Changes in Travel Behavior Affecting Transit TRB Executive Committee Wednesday, January 10, 2018 Steven E. Polzin, PhD.
Changes in Travel Behavior Affecting Transit
TRB Executive Committee Wednesday, January 10, 2018
Steven E. Polzin, PhD.
Outline
What is going on with travel
What factors are influencing transit use
Critical Issues going forward
U.S. Context and Travel Trends 2015/2014 2016/2015 2017/2016 YTD Months Source
U.S. Population 0.8% 0.5% 0.7% - Census
Total Employment 1.7% 1.7% 1.2% 11 BLS
Real GDP 2.9% 1.5% 2.2% 9 BEA (3rd estimate)
Gas Price -29.3% -14.8% 15.0% 11 EIA
Registered Cars and Light Trucks 2.1% 1.5% 3.0% 12 proj. Hedges
Co.
Light Vehicle Sales 5.8% 0.1% -1.5% 11 BEA
VMT 3.5% 2.8% 1.3% 10 FHWA
Public Transit Ridership -1.0% to -2.2% -2.3% to -1.6% -3.1% 9 APTA and
NTD
Amtrak Ridership (FY) -0.3% 1.9% 2.3% 8 Amtrak
Airline Passengers 5.3% 3.9% 3.2% 9 USDOT, BTS
National VMT and VMT per Capita Trend, Moving 12-Month Total, 1990–2016
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Jan-
92Ja
n-93
Jan-
94Ja
n-95
Jan-
96Ja
n-97
Jan-
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n-99
Jan-
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n-01
Jan-
02Ja
n-03
Jan-
04Ja
n-05
Jan-
06Ja
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Jan-
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n-09
Jan-
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n-11
Jan-
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Jan-
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n-15
Jan-
16Ja
n-17
VM
T pe
r Cap
ita, A
nnua
l
Vehi
cle-
Dis
tanc
e Tr
avel
ed (B
illio
n M
iles)
Annual Vehicle-DistanceTraveled (Billion Miles)
VMT per Capita
8 year reprieve
National VMT & Household Income of Bottom 80% of US Households
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
5,000,000
0
500
1,000
1,500
2,000
2,500
3,000
3,500
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
Tota
l Hou
seho
ld in
com
e of
Bot
tom
80%
in B
illio
ns 2
015
VMT
(Bill
ions
)
VMT Total (Billions)
Household Income ofBottom 80% (2015 $Millions)
0
2,500
5,000
7,500
10,000
12,500
15,000
17,500
20,000
0
500
1,000
1,500
2,000
2,500
3,000
3,500
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
GDP
in B
illio
ns o
f 201
6 U
S Do
llars
VMT
(bill
ions
)
VMT Total (Billions)
GDP in 2016 dollars($Billions)
National VMT & GDP Trends
U.S. Transit Ridership and Ridership per Capita
020406080100120140160180200
0
5
10
15
20
25
1918
1925
1932
1939
1946
1953
1960
1967
1974
1981
1988
1995
2002
2009
2016
Annu
al T
rips p
er C
apita
Annu
al R
ider
ship
, Bill
ions
Rides, Billion
U.S. Transit Ridership, Fixed Route, 12-Month Rolling Average
7.0
7.2
7.4
7.6
7.8
8.0
8.2
8.4
8.6
8.8JA
N08
APR
08JU
L08
OC
T08
JAN
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PR09
JUL0
9O
CT0
9JA
N10
APR
10JU
L10
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T10
JAN
11A
PR11
JUL1
1O
CT1
1JA
N12
APR
12JU
L12
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T12
JAN
13A
PR13
JUL1
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CT1
3JA
N14
APR
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L14
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JAN
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PR15
JUL1
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5JA
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APR
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L16
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T16
JAN
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PR17
JUL1
7O
CT1
7
Hun
dred
s of
Mill
ions
Top 40 UZAs by 2016 Transit Ridership, Change 2014-2016 (Millions)
Top 40 urban areas make up 83.9% of
U.S. ridership decline from 2014-2016.
Source: NTD Monthly Raw Database
9.00%
5.10%
2.70%
0.60% 1.20%
5.00%
0%
2%
4%
6%
8%
10%
12%
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Mod
e Sh
are,
Usu
al C
omm
ute
Car, truck, or van -- carpooled Public transportation Walked Bicycle Other means Worked at home
Declining Carpooling and Growing Work-at-Home Dominate Trends
Where are We Headed?
2012-2014
2018
?
2015-2017 Transit ridership near 60 year high
Millennials are different
We passed peak VMT
We are urbanizing and CBD’s are thriving
Developers embrace transit
Strong Referendum success
TNC’s address first-mile/last-mile issue
Millennials buy cars and move to suburbs
Transit ridership loss accelerates in 3rd year of decline
VMT and VMT/Capita continue growth
Growth and migration resume historic patterns
System conditions, reliability, health care costs, etc. plague transit operators
How much will that subway cost? When will Hawaii's rail system open? How is that new streetcar doing?
TNC’s can cannibalize transit ridership
Why do we need transit with CAV?
Framework for Understanding Changes in Transit Ridership
1. Demographics and Land-Use
3. Competition
2. Transit Service Quality How much of ridership change is explained by these factors?
Demand
Supply
Framework for Understanding Changes in Transit Ridership
1. Demographics and Land-Use Age Geographic Distribution across Metros Geographic Distribution within Metros (within proximity of service?/gentrification) Income Licensure Levels Auto Ownership Poverty Levels (SNAP enrollment) Unemployment Reduced College Student Ridership (APTA report) Core Values
3.2 3.5
4.0 4.3 4.2 4.0
3.6
2.9
2.0
0
1
2
3
4
5
5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+
Tirp
s per
per
son
per d
ay
Age group
1.0%
2.9% 2.6%
1.8% 2.0%
1.6% 1.5% 1.2% 1.1%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+Shar
e of
trip
s tak
en v
ia tr
ansi
t
Age group
0
10
20
30
40
50
5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+
Pers
ons (
Mill
ions
)
2015
2010
2000
1990
1980
Aging Population has a Negative Impact on Ridership
Top 10 Largest-Gaining Counties (Numeric Change): July 1, 2015 to July 1, 2016
Largest-Declining Counties or County Equivalents (Numeric Change): July 1, 2015 to July 1, 2016
County Population Numeric Change
Percent Change
Transit Commute Share 2015
County Population Numeric
Change Percent Change
Transit Commute
Share 2015
Maricopa County, 4,242,997 81,360 1.95 2.3% Cook County, 5,203,499 -21,324 -0.41 18.8%
Arizona Illinois Harris County, 4,589,928 56,587 1.25 2.8% Wayne County, 1,749,366 -7,696 -0.44 2.5% Texas Michigan Clark County, 2,155,664 46,375 2.2 4.2% Baltimore city, 614,664 -6,738 -1.08 19.6% Nevada Maryland
King County, 2,149,970 35,714 1.69 12.6% Cuyahoga County, 1,249,352 -5,673 -0.45 5.1%
Washington Ohio
Tarrant County, 2,016,872 35,462 1.79 0.6% Suffolk County, 1,492,583 -5,320 -0.36 6.8%
Texas New York
Riverside County, 2,387,741 34,849 1.48 1.4% Milwaukee County, 951,448 -4,866 -0.51 6.2%
California Wisconsin
Bexar County, 1,928,680 33,198 1.75 2.6% Allegheny County, 1,225,365 -3,933 -0.32 9.1%
Texas Pennsylvania
Orange County, 1,314,367 29,503 2.3 3.2% San Juan County, 115,079 -3,622 -3.05 0.3%
Florida New Mexico Dallas County, 2,574,984 29,209 1.15 2.9% St. Louis City, 311,404 -3,471 -1.1 9.7% Texas Missouri Hillsborough County, 1,376,238 29,161 2.16 1.7% Jefferson County, 114,006 -3,254 -2.78 0.0%
Florida New York Average 3.4% Average 7.8%
Migration and Growth are Higher in Low Transit Use Areas
Improving Vehicle Availability Coincides with Declining Transit Ridership
-10%
-5%
0%
5%
10%
15%
20%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Percent Change in Transit Ridership and Zero-Vehicle Households from 2005
Ridership Percent Change from 2005 Percent Change Zero-Vehicle Households from 2005
1.3 million fewer persons lived in zero vehicle households in 2016 than in 2014.
Transit Use Correlates with Need-Based Program Participation
0%
30%
60%
90%
120%
150%
0%
5%
10%
15%
20%
25%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
SNAP
Use
rs P
erce
nt C
hang
e fr
om 2
002
Ride
rshi
p Pe
rcen
t Cha
nge
from
200
2
Percent Change U.S. Transit Ridership and SNAP Enrollment
Ridership Percent Change from 2002
SNAP Users Percent Change from 2002
Are Core Values that Impact Travel Changing?
Do we value autonomy, privacy, flexibility, convenience, etc. more than in the past?
Money Cost
Reliability
Travel Behavior
Comfort
Safety
Time Cost
Convenience
Flexibility
Image Environmental, Social Impact
Framework for Understanding Changes in Transit Ridership
2. Transit Service Quality Fares (levels, convenience, ease of use) Level of Service (coverage, frequency, hours of operation) Speed (access, wait, in vehicle, transfer, egress)(tolerance for waiting in our immediate gratification culture) Reliability Safety/Security
• Accident Safety, In-Vehicle/Facility Crime Image
• Cleanliness • Interpersonal Compatibility - Increased homeless/mental ill ridership (APTA report) • Status/Persona
Environmental Impacts Awareness/Marketing (trip planning, real time information, digital fare payment, etc.) Amenities (Wi-Fi, shelter, convenience retail, etc.)
Average Fare Revenue per Passenger Trip and Passenger Mile (2017 Dollars)
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
$1.60
$1.80Av
erag
e Fa
re R
even
ue
per Passenger Trip per Passenger Mile
Pre 2014 data from APTA Fact Book, Post 2014 data from NTD
Service Supply
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dred
s of
Mill
ions
(Trip
s an
d V
RM
)
12-Month Rolling Average of U.S. Transit Ridership and Service, Fixed Route
Ridership Service
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illio
ns (T
rips
and
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12-Month Rolling Average of U.S. Transit Ridership and Service, Metro Bus
Ridership Service
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1015202530354045
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Mill
ions
(Trip
s an
d V
RM
) 12-Month Rolling Average of U.S. Transit Ridership and Service,
Commuter Rail
Ridership Service
Service Supply
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5D
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ions
(Trip
s an
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RM
) 12-Month Rolling Average of U.S. Transit Ridership and Service, Heavy Rail
Ridership Service
0
5
10
15
20
25
30
35
40
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Mill
ions
(Trip
s an
d V
RM
) 12-Month Rolling Average of U.S. Transit Ridership and Service, Light Rail
Ridership Service
Framework for Understanding Changes in Transit Ridership
3. Competition Communication Substitution for Travel Trip making levels (telecommuting, e-commerce, distant learning, online
banking etc.) TNC availability/LOS/price Bike/Bikeshare Auto Cost
• Fuel Cost • Purchase/Lease/Finance Cost • Parking Cost/Other Auto Costs
Roadway Congestion/Speed
$0.00
$0.50
$1.00
$1.50
$2.00
$2.50
$3.00
$3.50
$4.00
0
2,000
4,000
6,000
8,000
10,000
12,000
Aver
age
U.S
. Gas
Pric
e
Unl
inke
d Pa
ssen
ger T
rips
(Mill
ions
) U.S. Average Gas Price U.S. Ridership
*Inflation adjustment performed using Bureau of Labor Statistics inflation calculator using CPI, UPT for 2015 and 2016 from Bureau of Transportation Statistics, Gas prices from EIA
Gas Prices and Transit Ridership, 1994-2016
Ridership trends are context specific and vary significantly across geography/property.
The reasons for soft ridership differ across contexts with telecommuting, TNC’s, service reliability, auto ownership trends, fares, and other factors having different impacts in different markets.
Transit has historically had the lowest mode loyalty (mode of last resort in many contexts).
If declining fare revenues and/or dampened public willingness to increase subsidies result from soft ridership, the downward spiral of transit ridership may continue.
Key Issues – Travel Behavior
Strong employment growth and growing real income could continue to undermine transit dependency and jeopardize ridership. Urban civility may influence future ridership trends. Demographic trends in proximity to transit services (TOD) will influence
future ridership. Increasing roadway congestion could favor premium transit services but
undermine mixed traffic transit operations. System condition and quality of industry execution may influence ridership.
Key Issues – Travel Behavior
Is there an inflection point where service becomes more attractive to choice travelers?
Ride
rshi
p
Pr
oduc
tivity
Accessibility Speed
Frequency Convenience, etc.
?
Key Issues – Strategic
Density
The disconnect between the beneficiaries of transit services and the sources of funding for transit may impede the future financial sustainability of transit.
General Public
Funding Sources Beneficiaries
Adjacent Landholders
Riders
Key Issues – Strategic
Key transportation goals 1. Mobility 2. Economic competitiveness 3. Resource efficiency
May be best addressed with multiple • Technologies and services • Mixes of public and private providers • Different pricing and funding strategies
Today’s modal silos will disappear – we won’t worry about the future of
transit or transit ridership but instead worry about mobility.
Key Issues – Strategic