Analyzing fault in pedestrian–motor vehicle crashes in North Carolina

Crashes between pedestrians and motor vehicles are an important traffic safety concern. This paper explores the assignment of fault in such crashes, where observed factors are associated with pedestrian at fault, driver at fault, or both at fault. The analysis is based on police reported crash data for 1997 through 2000 in North Carolina, U.S.A.The results show that pedestrians are found at fault in 59% of the crashes, drivers in 32%, and both are found at fault in 9%. The results indicate drivers need to take greater notice of pedestrians when drivers are turning, merging, and backing up as these are some of the prime factors associated with the driver being found at fault in a crash.Pedestrians must apply greater caution when crossing streets, waiting to cross, and when walking along roads, as these are correlated with pedestrians being found at fault. The results suggest a need for campaigns focused on positively affecting pedestrian street-crossing behavior in combination with added jaywalking enforcement. The results also indicate that campaigns to increase the use of pedestrian visibility improvements at night can have a significant positive impact on traffic safety. Intoxication is a concern and the results show that it is not only driver intoxication that is affecting safety, but also pedestrian intoxication.The findings show in combination with other research in the field, that results from traffic safety studies are not necessarily transferable between distant geographic locations, and that location-specific safety research needs to take place. It is also important to further study the specific effects of the design of the pedestrian environment on safety, e.g. crosswalk spacing, signal timings, etc., which together may affect pedestrian safety and pedestrian behavior.     

Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida

This study analyzes vehicle-pedestrian crashes at intersections in Florida over 4 years, 1999-2002. The study identifies the group of drivers and pedestrians, and traffic and environmental characteristics that are correlated with high pedestrian crashes using log-linear models. The study also estimates the likelihood of pedestrian injury severity when pedestrians are involved in crashes using an ordered probit model. To better reflect pedestrian crash risk, a logical measure of exposure is developed using the information on individual walking trips in the household travel survey. Lastly, the impact of average traffic volume on pedestrian crashes is examined. As a result of the analysis, it was found that pedestrian and driver demographic factors, and road geometric, traffic and environment conditions are closely related to the frequency and injury severity of pedestrian crashes. Higher average traffic volume at intersections increases the number of pedestrian crashes; however, the rate of increase is steeper at lower values of average traffic volume. Based on the findings in the analysis, some countermeasures are recommended to improve pedestrian safety.     

Pedestrian crash trends and potential countermeasures from around the world

As automobile transportation continues to increase around the world, bicyclists, pedestrians, and motorcyclists, also known as vulnerable road users (VRUs), will become more susceptible to traffic crashes, especially in countries where traffic laws are poorly enforced. Many countries, however, are employing innovative strategies to ensure that road users can more safely navigate the urban landscape. While bicyclists and motorcyclists are important road users, this paper will focus on pedestrian crash problems and solutions. Pedestrians are most at risk in urban areas due in part to the large amount of pedestrian and vehicle activity in urban areas. With this in mind, designing safe, accessible, and comprehensive facilities for pedestrians is vital to reducing pedestrian crashes. This paper will provide some insight into the magnitude of the pedestrian crash problem around the world, and will offer some lessons learned from several countries, particularly in Europe and the U.S., for improving pedestrian safety. Beginning with pedestrian safety statistics at the global, regional, and national levels, this paper will address potential countermeasures and strategies for improving pedestrian safety from an international perspective.     

Analyzing fault and severity in pedestrian–motor vehicle accidents in China

The number of pedestrian–motor vehicle accidents and pedestrian deaths in China surged in recent years. However, a large scale empirical research on pedestrian traffic crashes in China is lacking. In this study, we identify significant risk factors associated with fault and severity in pedestrian–motor vehicle accidents. Risk factors in several different dimensions, including pedestrian, driver, vehicle, road and environmental factors, are considered. We analyze 6967 pedestrian traffic accident reports for the period 2006–2010 in Guangdong Province, China. These data, obtained from the Guangdong Provincial Security Department, are extracted from the Traffic Management Sector-Specific Incident Case Data Report. Pedestrian traffic crashes have a unique inevitability and particular high risk, due to pedestrians’ fragility, slow movement and lack of lighting equipment. The empirical analysis of the present study has the following policy implications. First, traffic crashes in which pedestrians are at fault are more likely to cause serious injuries or death, suggesting that relevant agencies should pay attention to measures that prevent pedestrians from violating traffic rules. Second, both the attention to elderly pedestrians, male and experienced drivers, the penalty to drunk driving, speeding, driving without a driver's license and other violation behaviors should be strengthened. Third, vehicle safety inspections and safety training sessions for truck drivers should be reinforced. Fourth, improving the road conditions and road lighting at night are important measures in reducing the probability of accident casualties. Fifth, specific road safety campaigns in rural areas, and education programs especially for young children and teens should be developed and promoted. Moreover, we reveal a country-specific factor, hukou, which has significant effect on the severity in pedestrian accidents due to the discrepancy in the level of social insurance/security, suggesting that equal social security level among urban and rural people should be set up. In addition, establishing a comprehensive liability distribution system for non-urban areas and roadways will be conducive to both pedestrians’ and drivers’ voluntary compliance with traffic rules.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Modeling fault among accident—Involved pedestrians and motorists in Hawaii

Using a comprehensive database of police-reported accidents in Hawaii, we describe the nature of pedestrian accidents over the period 2002–2005. Approximately 36% of the accidents occur in residential areas, while another 34% occur in business areas. Only 41.7% of the pedestrian accidents occur at intersections. More pedestrian crashes occur at non-intersection locations—including midblock locations, driveways, parking lots, and other off roadway locations. Approximately 38.2% of the crashes occur at crosswalk locations, while proportionately more (61.8%) of the pedestrian accidents occur at non-crosswalk locations. Using this database the human, temporal, roadway, and environmental factors associated with being “at-fault” for both pedestrians and drivers are also examined. Using techniques of logistic regression, several different explanatory models are constructed, to identify the factors associated with crashes producing fatalities and serious injuries. Finally, two pedestrian models (drunk males and young boys) and one driver model (male commuters) are developed to provide further understanding of pedestrian accident causation. Drunk male pedestrians who were jaywalking were in excess of 10× more likely than other groups to be at-fault in pedestrian accidents. Young boys in residential areas were also more likely to be at-fault. Male commuters in business areas in the morning were also found to have higher odds of being classified at-fault when involved in pedestrian accidents. The results of this study indicate that there should be a combination of enforcement and educational programs implemented for both the pedestrian and drivers to show those at-fault the consequences of their actions, and to reduce the overall number of accidents.     

Risk factors for causing road crashes involving cyclists: An application of a quasi-induced exposure method

A quasi-induced exposure approach was applied to the Spanish Register of Traffic Crashes to identify driver- and vehicle-related factors associated with the risk of causing a road crash involving a cyclist in Spain from 1993 to 2009. We analyzed 19,007 collisions between a bicycle and another vehicle in which only one of the drivers committed an infraction, and 13,540 records that included the group of non-infractor cyclists in the above collisions plus cyclists involved in single-bicycle crashes. Adjusted odds ratios were calculated for being responsible for each type of crash for each factor considered. Age from 10 to 19 years, male sex, alcohol or drug consumption and non-helmet use were cyclist-related variables associated with a higher risk of crash, whereas cycling more than 1 h increased only the risk of single crashes. Bicycles with brake defects and ridden by two occupants were also at higher risk of involvement in a crash, whereas light defects were associated only with collisions with another vehicle. For drivers of the other vehicle, age more than 60 years, alcohol, not using safety devices and nonprofessional drivers were at higher risk. The risk of colliding with a bicycle was higher for mopeds than for passenger cars.     

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.     

Stop versus yield on pedestrian-involved fatal crashes in the United States

In an effort to improve pedestrian safety, several states in the United States changed their pedestrian laws by changing the requirement that drivers yield to pedestrians in crosswalks to a requirement that drivers stop for pedestrians in crosswalks. This study examined whether this change had an effect on pedestrian safety in the United States, with its focus on low-speed roads. To examine the association between changes in pedestrian laws and changes in pedestrian-involved fatal crashes, three approaches were employed: before–after analysis, time-series analysis, and cross-sectional analysis. Pedestrian-involved fatal traffic crashes on low-speed roads were extracted from the U.S. national fatal crash database, the Fatality Analysis Reporting System (FARS), from 1980 through 2005. This study found no statistically significant reduction in pedestrian-involved fatal crashes attributable to changes in the laws, yet this finding is not definitive because of study limitations such as the omission of relevant exposure data.     

Pedestrian crashes in Washington,DC and Baltimore

Police crash reports were obtained for pedestrian-motor vehicle crashes in Washington, DC (N = 852) and Baltimore (N = 1234) for the year 1998. Reports were coded using procedures developed and applied in these two cities during the 1970s, including the determination of pedestrian crash type, primary precipitating factor, and culpability. Results indicated substantial differences between crash patterns observed during the 1970s and those observed during 1998. Midblock dart-dash crashes, which typically involve a precipitating factor or critical error by a child pedestrian, decreased (from 37% to 15% in Washington). Across all crashes in both cities, the number of drivers who made a critical error leading to the crash was nearly equivalent to the number of pedestrians who made a critical error. Overall, pedestrians were slightly more likely to be judged culpable (50% vs. 39%). Turning vehicle crashes, which typically involve a driver's failure to grant a pedestrian the right of way at a signalized intersection, increased (from 9% to 25% in Washington). Countermeasures to reduce the number of pedestrians hit by turning vehicles are discussed.     

Driver fatalities versus car mass using a new exposure approach

A new approach to estimating exposure is presented and applied to determining relations between car mass and driver fatality likelihood. The new approach considers two groups of fatal crashes in the FARS files. The first group contains crashes in which car drivers are killed in single car crashes or in crashes with trucks. These are both examples of non-two car crashes. It is hypothesized that the likelihood of a car driver fatality in such crashes depends on car mass. The second group of fatal crashes contains crashes in which either pedestrians or motorcyclists are killed in crashes with cars. It is hypothesized that the likelihood of the pedestrian or motorcyclist being killed in such crashes is independent of the mass of the car. The new exposure approach implies that the ratio of the number of people killed in the mass dependent crash to those killed in the mass independent crash gives an estimate of how car mass affects the likelihood of a driver fatality. The approach further implies that the estimate obtained is an estimate of the physical effect of mass, essentially independent of driver behavior. It is found that the new exposure approach yields relationships between driver fatality likelihood and car mass that are more precise and consistent than can normally be obtained in accident research. The effects found, which are attributed to the physical properties of the vehicle, essentially independent of driver behavior, are larger (for example, a driver of a 900 kg car is 2.6 times as likely to be killed as is a driver of a 1800kg car) than those based on fatalities per car.     

Fatality risk for belted drivers versus car mass

This study was performed to determine how the likelihood of a belted driver being killed in a single car crash depends on the mass of the car. This was done by applying the pedestrian fatality exposure approach to the subset of fatalities in the Fatal Accident Reporting System (FARS) for which the driver was coded as using a shoulder belt and/or a lap belt. Combining the 1975 through 1982 data provided a sufficiently large population of belted drivers to perform the analysis. In the exposure approach used, the number of car drivers killed in single car crashes is divided by the number of nonoccupant fatalities (pedestrians or motorcyclists) associated with the same group of cars. The ratio is interpreted to reflect the physical effect of car mass, essentially independent of driver behavior effects. In the present application, car mass effects for belted drivers were determined by considering the number of belted drivers killed divided by the number of nonoccupants killed in crashes involving cars whose drivers were coded in the FARS files as being belted. Because the belt use of surviving drivers is, to some extent, self-reported, it is considered that the data given in the report should be not used to estimate the effectiveness of seat belts in preventing fatalities. The results are presented as graphical and analytical comparisons of fatality likelihood versus car mass for belted and unbelted drivers. It is concluded that the effect of car mass on relative driver fatality likelihood is essentially the same for belted and unbelted drivers (for example, the present analysis gives that a belted driver in a 900 kg car is 2.3 times as likely to be killed in a single car crash as is the belted driver in an 1800 kg car. The corresponding ratio determined here for unbelted drivers is 2.4). As a consequence of this conclusion, the relative effectiveness of seat belts in preventing driver fatalities is similar for cars of different masses.     

Fatal crash involvement of unlicensed young drivers: County level differences according to material deprivation and urbanicity in the United States

Objectives

This study assessed the association between county level material deprivation and urbanization with fatal road traffic crashes involving young unlicensed drivers in the United States (US).

Background

Road traffic crashes have been positively associated with area deprivation and low population density but thus far few studies have been concerned specifically with young drivers, especially those that are unlicensed.

Methods

A county material deprivation index was derived from the Townsend Material Deprivation Index, with variables extracted from the US Census (2000). An urbanicity scale was adapted from the US Department of Agriculture's Rural–Urban Continuum Codes (2003). Data on fatal crashes involving a young unlicensed driver during a seven-year period (2000–2006; n = 3059) were extracted from the Fatality Analysis Reporting System. The effect of deprivation and urbanicity on the odds of the occurrence of at least one fatal crash at the county level was modeled by conditional and unconditional logistic regression.

Results

The conditional model found a positive association between material deprivation and a fatal crash involving a young unlicensed driver (OR = 1.19, 95% CI 1.17, 1.21). The interaction between urbanicity and material deprivation was negatively associated in suburban counties for fatal crashes (OR = 0.92, 95% CI 0.90, 0.95).

Conclusions

An association with material deprivation and the likelihood of a fatal crash involving a young unlicensed driver is a new finding. It can be used to inform specific county-level interventions and promote state licensing policies to provide equity in young people's mobility regardless of where they live.     

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.     

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.     

Factors associated with hit-and-run pedestrian fatalities and driver identification

As hit-and-run crashes account for a significant proportion of pedestrian fatalities, a better understanding of these crash types will assist efforts to reduce these fatalities. Of the more than 48,000 pedestrian deaths that were recorded in the United States between 1998 and 2007, 18.1% of them were caused by hit-and-run drivers. Using national data on single pedestrian-motor vehicle fatal crashes (1998–2007), logistic regression analyses were conducted to identify factors related to hit-and-run and to identify factors related to the identification of the hit-and-run driver. Results indicate an increased risk of hit-and-run in the early morning, poor light conditions, and on the weekend. There may also be an association between the type of victim and the likelihood of the driver leaving and being identified. Results also indicate that certain driver characteristics, behavior, and driving history are associated with hit-and-run. Alcohol use and invalid license were among the leading driver factor associated with an increased risk of hit-and-run. Prevention efforts that address such issues could substantially reduce pedestrian fatalities as a result of hit-and-run. However, more information about this driver population may be necessary.     

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.     

Age and pedestrian injury severity in motor-vehicle crashes: a heteroskedastic logit analysis

This research explores the injury severity of pedestrians in motor-vehicle crashes. It is hypothesized that the variance of unobserved pedestrian characteristics increases with age. In response, a heteroskedastic generalized extreme value model is used. The analysis links explanatory factors with four injury outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. Police-reported crash data between 1997 and 2000 from North Carolina, USA, are used. The results show that pedestrian age induces heteroskedasticity which affects the probability of fatal injury. The effect grows more pronounced with increasing age past 65. The heteroskedastic model provides a better fit than the multinomial logit model. Notable factors increasing the probability of fatal pedestrian injury: increasing pedestrian age, male driver, intoxicated driver (2.7 times greater probability of fatality), traffic sign, commercial area, darkness with or without streetlights (2-4 times greater probability of fatality), sport-utility vehicle, truck, freeway, two-way divided roadway, speeding-involved, off roadway, motorist turning or backing, both driver and pedestrian at fault, and pedestrian only at fault. Conversely, the probability of a fatal injury decreased: with increasing driver age, during the PM traffic peak, with traffic signal control, in inclement weather, on a curved roadway, at a crosswalk, and when walking along roadway.     

Crash characteristics of older pedestrian fatalities: dementia pathology may be related to 'at risk' traffic situations

Older people are over represented among pedestrian casualties, and cognitive decline is an often cited possible contributory factor. Cognitive decline and dementia are intimately associated, however the role dementia might play in older pedestrian crashes has received little attention. This study describes crash characteristics for 52 fatally injured older pedestrians in the Sydney metropolitan area. It investigates the relationship between the extent of neurofibrillary tangles (NFT), a hallmark of Alzheimer's disease in the brain, and particular crash situations. The results demonstrate crash characteristics that are similar to that reported in other studies of older pedestrians. Furthermore, the results suggest that cognitive decline associated with dementia related neuropathology may be associated with specific crash situations. Compared to older pedestrians with no, or low NFT, those with moderate to high NFT were more likely to be: at least partially responsible for the incident; injured while in low complexity situations; involved in impacts with reversing vehicles; impacted in near lanes of traffic; and struck by a vehicle off road. While described as trends only (p < 0.2), these findings highlight areas of concern for older pedestrians and suggest potential targets for engineering and behaviour-based countermeasures aimed at reducing casualty numbers among older pedestrians.     

The impact of driver age on lost life years for other road users in France: A population based study of crash-involved road users

BACKGROUND: One of the concerns in road safety is the threat older drivers may pose to other road users. Using the rate of lost life years, the present study provides a public health approach to quantify this potential threat. METHODS: A total of 1570686 motorised vehicle drivers or motorcycle riders and 652246 non-drivers, i.e. vehicle passengers, pedestrians and cyclists involved in injury crashes in France between 1996 and 2004, were included in a population based cross-sectional study. Fatality rates and rate of lost life years for each crash-involved driver age class were calculated for the drivers themselves and for other road users. RESULTS: The study has shown a significant reduction in the rate of lost life years for crash-involved other road users (whether passengers, pedestrians, cyclists or opposing drivers) as driver age increases. Other road users lost half as many years of life when involved in crashes with drivers aged over 85 than with drivers under 65 (1.26 and 2.32 per 100 expected remaining life years, respectively). CONCLUSION: Our findings suggest that among road users involved in injury crashes, older drivers are less dangerous for the other road users. By attributing other road users' lost life years to each driver age, this study represents a new contribution to the debate about ageing and road safety.