Comparison of teen and adult driver crash scenarios in a nationally representative sample of serious crashes

Motor vehicle crashes are the leading cause of death and acquired disability during the first four decades of life. While teen drivers have the highest crash risk, few studies examine the similarities and differences in teen and adult driver crashes. We aimed to: (1) identify and compare the most frequent crash scenarios—integrated information on a vehicle's movement prior to crash, immediate pre-crash event, and crash configuration—for teen and adult drivers involved in serious crashes, and (2) for the most frequent scenarios, explore whether the distribution of driver critical errors differed for teens and adult drivers. We analyzed data from the National Motor Vehicle Crash Causation Survey, a nationally representative study of serious crashes conducted by the U.S. National Highway Traffic Safety Administration from 2005 to 2007. Our sample included 642 16- to 19-year-old and 1167 35- to 54-year-old crash-involved drivers (weighted n = 296,482 and 439,356, respectively) who made a critical error that led to their crash's critical pre-crash event (i.e., event that made the crash inevitable). We estimated prevalence ratios (PR) and 95% confidence intervals (CI) to compare the relative frequency of crash scenarios and driver critical errors. The top five crash scenarios among teen drivers, accounting for 37.3% of their crashes, included: (1) going straight, other vehicle stopped, rear end; (2) stopped in traffic lane, turning left at intersection, turn into path of other vehicle; (3) negotiating curve, off right edge of road, right roadside departure; (4) going straight, off right edge of road, right roadside departure; and (5) stopped in lane, turning left at intersection, turn across path of other vehicle. The top five crash scenarios among adult drivers, accounting for 33.9% of their crashes, included the same scenarios as the teen drivers with the exception of scenario (3) and the addition of going straight, crossing over an intersection, and continuing on a straight path. For two scenarios ((1) and (3) above), teens were more likely than adults to make a critical decision error (e.g., traveling too fast for conditions). Our findings indicate that among those who make a driver critical error in a serious crash, there are few differences in the scenarios or critical driver errors for teen and adult drivers.     

Heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes

In this study, a mixed logit model is developed to identify the heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes. The random parameter of the variables in the mixed logit model, the heterogeneous mean, is elaborated by driver gender-based linear regression models. The model is estimated using crash data in New Mexico from 2010 to 2012. The percentage changes of factors’ predicted probabilities are calculated in order to better understand the model specifications. Female drivers are found more likely to experience severe or fatal injuries in rollover crashes than male drivers. However, the probability of male drivers being severely injured is higher than female drivers when the road surface is unpaved. Two other factors with fixed parameters are also found to significantly increase driver injury severities, including Wet and Alcohol Influenced. This study provides a better understanding of contributing factors influencing driver injury severities in rollover crashes as well as their heterogeneous impacts in terms of driver gender. Those results are also helpful to develop appropriate countermeasures and policies to reduce driver injury severities in single-vehicle rollover crashes.     

An analysis of common patterns in aggregated causation charts from intersection crashes

Intersection crashes are a major traffic problem. Greater knowledge of causation is required in order to prevent them with the implementation of active safety measures. Causation charts were aggregated to establish whether common patterns of interlinked factors could be found. The data used comprised causation charts for 52 drivers involved in 26 in-depth investigated urban intersection crashes. The charts were compiled by means of the Driving Reliability and Error Analysis Method (DREAM) version 2.1, in which contributing factors are systematically analysed, classified and linked in a causation chart. The charts were aggregated for six defined risk situations, four for drivers without the right of way and two for those with the right of way. In two risk situations, one for drivers with and one for the drivers without the right of way, common patterns showed that the drivers had not seen the other vehicle due to distractions and/or sight obstructions. A frequently occurring pattern for the drivers with the right of way was that they had not expected another vehicle to cross their path. The absence of clear patterns in three risk situations for the drivers without the right of way was due to the low number of charts and rather unique circumstances. Parts of the aggregated charts showed an unwarranted variation, identified as a consequence of inconsistent charts. The present study shows that the rather unique approach of aggregating causation charts has potential, provided that the charts are consistent.     

Segment characteristics and severity of head-on crashes on two-lane rural highways in Maine

More than two out of three of all fatal crashes in Maine occur on rural, two-lane collector or arterial roads. Head-on crashes on these roads account for less than 5% of the crashes, but they are responsible for almost half of all fatalities. Data analyzed in this study was provided by Maine Department of Transportation and covers all head-on crashes for 2000-2002 during which period there were 3,136 head-on crashes reported. Out of these, 127 were fatal crashes and 235 produced incapacitating but not fatal injuries. These two categories made up over 75% of the crash cost. A clear majority of head-on crashes on two-lane, rural roads in Maine were caused by drivers making errors or misjudging situations. Illegal/unsafe speed was a factor in 32% of the crashes while driver inattention/distraction was a primary factor in 28%. Fatigue was responsible for around one in 40 crashes and one in 12 fatal crashes. Alcohol or drugs was a factor in one in 12 crashes and one in nine fatal head-on crashes. Less than 8% of fatalities involved someone overtaking another vehicle, and only around 14% involved a driver intentionally crossing the centerline. Two in three fatal head-on crashes occurred on straight segments and 67% of these happened on dry pavement. There is a clear trend towards higher speed limits leading to a higher percentage of crashes becoming fatal or having incapacitating injuries. There is also a clear trend - if one keeps speeds constant and AADT within a certain range - that wider shoulders give higher crash severities. Also, for higher-speed roads, more travel lanes (than two) increase crash severity. In summary, there seems to be two major reasons why people get across the centerline and have head-on collisions: (a) people are going too fast for the roadway conditions; or (b) people are inattentive and get across the centerline more or less without noticing it. The latter category of crashes could probably be reduced if centerline rumble-strips were installed. More or less all head-on collisions could be eliminated if median barriers were installed. In-vehicle technology could also be used to significantly reduce the incidence of lane departures. Furthermore, today's speed limits should be better enforced since a high percentage of serious crashes involve illegal speeding. This should be combined with lowered speed limits for targeted high-crash segments.     

Declines in fatal crashes of older drivers: changes in crash risk and survivability

Objectives

Previous research has found that older driver fatal crash involvement rates per licensed driver declined substantially in the United States during 1997–2006 and declined much faster than the rate for middle-age drivers. The current study examined whether the larger-than-expected decline for older drivers extended to nonfatal crashes and whether the decline in fatal crash risk reflects lower likelihood of crashing or an improvement in survivability of the crashes that occur.

Methods

Trends in the rates of passenger vehicle crash involvements per 100,000 licensed drivers for drivers 70 and older (older drivers) were compared with trends for drivers ages 35–54 (middle-age drivers). Fatal crash information was obtained from the Fatality Analysis Reporting System for years 1997–2008, and nonfatal crash information was obtained from 13 states with good reporting information for years 1997–2005. Analysis of covariance models compared trends in annual crash rates for older drivers relative to rates for middle-age drivers. Differences in crash survivability were measured in terms of the odds of fatality given a crash each year, and the historical trends for older versus middle-age drivers were compared.

Results

Fatal crash involvement rates declined for older and middle-age drivers during 1997–2008 (1997–2005 for the 13 state subsample), but the decline for drivers 70 and older far exceeded the decline for drivers ages 35–54 (37 versus 23 percent, nationally; 22 versus 1 percent, 13 states). Nonfatal injury crash involvement rates showed similarly larger-than-expected declines for older drivers in the 13 state subsample, but the differences were smaller and not statistically significant (27 percent reduction for older drivers versus 16 percent for middle-age drivers). Property-damage-only crash involvement rates declined for older drivers (10 percent) but increased for middle-age drivers (1 percent). In 1997, older drivers were 3.5 times more likely than middle-age drivers to die in police-reported crashes (6.2 versus 1.8 deaths per 1000 crashes), but this difference was reduced during the 9-year study period to 2.9 times, as the rate of older drivers dying in a crash declined (5.5 deaths per 1000 crashes in 2005) and the death risk remained relatively stable for middle-age drivers.

Conclusions

Contrary to expectations based on increased licensure and travel by older drivers, their fatal crash risk has declined during the past decade and has declined at a faster rate than for middle-age drivers. The decreased risk for older drivers appears to extend not only to nonfatal injury crashes but also to property-damage-only crashes, at least as reported to police in the 13 states included in the nonfatal injury analysis. Although insurance collision data suggest that overall crash risk of older drivers may not be changing relative to middle-age drivers, the current analysis indicates that the reduced fatality risk of older drivers reflects both less likelihood of being involved in a police-reported crash and greater likelihood that they will survive when they do crash.     

Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM)

To develop relevant road safety countermeasures, it is necessary to first obtain an in-depth understanding of how and why safety-critical situations such as incidents, near-crashes, and crashes occur. Video-recordings from naturalistic driving studies provide detailed information on events and circumstances prior to such situations that is difficult to obtain from traditional crash investigations, at least when it comes to the observable driver behavior. This study analyzed causation in 90 video-recordings of car-to-pedestrian incidents captured by onboard cameras in a naturalistic driving study in Japan. The Driving Reliability and Error Analysis Method (DREAM) was modified and used to identify contributing factors and causation patterns in these incidents. Two main causation patterns were found. In intersections, drivers failed to recognize the presence of the conflict pedestrian due to visual obstructions and/or because their attention was allocated towards something other than the conflict pedestrian. In incidents away from intersections, this pattern reoccurred along with another pattern showing that pedestrians often behaved in unexpected ways. These patterns indicate that an interactive advanced driver assistance system (ADAS) able to redirect the driver's attention could have averted many of the intersection incidents, while autonomous systems may be needed away from intersections. Cooperative ADAS may be needed to address issues raised by visual obstructions.     

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention.     

Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways

This study analyzes driver injury severities for single-vehicle crashes occurring in rural and urban areas using data collected in New Mexico from 2010 to 2011. Nested logit models and mixed logit models are developed in order to account for the correlation between severity categories (No injury, Possible injury, Visible injury, Incapacitating injury and fatality) and individual heterogeneity among drivers. Various factors, such as crash and environment characteristics, geometric features, and driver behavior are examined in this study. Nested logit model and mixed logit model reveal similar results in terms of identifying contributing factors for driver injury severities. In the analysis of urban crashes, only the nested logit model is presented since no random parameter is found in the mixed logit model. The results indicate that significant differences exist between factors contributing to driver injury severity in single-vehicle crashes in rural and urban areas. There are 5 variables found only significant in the rural model and six significant variables identified only in the urban crash model. These findings can help transportation agencies develop effective policies or appropriate strategies to reduce injury severity resulting from single-vehicle crashes.     

Hearing loss and automobile airbag deployments

In an on-going research program, on the causation of injuries in motor vehicle accidents, at the University of Michigan Transportation Research Institute, crashes with airbags have been, and are continuing to be, investigated. In order to determine the occurrence, if any, of ‘hearing problems’ associated with airbag deployments, drivers and passengers who had been involved in ‘airbag’ automobile crashes were interviewed by telephone. From the crashes investigated, 225 attempts were made to contact drivers who were exposed to airbag deployments. From these telephone interviews, contacts were made with 177 car occupants. Only three reported that they had experienced any type of hearing-related problems subsequent to their crash. One other case is reported of a driver who had pre-crash hearing loss. It appears that permanent hearing deficit due to airbag deployment, both in cars with the steering wheel airbag alone, and in those with a passenger side airbag, is an infrequent event (1.7%) from the data of this study.     

Requirements of a system to reduce car-to-vulnerable road user crashes in urban intersections

Intersection crashes between cars and vulnerable road users (VRUs), such as pedestrians and bicyclists, often result in injuries and fatalities. Advanced driver assistance systems (ADASs) can prevent, or mitigate, these crashes. To derive functional requirements for such systems, an understanding of the underlying contributing factors and the context in which the crashes occur is essential. The aim of this study is to use microscopic and macroscopic crash data to explore the potential of information and warning providing ADASs, and then to derive functional sensor, collision detection, and human–machine interface (HMI) requirements. The microscopic data were obtained from the European project SafetyNet. Causation charts describing contributing factors for 60 car-to-VRU crashes had been compiled and were then also aggregated using the SafetyNet Accident Causation System (SNACS). The macroscopic data were obtained from the Swedish national crash database, STRADA. A total of 9702 crashes were analyzed. The results show that the most frequent contributing factor to the crashes was the drivers’ failure to observe VRUs due to reduced visibility, reduced awareness, and/or insufficient comprehension. An ADAS should therefore help drivers to observe the VRUs in time and to enhance their ability to interpret the development of events in the near future. The system should include a combination of imminent and cautionary collision warnings, with additional support in the form of information about intersection geometry and traffic regulations. The warnings should be deployed via an in-vehicle HMI and according to the likelihood of crash risk. The system should be able to operate under a variety of weather and light conditions. It should have the capacity to support drivers when their view is obstructed by physical objects. To address problems that vehicle-based sensors may face in this regard, the use of cooperative systems is recommended.     

A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes

Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.     

Trends in older driver crash involvement rates and survivability in the United States: An update

Objective

Previous research has shown that fatal crash involvement rates per licensed driver aged 70 and older declined significantly more per year in the United States than rates for middle-aged drivers aged 35–54 during 1997–2008, and per vehicle mile traveled from 1995–1996 to 2001–2002. Analyses of police-reported crash data during 1997–2005 indicated that the greater declines for older drivers were due to decreases in crash involvement and in the risk of dying in the crashes that occurred. The current study examined if trends in crash rates, crash involvements, and survivability persisted into more recent years.

Methods

Trends for drivers 70 and older were compared with trends for drivers aged 35–54 for U.S. national fatal passenger vehicle crash involvements per 100,000 licensed drivers during 1997–2012 and for U.S. national fatal passenger vehicle crash involvements per vehicle miles traveled in 1995–1996, 2001–2002, and 2008. Using police-reported crash data during 1997–2008 from 20 U.S. states, trends in involvement rates in non-fatal crashes of various severities per 100,000 licensed drivers and changes in the odds of death and the odds of death or serious injury in a crash were compared between older and middle-aged drivers.

Results

During 2007–2012, declines in national fatal crash involvement rates per licensed driver were similar for drivers 70 and older and middle-aged drivers (18 percent each). However, when considering the entire study period, fatal crash involvement rates continued to reflect a substantially larger decline for drivers 70 and older than for middle-aged drivers (42 vs. 30 percent per licensed driver during 1997–2012, 39 vs. 26 percent per vehicle mile traveled from 1995–2006 to 2008). When analyses of police-reported crash data were extended through 2008, non-fatal injury crash involvement rates per licensed driver declined more for older than for middle-aged drivers (39 vs. 30 percent), and unlike in prior research, average annual declines were significantly larger for drivers 80 and older. Property damage-only crash involvement rates similarly declined significantly more for older than for middle-aged drivers (15 vs. 3 percent). Drivers 70 and older in 1997 were 3.5 times more likely than middle-aged drivers to die in a crash, and this ratio declined to 3.2 by 2008.

Conclusions

Although declines in fatal crash involvement rates in recent years have not differed between older and middle-aged drivers, this did not undo earlier gains for older drivers. The recent slowing in the relative magnitude of the decline for older drivers may be related to the differential effect of the U.S. recession on fatal crash involvements of drivers in these age groups. The decreased likelihood of being involved in a crash of any severity and increased survivability when a crash occurred held when examining data through 2008, and for drivers 80 and older, significant declines in crash involvement relative to middle-aged drivers extended to non-fatal injury crashes.     

Older drivers’ crashes in Queensland,Australia

Background

The growing proportion of older adults in Australia is predicted to comprise 23% of the population by 2030. Accordingly, an increasing number of older drivers and fatal crashes of these drivers could also be expected. While the cognitive and physiological limitations of ageing and their road safety implications have been widely documented, research has generally considered older drivers as a homogeneous group. Knowledge of age-related crash trends within the older driver group itself is currently limited.

Objective

The aim of this research was to identify age-related differences in serious road crashes of older drivers. This was achieved by comparing crash characteristics between older and younger drivers and between sub-groups of older drivers. Particular attention was paid to serious crashes (crashes resulting in hospitalisation and fatalities) as they place the greatest burden on the Australian health system.

Method

Using Queensland Crash data, a total of 191,709 crashes of all-aged drivers (17–80+) over a 9-year period were analysed. Crash patterns of drivers’ aged 17–24, 25–39, 40–49, 50–59, 60–69, 70–79 and 80+ were compared in terms of crash severity (e.g., fatal), at fault levels, traffic control measures (e.g., stop signs) and road features (e.g., intersections). Crashes of older driver sub-groups (60–69, 70–79, 80+) were also compared to those of middle-aged drivers (40–49 and 50–59 combined, who were identified as the safest driving cohort) with respect to crash-related traffic control features and other factors (e.g., speed). Confounding factors including speed and crash nature (e.g., sideswipe) were controlled for.

Results and discussion

Results indicated that patterns of serious crashes, as a function of crash severity, at-fault levels, road conditions and traffic control measures, differed significantly between age groups. As a group, older drivers (60+) represented the greatest proportion of crashes resulting in fatalities and hospitalisation, as well as those involving uncontrolled intersections and failure to give way. The opposite was found for middle-aged drivers, although they had the highest proportion of alcohol and speed-related crashes when compared to older drivers. Among all older drivers, those aged 60–69 were least likely to be involved in or the cause of crashes, but most likely to crash at interchanges and as a result of driving while fatigued or after consuming alcohol. Drivers aged 70–79 represented a mid-range level of crash involvement and culpability, and were most likely to crash at stop and give way signs. Drivers aged 80 years and beyond were most likely to be seriously injured or killed in, and at-fault for, crashes, and had the greatest number of crashes at both conventional and circular intersections. Overall, our findings highlight the heterogeneity of older drivers’ crash patterns and suggest that age-related differences must be considered in measures designed to improve older driver safety.     

Fragility and crash over-representation among older drivers in Western Australia

This study assessed age-related and gender differences in the relative contribution of fragility and crash over-representation to serious injuries per crash-involved driver in Western Australia. Police-reported crashes for the period 1998-2003 were extracted from the Western Australian Road Injury Database. For each passenger vehicle driver age and gender group, serious injuries per crash-involved driver and driver involvements in crashes per 100 million vehicle-kilometre travelled (VKT) were calculated as the respective measure of fragility and crash over-representation. Results from the decomposition method of analysis showed that older drivers over the age of 70 sustained serious injury rates more than twice as high as those of the 30-59-year-old drivers. Fragility increased with age, contributing between 47% and 95% for drivers above 65 years, but crash over-representation was the dominant factor for male drivers above 80 years. In contrast, fragility contributed little to the excess injury risk of younger drivers under the age of 30. The importance of fragility as a contributing factor to the inflated serious injury risk per vehicle-kilometre travelled for older drivers suggested that road safety initiatives should be directed towards the protection of vehicle occupants as well as screening for their driving ability.     

Some consequences of different older driver licensing procedures in Australia

Given both the expected growth in the number of older drivers and their over-involvement in fatal and serious injury crashes, there has been a world-wide call for improved licensing procedures to manage older driver safety. In particular, licensing authorities have been urged to move from mandatory assessment of all older drivers to assessment practices targeting only those at higher crash risk. The current study examined older driver fatal and serious injury crash involvement rates across all Australian States to determine a possible association with the different licensing procedures. In particular, older driver crash involvement rates in Victoria (where there is no age-based assessment program) have been compared with rates in other jurisdictions with assessment programs. Crash involvement rates have been calculated using two denominators: per population and per number of licensed drivers. Some data limitations notwithstanding, older drivers in jurisdictions with age-based mandatory assessment programs could not be shown to be safer than drivers in Victoria. Further, there is some indicative evidence that older drivers in Victoria may have a significantly safer record regarding overall involvement in serious casualty crashes.     

Prevalence of motor vehicle crashes involving drowsy drivers,United States, 1999–2008

The proportion of motor vehicle crashes that involve a drowsy driver likely is greater than existing crash databases reflect, due to the possibility that some drivers whose pre-crash state of attention was unknown may have been drowsy. This study estimated the proportion of crashes that involved a drowsy driver in a representative sample of 47,597 crashes in the United States from 1999 through 2008 that involved a passenger vehicle that was towed from the scene. Multiple imputation was used to address missing data on driver drowsiness. In the original (non-imputed) data, 3.9% of all crashes, 7.7% of non-fatal crashes that resulted in hospital admission, and 3.6% of fatal crashes involved a driver coded as drowsy; however, the drowsiness status of 45% of drivers was unknown. In the imputed data, an estimated 7.0% of all crashes (95% confidence interval: 4.6%, 9.3%), 13.1% of non-fatal crashes that resulted in hospital admission (95% confidence interval: 8.8%, 17.3%), and 16.5% of fatal crashes (95% confidence interval: 12.5%, 20.6%) involved a drowsy driver. Results suggest that the prevalence of fatal crashes that involve a drowsy driver is over 350% greater than has been reported previously.     

An examination of the environmental,driver and vehicle factors associated with the serious and fatal crashes of older rural drivers

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004–2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100 km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances.     

Factors associated with civilian drivers involved in crashes with emergency vehicles

Motor vehicle crashes involving civilian and emergency vehicles (EVs) have been a known problem that contributes to fatal and nonfatal injuries; however, characteristics associated with civilian drivers have not been examined adequately. This study used data from The National Highway Traffic Safety Administration's Fatality Analysis Reporting System and the National Automotive Sampling System General Estimates System to identify driver, roadway, environmental, and crash factors, and consequences for civilian drivers involved in fatal and nonfatal crashes with in-use and in-transport EVs. In general, drivers involved in emergency–civilian crashes (ECCs) were more often driving: straight through intersections (vs. same direction) of four-points or more (vs. not at intersection); where traffic signals were present (vs. no traffic control device); and at night (vs. midday). For nonfatal ECCs, drivers were more often driving: distracted (vs. not distracted); with vision obstructed by external objects (vs. no obstruction); on dark but lighted roads (vs. daylight); and in opposite directions (vs. same directions) of the EVs. Consequences included increased risk of injury (vs. no injury) and receiving traffic violations (vs. no violation). Fatal ECCs were associated with driving on urban roads (vs. rural), although these types of crashes were less likely to occur on dark roads (vs. daylight). The findings of this study suggest drivers may have difficulties in visually detecting EVs in different environments.     

Crash involvement of drivers with multiple crashes

A goal for any licensing agency is the ability to identify high-risk drivers. Kentucky data show that a significant number of drivers are repeatedly involved in crashes. The objective of this study is the development of a crash prediction model that can be used to estimate the likelihood of a driver being at fault for a near future crash occurrence. Multiple logistic regression techniques were employed using the available data for the Kentucky licensed drivers. This study considers as crash predictors the driver's total number of previous crashes, citations accumulated, the time gap between the latest two crashes, crash type, and demographic factors. The driver's total number of previous crashes was further disaggregated into the drivers' total number of previous at-fault and not-at-fault crashes. The model can be used to correctly classify at-fault drivers up to 74.56% with an overall efficiency of 63.34%. The total number of previous at-fault crash involvements, and having previous driver license suspensions and traffic school referrals are strongly associated with a driver being responsible for a subsequent crash. In addition, a driver's likelihood to be at fault in a crash is higher for very young or very old, males, drivers with both speeding and non-speeding citations, and drivers that had a recent crash involvement. Thus, the model presented here enables agencies to more actively monitor the likelihood of a driver to be at fault in a crash.