factors affecting passenger travel...

November 18,

2015

FACTORS AFFECTING

PASSENGER TRAVEL

DEMAND IN THE UNITED

STATES

Dr. Giovanni CIRCELLAInst itute of Transpor tation Studies, UC Davis

gcircel [email protected]

1

Planning Horizons Seminar

Caltrans Headquarters, Sacramento, CA

NCST White Paper:

• Draft in November 2015

• Final by end of 2015

2

Vehicle Miles Traveled (VMT) per capita has declined in the United States

since the early 2000s (but i t is increasing again in 2015).

Car travel seems to have decoupled from economic activity.

Sociodemographic trends in the U.S. society include smaller household

sizes, delayed childbearing and increased presence of immigrants.

Baby boomers are star ting to retire (e.g. they make fewer commuting

tr ips), and new generations (e.g. mil lennials) tend to own fewer vehicles

and have increased multimodality.

There is a resurgence of the central par ts of c it ies, and increased

availabil ity of t ravel options also in non -central areas.

The impact of new transportation technologies, e .g. shared mobility

services today, and autonomous vehicles in the future, is uncertain.

KEY POINTS

3

4

OUTLINE OF THIS PRESENTATION

CURRENT TRENDS IN TRAVEL DEMAND

FACTORS AFFECTING TRAVEL CHOICES

CONCLUSIONS AND POLICY CONSIDERATIONS

WE LIVE IN A TIME OF CHANGE: VMT…

5

Source: Federal Highway Administration (FHWA)

NOT ONLY IN THE UNITED STATES…

6

Source: Kuhnimhof et al., 2013

PEAK IN VMT PER CAPITA BY STATE

Source: Garceau et. al., 20147

TRAVEL DEMAND IN THE U.S.

Peak in Average Miles Driven (per person , per driver, per vehicle , per household) in 2004

Source: Sivak (2013), based on FHWA data

8

AUTO OWNERSHIP IN THE U.S.

Vehicles per household:

2.05 (2001; 2006)

Vehicles per licensed

driver: 1.16 (2001; 2006)

Vehicles per person:

0.79 (2006)

9

So

urc

e: S

iva

k, 2

01

3

Year

Vehicles per

person

Vehicles per

driver

Vehicles per

household

2000 0.754 1.116 2.031

2001 0.778 1.160 2.050

2002 0.768 1.137 2.021

2003 0.768 1.136 2.003

2004 0.780 1.148 2.038

2005 0.785 1.156 2.046

2006 0.786 1.156 2.050

2007 0.782 1.146 2.032

2008 0.778 1.135 2.025

2009 0.764 1.119 2.001

2010 0.745 1.097 1.961

2011 0.750 1.104 1.950

2012 0.745 1.104 1.931

2013 0.747 1.112 1.927

AUTO OWNERSHIP IN THE U.S.

10Source: American Community Survey data

In particular, in all large cities:Nationwide:

11

HOUSEHOLDS WITHOUT A CAR

Source: Sivak, 2013; American Community Survey data

Year Percentage

2005 8.87

2006 8.78

2007 8.72

2008 8.84

2009 8.90

2010 9.01

2011 9.29

2012 9.22

2013 9.07

2014 9.10

VMT per capita dropped while the number of trips increased

Person-trips made by car: 87.8% in 1990, 89.3% in 1995, 83.4% in 2009

Person-trips made by transit: 1 .8% in 1990, 1.9% in 2009

Person-trips by walking: 7.2% in 1990, 10.4% in 2009

Percent of commute trips by bicycling: 0.4% in 2000, 0.6% in 2008–2012

Increase in the number of households who do not own a car

MOBILITY TRENDS: OTHER MODES

Sources: Santos et al. 2011; McKenzie 2014; using NHTS and ACS Data 13

SUMMARY TRAVEL STATISTICS

Source: Santos et al., 2011

• Data: 1969-1995 (NPTS), 2001-2009 (NHTS)

14

MOBILITY TRENDS: VMT

-

2,000

4,000

6,000

8,000

10,000

12,000

-

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

Per

Cap

ita

VM

T

Tota

l V

MT

(T

rill

ion m

iles

)

VMT (Trillion) VMT per capita

15Source: FHWA and Census data; 2015 data based on monthly-

updated moving annual-average VMT data from FHWA

IT’S THE ECONOMY, RIGHT?

0

10,000

20,000

30,000

40,000

50,000

60,000

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

19

36

19

39

19

42

19

45

19

48

19

51

19

54

19

57

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

19

99

20

02

20

05

20

08

20

11

VMT per capita

GDP per capita ($2009)


?

OR OTHER FACTORS?

Income

Fuel prices

Traffic congestion

Aging population

Regional migration

Back-to-the city

Smartphones

Others

17

18

WHAT ARE THE REASONS BEHIND THESE

TRENDS?

Economic activity

Travel demand “decoupled” from economic growth

Growth in high income brackets

Changes in fuel prices

The reversal of urban sprawl

The growth of “urban” lifestyles and culture

Traffic congestion

Investments in public transit

Ageing of the population, decrease in household size and

households with children

Generational changes in travel attitudes and behavior

Adoption of technology

ANOTHER WAY TO LOOK AT IT…

How do we as individuals

and households make

choices about travel?

How and why are these

choices changing?

19

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=PGoTeYrnPfmZDM&tbnid=GJM-4_KXGY_MaM:&ved=0CAUQjRw&url=http://www.whalebalanced.com/thinking-out-loud/&ei=atEzUs_oLYjPiwKDpoHwCA&bvm=bv.52164340,d.cGE&psig=AFQjCNFEh5yhBV7PGDOffZdy2ihnq1p3ng&ust=1379213952548474

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=PGoTeYrnPfmZDM&tbnid=GJM-4_KXGY_MaM:&ved=0CAUQjRw&url=http://www.whalebalanced.com/thinking-out-loud/&ei=atEzUs_oLYjPiwKDpoHwCA&bvm=bv.52164340,d.cGE&psig=AFQjCNFEh5yhBV7PGDOffZdy2ihnq1p3ng&ust=1379213952548474

Long-term

ChoicesLifestyle

Residential

Location

Mid-term

ChoicesDriver’s license

Auto ownership

Short-term

ChoicesTrip frequency

Trip destination

Mode choice

NESTED CHOICES

20

Knowledge, perceptions

CHOICE PROCESS

Set of

choices

available

Qualities of

choices

available

Value placed

on different

qualities

Drive alone

Shared ride

Bus

Rail

Bicycle

Walk

Skateboard

Cost

Time

Comfort

Safety

Cost

vs.

Time

vs.

Comfort

vs.

Safety

21

22

WHAT ARE THE REASONS BEHIND THE

OBSERVED TRAVEL CHOICES?

23



24



• Are the current trends a temporary or lasting phenomenon?

• Will, after removing some causes (such as the economic crisis), the growth in the use of private vehicles resume as before?

• Continuum of travel , only part of which translates into car travel:

• Empirical findings suggest a complex pattern of partial effects

• Some of these effects may extend to future years

TO

TAL T

RA

VE

L

25

PEAK CAR IN THE UNITED STATES?

CAR TRAVEL NON-MOTORIZED TRAVEL

MODE SHARE FOR CAR

ECONOMIC

GROWTH

AND GDP

GAS

PRICESURBAN

FORM

SOCIO-

DEMOGRAPHICS

AND

GENERATIONAL

EFFECTS

IMPACT OF

TECHNOLOGY

SHARED

MOBILITY

27

ECONOMIC GROWTH AND GDP


0

10,000

20,000

30,000

40,000

50,000

60,000

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

19

36

19

39

19

42

19

45

19

48

19

51

19

54

19

57

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

19

99

20

02

20

05

20

08

20

11

VMT per capita

GDP per capita ($2009)


Income growth only for higher income groups


0

10

20

30

40

50

60

70

Pe

rce

nt

Sh

are

of

Inco

me

Percent Share of Income by Quintile

Lowest Quintile

Second Quintile

Third Quintile

Fourth Quintile

Highest Quintile

Source: US Census (including ACS data)29

Income growth only for higher income groups

Impact on travel demand:

Non-linear relationship with income; income grows with income for lower income classes, but plateaus at higher levels; potential substitution with faster modes (air travel)

UNCERTAINTY: if trends in income inequality continue, slower growth in per-capita travel is expected


30Sources: Holtzclaw et al. 2002; Salon et al. 2013; Boarnet et al. 2011

Stronger growth in financial, technological and service sectors


Does a $1 of added value in the computer or financial sectors generate similar trips for commuting or other purposes to an equivalent amount in manufacturing?

UNCERTAINTY: changes to travel patterns; unclear effects on the spatial patterns of commuting vs. non commuting trips


31

From a different perspective:

Economic factors probably continue to play a role in the generation of travel, but the effect is downsized by current mutated conditions.

If economic factors operate in the same direction as demographic and other trends, the effects are amplif ied.

Economic effects may operate against dominant demographic trends, with the resulting effects on VMT largely canceling out.


32

CAR TRAVEL

33

GAS PRICES

GAS PRICES

0

0.5

1

1.5

2

2.5

3

3.5

4

-

2,000

4,000

6,000

8,000

10,000

12,000

19

71

19

73

19

75

19

77

19

79

19

81

19

83

19

85

19

87

19

89

19

91

19

93

19

95

19

97

19

99

20

01

20

03

20

05

20

07

20

09

20

11

20

13

Pri

ce o

f G

aso

line

(20

13

$)

VM

T p

er c

apit

a

VMT per capita Retail Gasoline Price (Constant 2013 dollars/gallon)

Source: EIA AEO, 201434

Historically, travel demand considered inelastic with respect

to gas price

Larger impacts in times of larger fluctuations in prices


In the short term: rather limited effect on VMT and mode choice

GAS PRICES

35

Historically, travel demand considered inelastic with respect

to gas price

Larger impacts in times of larger fluctuations in prices


In the medium term: impact on vehicle ownership and vehicle

choice

GAS PRICES

36

U.S. Energy Information Administration expects gasoline

prices to remain low: 0.3% annual growth rate (adjusted for

inflation).

Diminishing effects on future VMT, also due to increased fuel

efficiency and increased adoption of alternative fuels.

GAS PRICES

37Source: EIA’s Annual Energy Outlook, 2015

CAR TRAVEL

38

URBAN FORM

“Resurgence” of downtown

Access to alternative modes of travel

Mixed land use and transit oriented development

VMT changes mainly associated with very high -density areas


Urban residents travel less by car; increased availability of public transportation and walk/cycle options; lower auto ownership rates (in the medium term)

UNCERTAINTY: Need to account for residential self -selection!

URBAN FORM AND TRANSPORTATION

SUPPLY

39Sources: Ewing and Cervero, 2010; Voulgaris et al., 2015; Cao et al. 2009

POPULATION DENSITY

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Urban Suburban Rural

1990 2000 2010

40Source: US Census (including ACS data)

41

MOBILITY TRENDS: URBAN FORM

• Growth in central areas in many

US cities (often much faster

than in suburbs)

• Increase of mixed-use housing

• This is not (yet) the end of

suburbs…

Figure source: Denver Infill, 2014, denverinfill.com/blog)

42

MOBILITY TRENDS: URBAN FORM

• Population Growth (2000-2010)

in Midtown 15x faster than City of

Atlanta (45x in “Core”)

• Many young, high-income adults

• Prevalence of large condo/apt.

buildings

• Large proportion of very recent

(<10 y.o.) buildings

INVESTMENTS IN PUBLIC TRANSIT AND

ACTIVE MODES OF TRANSPORTATION

43

L.A. will add bike and bus lanes, cut car lanes in sweeping policy shift

“City leaders say the plan reflects a newfound view that simply widening streets is no longer feasible or, in many

cases, desirable. They contend that if even a small share of motorists change their travel behavior, choosing

alternatives to the car, the city can make a big dent in the overall number of miles traveled.” (August 11, 2015)

Source: http://www.latimes.com/local/lanow/la-me-ln-mobility-plan-20150811-story.html

Cities once associated with image of car-dependence are undergoing massive efforts to expand public transit

Improved pedestrian and bicycling infrastructure

Improved multimodal accessibility also in lower-density areas

Efforts for sustainability -inspired communities and TODs (e.g. California SB 375’s Sustainable Community Strategies )

Indirect effects on promoting awareness and perceived utility of non-car travel alternative modes

Increased tendency towards multimodality in U.S. Population

44

INVESTMENTS IN PUBLIC TRANSIT AND

ACTIVE MODES OF TRANSPORTATION

Sources: McKenzie, 2014; Buehler and Hamre, 2015

MULTIMODALITY

45

SOCIODEMOGRAPHIC TRENDS

Lifecycle effects

Period effects

Cohort effects

46


Slow population growth

Smaller household size and changes in family structure


47

42.9 44.3

30.723.5 20.2

4.3 4.1

7.2

9.29.6

33.4 30.5

30.2

28.128.2

9.46.2

5.6

7.1 8.5

7.8 13.4

22.625.8 26.7

2.2 1.7 3.8 6.1 6.8

0

10

20

30

40

50

60

70

80

90

100

1940 1960 1980 2000 2010

Pe

rce

nt

dis

trib

uti

on

of

ho

use

ho

ld t

yp

e

Married couples with children Single parents with children

Married couples without children Household with other family

One person Other non- family household

Source: US Census Data

Households with

children drive more

than those without




48Source: Blumenberg et al. (2012), using NHTS data



Gender gap not causing VMT growth

Larger prevalence of immigrants

Increased urban lifestyles among some population segments


Households without children travel less by car; f irst generation

immigrants travel dif ferently from U.S. born individuals; current

trends point to a decrease in per-capita VMT


49Sources: Zmund et al., 2014; Polzin et al., 2014; McDonald, 2015

CAR TRAVEL

50

GENERATIONAL EFFECTS

Change in

household

composition

Changes

observed

among all age

groups

DEMOGRAPHIC TRENDS AND VMT

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

1969 1977 1983 1990 1995 2001 2009

Ave

rag

e a

nn

ua

l V

MT p

er

lice

nse

d d

rive

r

16 to 19 20 to 34 35 to 54 55 to 64 65+

51Source: NHTS and FHWA data

Baby boomers transitioning into retirement

Higher income generation

Increased amount of discretionary funds for leisure trips

Less need for space in residential location


Fewer commuting trips; potential increase in less frequent long-

distance trips; unlikely to leave suburbs as they age

BABY BOOMERS

52Sources: Farber et al. 2011; Lee et al., 2014

CAR TRAVEL

Active workers

Often live with children

Telecommute more often

Increased adoption of e -commerce


Increased multimodality; probable decrease in future VMT as an

effect of lifecycle effects

GENERATION X

53Sources: LeVine and Jones, 2012; McDonald, 2015

CAR TRAVEL

Delay in marriage, childbearing and other l ife events

High adoption of technology

Credited to have higher preference for urban areas

Delay in driver’s l icensing compared to previous generations


Reduced use of private cars, increased multimodality, unclear

long-lasting trends of millennials travel

54

MILLENNIALS (OR GENERATION Y)

CAR TRAVEL

Sources: Blumenberg et al., 2102, 2014; Polzin et al., 2014;

McDonald, 2015; Ralph, 2015; Circella et al., 2015

POTENTIAL FACTORS AFFECTING THE

MOBILITY OF MILLENNIALS

55Source: Blumenberg et al., 2014

Source: http://www.pewsocialtrends.org/2014/03/07/millennials-in-adulthood/

WHAT ELSE DO WE KNOW…

56

A UBER-FRIENDLY GENERATION?

57

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

I have never

heard of it

I have heard of it

but I’ve never

used it

I use it when

traveling away

from home

I use it in my

hometown/city

I use it in my

hometown &

away from home

Familiarity with and usage of on-demand ride services (e.g. Uber, Lyft)

Millennials

Gen X

Source: Circella et al., 2015

Less studied than previous generations ( to date)

High use of technologies and social media

Entering soon into driving age


Unclear effects on VMT; many trends from millennials might

extend among members of Generation Z; supposed similarities

with silent generation

58

GENERATION Z

CAR TRAVEL ?

59

IMPACT OF TECHNOLOGY

Increase in individual users of ICT

Adoption of telecommuting

E-commerce

Online social media


Most likely increase VMT; unclear impact of telecommuting on

travel; increased alternatives for mode choice; probable slight

increase in per-capita VMT.

IMPACT OF TECHNOLOGY

60Sources: Mokhtarian, 2009; Zhu, 2012; Wilson et al. 2015

CAR TRAVEL

Over 90% of

Americans own a

cell phone and

nearly 70% own

a smartphone

Some trip

substitution,

some

complementary

SMARTPHONES AND TRAVEL

0

10

20

30

40

50

60

70

80

90

100

Ma

y-0

0

No

v-0

0

Ma

y-0

1

No

v-0

1

Ma

y-0

2

No

v-0

2

Ma

y-0

3

No

v-0

3

Ma

y-0

4

No

v-0

4

Ma

y-0

5

No

v-0

5

Ma

y-0

6

No

v-0

6

Ma

y-0

7

No

v-0

7

Ma

y-0

8

No

v-0

8

Ma

y-0

9

No

v-0

9

Ma

y-1

0

No

v-1

0

Ma

y-1

1

No

v-1

1

Ma

y-1

2

No

v-1

2

Ma

y-1

3

No

v-1

3

Ma

y-1

4

No

v-1

4

Ma

y-1

5

Pe

rce

nt

Mo

bile

de

vice

ow

ne

rsh

ip

Cellphone Smartphone

61Source: Pew Research Center, 2015

62

SMARTPHONES AND TRAVEL

Flexibility in activities Flexibility in travel Productive travel time

Source: http://www.bizjournals.com/sanfrancisco/blog/2015/03/leap-

transit-commuter-bus-san-francisco-loup.html

IMPACT ON MODE CHOICE

63

64

SHARED MOBILITY

CAR OWNERSHIP VS. SHARED MOBILITY

65

BIKE SHARING

66

Choice

Sets

Choice

Qualities

Value of

Qualities

Long-term Choices

Mid-term Choices

Short-term Choices

EXPANDING TRAVELER CHOICE

67

68

EXPANDING TRAVELER CHOICE

WHAT REPLACES WHAT?

69

Increasing number of services available in U.S. cities

Early studies report reduction in car ownership among carsharing members

Potential for expanding the catchment area of public transit

Eventual substitution with other means of travel


Uncertainty about dominant impact on VMT; bikesharing seems to reduce PT ridership in central areas; carsharing often reduces car ownership and use

70

WILL NEW OPTIONS MEAN

NEW TRAVEL?

Sources: Martin and Shaheen, 2011; Hallock and Inglis, 2015;

Shaheen et al., 2015

CAR TRAVEL ?

71

IMPACT OF ON-DEMAND RIDE SERVICES

ON USE OF OTHER MEANS OF TRAVEL

0% 10% 20% 30% 40% 50%

Other

It reduced the amount of

walking/biking I did

It increased my use of public

transportation by providing a ride

outside public transportation schedule

hours


transportation by providing a better

way to access public transportation

It increased the amount of


It reduced my use of public

transportation

It reduced the amount of driving I did

Millennials

0% 10% 20% 30% 40% 50%

Other




transportation by providing a

ride outside public

transportation schedule…


transportation by providing a

better way to access public

transportation

It increased the amount of


It reduced my use of public

transportation


driving I did

Generation X

SCAG

SANDAG

SACOG

NorCal and

OthersMTC

Central Valley

Source: Circella et al., 2015

72

THE FUTURE: DRIVERLESS VEHICLES?

73

CONNECTED AND AUTONOMOUS VEHICLES

Provide mobility for those who cannot drive

Increase road network capacity

Release latent demand

Reduce value of travel time


Probable increase in VMT if widely implemented; a lot will depend on policies and regulations

A White Paper from the National Center will focus on impact of autonomous vehicles on travel demand

74

CONNECTED AND AUTONOMOUS VEHICLES

Source: Fagnant and Kockelman, 2015; Krechmer et al., 2015;

Malokin et al., 2015

75

THE FUTURE OF TRANSPORTATION IN THE

21ST CENTURY…

VMT IN THE FUTURE?

“The aggregate trends discussed do not allow us to forecast with any

certainty the car use that we can expect in the future.”– Goodwin and Van Dender, 2013

?

-

2,000

4,000

6,000

8,000

10,000

12,000

19

36

19

40

19

44

19

48

19

52

19

56

19

60

19

64

19

68

19

72

19

76

19

80

19

84

19

88

19

92

19

96

20

00

20

04

20

08

20

12

76

ECONOMIC

GROWTH

AND GDP

GAS

PRICES

URBAN

FORM

SOCIO-DEMOGR./

GENERATIONAL

EFFECTS

IMPACT OF

TECHNOLOGY

SHARED

MOBILITY

?

The engine of growth of car travel has lost strength

Saturation level of auto ownership and car travel

Higher heterogeneity and uncertainty in travel patterns, due to increased accessibility, available choices and changing preferences

Future adjustments likely depend on what factors affecting demand, or combination of factors, prevail

Potential for policy to drive the change

Importance of policy that are robust to uncertainty

ROLE OF POLICY

78Sources: Van Dender and Clever, 2013; Goodwin and Van Dender, 2013;

Polzin et. al., 2014

ROLE OF POLICY

79

The goal is increased accessibility

80

NOT ALL VEHICLE TRIPS ARE “HIGH VALUE”

If driving is bad enough…

TIPPING THE BALANCE

If the options are good enough…

81

THANK YOU FOR YOUR

ATTENTION!

Dr. Giovanni CIRCELLAInst itute of Transpor tation Studies, UC Davis

gcircel [email protected]

mailto:[email protected]

factors affecting passenger travel...

Documents