Traffic Congestion and Transportation Trends


Neighborhoods and cities are becoming increasingly clogged by automobile traffic. Low rates of active transport among school aged children, especially high school students, are noted in the research. An increase in active transportation could impact vehicle miles traveled and reduce traffic congestion.

This section is a collection of transportation-related research addressing rates of active travel as well as walking and bicycling trends.

Research Highlights:

  • High school students have the lowest rates of active transport across all income and racial groups (McDonald, 2008).
  • In 1969, 40.7% of students walked or biked to school, by 2001 only 12.9% of children walked or biked to school (McDonald, 2007).
  • One article examines single-use, low-density land use patterns and reports that a 5% increase in neighborhood walkability is associated with 6.5 % fewer vehicle miles traveled (VMT) per capita (Lawrence, et al., 2006).
  • In 2001, only about one third (35.9%) of children aged 5 to 15 traveled 1 mile or less to school, and of these, 36% traveled by walking. This study reports that of trips in 1995, only 31.3% of these children walked to school (Ham, et al., 2005).
  • A review of the success of the Safe Routes to School program in Marin County reports a 64% increase in the number of children walking to school, 114% increase in the number of students biking, and 91% increase in the number of students carpooling (Staunton, et al., 2003).

See 2010 and Earlier Archived Articles

Academic Research Articles and Findings:

“Cobenefits of Replacing Car Trips with Alternative Transportation: A Review of Evidence and Methodological Issues” (2013)

  • It has been reported that motor vehicle emissions contribute nearly a quarter of world energy-related greenhouse gases and cause non-negligible air pollution primarily in urban areas.
  • Reducing car use and increasing ecofriendly alternative transport, such as public and active transport, are efficient approaches to mitigate harmful environmental impacts caused by a large amount of vehicle use. Besides the environmental benefits of promoting alternative transport, it can also induce other health and economic benefits.
  • At present, a number of studies have been conducted to evaluate co-benefits from greenhouse gas mitigation policies. However, relatively few have focused specifically on the transport sector. A comprehensive understanding of the multiple benefits of alternative transport could assist with policy making in the areas of transport, health, and environment. However, there is no straightforward method which could estimate co-benefits effect at one time.
  • In this paper, the links between vehicle emissions and air quality, as well as the health and economic benefits from alternative transport use, are considered, and methodological issues relating to the modelling of these co-benefits are discussed.

Ting Xia, Ying Zhang, Shona Crabb, and Pushan Shah, . (2013). “Cobenefits of Replacing Car Trips with Alternative Transportation: A Review of Evidence and Methodological Issues,”. Journal of Environmental and Public Health, 2013(Article ID 797312), Article ID 797312. doi: 10.1155/2013/797312


“Factors influencing mode of transport in older adolescents: a qualitative study” (2013)

  • Since a decline in activity levels occurs in adolescence, active transport could be important to increase daily physical activity in older adolescents (17–18 years). To promote active transport, it is necessary to be aware of the barriers and facilitators of this type of transport, but also of other transport modes. This study sought to uncover the factors influencing the choice of transport mode for short distance travel to various destinations in older adolescents using focus groups.
  • Thirty-two focus group volunteers (mean age of 17 ± 1.2 years) were recruited from the two final years of the secondary school in Antwerp (Belgium). Five focus groups were conducted (five to eight participants/group). Content analysis was performed using NVivo 9 software (QSR International). Grounded theory was used to derive categories and subcategories.
  • Data were categorized in three main themes with several subcategories: personal factors (high autonomy, low costs and health), social factors (good social support) and physical environmental factors (short travel time, good access to transport modes and to facilities, good weather, an adapted built environment, perceived safety and ecology).
  • For older adolescents, the interplay between short travel time, high autonomy, good social support, low costs, good access to transport modes and facilities, and good weather was important for choosing active transport over other transport forms for travelling short distances to various destinations. Other well-known factors such as safety, ecology and health seemed not to have a big influence on their transport mode choice.

Dorien Simons1, 2, 3*, Peter Clarys1, Ilse De Bourdeaudhuij2, Bas de Geus4, Corneel Vandelanotte5 and Benedicte Deforche1,2. (2013). Factors influencing mode of transport in older adolescents: a qualitative study. BMC Public Health, 13, 323. doi: 10.1186/1471-2458-13-323

Driving Down Daily Step Counts: The Impact of Being Driven to School on Physical Activity and Sedentary Behavior

  • This study investigated whether being driven to school was associated with lower weekday and weekend step counts, less active out-of-school leisure pursuits and more sedentary behavior.
  • Methods: Boys aged 10-13 years (n=384) and girls aged 9-13 years (n=500) attending 25 Australian primary schools wore a pedometer and completed a travel diary for one week. Parents and children completed surveys capturing leisure activity, screen-time and socio-demographics. Commute distance was objectively measured.
  • Car travel was the most frequent mode of school transportation (boys: 51%, girls 58%). After adjustment (socio-demographics, commute distance, and school clustering) children who were driven recorded fewer weekday steps than those who walked (girls: -1393 steps p<0.001, boys: -1569 steps, p=0.009) and participated in fewer active leisure activities (girls only p=0.043).
  • There were no differences in weekend steps or screen time.
  • Conclusion: Being driven to and from school is associated with fewer weekday pedometer-determined physical activity in 9-13 year-old elementary school children. Encouraging children, especially girls, to walk to and from school (even for part of the way for those living further distances) could protect the health and wellbeing of those children who are insufficiently active.

Trapp, G., Giles-Corti, B., Christian, H., Timperio, A. F., McCormack, G. R., Bulsara, M., & Villanueva, K. (2013). Driving Down Daily Step Counts: The Impact of Being Driven to School on Physical Activity and Sedentary Behavior. Pediatr Exerc Sci. 

"Emerging Technologies: Webcams and Crowd- Sourcing to Identify Active Transportation" (2013)

  • This novel interdisciplinary collaboration between public health and computer science provides automatic analysis of existing public data feeds to quantify the impact of built environment intervention on increasing bike travel mode share.
  • The Archive of Many Outdoor Scenes (AMOS) has archived over 225 million images of outdoor environments from more than 12,000 public webcams since 2006.  Using the publicly available webcams and a custom web crawler (similar to the web search engine or Google), webcam images are captured at the rate of one image per camera per hour and given a time stamp.  Many of the locations have had built environment improvements such as complete streets, bike share startups or walking school bus programs.  AMOS is able to document and allow quantification of population behavior changes following the built environment modification.
  • The intersection of Pennsylvania Ave NW and 9th ST NW in Washington, DC where bike lanes were installed was chosen as a location to monitor transportation mode share comparing the first workweek or June 2009 and the first week of June 2010 (pre-bicycle lane and post-bicycle lane).
  • Amazon Mechanical Turk (MTurk) website was used to crowd-source the image annotation.  MTurks are simple tasks not yet computer automated.  MTurk workers were paid US $0.01, in March 2012 to count each pedestrian, cyclist, and vehicle in a photograph.  Each image was counted 5 unique times (n=1200), completed in less than 8 hours. The counts per transportation mode were downloaded to SPSSv.19 for analysis.  Results showed a statistically significant difference in transportation mode share between the two years:  no significant increase in pedestrians but a four-fold increase in the number of cyclists per scene.
  • The investigators conclude that the use of AMOS and MTurks offer an inexpensive ($12.00 for this study) opportunity to quantify behavior change impact following built environment changes.  Future plans include monitoring other locations in the Washington DC Capitol Bikeshare program and developing computer algorithms to automate the counting process.

Hipp, J. Aaron; Adlakha, Deepti; Chang, Bill; Eyler, Amy A.; and Pless, Robert B. (2013). "Emerging Technologies: Webcams and Crowd- Sourcing to Identify Active Transportation" (2013). Brown School Faculty Publications (Paper 3).

“Is There an Association Between Gasoline Prices and Physical Activity? Evidence from American Time Use Data” (2012)

  • A recent paper in the economics literature finds an inverse relationship between gasoline prices and obesity risk—suggesting that increased gasoline prices via higher gasoline taxes may have the effect of reducing obesity prevalence. This study builds upon that paper.
  • This study utilizes cross-sectional time series data from the American Time Use Survey (ATUS) over 2003–2008, utilizes the increases that occurred in gasoline prices in this period due to Hurricane Katrina and to the global spike in gasoline prices as a “natural experiment,” and explores how time spent by Americans on different forms of physical activity is associated with gasoline price levels.
  • Economic theory suggests that higher gasoline prices may alter individual behavior both via a “substitution effect” whereby people seek alternatives to motorized transportation, and an “income effect” whereby the effect of higher gasoline prices on the disposable family budget leads people to make various adjustments to what they spend money on. Thus, ultimately, the relationship between gasoline prices and physical activity must be empirically determined.
  • Results from multivariate regression models with state and time fixed effects indicate that higher gasoline prices are associated with an overall increase of physical activity that is at least moderately energy intensive. The increases are most pronounced in periods where gasoline prices fluctuate more sharply and unexpectedly. These results appear robust to a number of model specifications. One of the major components of this increase appears to be an increase in housework that is at least moderately energy intensive—such as interior and exterior cleaning, garden, and yard work.
  • The results from this study tentatively suggest that there is an income effect of higher gasoline prices, or a possible increase in prices of such services when gasoline prices increase. However, the increases in physical activity associated with increased gasoline prices are weaker among minorities and low socioeconomic status (SES) individuals.
  • Hence, while a policy that increases gasoline prices via raised gasoline taxes may have benefits in terms of increasing overall physical activity levels in the United States, these benefits may not accrue to low SES individuals to the same extent as to their higher SES counterparts. This suggests that if increasing physical activity is the primary goal, then it may be more efficient to use a tax that can exert an income effect on mid-to-high SES households, such as a targeted income tax. On the other hand, if gasoline taxes are imposed to address other negative externalities of gasoline use, then these taxes may have the added benefit of increasing physical activity at least among some segments of U.S. society.

Sen, B. (2012). Is There an Association Between Gasoline Prices and Physical Activity? Evidence from American Time Use Data. Journal of Policy Analysis and Management 31(2): 338-366.

"U.S. School Travel, 2009 An Assessment of Trends" (2011)

  • The White House Task Force on Childhood Obesity has set a goal of increasing walking and biking to school by 50% within 5 years. Meeting the goal requires a detailed understanding of the current patterns of school travel.
  • Nationally representative estimates of the amount of school travel and the modes used to access school in 2009 were compared with 1969, 1995, and 2001.
  • The National Household Travel Survey collected data on the travel patterns of 150,147 households in 2008 and 2009. Analyses, conducted in 2010, documented the time, vehicle miles traveled, and modes used by American students to reach school. A binary logit model assessed the influence of trip, child, and household characteristics on the decision to walk to school.
  • In 2009, 12.7% of K– 8 students usually walked or biked to school compared with 47.7% in 1969. Rates of walking and biking to school were higher on the trip home from school in each survey year. During the morning peak period, school travel accounted for 5%–7% of vehicle miles traveled in 2009 and 10%–14% of all private vehicles on the road.
  • There have been sharp increases in driving children to school since 1969 and corresponding decreases in walking to school. This increase is particularly evident in the number of vehicle trips generated by parents dropping children at school and teens driving themselves. The NHTS survey provides a unique opportunity to monitor school travel mode share.

Noreen C. McDonald, PhD, Austin L. Brown, MRP, MPH, Lauren M. Marchetti, BA, Margo S. Pedroso, BA. (2011). U.S. School Travel, 2009 An Assessment of Trends.  Am J Prev Med, 41(2), 146-151.

“Kids and Cars: Environmental Attitudes in Children” (2011)

  • This article aims to supplement scarce research on the children’s attitudes to cars and the environment. Assuming that attitudes to cars develop in childhood, this article draws upon the writing assignments and interviews exploring the upper-elementary school children’s attitudes to cars.
  • The study was conducted in Amsterdam, The Netherlands, between January and December 2010.
  • Briefly examining existing research on children’s environmental attitudes in general, and in relation to cars in particular, the author argues that in-depth qualitative research is essential to the understanding of the factors that explain present attitudes and perhaps predicting the behavior of future drivers.
  • In conclusion, the author makes a recommendation for the development of a curriculum addressing the development of children’s awareness of sustainable transportation and the environmental implications of car driving.

Kopnina, Helen. (2011). “Kids and cars: Environmental attitudes in children.” Transport Policy 18(4): 573-578.

“Can Smart Growth Policies Conserve Energy and Reduce Emissions?” (2011)

  • This article examines the role smart growth can play in achieving planning objectives, including energy conservation and emission reductions. It summarizes existing literature on land use impacts on travel activity, energy consumption and pollution emissions. It examines claims that smart growth policies are ineffective and harmful.
  • Land use policies can significantly affect transportation options and costs, and therefore travel activity. People who live and work in automobile-dependent locations tend to drive more annual miles, consume more fuel and produce more pollution than they would in more accessible, multi-modal communities. As a result, smart growth reforms can provide various economic, social and environmental benefits.
  • Some critics claim that these impacts are small and not cost effective but their analysis tends to misrepresent key issues. The only consider land use density, ignoring the effects of other land use factors such as regional accessibility, land use mix, road and path connectivity, transport system diversity, and parking management. They overlook additional benefits, and growing consumer demand for more accessible, multi-modal home locations. As a result, they underestimate smart growth impacts and benefits.
  • This is important because existing land use development policies and planning practices tend to favor sprawl and automobile dependency. Smart growth requires policy reforms that allow more compact and mixed development, support alternative modes, and reduce existing subsidies to automobile such as generous minimum parking requirements. These reforms tend to face institutional inertia and political opposition. It is therefore important to have accurate information on the full potential impacts and benefits of smart growth policy reforms. When all impacts are considered, smart growth policies are often a cost effective way to achieve planning objectives.

Litman, Todd. (2011). “Can Smart Growth Policies Conserve Energy and Reduce Emissions?” Portland State University’s Center for Real Estate Quarterly 5(2): 21-30.

See 2010 and Earlier Archived Articles