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Page 18 Chapter 6. Trends in contributing factors It appears from the foregoing section that the very large drop in the number of traffic fatalities was the product of a decrease in exposure, albeit a relatively small decline in exposure, and a decline in the risk of a fatal crash and/or the risk of fatal injury, given the occurrence of a crash. That is, a decline in the risk of traffic fatalities can be the product of fewer crashes or better protection for people involved in a crash, or both. The Haddon Matrix essentially provides a comprehensive coverage of factors that affect the risk of a crash and risk of injury within a crash. This section describes the most important trends in the factors that affected crash and fatal injury risk over the period. The purpose is to describe the trends over the period in each of the areas of drivers, occupants, vehicles, highways, state regulatory laws, infrastructure and safety programs, and the economic environment. Each of these affected the baseline of traffic safety over the period. 6.1 Age This section considers trends in the age distribution of both drivers and victims in fatal traffic crashes, 2001-2012. Drivers were aggregated into four groups, reflecting crash risk and legal status: 15-17, the group subject to Graduated Driver Licensing (GDL) laws; drivers 18-25, who typically have higher crash rates; drivers 26-64, with typically lower crash rates over that span; and drivers 65 and older, when crash rates typically increase (Massie, Campbell et al. 1995). The trends were important in terms of the overall impact on fatal crash rates; in addition, the younger age groups were disproportionately involved in the decline in traffic fatalities beginning in 2008. Figure 6-1 illustrates long-term trends as well as changes in the distribution that occurred at about the time of the recession. The share of younger drivers in fatal crashes declined, while the share of older drivers increased. The proportion of drivers aged 15 to 17, declined from about 5% in 2001 to 2.4% in 2012 (left axis). The decline was relatively constant and not apparently affected by the recession. At the same time, the percentage of drivers 26-64 steadily increased over the entire period from 60% to about 63% annually (right axis). However, the 18-25 year-old group showed a marked decline beginning around 2008, from around 22% of drivers in fatal crashes to 20%. Older drivers increased their percentage at the start of the recession from around 10% to almost 13% by the end of the period.
Page 19 Figure 6-1 Percentage of driver age bands by crash year in fatal crashes It is likely there was an actual reduction in travel by teens and young adults (age 25 and under) at about this period. VMT data by driver age and each year in the period are not available, but there is some evidence of a reduction in travel from the National Household Travel Survey (NHTS). The NHTS (formerly the Nationwide Personal Transportation Survey (NPTS)) collected data from a representative sample of respondents on daily trips of individuals and households. The data are self-reported, but collected using a reasonably consistent methodology, so trends should be reliable. The surveys have been conducted every 5 to 8 years. The most recent surveys were conducted in 1990, 1995, 2001, and 2009. The youngest age group reported (16-19) showed a consistent reduction in average yearly travel from 1990 in subsequent survey years. Older age groups reported increases in yearly travel from 1990 through 2001. However, each age group reported a decline in average travel in 2009, which happened to be during the recession, except for the oldest group, 65 and older. Moreover, the reported decline in annual travel in 2009 for drivers 20 to 34 was substantially greater than any of the older age groups. Drivers 20 to 34 reported a 12.4% decline in travel from the previous survey in 2001, while drivers 16 to 19 reported a 14.8% reduction. The reported decline for drivers 35 to 54 was only 3.3%, while drivers 55 to 64 report driving 4.9% fewer miles in 2009 than in 2001 (Santos, McGuckin et al. 2011). The data are just a snapshot of travel estimates in 2001 and 2009; it is unfortunate that VMT estimates by driver age were not available for the years between and after the NHTS surveys. However, the evidence from the NHTS is consistent with the hypothesis that one effect of the recession was to reduce driving by teens and young adults more than older age cohorts. The figure above shows how the distribution of the age of drivers in fatal crashes changed over the period. The next figure (Figure 6-2) enlarges the scope to the age distribution of those who were actually killed in the crashes, including drivers, passengers, pedestrians, and other non-motorists. The ratio of fatalities in each year by age group to the number of fatalities in 2001 illustrates how traffic fatalities for the age groups changed over the period. Traffic fatalities for the younger groups dropped proportionately
Page 20 more than for other groups. The total of traffic deaths fluctuated within a narrow band prior to 2008, dropping thereafter. Disaggregating by age group, however, revealed different patterns. Traffic fatalities for persons 65 and older were actually increasing prior to 2008 relative to 2001 (ratio was greater than 1.0), while traffic fatalities for persons 26-64 started declining in 2006 and continued to decline to 2009 when the number leveled off. Fatalities among the younger group, those up to age 25, declined the most over the period. The number was reasonably stable from 2001 to 2006 (ratio about 1.0), but then declined, so that by 2010, almost 40% fewer persons 25 and younger were being killed annually in traffic crashes, compared with 2001. The sharp decline began in 2008, which is roughly coincident with the recession. Figure 6-2 Ratio of traffic fatalities by age groups, 2001 to 2012 The percentage of drivers 25 and under declined beginning in 2008, and the decline continued through 2012. Considering all fatalities, not just drivers involved in fatal crashes (whether or not they were fatally injured), the reduction in traffic fatalities in 2008 and later was disproportionately a decline in the number of people under 26 who died in traffic crashes. A simple estimate of the reduction in traffic fatalities 2008 through 2012, compared with 2007, was computed by assuming that each year after 2007 would have the same number of fatalities as 2007, taking the difference from the actual number, and then summing across the years from 2008 through 2012. In Figure 6-3, the group of columns on the left shows the percent distribution of traffic fatalities in 2007 by age group, while the group of columns on the right shows the percentage of the reduction in traffic fatalities accounted for by the different age groups. If the decline in fatalities was proportional for each of the age groups, the shapes of the distributions would be the same, but they are substantially different. In 2007, the under-26 group accounted for 31.1% of fatalities. However, that group accounted for 47.7% of the decline in fatalities, 2008 through 2012. In comparison, persons 26 to 64 were 54.9% of fatalities in 2007, but accounted for only 44.2% of the reduction. In other words, the decline in traffic fatalities 2008-2012 was driven more by reductions in the younger age cohorts than the older.
Page 21 Figure 6-3 Estimated reduction in traffic fatalities, 2008-2012, by age 6.2 Changes in vehicles and person types involved in fatal crashes This section provides perspective on the distribution of vehicles and persons involved in fatal crashes. Neither was particularly important in influencing the substantial decline in fatalities 2008-2012, but both reflected long-term trends that affect the overall level of traffic safety. Personal transportation seemed to rotate away from passenger cars to LTVs, which include minivans and sport utility vehicles (SUVs). The incidence of fatalities among vulnerable road usersâmotorcycles, pedestrians, bicyclistsâwas low relative to motor vehicle occupants, but generally trended up, though the trends varied among them. Over the years from 2001 through 2012, passenger vehicles declined in terms of the numbers involved in fatal crashes. The decline was reasonably steady up to 2007 and appeared to be part of a process in which LTVs gradually replaced passenger vehicles for personal travel (Figure 6-4, left axis). The number of trucks involved in fatal crashes was relatively constant up to 2007, dipped sharply in 2009, and then gradually recovered (right axis). Motorcycles increased up to 2009, declined and then recovered slowly, so that by 2012, the number was close to the pre-recession high. The number of buses involved in fatal crashes over the period was fairly stable, ranging from a low of 221 in 2009 to a high of 305 in 2001 and 2006. The âotherâ vehicle type consisted of a wide variety of all-terrain vehicles, snowmobiles, farm equipment, and the like. All vehicle types showed some sensitivity to the recession; trucks, as the most economically-sensitive type declined the most, but there are also clear long-term trends in the rotation from passenger cars to LTVs, and increase in motorcycle fatal involvements. Motorcycles in fact surpassed trucks in fatal crashes in 2007 and have been substantially greater since.
Page 22 Figure 6-4 Passenger car, LTV, truck, motorcycle, bus, and other motor vehicle involvements in fatal crashes, 2001-2012 Figure 6-5 illustrates how the involvement of different motor vehicle types changed over the period. Relative to 2001, the number of passenger cars in fatal crashes declined steadily, accelerating somewhat in 2008 before leveling off and then actually increasing slightly in 2012. LTVs actually increased in number up to 2008 and then declined through the recession and subsequent years. Trucks declined the most sharply and then rebounded after one year. Motorcycles increased each year from 2001 through 2008. In fact, in 2008, there were about 60% more motorcycles in fatal crashes than in 2001. The number decreased sharply in 2009, leveled off for a year and then increased again. Figure 6-5 Trends in vehicle involvements in fatal crashes, 2001-2012
Page 23 Most fatalities in traffic crashes are drivers of motor vehicles, and that did not change over the period (Figure 6-6). The percentage of drivers rose from about 61% of fatalities in 2001 to about 64% in 2012. The most significant decline was in the proportion of passengers, from about 25% in 2001 to 20% in 2012. The proportion of pedestrians and bicyclists actually increased, going from about 13% combined in 2001 to over 16% in 2012. These trends could reflect changing modal shares (more pedestrian and bicycle travel) or improvements to occupant protection through seat belts, air bags, and improved crashworthiness of light vehicles. Figure 6-6 Distribution of fatalities by person type, 2001-2012 Figure 6-7 illustrates more clearly how the number of fatalities by crash role changed over the period. The decline in passenger fatalities started before the beginning of the recession in December 2007, though the decline accelerated with the recession. The number of drivers killed actually increased somewhat prior, and then dropped sharply. Counts of pedestrian fatalities were relatively stable prior to the recession, then dropped in 2008 and 2009 before trending back up. Bicycle fatalities were comparatively few (averaging 805 over the period) and fluctuated within about a band Â±10%, declining at the recession, before increasing at the end of the period. The increases in the numbers of pedestrian and bicyclist fatalities may have reflected an increase in travel. As vulnerable road users, this would have represented upward pressure on the overall level of traffic safety. But, given the relatively low share they represented of the overall number of fatalities, they would not significantly mitigate the downward trend for drivers and passengers.
Page 24 Figure 6-7 Trends in fatalities by person type, 2001-2012 6.3 Roadway class & type Figure 4-2 above showed that VMT generally increased each year from 2001 through 2007, dipped slightly in 2008 and then remained relatively flat through 2012. This section disaggregates VMT by roadway function class and area type (urban/rural) to identify important trends that affected the traffic fatality totals. VMT tended to increase in terms of actual miles traveled over the period in urban areas and contemporaneously to decrease in rural areas (Figure 6-8). In urban areas, the trend started to flatten out the year prior to the official start of the recession, while rural travel continued its decline. The effect of the recession on VMT appears to have halted the gradual increase in urban travel, while the decline in rural VMT continued. Figure 6-8 illustrates this graphically; all the lines above the trend for all VMT are urban roads and all below are rural. Overall, the proportion of VMT in rural areas declined from about 39.7% in 2001 to 32.9% in 2012. This shift was important because rural VMT tended to have higher fatality rates than urban, so a shift to urban travel would result in lower fatality rates per VMT overall. In addition, travel on Interstate-quality roads had significantly lower fatality rates than lower road classes in both urban and rural areas (Table 6-1).
Page 25 Figure 6-8 Trends in VMT by area and road type, 2001-2012 Table 6-1 Fatality rates per 100 million VMT, by roadway function class, 2001-2012 YearÂ RuralÂ interstateÂ RuralÂ arterialÂ OtherÂ ruralÂ RuralÂ totalÂ UrbanÂ freewayÂ UrbanÂ arterialÂ OtherÂ urbanÂ UrbanÂ totalÂ AllÂ roadsÂ 2001Â 1.15Â 2.17Â 3.12Â 2.27Â 0.68Â 1.16Â 1.22Â 1.01Â 1.51Â 2002Â 1.18Â 2.16Â 3.21Â 2.30Â 0.67Â 1.11Â 1.23Â 0.98Â 1.51Â 2003Â 1.17Â 2.33Â 3.04Â 2.30Â 0.65Â 1.13Â 1.24Â 0.98Â 1.48Â 2004Â 1.21Â 2.49Â 2.99Â 2.36Â 0.64Â 1.04Â 1.17Â 0.93Â 1.44Â 2005Â 1.27Â 2.35Â 3.17Â 2.38Â 0.65Â 1.10Â 1.14Â 0.95Â 1.46Â 2006Â 1.12Â 2.26Â 3.08Â 2.28Â 0.63Â 1.10Â 1.18Â 0.95Â 1.42Â 2007Â 1.04Â 2.28Â 3.03Â 2.25Â 0.59Â 1.02Â 1.14Â 0.90Â 1.36Â 2008Â 1.00Â 2.11Â 2.88Â 2.12Â 0.55Â 0.91Â 1.05Â 0.82Â 1.26Â 2009Â 0.84Â 2.04Â 2.63Â 1.97Â 0.48Â 0.82Â 0.96Â 0.73Â 1.15Â 2010Â 0.86Â 1.86Â 2.48Â 1.84Â 0.48Â 0.87Â 0.90Â 0.74Â 1.11Â 2011Â 0.81Â 1.89Â 2.45Â 1.82Â 0.49Â 0.85Â 0.92Â 0.74Â 1.10Â 2012Â 0.75Â 2.07Â 2.46Â 1.88Â 0.47Â 0.92Â 0.98Â 0.77Â 1.14Â The result of the shift of travel from rural to urban roads, in combination with lower fatal crash risk on urban roads, was that rural roads, particularly rural Interstate highways and rural other roads, accounted for a somewhat disproportionate share of the reduction in traffic fatalities from 2008 through 2012. In 2007, about 6.5% of traffic fatalities occurred on rural Interstate highways, 21.7% on rural arterials and 28.1% on other rural roads. However, about 8.4% of the decrease in fatalities, 2008-2012, was accounted for by fewer traffic fatalities on rural Interstate highways and 31.1% of the reduction was accounted for
Page 26 by rural other roads (Figure 6-9). The difference between road types was not huge, but it was substantial and consistent with the change in travel patterns illustrated in Figure 6-8. Figure 6-9 Estimated reduction in traffic fatalities 2008-2012 by road type Aggregating across road types to urban/rural, traffic fatalities in rural areas fell persistently over the period. The decline began before the official start of the recession in December 2007, beginning in 2006- 2007. In urban areas, the number of traffic fatalities trended up prior to the recession in absolute terms, as shown by a ratio to 2001 greater than 1.0 in Figure 6-10. The decline in urban areas began in 2007 and accelerated in 2008 through 2009, and then stabilized before increasing slightly in 2012. In contrast, traffic fatalities in rural areas started a gradual decline in 2005, but then dropped sharply in 2008. The number continued to decline through 2011, before ticking up slightly in 2012. Figure 6-10 Ratio to 2001 of traffic fatalities in urban and rural areas, 2001 to 2012
Page 27 The net of these trends was that rural areas contributed disproportionately to the reduction of traffic fatalities in 2008 through 2011. In 2007, about 56.4% of traffic deaths occurred in rural areas, but rural areas accounted for over 60% of the reduction in fatalities subsequently (Figure 6-11). The difference between urban and rural areas was not overwhelming, but it was significant and consistent with changing travel patterns. Figure 6-11 Estimated reduction in traffic fatalities 2008-2012 by area type 6.4 Vehicle design and model year An 81% reduction in the VMT fatality rate has been documented over the period spanning 1960 to 2012 (Kahane 2015). Kahane showed a steadily-declining fatality risk related to improvements in occupant protection and crashworthiness over his study period of 1960 through 2012. The decline was related to changes in the Federal Motor Vehicle Safety Standards (FMVSS) to improve occupant protection (e.g., seat belts and air bags), crashworthiness (e.g., side impact protection, roof crush resistance, fuel system impact protection), and crash avoidance technologies (e.g., electronic stability control (ESC)). Many of the changes were implemented prior to the 2001-2012 target period; however, Kahaneâs model showed a decline in fatality risk at a relatively constant rate throughout the period. Thus, it is assumed here that fatality risk related to vehicle design and occupant protection improved at a constant rate over the period. In effect, the continual evolution of the vehicle fleet to newer models acts as a continuing and consistent downward pressure on traffic fatalities. Over the 2001-2012 target period, changes in the FMVSS safety standards included FMVSS No. 138 (2005) which required all new cars and LTVs TPMS built after September 1, 2007, be equipped with a tire pressure monitoring system. While this technology has likely improved fuel economy and vehicle handling for most drivers, it is unclear how much of a direct benefit in crash reduction has occurred as a consequence. Target crashes reductions would be related to tire blowouts and consequent loss of vehicle control. FMVSS No. 126 required electronic stability control (ESC) in all cars and LTVs. Kahane (2014)
Page 28 reported that ESC was responsible for a 60 percent reduction of fatal single-vehicle rollovers (Kahane 2014). Similarly, Farmer (2004) reported a 41% reduction in single-vehicle crash involvement, and a 56% reduction in single-vehicle fatal crash involvement. Estimates of fleet penetration over 2001 to 2013 begin at less than 1% and show a regular increase to about 42% in 2013 (Highway Loss Data Institute 2014). There is evidence that a significant decline in single vehicle rollover crashes can be related to ESC (National Highway Traffic Safety Administration 2007; Flannagan and Leslie 2012). Farmer and Lund (2006, 2014) reported significant declines in crash fatal injury risk related to improvements in both occupant protection and crashworthiness. The New Car Assessment Program (NCAP) was first implemented in the 1970âs, establishing star-ratings as a way to encourage automobile manufacturers to compete on occupant protection and safety (MacKenzie, Hoyt et al. 2003). There were some changes to the program during the period (Hsia and Shen 2011), as well as changes to the FMVSS to improve the crashworthiness of passenger cars and light truck vehicles. There were upgrades to the rear-impact standard phased in 2005-2007 to reduce post-crash fires, roof crush updates in 2009, and enhancements to the side door beam regulations in 2010 (Kahane 2015). Figure 6-12 presents the distribution of the age of motor vehicles in fatal crashes over the period. The right axis shows the percentages of vehicle cohorts aggregated into groups representing vehicles less than 3 years old, 3 to 5 years, 6 to 10 years, and more than 10 years old. The right axis shows the overall average age of the vehicles (top line). Prior to 2008, the share of the different age cohorts remained relative stable. Vehicles 6 to 10 and more than 10 years of age accounted for about 27% to 30% of vehicle involvements. Vehicles 3 to 5 years and less than 3 years old accounted for 20% to 23%. However, beginning in 2009 there was a sharp drop in the percentage of newer models and a corresponding increase in the share of the oldest age cohort. Some fraction in the drop in the proportion of newer models after 2010 may be attributed to the fact that the cutoff in the series is 2012. However, the mean age of vehicles involved followed the same pattern (right axis). Between 2008 and 2012, the mean age of motor vehicles involved in fatal crashes increased by almost two full years.
Page 29 Figure 6-12 Age of vehicles in fatal crashes, 2001-2012 The pattern may be partly explained by the penetration of ESC-equipped vehicles. ESC is particularly effective against âuntrippedâ rollovers (rollovers due to lateral acceleration rather than impact with objects) and crashes precipitated by loss of control, both of which are overrepresented in fatal crashes. Figure 6-13 shows the estimated penetration of ESC (left axis) into the registered vehicle fleet by calendar year. The data were extracted from (Highway Loss Data Institute 2014). These data are only available at the national level and were used in the statistical modeling, below, to capture the effect of ESC on the number of motor vehicle fatalities. Figure 6-13 Fleet penetration of ESC (adapted from (Highway Loss Data Institute 2014)) and penetration of post-1991 model year
Page 30 Figure 6-13 also shows the penetration of post-1991 model year vehicles on the roadway. This metric was used as a surrogate to reflect the improvements in crashworthiness and occupant protection identified by Kahane. Vehicle registration data could not be obtained over the target years to directly estimate the population of registered vehicles by model across the target years of the project,. Instead, an estimate was derived using quasi-induced exposure (QIE) (Chandraratna and Stamatiadis 2009; Keall and Newstead 2009). QIE is a method for indirectly estimating exposure data from crash data. QIE assumes that in certain crash types, certain vehicles did not contribute to the crash so those vehicles are in effect a sample of vehicles on the road. Vehicles that were struck in the rear in a rear-end crash are typically assumed to have not contributed to crashes, so they are treated as an acceptable surrogate of the population of vehicles on the road. In the present case, data from the National Automotive Sampling Survey General Estimates System (NASS GES) were used for the estimate (NHTSA 2014). The GES file is a nationally-representative sample of police-reported crashes. All vehicles struck in the rear in a rear-end crash were identified in the GES data for 2001 through 2012. For each year, the proportion of those vehicles that were model year 2001 or later was computed. The data are displayed in Figure 6-13 (right axis). Since the vehicles were all in use on the roadway, the estimate is a measure of their exposure to crashes. The assumption that rear- end struck are a valid sample of vehicles on the road may not be true in all cases, but it seems reasonable. Moreover, the estimates are plausible. The 1991 model year was chosen to get a span of about 10 years prior to the initial year of the period being studied. Moreover, the increased âpenetrationâ of the post- 1991 model year occurred at about the same rate as Kahaneâs vehicle-based risk index, so it is considered to be a reasonable surrogate for the effect of increased safety from improvements in vehicle design. 6.5 Restraint use Safety belts are a primary technology in motor vehicle occupant protection. Kahane (2004) estimated that belts are responsible for 60% of lives saved by all Federal Motor Vehicle Safety Standards (FMVSS) in 2002 (14,570 of 24,561) (Kahane 2004). Updated results in 2015 estimated that seat belts saved 56% of the total saved by FMVSS technologies in 2012 (Kahane 2015). Again, safety belts were by far the most effective occupant protection. Evans, in a classic 1986 paper demonstrating the double-pair comparison method, estimated the effectiveness of seat belts in preventing fatalities at 43%, +/- 3%, compared with no belts (Evans 1986). With the exception of New Hampshire, all states have mandatory seat belts laws. Many states have primary enforcement laws, meaning that traffic police may stop a vehicle solely to ticket occupants for non-use. The period between 2001 and 2012 experienced a reasonably steady increase in the proportion of front- seat occupants using safety belts. Figure 6-14 shows observed belt use (top line), belt use reported for all drivers in fatal crashes (middle line) and belt use reported for fatally-injured drivers in crashes. In 2001, the national average was 73% observed belt use, and by 2012, the percentage increased to 86% (Chen 2014; Pickrell and Liu 2014). Drivers in fatal crashes tended to have lower belt use, but the reported usage rate increased fairly steadily over the period. Fatally-injured drivers had yet lower reported belt use,
Page 31 but that too increased over time. There was a slight dip in 2008, but the trend continued to increase thereafter, flattening out slightly in 2010 through 2012. Figure 6-14 Driver safety belt use: Observed, drivers in fatal crashes, & fatally-injured drivers The above is reported for national-level statistics. There does not appear to be any discontinuity in the increasing penetration of safety belt use in the driving population. For the purposes of statistical modeling, state-level data for the observed level of safety belt use was used. Figure 6-15 illustrates the range of observed safety belt use across the years and among the states. It is not expected that the reader will be able to discern the pattern for any set of specific states; the data are shown in this way to convey that the overall trend was toward increased observed belt use, but also that there was significant variation among states and over time. Belt use rates ranged from a low of 49.6% in New Hampshire in 2003 to a high of 98.0% in Michigan in 2009. Individual state-level observed belt use rate data were used in the models developed for the project.
Page 32 Figure 6-15 Trends in observed safety belt use by state, 2001-2012 6.6 State regulation of driver behavior, alcohol consumption State legal environments attempt to motivate road users to adopt behaviors to increase traffic safety. A recent paper from Silver, Macinko, et al., measured the effect of state-level traffic safety policy on traffic fatalities from 1980 to 2010. An index of state laws, covering alcohol, restraints, and licensing, showed a consistent increase in regulations intended to increase safety over the period. This result is analogous to Kahaneâs observation of a relatively steady-state increase in safety related to vehicle design (Kahane 2015). Many reports and papers relate traffic safety regulation to lower crash rates and traffic fatalities. A paper by Dang (2008) showed the efficacy of alcohol-related legislation in an analysis of trends in the incidence of fatal traffic crashes (Dang 2008). Other measures related to alcohol consumption, such as beer taxes, have been shown to be associated with the incidence of traffic crashes. There is evidence that younger drivers are disproportionately affected by drunk driving laws, higher beer taxes, as well as GDL laws (Silver, Macinko et al. 2013; Macinko, Silver et al. 2015), though one study showed no effect for beer taxes on 15-17 year old drivers (Morrisey and Grabowski 2011). Differences in these laws regulating driver behavior have been shown to account for some of the state-to-state variation in fatal crashes and fatalities. Belt use laws, typically categorized as primary or secondary enforcement laws, appeared as significant variables in state-level analyses of trends in fatal crashes and traffic fatalities. For example, see (Grabowski and Morrisey 2004; Morrisey, Grabowski et al. 2006; Silver, Macinko et al. 2013; Ferdinand, Menachemi et al. 2014). In the present study, safety belt laws were rated based on whether there was primary or secondary enforcement, and whether belts were required for rear seating positions. Primary enforcement permits vehicles to be stopped solely for violation of belt laws; secondary enforcement means enforcement only
Page 33 occurs secondary to some other primary offense. Figure 6-16 shows an index of the relative ratings of states over the period, with 1 being the most restrictive and 0 no requirements. All 50 states were included in the graph. Sloping vertical lines indicate states that strengthened their belt use requirements, along with the years where laws were tightened. As the graph illustrates, belt use laws were strengthened in at least some states every year during the period from 2001 to 2012, except for 2008. Seven states had primary enforcement at all seating positions over the entire period. Fourteen states strengthened their safety belt laws in the period, mainly through moving to primary enforcement from secondary. By 2012, 18 states had primary enforcement for adults for both front and back seats. Alaska had no safety belt requirement before 2007; only New Hampshire had no safety belt requirement throughout the period. Figure 6-16 Safety belt laws rating index by state and year, 2001-2012 Motorcycle helmet laws were rated by coverage, whether adults or just youth (defined by thresholds ranging from 14 to 21) were covered, and whether all riders or just passengers were covered. Ratings ranged from 0 (no helmet use required for any rider) to 4 (universal coverage). Only two states made any changes in their coverage over the period. In 2003, Pennsylvania limited coverage to riders 20 and younger. In 2003, Louisiana required motorcycle helmets for all riders by removing the exemption for riders 18 or older. However, there was wide variation between states in requirements. Three states had no motorcycle helmet requirement during the period (Iowa, Illinois, and New Hampshire), while 19 had universal helmet laws, requiring motorcycle helmets for all riders. Other states required helmets only for passengers or only for youths, defined by a range of ages from 14 to 21. Twenty-five states required helmets only for youth, and two state required them only for passengers. The index covering the regulation of alcohol use incorporated a number of measures. The index included BAC level, jail terms and fines for violations and multiple offenses, license suspensions, third-offense
Page 34 felony laws, ignition interlocks for offenders, required treatment programs, victim rights laws, and increased penalties for so-called super drunks. All states had 0.08 blood alcohol concentration (BAC) laws by 2005, but states varied in penalties for alcohol-impaired driving, in terms of the strength of administrative license revocation rules, ignition interlock, and other related enforcement. Data on state laws prescribing allowable blood alcohol concentration (BAC) levels and penalties for violations was generously supplied by Kathleen Klinich of UMTRI (Klinich 2016). States varied in their approaches to alcohol-impaired driving over the period. For example, two states (New Hampshire and Wisconsin) had no jail time for a first offense, 18 had up to one year, and two (Massachusetts and Vermont) allowed up to two years in jail. Fines ranged from $250 for a first offense up to $10,000. Twenty-eight states had no provision for an ignition-interlock device for a first offense, but twenty did at some point over the period. In 2001, only one state (Oregon) had an ignition interlock provision for a first offense, but by 2012, twelve states had it for a first offense, 39 for a second offense, and 41 for a third offense. Figure 6-17 shows the trend of the alcohol-laws index over the period, by state. Each state was rated each year based on their laws on 21 items related to drunk driving. For the purposes of the figure, state ratings were scaled from 0 to 1, with one being the most strict on all dimensions. The figure illustrates the wide range of differences from state to state as well as a trend over the period toward increasing the stringency of alcohol laws through increased fines, jail terms, license suspensions, and reduced allowable BAC levels. Figure 6-17Alcohol laws rating index by state and year, 2001-2012\ The indexes for the regulation of the use of safety belts, alcohol, and motor cycle helmets were incorporated into models to measure the association with the overall level of traffic safety and their contribution to the drop in traffic fatalities 2008-2012.
Page 35 In addition to the foregoing indexes of state regulation of driver behavior, the models included a measure of alcohol consumption, which more directly reflects a critical element of actual driver behavior. Data on per capita alcohol consumption were compiled from (Haughwout, LaVallee et al. 2015). The data were from annual surveys by the National Institute on Alcohol Abuse and Alcoholism (NIAAA), based on sales data compiled from the states, industry, and other sources. The estimates of apparent per capita consumption were expressed gallon of ethanol equivalent. Figure 6-18 shows national trends in beer, wine, and liquor over the period. Note that the data were for alcohol consumption at the population level, not for motor vehicle drivers. Beer was the predominate form of alcohol consumed. Per capita consumption was relatively level through 2008 and then declined slightly through 2011, with a slight increase in 2012. The consumption of wine and liquor increased steadily over the period. Wine consumption increased about 3% annually and liquor consumption increased about 2% annually. At the national level, both were apparently unaffected by the recession, but beer consumption declined by about -2.5% in 2009 and -2.7% in 2010. Figure 6-18 Per capita consumption of beer, spirits, and wine 6.7 Economic factors, national trends Economic conditions played a major role in the decline in the number of fatalities in traffic crashes from 2008 through 2012. Numerous papers have documented an association of various measures of economic activity with fatal crash rates and traffic fatalities. Silver and Macinko used the poverty rate, unemployment rates, and tax revenues per capita (Silver, Macinko et al. 2013). Noland (2014) found significant effects for median income and the Gini coefficient (a measure of economic inequality) in some models of the decline in fatalities, 2006-2012 (Noland and Sun 2014). Kweon (2015), in an analysis of the decline associated with the recession in Virginia, found significant effects for changes in the rate of inflation as measured by the CPI, unemployment number and unemployment rate (Kweon 2015).
Page 36 Grabowski and Morrisey demonstrated a connection between fuel prices and fuel taxes, VMT, and crash fatalities (Grabowski and Morrisey 2004; Grabowski and Morrisey 2006; Morrisey and Grabowski 2011). There are at least three modes by which changes in the economic environment might affect the level of traffic fatalities and safety. The most direct is that the recession lead to reduced travel demand, which in turn decreased exposure to fatal crashes and thus the number of traffic fatalities. Figure 4-2 shows a decline in VMT over the period, but likely not enough to explain the decline in fatalities by pure exposure. Secondly, the recession may also have differentially affected different population groups, reducing the travel of riskier drivers or reducing travel on riskier roads. Finally, the recession may have reduced the amount of risky driving by reducing the amount of discretionary or leisure driving. These mechanisms were tested using data on per capita gross domestic product (GDP/capita), median income, unemployment rates by age group, and net fuel costs at the pump (fuel price plus taxes). Each measure is in effect a surrogate for measures that were not obtainable. For example, it would have been desirable to have data on travel by age group over the period, or employment status of the population involved in fatal crashes. But those data do not exist. Instead, GDP/capita and median income per household were used as surrogates for the propensity to travel, assuming that reduced income also reduces the ability to drive as much. Median income is believed to be a useful measure of the economic condition of the less affluent, while GDP/capita was used as a measure of the overall level of economic activity normalized to a stateâs population. Fuel costs, including taxes, directly affect amount of driving, since higher costs increase costs per mile of travel, which in turn was likely to reduce travel, and thus exposure to fatal crashes, and consequently the number of traffic fatalities. GDP per capita increased steadily over the first part of the period, increasing from about $37,000 dollars per capita in 2001 to $48,100 in 2008, the peak prior to the recession (Figure 6-19). There was a sharp dip in 2009, which saw the depth of the recession, but then a resumption of the steady increase through the rest of the period. GDP/capita recovered to its pre-recession peak by 2010 and was $52,500 in 2012. The pattern for median income was substantially different. Median income was measured at the household level, and so can be greater than GDP/capita because of multiple-income households. Median income, again in constant (2013) dollars, fluctuated in a narrow band up to 2007, ranging from a high of $56,600 in 2001 to a low of $54,500 in 2004. Median income then began a steady decline in 2008, and by 2012 was $4,700 lower in 2012 than in 2007. GDP/capita recovered from the recession, but there was no recovery reflected in median household income (US Bureau of the Census 2016; World Bank 2016).
Page 37 Figure 6-19 Trends in median household income and GDP/capita, 2001-2012 Unemployment was relatively stable from 2001 to prior to the recession (Figure 6-20). The left axis, for unemployment, is inverted so that increases in the unemployment rate slope down and decreases in the rate slope up. For all Americans, the rate increased from 4.8% in 2001 to 6.0% in the downturn of 2003, before declining again to about 4.6% just prior to the recession that officially began in December 2007. Then the rate increased sharply to 9.6% in 2010 before declining again to 8.1% in 2012. For younger members of the labor force, 16-24 years of age, unemployment rates followed a similar pattern but were about double the rates of older workers. Unemployment for teens and young adults ranged from 10.6% to 12.5% in the years up to the recession, but then increased to 18.6% in 2010 (Bureau of Labor Statistics 2016). Figure 6-20 Unemployment rate by age
Page 38 Figure 6-21 shows fuel costs, which represents the price at the pump, including taxes, in constant 2013 dollars. Fuel costs increased steadily from 2002 ($1.84/gallon) to 2008 ($3.46/gallon), dropped sharply in 2009 to $2.61/gallon, and then resumed the upward trend, closing the period at $3.67/gallon for 2011 and 2012 (US EIA 2016). Increasing fuel costs, other things being equal, should reduce the amount of travel and thus exposure to fatal crashes. Figure 6-21 Fuel prices, constant 2013 dollars, 2001-2012 Unemployment rates and fuel costs by year and state were used in the models to capture variability associated with the different state economies. For example, in the recession year of 2009, the unemployment rate for 16-24 year olds ranged from 8.3% in Nebraska to 22.2% in Alabama. Similarly, fuel prices varied by state. For example, in 2009, prices ranged from $2.26/gallon in Georgia to $3.07/gallon in Washington. 6.8 Highway and infrastructure The design, condition, and level of enforcement and related safety programs on the roadway system are also critical elements in the level of traffic safety. Table 6-1 above illustrated the variation of fatal crash rates across different roadway function classes. Differences in fatal crash rates reflect traffic density and speed, but also includes geometric design elements such as lane widths, presence and type of shoulder, degree of curvature, and protective features such as guard rails. Other safety-related roadway factors include the level of traffic safety enforcement and educational programs such as campaigns to increase seatbelt use or reduce drunk driving. Albalate et al. (2013) used variables such as spending on construction and maintenance to capture the improvements of the infrastructure on reducing traffic fatalities (Albalate, FernÃ¡ndez et al. 2013). Infrastructure improvements include widening narrow roads, installation of rumble strips, road markings, signing, lighting, median separation, deployment of yield to pedestrian channelizing devices, providing
Page 39 curve warning signs, removal of sight distance obstructions, removal of fixed objects along the road, anti- skid surfaces, guard rails, and wrong way driving countermeasures, among others (AASHTO 2010; Wunderlich 2015). These programs are generally focused on removing hotspots in the road network that tend to have higher crash risks. Although there is a substantial body of research to show that these programs reduce traffic fatalities, it is not possible to explicitly control for the effect of specific programs in a nationwide analysis. Moreover, by their very nature, improvements to the roadway system as a whole tend to be incremental and long-term, rather than resulting in sharp, system-wide declines. State highway fund expenditures were used to capture the safety effect of highway spending and infrastructure improvements. Comprehensive data were used to capture state highway expenditures in four broad areas: capital expenditures for construction; maintenance and repair; administration, research, and planning, and law enforcement and safety programs. The expenditures included funding from Federal safety programs under sections 402, 403, 405,406, 407,408, 410, and 411, as well as funding provided by the Motor Carrier Safety Assistance Program (MCSAP) (Federal Highway Administration N.D.). In addition, funding under the Highway Safety Improvement Program (HSIP) was included (FHWA 2016a; FHWA 2016b). Each year, states used HSIP funds to implement low- to medium-cost safety improvements throughout the nation. The overall purpose of the HSIP program was to achieve a significant reduction in traffic fatalities and serious injuries on state roads through the implementation of medium cost infrastructure-related highway safety improvement projects. State highway expenditures were classified into four areas (definitions taken from (Federal Highway Administration N.D.)): Capital: all expenditures for construction, relocation, resurfacing, restoration, rehabilitation and reconstruction (3R/4R), widening, capacity improvements, restoration of failed components, additions and betterments of roads and bridges. Here and for the purposes of the statistical modeling (section 7), the proportion of capital spending designated by the state as safety-related was excluded from capital expenditures and added to the highway law enforcement and safety spending category below. Maintenance: the function of preserving and keeping the entire highway, including surface, shoulders, roadsides, structures, and traffic control devices, as close as possible to the original condition as designed and constructed. For improved or reconstructed facilities, subsequent maintenance work only insures continued service as redesigned. Also include preventive maintenance activities. Administration, research, and planning: includes general administration, supervision, DOT overhead, not directly related to specific projects, as well as expenditures for highway planning and research to support road planning and design and traffic research. Highway law enforcement and safety: highway law enforcement and safety expenditures by the State DOT, State police, department of public safety, traffic safety commission, and other agencies. These expenditures are classified as: (1) traffic supervision and the enforcement of State highway laws and ordinances; (2) highway, traffic, and driver safety programs; (3) motor-vehicle inspection programs; and
Page 40 (4) enforcement of vehicle size and weight limitations. Safety also included the safety proportion, as determined by each state, of expenditures on capital improvements. HSIP funds were included as safety related. HSIP funds can be used for infrastructure programs related to safety, but also for non- infrastructure activities. Any highway safety program, identified through a data-driven process, may be funded under HSIP.2 Highway expenditures for each year were converted into 2013 dollars to control for the effect of inflation. To control for the fact that states differ in terms of population size, area, and the size of the roadway system, expenditures were normalized by dividing expenditures (in constant, 2013 dollars) by the number of highway miles in each state. This partially controls for the fact that states with large populations and roadway systems spent significantly more in absolute terms on highways than smaller states with smaller populations and road systems. Expenditures on the four areasâcapital, maintenance, administration, and safetyâwere used to examine the association with the traffic fatalities over the period. Figure 6-22 shows general national trends over the entire period for the four categories, along with total. Expenditures were summed across states and then divided by the sum of highway miles to get national averages. Capital expenditures (right axis) accounted for the greatest share, ranging from an average of about $49,000/mile in 2004 to $60,000/per mile in 2009. There was a gradual increase over the period, with a slight drop in the recession year of 2008, an increase to 2009 and then relatively stable thereafter. In comparison, safety-related spending, on a per highway mile basis, was substantially lower, though increasing fairly steadily over the period. The low was $7,600/highway mile in 2001 to $10,900/highway mile in 2012. Figure 6-22 Highway spending per mile of highway, 2001-2012 2 See http://www.fhwa.dot.gov/map21/qandas/qahsip.cfm
Page 41 Table 6-2 provides some descriptive statistics at the state level. The amounts that states spent on a per- highway-mile basis varied substantially from state to state. On average, states spent about $64,700/highway mile on capital expenditures, varying from a low of $11,100/highway mile (South Dakota) to $282,000/mile in Delaware. Maintenance, administration/research/planning, and safety expenditures also varied materially between states and across years. State expenditures across the four categories, by year, were used in the statistical modeling to measure the association with traffic fatalities. Table 6-2 State highway expenditures per highway mile, 2010-2012, in 1000s of 2013 dollars HighwayÂ spendingÂ perÂ mileÂ ExpenditureÂ typeÂ TotalÂ CapitalÂ MaintenanceÂ Administration,Â research,Â planningÂ SafetyÂ AverageÂ 64.7Â 20.7Â 10.2Â 10.9Â 106.6Â MinimumÂ 11.1Â 0.8Â 1.0Â 1.0Â 20.5Â MaximumÂ 282.0Â 266.7Â 150.5Â 60.7Â 459.3Â Part of the variation between states was likely related to geographical and demographic differences between them. The states that tended to rank toward the top of per mile spending were typically small and densely populated (Connecticut, Delaware, Maryland, Rhode Island). In the table above, Delaware was an outlier in spending per mile of highway over the period in each category. In terms of safety spending per mile of highway, the top five states were Delaware, New Jersey, California, Massachusetts, and Maryland. States that ranked toward the bottom on a spending per mile basis tended to be large and less densely populated. The bottom five for safety spending per mile of highway were South Dakota, North Dakota, Kansas, Mississippi, and Arizona.