2% 91.8% 91.5% 91.9% 93.0% 93.7% 93.6% 94.3% 92.5% 92.3% 94.8% 94.6% 92.8% 94.8% 95.4% 93.7% 94.5% 94.5% 94.1% 95.9% 96.2% 95.3% 95.1% 95.6% 95.4% 95.2% 96.1% 96.1% 96.2% 96.5% Employment Rate Trends 98.0% Employment Rates DART Service Area 98.0% 97.0% 97.0% 96.0% 96.0% 95.0% 95.0% 94.0% 94.0% 93.0% 93.0% 92.0% 92.0% 91.0% 90.0% 89.0% 91.0% 90.0% 89.0% 88.0% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Dallas DART Suburbs 88.0% Source: U. S. Bureau of Labor Statistics 45
Dallas County Employment Totals 855,000 Dallas County Employment 840,000 849,667 825,000 810,000 815,631 795,000 780,000 779,728 765,000 750,000 2002 2008 2014 Source: U. S. Bureau of the Census Linear Household-Employment Data 46
Employment and Demographic Trends Present Challenges Looking at employment trends in more detail reveals challenges for DART in building ridership Transit ridership is generally younger, but employment rates for younger residents are actually declining workers are getting older Jobs in our area are trending to higher levels of pay and this can also impact ridership 47
Employment and Age Employment for younger workers has declined in Dallas County, which is especially important given the relative youth of DART ridership Age Group 2002 2008 2014 Under 30 204,215 205,010 176,861 30 to 54 477,082 480,137 497,237 55 and Over 98,421 130,484 175,569 Source: U. S. Bureau of the Census American Community Survey 48
Employment and Earnings Employment for lower-wage workers, which is important given that low-income workers are more likely to use transit Wage Group 2002 2008 2014 $1250/ month or less $1251-3333 More than $3333 191,243 168,345 159,756 318,130 286,058 268,640 270,355 361,228 421,271 Source: U. S. Bureau of the Census American Community Survey 49
Location of Jobs, Worker Residences Affects Ridership Critical parts of DART s rail and bus networks are aligned to serve Downtown Dallas, but employment in the CBD is actually falling over time Relatively few riders live and work within walking distance of rail stations, and rail is not enough bus networks are crucial Population losses in areas with high transit-dependent ridership also affect transit ridership levels 50
Employment in the CBD Employment in the core CBD in Dallas has been declining With the concentration of transit in this area, this could have significant implications for ridership trends 120,000 115,000 110,000 105,000 100,000 Dallas CBD (Within the Freeway Loop) Employment 115,206 114,586 108,991 95,000 2002 2008 2014 Source: U. S. Bureau of the Census Linear Household-Employment Data 51
Linkage Between Where People Work and Live, and Transit Impact 1,637,504 jobs are located in service area as of 2014 54% of these service area jobs are worked by non-residents to the service area 439,690 jobs are located within ½ mile of rail station 192,558 residents live within ½ mile of a rail station Only 54,852 residents actually live & work within ½ mile of a station Key Point---rail ridership is extremely dependent upon bus service or Park & Ride to generate ridership 52
Changes in Employee Residential Riders and Transit Impact Example: Oak Cliff along the Blue Line LRT corridor Area reviewed: between IH-45 and Marsalis, and IH-20 on South Employed population and bus ridership are both declining in this area, which has traditionally generated heavy transit ridership 53
Blue Line Corridor Employed Population Trends Employed population in this area is steadily declining The percentage of work commuters from this area working in Dallas County has declined, making it more likely that workers will not be able to use DART to complete their trips Year Employed population within Corridor Percent Working in Dallas County 2002 22,270 79.6% 2008 21,293 73.8% 2014 19,266 74.2% Source: U. S. Bureau of the Census Linear Household-Employment Data 54
GEOGRAPHY AND PHYSICAL DEVELOPMENT 55
Geography and Physical Development Physical geography and development also have significant impacts on ridership Mountains, lakes, ocean constraints can dramatically increase ridership Here in Dallas, apartment tear-downs have had a major impact on ridership on individual routes and parts of the route network 56
Geography Some cities that have not seen ridership losses have significant geographical issues that limit commute options and encourage people to look for alternatives The San Francisco Bay Area is a good example; water funnels traffic over strategic bridge and ferry corridors Dallas (or most Texas cities) does not have any such geographical issues Bay Area 57
Residential Tear-Downs Replacement of urban housing stock has had significant impacts on ridership in parts of the system Large-scale tear-downs of apartments and singlefamily homes displace residents and riders Unfortunately, we do not have any way to track where displaced residents relocate The result permanent ridership losses on affected routes 58
Route 583 Example Route 583 serves a section of Skillman in Lake Highlands that has seen major apartment teardowns over the past decade Many of the tear-downs have not been replaced, or have been replaced with more expensive units serving a different demographic Ridership has plunged from 3,500/day to 2,000/day even as the route transitioned to feed riders into the new Lake Highlands LRT Station 59
Route 24 Example Route 24 operates between Mockingbird Station and Downtown Dallas, and some parts of the route have seen major redevelopment e.g. Capitol Ridership has dropped from 1,600/day to 1,200/day even though much of the lost housing has been replaced by higher-density apartments 60
Transit Oriented Development and Rail Ridership In theory, transit oriented development near stations should increase ridership at the adjacent stations Two examples: Residential conversions near St. Paul Station have had a very noticeable positive impact on ridership (7-11 has not hurt, either!) Ridership at CityLine/Bush Station has begun to observe small increases in ridership based upon riders who live and work adjacent this station. Previously almost all of the ridership was from park & ride commuters destined for somewhere other than CityLine/Bush Station. 61
Nov-09 Feb-10 May-10 Aug-10 Nov-10 Feb-11 May-11 Aug-11 Nov-11 Feb-12 May-12 Aug-12 Nov-12 Feb-13 May-13 Aug-13 Nov-13 Feb-14 May-14 Aug-14 Nov-14 Feb-15 May-15 Aug-15 Nov-15 Feb-16 May-16 Aug-16 Nov-16 Feb-17 May-17 Aug-17 St. Paul Station Ridership Trends Average Weekday Riders 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 St. Paul 12 per. Mov. Avg. (St. Paul) 62
Oct-09 Jan-10 Apr-10 Jul-10 Oct-10 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Apr-16 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 CityLine/Bush Station Trends Average Weekday Riders 2,000 1,800 1,600 1,400 1,200 1,000 800 600 400 Peak ridership during paid parking at Parker Road CityLine/Bush 12 per. Mov. Avg. (CityLine/Bush) 63
OTHER FACTORS 64
Gasoline Prices and Ridership In the years we have been tracking ridership and gasoline prices, there is definitely a general correlation between the two Gasoline prices, however, have been far more volatile than ridership The 2008 gasoline price spike corresponded with a noticeable spike in ridership Gas prices are probably a factor, though one of many 65
Gasoline Prices and DART Ridership 80,000,000 $4.000 70,000,000 $3.500 60,000,000 $3.000 50,000,000 $2.500 40,000,000 $2.000 30,000,000 $1.500 20,000,000 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 $1.000 Fixed-Route Riders Gasoline Price 66
Crime and Ridership Staff have reviewed the last four years of arrest and police call data for the system and arrest data for individual rail stations We see no correlations that would suggest a direct relationship between DART crime statistics and ridership trends Whether or not perception of crime is a factor in ridership cannot be directly determined with available data If perception is a recent factor, we do not see a direct impact in underlying ridership trends for bus or rail 67
SERVICE CHARACTERISTICS 68
Service Characteristics The characteristics of service also play a role in ridership trends More frequent service usually translates into more ridership but not always more efficient service Until recently, DART has generally been trending toward less frequent bus service due to the financial impacts of the last two recessions Reductions were generally on low performing routes or routes duplicating light rail Some recent frequency improvements have been paying almost immediate dividends in higher ridership 69
Impact of Frequency Improvements DART has made frequency improvements on selected routes over the past few years, and these routes have been near the top of longer-term ridership growth trends: Route 11 went to 15 minute daytime service (peak and midday) and ridership has trended upward, while other comparable routes have seen declines Route 463 midday service went from every 60 minutes to every 40-45 minutes, and average weekday ridership grew from around 1,300 to as much as 1,700 Route 549 midday service went from every 60 minutes to every 30 minutes, and average weekday ridership grew from around 900 to over 1,100 in many months 70
Future Frequency Improvements Frequency improvements are a big part of DART s planning for future service changes 10 routes will have off-peak service frequency improvements in March 2018, with others to follow in 2019 Comprehensive Operations Analysis (COA) work envisioned a network of core frequent service routes 71
Ridership and Service Levels Service levels also have an impact on ridership Over the past 15 years, DART has significantly expanded rail service and has reduced bus service The reduction in bus services generally targeted the following: Bus routes duplicating new rail Bus routes ranking very low in route performance In 2011 DART reduced rail frequency during the peak hours from 10 minute to 15 minute frequency 72
Bus+LRT Combined Ridership vs. Service Levels 70,000,000 40,000,000 38,000,000 65,000,000 36,000,000 34,000,000 60,000,000 32,000,000 30,000,000 55,000,000 28,000,000 26,000,000 50,000,000 24,000,000 45,000,000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 22,000,000 20,000,000 Riders Revenue Miles 73
LRT Ridership vs. Service Levels 35,000,000 6,000,000 30,000,000 5,500,000 5,000,000 25,000,000 4,500,000 20,000,000 4,000,000 15,000,000 3,500,000 3,000,000 10,000,000 2,500,000 5,000,000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2,000,000 Riders Revenue Miles 74
Bus Ridership vs. Service Levels 46,000,000 33,000,000 44,000,000 31,000,000 42,000,000 40,000,000 29,000,000 38,000,000 27,000,000 36,000,000 25,000,000 34,000,000 32,000,000 23,000,000 30,000,000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 21,000,000 Riders Revenue Miles 75
RIDERSHIP COUNTING IMPACTS 76
Ridership Counting Methodology DART has traditionally counted ridership through the farebox system As the current technology has aged and more and more units malfunction, we do not believe we are counting all passengers using DART buses, and that the situation is getting worse Actual ridership counts are likely higher than our farebox numbers potentially by as much as 20%, and more on routes like D-Link that do not involve cash fares We are in the process of validating automatic passenger counter (APC) units on buses for ridership collection matching the process used for DART light rail APC counts will likely result in an immediate bump in ridership levels, as we saw for rail 77
542 397 616 435 757 805 682 981 943 783 839 681 1,423 1,159 1,152 909 1,128 899 1,057 841 913 777 948 1,804 1,550 1,394 1,397 1,121 1,790 1,522 2,183 1,953 1,892 1,900 2,236 2,267 2,766 2,934 2,670 3,178 3,500 APC Counts vs. Farebox Counts Selected Bus Routes Average Weekday Ridership 3,000 2,500 2,000 1,500 1,000 500 0 35 36 39 60 164 360 374 400 401 404 408 410 415 428 451 463 488 501 551 571 Routes APC Farebox These APC Counts Average Approximately 20% Higher 78
350 APC Counts vs. Farebox Counts D-Link Service Route 722 D-Link Average Daily Ridership 350 300 311 300 250 284 250 200 213 231 231 240 200 150 100 157 168 108 137 185 119 150 100 50 50 0 16-Jan 17-Jan 18-Jan 19-Jan 20-Jan 21-Jan 0 APC Farebox D-Link is fare free requiring manual input of counts to Farebox These APC counts average almost 73% higher. 79
WHAT CAN BE DONE TO IMPROVE RIDERSHIP 80
What Can Be Done To Improve Ridership? In the past decade many of DART s peers have sought improved ridership through bus system redesign and the addition of high frequency bus routes Improved ridership is the objective of DART s Comprehensive Operation Analysis in addition to efforts to improve safety, passenger amenities, fare payment, and new last mile services Unfortunately in FY16 and FY17, most of DART s transit peers including those who have redesigned their bus system are experiencing declining bus ridership and some are experiencing declining rail ridership Seattle is a good example of a system that has bucked the recent trend of ridership decline 81
Seattle The Seattle area has seen notable transit ridership growth over the past year From our review of FTA reports, most of the gains have been as a result of rail ridership growth as the light rail system continues to expand Supportive of this multi-modal system, City of Seattle has levied an additional car registration tax to help fund expanded bus service, and are investing an extra $36 million per year in King County Metro bus service to support high frequency routes Metro has added more than 300,000 additional bus service hours in the past year This translates into more frequent bus service on 66 bus routes The City of Seattle is also expanding the network of bus-only lanes and traffic signal priority improvements to improve bus performance 82
83 83
Core Frequent Route Network Weekday Peak Service (15 minute or less) 84
Core Frequent Route Network Weekday Midday Service (20 minute or less) 85
Core Frequent Route Network Saturday Midday Service (30 minute or less) 86
Core Frequent Route Network Sunday Midday Service (30 minute or less) 87