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The Next Generation of Travel: Research, Analysis and Scenario Development

Literature Scan Report Summary

FHWA Office of Policy and Governmental Affairs, Transportation Studies (HPTS)

November 2011


The travel of people in the United States is influenced by a combination of events, including life cycle changes, demographic and socioeconomic factors, generational social norms, and the exposure and adaptation of people to new technologies and travel options. In the Federal Highway Administration's (FHWA) research on meeting future travel demand on the transportation system, the transportation perspectives, preferences and needs of the younger traveler (under the age of 30), is an area that needs further research. The FHWA Office of Policy, Transportation Studies Futures Team is conducting a formal study to examine youth travel, which will be used to develop policy recommendations based on improved forecasts of demand, vehicle usage and the impacts of new transportation technologies on personal travel.

The work completed under this project involves a quantitative and qualitative evaluation of current and emerging travel shifts among the different generations. The quantitative portion of this project is the cohort analysis, using primarily National Household Travel Survey (NHTS) data to analyze differences across age groups and generations over time and to identify any new or emerging predictors of travel and changes in travel behavior that fall outside the traditional norms of travel as a person ages from youth to retirement. The qualitative portion of this project will include the conduct of several nationwide focus groups to gather detailed information on generational perceptions and attitudes regarding personal travel, the environment, communications and technology.

In addition to both the cohort analysis and focus groups, in-depth literature reviews were written on both generational travel trends (with a focus on younger populations), and how future generations will interface with emerging technologies in the areas of Information and Communication Technologies (ICT), Global Positioning Systems (GPS), Intelligent Transportation Systems (ITS), electronic payment systems and fuel efficient vehicles. The results of the analyses will be used to develop profiles of the future traveler and to forecast future travel demand and characteristics through scenario development. The information to be presented in the final report is ultimately intended to be used in reference to the development of current and future transportation policies.


For the purposes of this study, age group differences will be analyzed as a result of three overlapping processes—life cycle effects, period effects and cohort effects,1 with an emphasis on how these differences affect travel.

Life Cycle Effects

Life cycle effects can be defined as the characteristics or events that occur within a person's life that create a change in one's lifestyle. Life cycle effects considered most often in travel behavior-related studies include age, income, whether children are present in the household, household size, worker status and vehicle ownership. Of all the life cycle effects identified, age and income have been noted to have the greatest impact on how much a person travels. Research has shown that over time the amount of vehicle miles people travel peaks around mid life and then gradually decreases as they age, most likely due to health issues that impede driving as a person ages, such as poor vision.

Income is also a strong indicator of how much a people travel. Historical trends have shown that as real personal incomes have risen, so has vehicle miles traveled (VMT).2 Higher incomes contribute to increased car ownership and expenditures on transportation and can influence the length and number of trips people take as they may commute longer distances from areas of choice housing and/or take more discretionary trips.

In addition to the life cycle effects mentioned above, this study will consider the lifestyle of today's young people, where and how they live, and how new technologies and viewpoints may affect the way they use their time and how they make their travel decisions.

Period Effects

Period effects are social movements, economic downturns, major events, medical, scientific, or technological breakthroughs that affect all age groups on a large scale and simultaneously, but the degree of impact may differ according to where people are in their life cycle.

The economy plays a significant role in increases and decreases in VMT because of its effect on gas prices, personal income and the household budget. In the short term, rises in the price of gas have contributed to drops in VMT, as this has occurred during times of past economic recessions and/or crises, namely the 1973 OAPEC Oil Embargo, the1979 Oil crisis, the 1981-1982 Global Recession and the Great Recession of 2008.

As people lose their jobs or experience limited income growth during a recession, they adjust their household budget to meet the demands of rising transportation costs. In addition to fuel, insurance, vehicle repair and maintenance expenses, other factors that affect household transportation costs include the number of miles someone needs to travel, the number of wage earners per household, location, vehicle fuel efficiency and the costs for bus and rail services. Often there is a tradeoff between what a household spends on housing vs. transportation (i.e. if more is spent on housing, then less is spent on transportation and vice versa.3)

Impacts of the current recession have especially effected younger generations, specifically Generation Y (ages 18-29). A Pew Center survey in February 2010 stated that 37 percent of young respondents were either underemployed or out of work, the highest share within this age group in more than three decades. Long spans of unemployment not only causes depression, anxiety and other health-related issues, but can affect long-term income growth, as noted in a recent Time article, "if and when these young people return to work, they'll earn 20% less over the next 15-20 years compared to peers who were employed."4Because of their financial situation, many young people are delaying marriage, staying in school, and choosing to remain living at home with their parents. Their financial situation also affects their travel mode of choice, whether or not they own a fuel efficient vehicle and other income-related travel decisions which are made in the context in rising fuel prices and transportation costs. In addition, current high unemployment has overall resulted in fewer people driving to work. 5Reductions in consumer spending have resulted in fewer shopping trips and lower shipment of freight, contributing to declines in VMT. Although these declines may not have a lasting effect, they show how sensitive changes in VMT are related to changes in the economy.

Public sector and private sector policies and programs affect personal travel behavior. In the past 10 to 15 years, regulatory initiatives from the public sector have made the process for obtaining a driver's license more rigorous. Since 1996, all 50 US States have adopted some form of a graduated licensing, which usually involves a multiple step process for young drivers to get their driver's license, including a minimum number of supervised driving hours, restrictions on the hours of the day young people can drive, as well as on the number of passengers they can carry. Due to budget constraints, many school systems which once offered driver's education as part of the high school curriculum have eliminated the program, shifting the cost of driver's education from the state to parents. Today, only 15 percent of students are enrolled in driver's education through their schools. Additionally, student and employer subsidies in urban areas and other public subsidies for public transportation use may encourage a shift to other modes.

Social trends and movements over time have affected personal travel in a variety of ways; for instance, the trend of women entering the workforce over the past 50 years has added to the number of vehicle trips,6 and an increase in trip chaining, as women often combine their commute with transporting children and other household responsibilities. This change has resulted in a permanent shift in travel demand and vehicle ownership. The environmental movements of the 1970s which fostered the Clean Air Act and Corporate Average Fuel Economy (CAFE) standards have led to improvements in vehicle fuel efficiency and to programs such as the Congestion Mitigation Air Quality (CMAQ) federal program, which requires transportation planning agencies to implement measures for reducing number of vehicles on the road in areas not meeting air quality standards. Since 1970, harmful emissions from exhaust fumes have been reduced significantly, and increases have been made in mobility options, such as transit.7

Large-scale catastrophes and tragic events may also lead to changes in public opinion that could affect travel; for instance, incidents like the Deepwater Horizon oil spill in the Gulf Coast in April 2010, remembered as the largest marine oil spill in petroleum industry history, have raised the public's environmental awareness. A poll conducted through the Pew Center in June 20108, reported that sixty-five percent of young people surveyed said that the highest goal of U.S. policy should be protecting the environment. If youth continue to hold fast to their views, it's possible that there may be changes in their vehicle purchases, as well as in their efforts to reduce their driving based on how they feel about the environment. Currently, economics still plays a large role in their purchasing decisions as most people under 30 drive gasoline-powered vehicles;9 however, it is possible they may develop a future preferences for smaller vehicles or increase their usage other modes of travel for both environmental and economic reasons.

Technological breakthroughs and market-wide adoption of products in the realm of Information Communication Technologies (ICT) and wireless platforms have changed the way many of us interact with one another. Currently, nearly all of U.S. zip codes have some level of broadband access, further making these technologies available to a majority of households in the U.S. Younger generations, who have grown up using the Internet, have been noted for their high usage of online and instant communication. Seventy-eight percent of persons ages 12-24 and sixty-five percent of persons ages 25-34 have a social networking profile page on Facebook, MySpace, LinkedIn or other social networking site10, and ninety-four percent of persons aged 18-34 use their phone for text messaging.11 As many youth now spend a significant amount of time online, it raises the question to whether they communicate and socialize differently than generations before them, perhaps reducing their need to travel, or in some cases increasing it depending on the area they live in.

Many State Departments of Transportation have recognized the need for reaching younger audiences using online social media tools and digital platforms, and have integrated social networking sites into their communication programs. According to an AASHTO survey in February 2010, about half of all DOTs have an active Facebook page, and use Twitter to communicate traffic incidents and road closings.12 These states report that these methods of communication are decidedly more efficient in reaching the public with time sensitive traffic and travel information, especially the youth.

Younger generations may also be more willing and open than older generations to publically share information and less concerned over privacy issues related to new transportation-related technologies, such as GPS systems, electronic toll collection, or paying virtually for travel. A Pew Center report on people's expectations for the future of the Internet, says that, "Tech experts generally believe that today's tech-savvy young people will retain their willingness to share personal information online even as they get older and take on more responsibilities," and that the benefits of personal disclosure will outweigh their concerns over their privacy.13

Technology use may also change how young people use their time and, therefore, how much they travel and for what purposes (Kwan, 2002). 2009 NHTS results show that seventy percent of people under the age 40 use the Internet on a daily basis, a significantly higher percentage than those persons over the age of 40. Within the past decade, there have been various studies with mixed results on the effects of Internet use on travel using the following paradigm:

  1. Substitution: Does Internet use replace a physical trip? Therefore, decreases travel.
  2. Complementarity: Does Internet use create and additional demand for a trip? Therefore, increases travel.
  3. Modification: Does Internet use change the characteristic of a trip? Such as timing, chaining and purpose distribution. An additional example would be related to an online purchase which may reduce a shopping trip, but create a trip associated with the delivery of a package.
  4. Neutrality: Internet use is independent of/has no effect on trip making.

There are a number of additional considerations when relating Internet use to travel including the following: 1) the types of goods being purchased online (whether they actually replace a shopping trip), 2) trips that generate a shopping trip because of information obtained, 3) activities that are more attractive for completing a task online (such as banking), 4) the time of the year when internet activity may be higher, 5) time spent engaged in social networking, and 6) internet applications that support travel, such as real time travel information, mapping and route choice services Whether people live in a more rural or urban area may also affect the frequency of their Internet usage, as well the time they are willing to spend traveling each day. Taking all these considerations into account increases the complexity of drawing definite conclusions, as it is a topic for further study.

The Internet and mobile technologies have enabled people to access information from almost any location, increasing mobility and changing the way we work and socialize. Some researchers believe that younger persons' preoccupation with the Internet and mobile devices plays a role in reducing their driving because they have become more preoccupied with their mobile devices, making cars less desirable or useful and public transportation more relevant.14 Present mobile phone applications that provide travel information have enabled people to become smarter and more efficient travelers. With these technologies, people can map out routes instantly, avoid congestion, find parking, pay for a transit trip, arrange for carpooling and locate a vehicle, if using a car sharing service. Younger populations have been especially noted for their preference in using digital directions, rather than reverting to a map or stopping at a gas station.15 Web-based technologies have also enabled more people to work from home, as teleworking has increased 92 percent from 1980 to 2000. It is expected that as society's familiarity with the technology and desire for work-life balance grows, especially among younger generations, working from an alternate locations will continue to increase.

Other technological advancements in transportation in ICT as applied to transportation infrastructure and vehicles, also include some of the following ITS applications: Global Positioning Systems (GPS), electronic toll collection, vehicle tag recognition, variable message signs and High Occupancy Toll (HOT) lanes.16 As of 2010, over fifty percent of freeway miles have real-time data collection activities, and dynamic message signs have been deployed in nearly ninety-five percent of all freeway miles.17 Further research is yet to be done on how the integration of these technologies into present day and future transportation systems will affect personal travel and VMT. As a part of this project, a accompanying scan report has been completed on ICT, GPS ITS, payment systems and fuel efficient vehicles as related to the user.

Cohort Effects

Period events, social trends and technological advancements leave a deep impression on young adults because they are still developing their core values at an early part of their life cycle.18 It is difficult to say which formative experiences younger generations will carry forward throughout their life because as people age they tend to become more alike and more like previous generations before them. One example of this would be the amount of miles someone travels over their lifetime, typically, people travel more in their younger and working years, but as they age, they travel less, as shown in the figure below. This is a generational travel norm that isn't expected to change much over time, as often a person's travel decreases because of health limitations that occur with age.

Figure 1

The purpose of the literature scan was to help identify differences in generations that may have a lasting change, and define what these variables might be through further analysis. Variables which are known to be, or seem likely to be subject to short-term fluctuation, need to be considered for their lasting impact; for instance, rises and falls in response to unevenly space phenomena such as economic recessions.19 The 2009 NHTS data, for instance, was collected during 2008, a peak recession year, which is believed to account for significant drops in travel, as shown in the table below. The travel of respondents under the age of 30; however, has been declining for some time, which raises the question as to whether there may other reasons for the steady drop in travel among younger populations, even in times when total population is steadily increasing.

Figure 2. Percent Change in VMT and PMT for NHTS Survey Years 1995, 2001 and 2009

Survey Year Average Annual VMT1
(per person)
Percent Change
16-30 31-55 56+ 16-30 31-55 56+
1995 9,872 12,446 7,081 - - -
2001 9,748 12,892 7,951 -1.25 3.58 12.28
2009 7,319 11,493 7,781 -24.9 -10.8 -2.06

Survey Year Average Annual PMT
(per person)
Percent Change
16-30 31-55 56+ 16-30 31-55 56+
1995 15,524 17,041 11,309 - - -
2001 15,552 18,299 12,220 0.18 7.38 8.05
2009 12,253 16,214 11,704 -21.2 -11.3 -4.2

The purpose of the cohort analysis is not only to determine travel differences between generations, but to identify the influencing factors that cause there to be differences. For instance, the recession has caused many young people to delay marriage and live at home longer with family members, less likely to own a vehicle and more reliant on car pooling, car sharing and other modes for travel. Graduated licensing laws and regulations might cause young people to delay getting their license and depend on other modes for travel. In addition, environmental views and preferences for being driven because of their use of handheld devices may be additional reasons for other mode use.

Today's youth also spend a considerable amount of time online socializing, shopping and going about other daily activities; this raises the question to whether any of this activity replaces trip making or has any effect on changing travel preferences. Advancements in ICT and ITS technologies have changed the way people interact and communicate with one another, as well as have enabled them to become more mobile, informed and more in control of their travel decisions. The reliance of today's youth on technology may be a cohort effect that accounts for differences in travel from older generations, and will be explored further through the nationwide focus groups, in addition to data analysis on travel and Internet use.

Figure 3. Potential Explanations for Travel Differences between Younger and Older Adults

Type of effect Factors
Life cycle Delayed marriage
Multigenerational households
Period Effects Economic downturn (Great Recession)
Changes in driver's licensing laws/regulations
Views about the environment
Cohort Effects Reliance on technology

Cohort Analysis Framework

Typically people are grouped into age cohorts around decades or significant time periods. People born in the same year, for example, are birth cohorts (generation) for that year.20 For the purpose of this scan report, conventional definitions of generations have been used as the unit of analysis, to understand the travel characteristics of Generation Y; however, further study to be included into the final report, will include the results of a cluster analysis of the aged16-30 group to determine whether there are natural "travel behavior breakpoints" among teens and young adults that can be used to better define the age categories.

The cohort analysis plan is to use the NHTS data sets (1990-2009) to construct a set of statistical models to predict the determinants of transportation outcomes for youth who live in urban areas. It will be supplemented by data on state driver's licensing regulations and local unemployment rate data from the Bureau of Labor Statistics to fully construct these models. A set of cross sectional models will be constructed by age cohort will then be developed to examine key determinants of travel, including sex, race/ethnicity, education, household size and structure, household income, education, worker/student status, vehicle ownership/access, use of technology, driver's licensing regulations in state in which respondent lives, local unemployment rate, and residential location (i.e. metropolitan area, central city/suburb, residential density, presence of rail).

In a separate analysis, multiple years of the NHTS will be used to construct a "pseudo-cohort analysis" (as panel data is not available), in which multiple cross-sectional data sets will be used to track the behavior of age cohorts across survey years,21 as shown in the sample table below.

Figure 4. Age Cohorts

Survey Years Age Cohorts
1990 18-29 30-39 40-49 50-59 60-69    
2001   29-40 41-50 51-60 61-70 71-80  
2009     37-48 49-58 59-68 69-78 79-88

The multiple cross-sectional data will then be used in a set of statistical models to examine whether the results differ from those produced by the cross sectional models. Approximately ten models will be produced to analyze two outcomes measures: (1) PMT and trip frequency, or (2) travel mode for work and non-work travel. Through this analysis, the independent effects of a number of factors on the travel of young adults will be explored quantitatively.

Summary of Key Points

The following is a list of summary points and conclusions drawn from the literature scan on The Next Generation of Travel, which will be considered when writing the final report, due to be completed in late 2012:

Demographic Trends

Trends in Trip Making


Vehicle Ownership

Economic Effects

Regulatory Effects




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1 The Pew Research Center, Millennials: A Portrait of Generation Next, February 2010, Preface

2 The National Surface Transportation Policy and Revenue Study Commission, Commission Briefing Paper 4A-06, Implications of Rising Household Income on Passenger Travel Demand, 2007, Figure 1, pg. 2

3A Heavy Load: The Combined Housing and Transportation Burdens of Working Families, Center for Neighborhood Technology, October 2006, Figures derived from 2002 Consumer Expenditure Survey

4 Time Magazine. June 2011

5 Fairfield, Hannah. "Driving Shifts Into Reverse." The New York Times. New York Edition page BU7. May 2, 2010.

6 Pisarski, Alan, Commuting in America III: The Third National Report on Commuting Patterns and Trends, Transportation Research Board, 2006, pg. 19

7 CMAQ brochure, www.fhwa.dot.gov/environment/air_quality/cmaq/.../cmaqbroc.pdf

8A Society for Human Resource Management/National Journal Congressional Poll, June 2010

9 2009 NHTS

10 18th Edison Research/Arbitron Internet and Multimedia Study (2010)

11 Generations and their gadgets, Pew Center's Internet and America Life Project, February 2011, http://pewinternet.org/Reports/2011/Generations-and-gadgets.aspx

12 State Departments of Transportation Lead the Way Using New Media, AASHTO Communications Brief, February 2010

13 Millennials will make online sharing in networks a lifelong habit, Pew Internet and American Life Project, The Pew Center, July 2010

14 Neff, Jack, Is Digital Revolution Driving Decline in U.S. Car Culture? Advertising Age, May 2010

15 TeleAtlas survey, 2008 (company bought by TomTom)

16 Our Nation's Travel: Current Issues, FHWA Publication No. PL-05-015, 2001

17 RITA ITS Deployment Tracking Survey, http://www.itsdeployment.its.dot.gov/FM.aspx, 2010

18 The Pew Research Center, Millennials: A Portrait of Generation Next, February 2010, Preface

19 Glenn, Norval, Cohort Analysis, Sage Publications, 1977

20 http://www.businessdictionary.com/definition/cohort.html.

21 This type of analysis has been done by Meyers at the University of Southern California using data from the decennial census. See http://www-bcf.usc.edu/~dowell/index.htm for examples of this type of analysis.

22 2002 Consumer Expenditure Survey

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