3/29/2018

1

Trends in Travel Behavior and  

Transit Ridership

CUTR WebinarThursday, March 29, 2018

Steven E. Polzin, PhD.

Outline

What is going on with travel

Trends and underlying causes of transit ridership decline

Implications going forward

3/29/2018

2

U.S. Context and Travel Trends2015/2014 2016/2015 2017/2016 YTD Months Source

U.S. Population 0.8% 0.5% 0.7% - Census

Total Employment 1.7% 1.7% 1.3% 12 BLS

Real GDP 2.9% 1.5% 2.3% 12 BEA (1st est.)

Gas Price -29.3% -14.8% 15.1% 12 EIA

Registered Cars andLight Trucks 2.1% 1.5% 3.0% 12 proj. Hedges Co.

Light Vehicle Sales 5.8% 0.1% -1.8% 12 BEA

Count of Zero-VehicleHouseholds -1.0% -1.9% Census

VMT 2.3% 2.4% 1.2% 12 FHWA

Public Transit Ridership -1.0% to -2.2% -2.3% to -1.6% -3.1, -2.6% 9, 12 APTA and NTD

Amtrak Ridership (FY) -0.3% 1.9% 1.9% 12 Amtrak

Airline Passengers 5.3% 3.9% 3.5% 11 USDOT, BTS

As of March 27, 2018

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-

92N

ov-9

2Sep

-93

Jul-

94M

ay-9

5M

ar-9

6Ja

n-97

Nov

-97

Sep

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Jul-

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ay-0

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-02

Sep

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Jul-

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Nov

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Sep

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Jul-

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Nov

-12

Sep

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Nov

-17

VM

T pe

r Cap

ita,

Ann

ual

Vehi

cle-

Dis

tanc

e Tr

avel

ed (

Bill

ion

Mile

s)

Annual Vehicle-Distance Traveled (Billions)

VMT per Capita

National VMT and VMT per Capita Trend, Moving 12‐Month Total, 1992–2016

8 year reprieve

3/29/2018

3

0

20

40

60

80

100

120

140

160

180

200

0

5

10

15

20

25

1917

1921

1925

1929

1933

1937

1941

1945

1949

1953

1957

1961

1965

1969

1973

1977

1981

1985

1989

1993

1997

2001

2005

2009

2013

2017

Ann

ual T

rips

per

Cap

ita

Ann

ual R

ider

ship

, Bill

ions

Rides, Billion Per Capita Rides

U.S. Transit Ridership and Ridership per Capita

16.0

17.0

18.0

19.0

20.0

21.0

22.0

23.0

24.0

6.0

6.5

7.0

7.5

8.0

8.5

9.0

JAN

08M

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ip, H

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Mil

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US Florida

U.S. Transit Ridership, Fixed Route, 12‐Month Rolling Average

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4

Top 40 UZAs by 2016 Transit Ridership, 2014‐2016 Change (Millions)

Top 40 urban areas make up 83.9% of U.S. ridership decline from 2014‐2016

Source: NTD Monthly Raw Database

Miami‐Dade Transit

‐14.653, ‐13.4%

Broward County Transit

‐6.302, ‐16.6%

Central FL RTA‐3.011, ‐10.4%

Hillsborough Area Rapid Transit‐1.081, ‐7.2%

Jacksonville Transportation Authority

+0.491, +4.0%

Pinellas SuncoastTransportation 

Authority‐1.826, ‐12.9%

PalmTran‐2.479, ‐20.8%

Gainesville RTS‐1.272, ‐11.8%

South Florida RTA‐0.150 ‐1.5%

City of Tallahassee‐0.650, ‐15.0%

Top 10 Agencies in Florida by 2016 Transit Ridership, 2013‐2016 Change (Millions)

Top 10 agencies make up 87.7% 

of Florida ridership from 2013‐2016

Source: NTD Monthly Raw Database

3/29/2018

5

9.0%

5.1%

2.7%

0.6%

1.2%

5.0%

0%

2%

4%

6%

8%

10%

12%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Mode Share, U

sual Commute   Car, truck, or van ‐‐

carpooled  Public transportation

  Walked

  Bicycle

  Other means

  Worked at home

Declining Carpooling and Growing Work‐at‐Home Dominate Trends  

10 year trend – 

2017‐2007

3‐year trend – 

2017‐2014

1 year trend – 

2017‐2016

Trending – Q4 2017 ‐ 

Q4 2016

All bus ‐15.2% ‐11.3% ‐5.1% ‐3.4%

Light rail (LR & SR) 20.7% 1.4% ‐0.8% ‐3.6%

Commuter rail 5.6% ‐1.3% ‐1.7% ‐1.3%

Heavy rail 9.8% ‐3.8% ‐0.4% 1.2%

Demand Response (DR‐DT) 10.4% ‐1.3% ‐0.5% 0.2%

Total ‐3.4% ‐7.1% ‐2.8% ‐1.4%

All bus ‐3.5% 3.7% 0.5% 0.3%

Light rail 54.9% 17.4% 6.8% 5.2%

Commuter rail 16.5% 1.1% 0.9% 1.3%

Heavy rail 7.8% 3.0% 1.8% 0.7%

Demand Response 15.5% 1.2% 0.1% 0.8%

Total 4.7% 3.2% 0.9% 0.7%

National

Service miles

Transit Ridership and Service Summary ‐ National

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6

Transit Ridership and Service Summary ‐ Florida

All bus ‐18.4% ‐20.5% ‐7.6% ‐5.6%

Light rail ‐50.0% 2.5% ‐4.1% 2.7%

Commuter rail 22.4% ‐2.4% 2.0% 6.5%

Heavy rail 15.3% ‐9.4% ‐6.7% ‐3.8%

Demand Response ‐0.2% 6.6% 4.3% 6.4%

Total ‐15.1% ‐18.6% ‐7.0% ‐4.9%

All bus ‐4.6% 1.2% ‐0.8% ‐1.9%

Light rail ‐20.2% 2.4% ‐1.7% ‐16.6%

Commuter rail 270.2% 1.9% 1.1% 7.7%

Heavy rail ‐9.0% ‐7.5% ‐8.9% ‐18.8%

Demand Response 9.1% 17.1% 5.8% 5.7%

Total 0.8% 5.7% 1.0% 5.7%

Florida

Ridership

Service miles

10 year trend – 

2017‐2007

3‐year trend – 

2017‐2014

1 year trend – 

2017‐2016

Trending – Q4 2017 ‐ 

Q4 2016

Where are We Headed?

2012‐2014

2018 

?

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

2015‐2017

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?

3/29/2018

7

Framework for Understanding Changes in Transit Ridership

1.  Demographics and Land‐Use

3.  Competition

2.  Transit Service Quality

How much of ridership’s change is explained by these factors?

Demand

Supply

Framework used in Metro analysis

Considers agency control

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8

Framework for Understanding Changes in Transit Ridership

1. Demographics and Land‐Use Age

Geographic Distribution across Metros – Migration and Growth Trends, International Migration Trends

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

3.23.5

4.04.3 4.2

4.03.6

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+

Tirps per person per day

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+Share of trips taken via transit

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+

Persons (M

illions)

2015

2010

2000

1990

1980

Aging Population has a Negative Impact on Ridership

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9

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 PopulationNumeric Change

Percent Change

Transit Commute Share 2015

County PopulationNumeric Change

Percent Change

Transit Commute

Share 2015

Maricopa County,Arizona

4,242,997 81,360 1.95 2.3%Cook County,Illinois

5,203,499 -21,324 -0.41 18.8%

Harris County,Texas

4,589,928 56,587 1.25 2.8%Wayne County,Michigan

1,749,366 -7,696 -0.44 2.5%

Clark County,Nevada

2,155,664 46,375 2.2 4.2%Baltimore city,Maryland

614,664 -6,738 -1.08 19.6%

King County,Washington

2,149,970 35,714 1.69 12.6%Cuyahoga County,Ohio

1,249,352 -5,673 -0.45 5.1%

Tarrant County,Texas

2,016,872 35,462 1.79 0.6%Suffolk County,New York

1,492,583 -5,320 -0.36 6.8%

Riverside County,California

2,387,741 34,849 1.48 1.4%Milwaukee County,Wisconsin

951,448 -4,866 -0.51 6.2%

Bexar County,Texas

1,928,680 33,198 1.75 2.6%Allegheny County,Pennsylvania

1,225,365 -3,933 -0.32 9.1%

Orange County,Florida

1,314,367 29,503 2.3 3.2%San Juan County,New Mexico

115,079 -3,622 -3.05 0.3%

Dallas County,Texas

2,574,984 29,209 1.15 2.9%St. Louis City,Missouri

311,404 -3,471 -1.1 9.7%

Hillsborough County,Florida

1,376,238 29,161 2.16 1.7%Jefferson County,New York

114,006 -3,254 -2.78 0.0%

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.

3/29/2018

10

229

3810

0

50

100

150

200

250

300

An

nu

al T

ran

sit

Trip

s P

er

Per

son

Vehicles in Household 0 1 2+ Total

Change in Population(5 and up), 2014-2016

-1.094 million -1.440 million +5.360 million +4.265 million

Estimated Transit Trip Change

-251 million -55 million +67 million -239 million

Total Population(5 and up), 2016

19.036 million 73.889 million 221.115 million 295.004 million

Each Fewer Resident in a Zero-Vehicle Household is Estimated to Reduce Annual Transit Trips by 191

Impact of Greater Auto Availability

Note: Fixed-route transit ridership was 10,331 million in 2014 and 9,881 million in 2016, declining 449 million trips.

Transit trip rates based on 2009 National Household Travel Survey and Census data suggest 240 million, or 53%, of the decline is explained by changes in vehicle availability.

Sources:2009 NHTS,U.S. Census,NTD

191

Zero‐Vehicle Household Trend

VEHICLES AVAILABLE – U.S.

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

No vehicles available

8.70% 8.80% 8.90% 9.10% 9.30% 9.20% 9.10% 9.10% 8.90% 8.70%

• Nearly half of all transit trips are made by residents of zero‐vehicle households – 44.6% in 2001 NHTS, 48.1% in 2009 NHTS,  43.0% 

in 2017 NHTS

• We do not know what share of zero‐vehicle households are zero‐vehicle by choice, law, physical/medical condition, or income

• The share of zero‐vehicle households ranges from 4% in Utah to 12.6% in Massachusetts then 29% in New York and 37.3% in DC

choice

legal

medical

income

8.7%

?

?

?

?

3/29/2018

11

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 Users Percent Change from 2002

Ridership Percent Change from 2002

Percent Change U.S. Transit Ridership and SNAP Enrollment

Ridership Percent Change from 2002

SNAP Users Percent Change from 2002

Other Hypothesized Demographic Factors

Resumption of suburban growth trend

International immigrants may have a different demographic profile than in the past

International immigrants may be arriving at, or moving to, less transit intensive areas

Undocumented immigrant drivers license authorization may be spurring auto ownership

3/29/2018

12

Are Core Values that Impact Travel Changing?

Do we value autonomy, privacy, flexibility, convenience, etc. more than in the past?

Money 

Cost

Reliability

Travel 

BehaviorComfort

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/mentally 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.)

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13

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

$1.80

Average Fare Reven

ue 

per Passenger Trip per Passenger Mile

Pre 2014 data from APTA Fact Book, Post 2014 data from NTD

Service Supply

0

1

2

3

4

5

6

7

8

9

10

DE

C02

AP

R03

AU

G03

DE

C03

AP

R04

AU

G04

DE

C04

AP

R05

AU

G05

DE

C05

AP

R06

AU

G06

DE

C06

AP

R07

AU

G07

DE

C07

AP

R08

AU

G08

DE

C08

AP

R09

AU

G09

DE

C09

AP

R10

AU

G10

DE

C10

AP

R11

AU

G11

DE

C11

AP

R12

AU

G12

DE

C12

AP

R13

AU

G13

DE

C13

AP

R14

AU

G14

DE

C14

AP

R15

AU

G15

DE

C15

AP

R16

AU

G16

DE

C16

AP

R17

AU

G17

Hun

dred

s of

Mill

ions

(T

rips

and

VR

M)

12-Month Rolling Average of U.S. Transit Ridership and Service, Fixed Route

Ridership Service

3/29/2018

14

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

DE

C02

MA

Y03

OC

T03

MA

R04

AU

G04

JAN

05JU

N05

NO

V05

AP

R06

SE

P06

FE

B07

JUL0

7D

EC

07M

AY

08O

CT

08M

AR

09A

UG

09JA

N10

JUN

10N

OV

10A

PR

11S

EP

11F

EB

12JU

L12

DE

C12

MA

Y13

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T13

MA

R14

AU

G14

JAN

15JU

N15

NO

V15

AP

R16

SE

P16

FE

B17

JUL1

7Hun

dred

s of

Mill

ions

(T

rips

and

VR

M)

12-Month Rolling Average of U.S. Transit Ridership and Service, Metro Bus

Ridership Service

Service Supply

Service Supply

0

5

10

15

20

25

30

35

40

45

DE

C02

MA

Y03

OC

T03

MA

R04

AU

G04

JAN

05JU

N05

NO

V05

AP

R06

SE

P06

FE

B07

JUL0

7D

EC

07M

AY

08O

CT

08M

AR

09A

UG

09JA

N10

JUN

10N

OV

10A

PR

11S

EP

11F

EB

12JU

L12

DE

C12

MA

Y13

OC

T13

MA

R14

AU

G14

JAN

15JU

N15

NO

V15

AP

R16

SE

P16

FE

B17

JUL1

7

Mill

ions

(T

rips

and

VR

M)

12-Month Rolling Average of U.S. Transit Ridership and Service, Light Rail

Ridership Service

3/29/2018

15

Service Supply

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5D

EC

02M

AY

03O

CT

03M

AR

04A

UG

04JA

N05

JUN

05N

OV

05A

PR

06S

EP

06F

EB

07JU

L07

DE

C07

MA

Y08

OC

T08

MA

R09

AU

G09

JAN

10JU

N10

NO

V10

AP

R11

SE

P11

FE

B12

JUL1

2D

EC

12M

AY

13O

CT

13M

AR

14A

UG

14JA

N15

JUN

15N

OV

15A

PR

16S

EP

16F

EB

17JU

L17Hun

dred

s of

Mill

ions

(T

rips

and

VR

M)

12-Month Rolling Average of U.S. Transit Ridership and Service, Heavy Rail

Ridership Service

0

5

10

15

20

25

30

35

40

45

DE

C02

MA

Y03

OC

T03

MA

R04

AU

G04

JAN

05JU

N05

NO

V05

AP

R06

SE

P06

FE

B07

JUL0

7D

EC

07M

AY

08O

CT

08M

AR

09A

UG

09JA

N10

JUN

10N

OV

10A

PR

11S

EP

11F

EB

12JU

L12

DE

C12

MA

Y13

OC

T13

MA

R14

AU

G14

JAN

15JU

N15

NO

V15

AP

R16

SE

P16

FE

B17

JUL1

7

Mill

ions

(T

rips

and

VR

M)

12-Month Rolling Average of U.S. Transit Ridership and Service, Commuter Rail

Ridership Service

Service Supply

3/29/2018

16

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

Ave

rag

e U

.S. G

as P

rice

Un

linke

d P

asse

ng

er T

rip

s (M

illio

ns) 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

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Ridership trends are context specific and vary significantly across geography.

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).

Declining fare revenues and/or dampened public willingness to increase subsidies resulting from soft ridership could contribute to continuing declines in ridership.

Key Issues – Travel Behavior

Influences on Transit Choice (Hypothesized)

Economic Status

TNC Availability

Car Affordability

E‐commerce, Telework

Safety, Reliability, Quality

Gas Price

Fares

Speed

Geograp

hic and Economic Distribution of 

Population

Service availability

Gentrification/Housing Affordability

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Wild Guess as to Attribution of Causes of Ridership Decline

Increased auto availability, 53

Aging, 0.5

Migration trends/gentrification, 2.23 Transportation network 

companies (Uber, Lyft), 6

Telecommuting/e‐commerce, etc., 9

Bikeshare, carshare, 1

System safety/reliability, 8

Personal safety/cleanliness, 8

Gas prices, 7

Service supply, 0

Fares, 1

Leap year, 0.27Weather, 2

Parking cost/availability, 0

Commuter benefits program changes, 0

Enhanced traveler expectations, 1

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

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Is there an inflection point where service becomes more attractive to choice travelers?

What transit quality of service is required to make it attractive?

What transit service concepts are sustainable in low to moderate density dispersed activity environments?

Ridership 

Productivity 

Accessibility 

Speed 

Frequency Convenience, etc. 

?

Key Issues – Strategic

What do These Curves Really Look Like?

Better Service attracts travelers but capacity

overwhelms market size and resources unless

densely developed and well funded

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

60 57.5 55 52.5 50 47.5 45 42.5 40 37.5 35 32.5 30 27.5 25 22.5 20 17.5 15 12.5 10 7.5 5 2.5Probab

ility of Taking Tran

sit

Minutes between Vehicles

Mode Share on Transit

CaptiveChoice

0%

5%

10%

15%

20%

25%

30%

60 57.5 55 52.5 50 47.5 45 42.5 40 37.5 35 32.5 30 27.5 25 22.5 20 17.5 15 12.5 10 7.5 5 2.5

Pro

bab

ilit

y o

f T

akin

g T

ran

sit

Minutes between Vehicles

Probability of a Given Trip Being on Transit for Choice Traveler

Transit expansion fails to attract many new travelers?

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20

Research on Ridership Trends

APTA. “Understanding Recent Ridership Changes: Trends and Applications.” Policy Development and Research. Nov. 2017.

Agency Initiatives: “Falling Transit Ridership: California and Southern California.” UCLA Institute of Transportation Studies. Dec. 2017.

FDOT, Understanding Ridership Trends in Transit – in progress

TCRP J‐11/Task 28, Synthesis, “Analysis of Recent Public Transit Ridership Trends”, Georg Tech.   

Pending:

TCRP A‐43, “Recent Decline in Public Transportation Ridership: Analysis, Causes, Responses,” $400,000. 

TCRP H‐56, “Reinventing Transit Networks for a New Mobility Future,” $300,000. 

How Should Stakeholders Respond?

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[THIS PAGE INTENTIONALLY LEFT BLANK]

Key goals

1. Mobility 2. Resource efficiency 3. Economic 

competitiveness 

New Technologies are Leading to New Mode Concepts and Business Models  

May be best addressed with multiple 

1. Technologies and services 

2. Mixes of public and private providers 

3. Different pricing and funding strategies 

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22

Today’s modal silos will disappear 

We won’t worry about the future of transit but instead worry about the future of mobility

Upcoming seminar

CUTR Webcast Series Presents:

Understanding the Effects of Demographic and Socio-Economic Factors on Public

Transit Ridership Trends

Kurt LehmannGraduate Research AssistantCUTR · USF

April 12th · 12pm-1pm

More Information: https://www.cutr.usf.edu/2018/

3/29/2018

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You may find the new book of interest. I was the principal author of Chapter 5, Upgrading Transit for the Twenty‐First Century, of the recently released text, Three Revolutions Steering Automated, Shared, and Electric Vehicles to a Better Future. https://islandpress.org/book/three‐revolutions

If you’d like to purchase a copy of the book from Island Press, use the code 4SPERLING, which is good for a 20% discount. You can also order it from Amazon, Barnes and Noble, and your local independent bookseller.

http://scholarcommons.usf.edu/jpt/vol21/iss1/Joel Volinski  Prologue     Reflections on the Future of Public Transportation

Dan Boyle  The Future of TransitRalph Buehler  Can Public Transportation Compete with Automated and Connected Cars?Graham Currie  Lies, Damned Lies, AVs, Shared Mobility, and Urban Transit FuturesJill Hough and Ali Rahim Taleqani Future of Rural TransitSteven E. Polzin  Just Around the Corner: The Future of U.S. Public TransportationKari Watkins  Does the Future of Mobility Depend on Public Transportation?Carol Schweiger Improved Mobility through Blurred LinesSusan Shaheen and Adam Cohen Is It Time for a Public Transit Renaissance?: Navigating Travel Behavior,

Technology, and Business Model Shifts in a Brave New WorldEric Schreffler Better Integrating Travel Choices into Future Urban Mobility Systems: The Day

the Highways Stood StillJerome Lutin Not If, but When: Autonomous Driving and the Future of TransitMichael Manville, Brian D. Taylor, and Evelyn Blumenberg

Transit in the 2000s: Where Does It Stand and Where Is It Headed?Jarrett Walker  To Predict with Confidence, Plan for Freedom

The Future of Public Transportation

3/29/2018

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Thank You!