Center for Urban Transportation Research | University of South Florida

Steven E. Polzin, PhD.

July 11, 2017

Vehicle Miles Traveled Trends and Implications for the US Interstate

Highway System

The National Academies of Sciences, Engineering, and Medicine Transportation Research Board

Future Interstate Study

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Disclaimer: “Prediction is very difficult, especially if it's about the future." Nils Bohr, Nobel laureate

How are we doing at forecasting:

Stock market?

Election results?

Retail hot sellers?

Movie/media hits?

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Factors Influencing Travel Demand

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Characteristics that Influence Travel Decisions

ENVIRONMENTAL IMPACT

FLEXIBILITY

COMFORT

SOCIAL IMPACT

IMAGE

MONEY COST

TIME COST

SAFETY

CONVENIENCE

RELIABILITY

HOUSEHOLD TRAVEL

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“…the current pace of change and uncertainty with regard to key factors that influence travel demand is unprecedented in the history of our Interstate System.”

Historic Considerations • Population • Demographic/household

characteristics • Geographic distribution • Economic conditions • Capital and operating/fuel costs • Modal traits/preferences

Emerging Considerations • Environmental/social values • Communication substitution for

travel • Emerging mobility options (TNC,

Bikeshare, carshare, etc.) • Driverless/autonomous vehicles and

mobility services

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Predicting Future Demand

1. Determine factors that impact demand. 2. Determine the relationship between those

factors and travel (and all the interrelationships).

3. Predict those factors into the future.

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Therefore: Uncertainty

• Uncertainty regarding our knowledge of travel behavior in the emerging contexts.

• Uncertainty regarding future demand – In total – By mode – By functional class/on the Interstate

• Uncertainty regarding future facility capacity – Amount of transportation infrastructure that will be

available – Throughput of a given facility

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National Annual VMT Trend and Population Trends, 1900–2016

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Popu

latio

n (1

,000

,000

)

VMT

(1,0

00,0

00)

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National VMT and VMT per Capita Trend, Moving 12-Month Total, 1990–2016

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VMT

per C

apita

, Ann

ual

Vehi

cle-

Dist

ance

Tra

vele

d (B

illio

n M

iles)

Annual Vehicle-Distance Traveled (Billion Miles) VMT per Capita

8 year reprieve

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National VMT and VMT per Capita, Percent Change from 1992

0%

5%

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Perc

ent C

hang

e fr

om 1

992

Annual Vehicle-Distance Traveled (BillionMiles) % change from 1992VMT per Capita % change from 1992

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Vehicle Miles of Travel Shares by Market Segment

Light Vehicles Heavy

Vehicles Total

Urban

64.56%

5.45% 70.0% Household-Based Public Vehicle, Utility, Service-

Based

55.52% 9.04%

25.46%

4.54% 30.0% Rural Household-Based Public Vehicle, Utility, Service-

Based

21.90% 3.56%

Total

77.42% 12.60%

90.02% 9.98% 100.0%

Sources: CIA 2013, Table 2-1, Commuting in Perspective; 2015 Highway Statistics, Tables VM2 and VM4

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Role of Urban and Rural Interstate Highways in Accommodating VMT

0%

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Urban Interstate as a share of total VMT

Rural Interstate as a share of total VMT

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Changes in US Interstate Extent and Use, 1980–2015

Centerline Miles Lane Miles VMT (M)

Urban Interstate

Change 9,848.1 56,279.5 379,944.3

Percent 106.9% 116.1% 235.6%

Rural Interstate

Change -2,914.9 -12,728.3 100,681.6

Percent -9.14% -9.7% 74.53% Note: Decline in centerline miles and lane miles for rural Interstate attributable to reclassification of

roadway segments to urban. As urban areas expand, more geography classified as urban. Source: Highway Statistic Series, Tables VM-202, HM-260, HM-220

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VMT

(tho

usan

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Average Daily Rural Interstate VMT/Lane Mile

Average Daily Urban Interstate VMT/Lane Mile

Average Daily VMT per Lane Mile, Urban and Rural

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Uncertainty Favors Seeking Robust Strategies and Testing against a Range of Conditions

(Merriam-Webster)

• robust d : capable of performing without failure under a wide range of conditions

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What Considerations go into Scenario Development?

• What consideration do we believe will be significant with respect to future travel demand?

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Land Use Context • Regional/national distribution • Density • Mix of land uses • Urban form • Urban/network design • Contiguousness of development

Travel Demand Local person travel Tourism/long trips Freight Commercial travel

Socio-Demographic Conditions Household/Person Characteristics Income/wealth levels and distribution Age/activity level Culture/values Racial/ethnic composition Immigration status/tenure Gender Family/household composition

Transportation Supply/ Performance Modal availability and non-travel options to carry out activity Modal performance

Cost Speed/congestion Safety, security Reliability Convenience Image, etc. Flexibility Environmental impact Multi-tasking opportunity

Legal/Political Climate Culture Technology Security Economy

Business, Governance, Institutional Context Scale of activity concentration Economic structure of service delivery (healthcare, education,

government services, etc.

Travel Impacts: Change Trip Frequency Change Destination Change Mode Change Path

Framework for Exploring Factors Influencing Travel Demand

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Population Growth Considerations

US Population Change by Census Region

Census Region Net Change 2000–2016

Northeast 4.88%

Midwest 5.51%

South 22.03%

West 21.30%

Source: Census Fact Finder, Table B01003

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US County Population Growth Trends, 2000–2016

Growth Category Number of Counties

Sum of Change

Percent of Counties

Percent of Growth

Counties that grew more than 25,000 377 37,783,846 12.00% 91.31%

Counties that grew more than 5,000 to 24,999 439 5,160,638 13.97% 12.47%

Counties that grew more than 1,000 to 4,999 574 1,443,389 18.27% 3.49%

Counties that grew less than 1,000 457 189,584 14.54% 0.46%

Counties that shrunk from 1 to 999 749 -325,475 23.84% -0.79%

Counties that shrunk from 1,000 to 4,999 472 -997,254 15.02% -2.41%

Counties that shrunk more than 5,000 to 24,999 59 -577,965 1.88% -1.40%

Counties that shrunk more than 25,000 15 -1,299,029 0.48% -3.14%

Total 3,142 41,377,734

Source: Census Fact Finder, Table B01003

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Population Growth Variation across US Counties

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Implication of Population Growth and Settlement Patterns

• Base growth around 0.7% per year for next few decades

• Growth highly concentrated in modest share of geography

• Growth highly concentrated in urban areas • Interstate capacity challenges exacerbated

by the relocating population (net relocation has approximated half of net growth).

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Aggregate analyses at the national level are inherently different from those that consider specific facilities. In the case of the latter, more granularity is not only possible but critical. Thus, the percentage increase in additional capacity to maintain performance will be larger than the average percent increase in roadway volumes.

Implication of Population Growth and Settlement Patterns

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Economic Growth Considerations

• The GDP – VMT relationship is changing

• Income distribution impacts travel demand

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National VMT & GDP Trends

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GDP

in B

illio

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f 201

6 U

S D

olla

rs

VMT

(bill

ions

)

VMT Total (Billions)

GDP in 2016 dollars ($Billions)

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Transportation Intensiveness of Economic Sectors

Sector Amount of Transportation Required to Produce $1 of

Output (2014)

Contribution to GDP

(2015, billions)

Natural Resources and Mining Sector 4.2¢ $500.9

Utilities Sector 4.6¢ $288.3 Construction 3.8¢ $716.9

Manufacturing 3.7¢ $2,167.8 Wholesale and Retail Trade 9.9¢ $2,130.1

Service Sectors: Information

Financial Professional/business Education and Health

Leisure and Hospitality Other

1.5¢ 0.8¢ 2.8¢ 1.6¢ 3.2¢ 2.9¢

$9,291.7

Government 4.7¢ $2,323.6 Source: “Industry Snapshots: Uses Of Transportation,” 2015, Bureau of Transportation Statistics, US

Department of Transportation

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National VMT & Household Income in Bottom 80% of US Households

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Tota

l Hou

seho

ld in

com

e of

Bot

tom

80%

in B

illio

ns

2015

VMT

(Bill

ions

)

VMT Total (Billions)

Household Income of Bottom 80% (2015 $Millions)

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Key Factors in Travel Demand

• Fuel Prices • Congestion/Travel Time • Induced Demand • Transportation Land Use • Automation – Self-Driving Vehicles

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How Fuel Prices Influence VMT

A change in fuel price results in changes in the cost of driving, which, in turn, leads to changes in the amount of driving or VMT. VMT is relatively insensitive to changes in fuel prices, (“inelastic”), especially in the short run. A study by Small and Van Dender estimates the fuel price elasticity of VMT in the US during 1966-2001 at -0.047 in the short term (≈20% decrease in fuel price results in ≈ 1% increase in VMT). The study estimates the long-run fuel price elasticity of VMT to be -0.22, almost five times as large as the short run value.

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How Travel Time Influences VMT

Travel Time Elasticity of VMT

Short run: -0.38 Long-run: -0.68 Lee, Douglass B., and Mark W. Burris (2005), “Demand Elasticities for Highway Travel, Appendix C,” Highway Economic Requirements System-State Version, Technical Report, Federal Highway Administration, p C-14.

Short run: -0.5 Long-run: -1.0 Urban Rural

Short-run -0.27 -0.67 Long-run -0.57 -1.33

Litman, Todd (2017), “Understanding Transport Demands and Elasticities,” Victoria Transport Policy Institute, p. 48.

• Congestion increases time cost of travel and discourages travel.

• With Self-driving vehicles, travel time will not be as important to travelers because they can be doing other things simultaneously.

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Induced Travel Induced travel is the increase in use of a transportation facility due to a reduction in the cost of travel that results from capacity expansion to an existing highway.

Recent evidence suggests a range of 0.3–0.6 for the short-run elasticity of VMT with respect to highway lane-miles. Thus a 100 percent increase in roadway lane miles could result in a near-term 30–60 percent increase in VMT. The long-run elasticity is estimated to range from 0.6–1.0, indicating that roadway expansion in congested environments might ultimately produce 60–100 percent more VMT as travelers took advantage of the new capacity in the short term and perhaps made residential and travel destination decisions in the long term that further increased their travel.

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Land Use Context – Per Capita VMT by Location Type

Urban Continuum Daily VMT per Capita (Ages

20–39) Urban 18.0

Second City 23.1 Suburban 27.1

Town and Country 32.7 Location in Urbanized Area

In an urban area 24.1 In an Urban cluster 25.7

In an area surrounded by urban areas 32.9

Not in urban area 35.2 Size of Urbanized Area

1 million + with subway or rail 20.2 1 million + w/o subway or rail 25.8

500,000–999,999 27.9 200,000–499,999 24.7

50,000–199,999 25.9 Not in urbanized area 32.4 Urban/Rural

Urban 24.3 Rural 35.2

Source: Polzin, S. E., et al., “The Impact of Millennials’ Travel Behavior on Future Personal Vehicle Travel,”

Energy Strategy Reviews (2014), http://dx.doi.org/10.1016/j.esr.2014.10.003

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Automation – Self-Driving Vehicles

• Technology changes are unique in that they affect both demand and supply

Technology Deployment and

Self-Driving Vehicles Impacts on

Transportation System Demand

Impacts on Transportation

System Capacity

• Scenario research suggests VMT impacts of automation ranging from -35% to plus 130%

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VMT Forecast Sources

• FHWA forecasts an annual average growth rate of 0.47 percent for light-duty vehicles, 1.50 percent for single-unit trucks, and 1.87 percent for combination trucks, and 0.61 percent for all vehicles combined during 2014-2044.

• DOE for its 2017 Annual Energy Outlook, projects an average annual growth rate of 0.70 percent for personal and light-duty fleet travel, 1.50 percent for light commercial truck travel, and 1.3 percent for freight truck travel during 2015-2050.

• 2015 AASHTO Bottom Line Report uses 1.0 and 1.4% per year VMT growth Scenarios.

• 2015 Status of the Nation's Highways, Bridges, and Transit: Conditions and Performance uses 1.04% per year growth in VMT.

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Role of Forecasts

• VMT forecasts can inform discussion regarding future Interstate System capacity requirements; however, financial and policy decisions, many made locally, will inevitably govern actual capacity expansion.

• The criticality of precision in VMT forecasts is muted by the fact that the Interstate System is part of a broader network of transportation facilities and services in which the consequences of failing to expand capacity are spread over a broader network.

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Average VMT Growth in Context

<1 % increase in population 2 % increase in GDP = ≈ 2 % increase in total VMT = need for ≈ 3 % increase in Interstate System

capacity, = ≈ 5+% increment in Interstate infrastructure

asset value to sustain Interstate System performance.

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VMT Growth Levels

For the next two decades VMT growth levels between 0.7% (population growth level) to 2% are reasonable absent extraordinary economic events. Beyond two decades, automation may impact

demand and capacity in ways that will require scenario updates based on emerging evidence.

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Caveats

• Urban Interstate capacity expansion is the most complex and expensive context for capacity expansion. In urban environments, policy considerations associated with the social, environmental, and financial implications of capacity expansion will create huge challenges and place a premium on capacity expansion strategies that can be deployed within existing facility footprints.

• The investment requirements will be even higher if the cost of consensus results in low-priority investments working their way into the program of improvements.

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Contact Information