National Academies Press: OpenBook
« Previous: Contents
Page 8
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 8
Page 9
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 9
Page 10
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 10
Page 11
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 11
Page 12
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 12
Page 13
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 13
Page 14
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 14
Page 15
Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012. Washington, DC: The National Academies Press. doi: 10.17226/25590.
×
Page 15

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

ix Summary Objective The research objective, as outlined in the original Request for Proposal, was to “provide a multidisciplinary analysis of the relative influence of the types of factors that contributed to the recent national decline in the number of highway fatalities and rates in the United States.” Between 2005 and 2011, peak to trough, the number of traffic fatalities in the U.S. declined by 11,031, from 43,510 in 2005 to 32,479 in 2011. This decline amounted to a reduction in traffic-related deaths by 25.4%, by far the greatest decline over a comparable period in the last 30 years. Figure S-1 Traffic fatalities, 2001-2012 Historically, significant drops in traffic fatalities over a short period of time have coincided with economic recessions. Figure S-2 displays the number of traffic fatalities by year from 1966 through 2016, along with the periods of the seven recessions during that span. (Traffic fatalities for 2016 were projected from an early estimate by the National Highway Traffic Safety Administration (NHTSA) of the number of fatalities during the first half of 2016 (NHTSA 2016a).) Longer recessions have coincided with deeper declines in the number of traffic fatalities. This project provides an analysis that identifies the specific factors in the economic decline that affected fatal crash risk, while taking into account the long-term factors that determine the level of traffic safety.

x Figure S-2 Motor vehicle traffic fatalities and periods of recession, 1966-2012 The fundamental approach of this research project was based on the understanding that the number of fatalities and injuries in crashes is the product of risk times exposure: Fatalities = Risk × Exposure Eq. S-1 Figure S-3 displays the relationship between VMT (exposure), traffic fatalities (outcomes), and traffic fatality rates by VMT (risk), over the period. The figure shows the ratio of the values for each year to the base year of 2001. Exposure as measured by VMT was relatively stable. However, a reduction in the risk of travel pulled down the number of traffic fatalities. Thus, the fatality risk of travel contributed significantly to the substantial decline in fatalities over the period. The decrease in exposure due to the recession and subsequent slowdown in economic activity contributed less. The goal of this project was to identify the sources of reduced risk.

xi Figure S-3 Fatality rates by VMT and vehicle registrations, and fatalities, normalized to 2001 Analysis approach Factors that affected the incidence and risk of fatal crashes and fatal crash injuries over the period were organized using the Haddon Matrix. The Haddon Matrix provides a framework that covers the factors comprehensively (Williams 1999). The utility of the Haddon Matrix was to ensure that all components of what might be called the crash system—vehicle, drivers, and environment—were considered. Fundamentally, two processes were at work over the period. The first process set the baseline level of safety that influenced the number of traffic deaths each year. The baseline level was the product of long- term trends in factors known to affect traffic safety, such as safety belt use, improvements in the crashworthiness of cars, highway infrastructure, traffic enforcement and safety campaigns, driver license laws, and other efforts to reduce the number of fatalities on U.S. roads. Most of these factors operated incrementally and changed relatively slowly over time. Highway infrastructure cannot change dramatically over a short period of time. Safety belt use is known to be a primary safety intervention, but belt use increased slowly and monotonically over the period. The second process at work over the period consisted of the factors that precipitated the sharp decline in fatal crashes and deaths in 2008-2011. The major event in this period was the recession that started in December 2007 and ended in June 2009 (NBER 2010). Of the components of the crash system—vehicle, drivers, and environment—recessions have a short-term and substantial impact on drivers. Moreover, the recession affected some high-risk groups more than others, particularly younger drivers, so it may have taken some risky drivers off the road and also reduced the amount of risky driving. At the same time, the long-term factors that influenced safety continued, such as incremental increases in safety belt use, the penetration of more crashworthy passenger vehicles into the fleet, safety campaigns to improve driver behavior, infrastructure improvements, and other factors. Explaining the drop in traffic

xii fatalities between 2008 and 2011 was a major goal of the project, but the explanation is undertaken within the context of overall trends in traffic safety over the period. Findings and statistical models A key insight into the analysis of the factors that produced the sharp drop in traffic fatalities was that the young contributed disproportionately to the drop-off in traffic fatalities. Of the reduction in traffic fatalities from 2007 to 2011, persons less than 26 years of age accounted for almost 48% of the drop, though they were only about 28% of total traffic fatalities prior to the decline. Figure S-4 shows that traffic deaths among persons 25 years-old or less dropped substantially more than other groups. Young drivers are known to be a high-risk group and can be readily identified in the crash data. Other high risk groups also likely contributed to the decline but they cannot be identified as well as age can. Figure S-4 Ratio of traffic fatalities by age groups, normalized to 2001 Using the Haddon Matrix and the research team’s broad expertise, a comprehensive set of parameters were identified to evaluate their contribution to the drop in traffic fatalities after 2007. Statistical models of the incidence of traffic fatalities over the period were developed using these parameters. Table S-1 provides the expected association of the various parameters in the models and describes the mechanisms through which they were hypothesized to affect the number of traffic fatalities. Most of the modeling results were consistent with these expectations, though not all.

xiii Table S-1 Explanatory factors and expected mechanisms of activity Variable  Expected  association  with traffic  fatalities  Expected mechanism  Total VMT  Positive  Increase in VMT increases exposure to traffic crashes and therefore fatalities.  Proportion rural VMT  Positive  Increased proportion of rural VMT increases proportion of travel on riskier roads, leading to more fatalities.  Pump price  Negative  Increased pump price raises cost of travel, reducing total travel and discretionary travel, reducing exposure to fatal crashes.  GDP per cap  Positive  GDP per capita reflects economic activity which in turn leads to more travel, more exposure to crashes, and more fatalities.  Median Income  Positive  Increased median income increases discretionary and leisure travel, resulting in more exposure and more fatalities.  16‐24 Unemployment  Negative  Increased unemployment reduces total travel and discretionary, leisure travel, resulting in fewer fatalities.  Capital spend/mile  (lag)  Mixed  Improved infrastructure would be expected to shift travel to higher  quality roads. It may also induce more travel, thus more exposure to  fatalities.  Safety spend/mile  (lag)  Negative  Increased traffic enforcement, education, and safety programs would  reduce risky driving and reduce fatalities.  Belt use rate  Negative  Increased belt use provides more protection to vehicle occupants and reduces the probability of fatal injury, given a crash.  DUI law rating  Negative  Increased stringency of DUI laws reduces drunk (risky) driving and traffic fatalities.  Motorcycle helmet  law rating  Negative  Increased stringency of motorcycle helmet laws provides more  protection to motorcycle riders and reduce the probability of fatality  given a crash.  Beer consumption  Positive  Increased beer consumption may increase driving while under the  influence of alcohol, increase risky driving, and increase traffic  fatalities.  Wine consumption  Positive  Increased wine consumption may increase driving while under the  influence of alcohol, increase risky driving, and increase traffic  fatalities.  Penetration of model  year >1991  Negative  Increased penetration of vehicles that provide more occupant  protection and more safety features reduces the probability of a crash,  and reduces the probability of fatal injury given a crash.  Two basic approaches were used to model the factors that were associated with the drop in traffic fatalities after 2007. The first approach was a set of count models, using negative binomial models to examine the associations between predictors (the variables in the table above) and raw fatality counts. Two count models were developed. One used a state fixed effect to remove the stable differences between

xiv states and focus on changes over time (labelled the model considering state or MCS model). The other left out this fixed effect, allowing differences between states to be captured by the measured predictors (model not considering state (MNCS)). The other statistical modeling technique was a log-change regression model, to model the association between the change in predictor variables in one year with the change in the outcome variable (traffic fatalities) in the following year. Table S-2 shows the results from the two count models. Table S-3 provides the results from the change model. Table S-2 Effects of Count Model Factors Variable  Change in  Parameter  Value from  2007 to 2011  MNCS model  MCS model  Predicted  Change in  Fatalities  Statistically  Significant at  5% level?  Predicted  Change in  Fatalities  Statistically  Significant at  5% level?  Rural VMT Proportion as  percent of total  ‐0.8 % ‐103  Yes  95  Yes  State Gross Domestic  Product per Capita  ‐$6301 per  person  ‐617  Yes ‐1236  Yes  Unemployment Rate for  16 to 24 year olds  +6.39% ‐3305  Yes ‐3125  Yes  Pump price  +$0.55/gallon  ‐877  No  127  No  Per Capita Beer  Consumption  ‐0.08  Gal./person  ‐835  Yes ‐1312  Yes  Median income ‐$3760  2677  Yes ‐466  Yes  DUI laws rating ‐1.05 ‐120  No ‐261  Yes  Safety Belt laws rating ‐0.16  5  No ‐28  No  Motorcycle helmet law  rating  0  0  Yes  0  No  Table S-3 Effects of change-model predictors for 2007-2011 Variable  2007 Mean  2011 Mean  Percent change  in predictor  2007‐2011  Percent change  in predicted  fatalities   2007‐2011  Total VMT  3,031,124  2,962,740 ‐2.3% ‐1.2%  Proportion rural VMT  0.33  0.32 ‐1.6% ‐0.1%  Pump price change  3.11  3.20  2.6% ‐0.1%  GDP per cap change  59,687  54,519 ‐7.5% ‐1.2%  Median income  change  56,081  53,621 ‐4.3% ‐2.2%  16‐24 unemp. change  10.59  16.69  55.7% ‐6.1% 

xv Variable  2007 Mean  2011 Mean  Percent change  in predictor  2007‐2011  Percent change  in predicted  fatalities   2007‐2011  Capital spend/mile  (lag) change  73.69  81.27  7.9% ‐0.1%  Safety spending/mile  (lag) change  13.61  14.68  9.3%  0.1%  Belt use rate change  85.77  88.10  2.4% ‐0.1%  DUI law rating change  19.77  20.50  4.0% ‐0.7%  Motorcycle helmet  law rating change  2.91  2.91  0.0%  0.0%  Beer consumption  change  1.21  1.15 ‐3.5% ‐0.7%  Wine consumption  change  0.37  0.39  5.0% ‐0.1%  MY>1991 change  95.80  97.11  1.4%  0.1%  The two modeling approaches were in broad agreement. The most significant contributors to the drop in traffic fatalities after 2007 were the substantial increase in teen and young adult unemployment, the reductions in median household income, and the reduction GDP/capita income. The right-most column in Table S-3 estimates the percentage decline contributed by each factor in the change model. The decline in rural VMT, increased strictness of DUI laws, and decreased beer consumption also contributed. State highway spending was not a significant contributor to the drop; the effect of changes in infrastructure was likely more cumulative and longer term. Changes in safety belt use rates and fuel prices were not significant contributors to the decline in traffic fatalities after 2007 because they did not change much over the period. It should be noted that failing to find that certain well-established safety interventions (safety-belt usage, highway capital improvements) did not contribute significantly to the sharp drop in traffic fatalities during the recession does not mean that they are not essential tools to reduce traffic fatalities. It means that their impact was not detectable given the magnitude of the short-term effects of other factors. The long-term factors that set the baseline of traffic safety continued to operate. Overlaid on top of them was the short term shock of the recession that drove up unemployment, particularly among teens and young adults, and declining median income that likely reduced driving and risky driving among high-risk populations. Implications and further research  Teens and young adults contributed disproportionately to the reduction in traffic fatalities 2008 through 2011. It is suggested here that the mechanism was economic constraints reduced total travel and risky (discretionary and leisure) travel. It has long been known that teens and young

xvi adults have disproportionately high crash risk, but the results from this study suggest that their behavior can be significantly modified over the short run, substantially reducing fatalities.  The findings related to median household income are consistent with an income effect. This finding warrants further investigation, but interventions aimed at lower income groups may have a disproportionately positive effect, similar to reducing crash risk among teens and young adults.  DUI laws showed a significant positive effect in reducing traffic fatalities, even over the short term of this study and even within the substantial impact of the economic contraction. Reduced beer consumption similarly showed a significant, positive effect. It is clear that continuing to focus on reducing drunk driving can have a disproportionate effect on reducing traffic fatalities.  Rural VMT bears a higher risk of fatal crashes across all road types; reduction in the proportion of rural VMT was significant in all models. Programs aimed at reducing the risk of rural travel can substantially reduce traffic fatalities.  It may be difficult to discern in any given year the effects of safety countermeasures, due to the significant influence of other factors on traffic fatalities. There is a need to more fully document and assess safety advances from countermeasures because these other factors may obscure them.  The results here clearly illustrate that factors outside the authority of safety professionals can have highly significant impacts on the level of highway safety. In the short term, shocks in the economy can overwhelm the effect of safety interventions that generally influence crash risk in the long term. It is clear that exogenous factors such as economic trends should be accounted for in setting realistic goals and evaluating traffic safety programs.

Next: Chapter 1. Statement of the problem »
Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012 Get This Book
×
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

Between 2005 and 2011, the number of traffic fatalities in the U.S. declined by 11,031, from 43,510 in 2005 to 32,479 in 2011. This decline amounted to a reduction in traffic-related deaths of 25.4 percent, by far the greatest decline over a comparable period in the last 30 years.

Historically, significant drops in traffic fatalities over a short period of time have coincided with economic recessions. Longer recessions have coincided with deeper declines in the number of traffic fatalities. This report from the National Cooperative Highway Research Program, NCHRP Research Report 928: Identification of Factors Contributing to the Decline of Traffic Fatalities in the United States from 2008 to 2012, provides an analysis that identifies the specific factors in the economic decline that affected fatal crash risk, while taking into account the long-term factors that determine the level of traffic safety.

A key insight into the analysis of the factors that produced the sharp drop in traffic fatalities was that the young contributed disproportionately to the drop-off in traffic fatalities. Of the reduction in traffic fatalities from 2007 to 2011, people 25-years-old and younger accounted for nearly 48 percent of the drop, though they were only about 28 percent of total traffic fatalities prior to the decline. Traffic deaths among people 25-years-old and younger dropped substantially more than other groups. Young drivers are known to be a high-risk group and can be readily identified in the crash data. Other high-risk groups also likely contributed to the decline but they cannot be identified as well as age can.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!