Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Factors leading to older drivers' intersection crashes

OBJECTIVES: Older drivers are overinvolved in intersection crashes compared with younger drivers, but the reasons are not clearly understood. The purpose of the present study was to identify the factors that lead to older drivers' intersection crashes. METHOD: Study participants were composed of two groups of older drivers -- ages 70-79 (n = 78) and 80 and older (n = 76) -- and a comparison group of drivers ages 35-54 (n = 73); all were at fault in intersection crashes involving nonfatal injuries. Police crash reports, telephone interviews with at-fault drivers, and photographs of intersections were used to determine the kinds of driver actions and errors that led to the intersection crashes. RESULTS: Drivers 80 and older had fewer rear-end crashes than drivers ages 35-54 and 70-79, and both groups of older drivers had fewer ran-off-road crashes than drivers ages 35-54. Crashes where drivers failed to yield the right-of-way increased with age and occurred mostly at stop sign-controlled intersections, generally when drivers were turning left. The reasons for failure-to-yield crashes tended to vary by age. Compared with drivers ages 35-54 and 80 and older, drivers ages 70-79 made more evaluation errors -- seeing another vehicle but misjudging whether there was adequate time to proceed. In contrast, drivers 80 and older predominantly failed to see or detect the other vehicle. Drivers ages 35-54 also tended to make search errors, but theirs were due more often to distraction. CONCLUSIONS: Factors leading to intersection crashes vary with age, even between two age groups of older drivers. Because the number of older drivers is projected to increase, it is important to identify ways to reduce the frequency and severity of their intersection crashes. Roundabouts and protected left turn lanes at signalized intersections may help to reduce failure-to-yield crashes at intersections, especially among older drivers. Crash avoidance systems may help to reduce crashes for drivers of all ages, but most systems have not been thoroughly investigated using real-world crash data.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Driver licensing,motor-vehicle crashes,and moving violations among older adults

IntroductionDriving is important for well-being among older adults, but age-related conditions are associated with driving reduction or cessation and increased crash risk for older drivers. Our objectives were to describe population-based rates of older drivers’ licensing and per-driver rates of crashes and moving violations.Methods: We examined individual-level statewide driver licensing, crash, and traffic citation data among all New Jersey drivers aged ≥ 65 and a 35- to 54-year-old comparison group during 2010–2014. Rate ratios (RR) of crashes and moving violations were estimated using Poisson regression.Results: Overall, 86% of males and 71% of females aged ≥ 65 held a valid driver’s license. Older drivers had 27% lower per-driver crash rates than middle-aged drivers (RR: 0.73, 95% CI: 0.73, 0.74)—with appreciable differences by sex—but 40% higher fatal crash rates (RR: 1.40 [1.24, 1.58]). Moving violation rates among older drivers were 72% lower than middle-aged drivers (RR: 0.28 [0.28, 0.28]).Conclusion: The majority of older adults are licensed, with substantial variation by age and sex. Older drivers have higher rates of fatal crashes but lower rates of moving violations compared with middle-aged drivers.Practical applications: Future research is needed to understand the extent to which older adults drive and to identify opportunities to further reduce risk of crashes and resultant injuries among older adults.     

Do recommended driving limits affect teen-reported traffic violations and crashes during the first 12 months of independent driving?

OBJECTIVES: Motor vehicle crashes are highly elevated among newly licensed teenage drivers. Limits on high-risk driving conditions by driver licensing policies and parents can protect novice teens from negative driving outcomes, while they experience and driving proficiency. The purpose of this research was to evaluate the effects of strict parent-imposed driving limits on driving outcomes during the first year of licensure. METHODS: A sample of 3,743 Connecticut teens was recruited and randomized to the Checkpoints Program or comparison condition. Assessments conducted at baseline, licensure, 3-, 6-, and 12-months postlicensure included parent-imposed driving limits, traffic violations, and crashes. Bivariate and multivariate analyses were conducted to assess the effects of strict parent limits on traffic violations and crashes during the first year of licensure. RESULTS: Thirty percent of teens reported at least one traffic violation and 40% reported at least one crash. More strict parent-imposed limits at licensure, 3-, 6-, and 12-months postlicensure, were associated with fewer violations and crashes in multivariate analyses. Notably, adherence to recommended night curfew was consistently associated with fewer violations and crashes. CONCLUSIONS: The findings indicate that strict parent-imposed limits may protect novice teen drivers from negative driving outcomes.     

The impact of environmental, vehicle and driver characteristics on injury severity in older drivers hospitalized as a result of a traffic crash

INTRODUCTION: Compared to younger age groups, older people are more likely to be seriously injured or to die as a result of a traffic crash. METHOD: The aim of the study is to examine the impact of environmental, vehicle, crash, and driver characteristics on injury severity in older drivers involved in traffic crashes by using recently linked police crash records and hospitalization data from New South Wales, Australia. The severity of injury resulting from traffic crashes was measured using the International Classification of Diseases, 10th revision (ICD-10) Injury Severity Score (ICISS). RESULTS: Multivariate analysis identified rurality, presence of complex intersections, road speed limit, driver error, speeding, and seat belt use as independent predictors of injury severity in older people. The type of intersection configuration explained over half of the observed variations in injury severity. IMPACT ON INDUSTRY: Environmental modification such as intersection treatments might contribute to a decrease in the severity of injury in older people involved in road crashes.     

Analysis of Driver Evasive Maneuvering Prior to Intersection Crashes Using Event Data Recorders

Objective: Intersection crashes account for over 4,500 fatalities in the United States each year. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that have the potential to help drivers safely navigate across intersections and prevent intersection crashes and injuries. The performance of an I-ADAS is expected to be highly dependent upon driver evasive maneuvering prior to an intersection crash. Little has been published, however, on the detailed evasive kinematics followed by drivers prior to real-world intersection crashes. The objective of this study was to characterize the frequency, timing, and kinematics of driver evasive maneuvers prior to intersection crashes.

Methods: Event data recorders (EDRs) downloaded from vehicles involved in intersection crashes were investigated as part of NASS-CDS years 2001 to 2013. A total of 135 EDRs with precrash vehicle speed and braking application were downloaded to investigate evasive braking. A smaller subset of 59 EDRs that collected vehicle yaw rate was additionally analyzed to investigate evasive steering. Each vehicle was assigned to one of 3 precrash movement classifiers (traveling through the intersection, completely stopped, or rolling stop) based on the vehicle's calculated acceleration and observed velocity profile. To ensure that any significant steering input observed was an attempted evasive maneuver, the analysis excluded vehicles at intersections that were turning, driving on a curved road, or performing a lane change. Braking application at the last EDR-recorded time point was assumed to indicate evasive braking. A vehicle yaw rate greater than 4° per second was assumed to indicate an evasive steering maneuver.

Results: Drivers executed crash avoidance maneuvers in four-fifths of intersection crashes. A more detailed analysis of evasive braking frequency by precrash maneuver revealed that drivers performing complete or rolling stops (61.3%) braked less often than drivers traveling through the intersection without yielding (79.0%). After accounting for uncertainty in the timing of braking and steering data, the median evasive braking time was found to be between 0.5 to 1.5 s prior to impact, and the median initial evasive steering time was found to occur between 0.5 and 0.9 s prior to impact. The median average evasive braking deceleration for all cases was found to be 0.58 g. The median of the maximum evasive vehicle yaw rates was found to be 8.2° per second. Evasive steering direction was found to be most frequently in the direction of travel of the approaching vehicle.

Conclusions: The majority of drivers involved in intersection crashes were alert enough to perform an evasive action. Most drivers used a combination of steering and braking to avoid a crash. The average driver attempted to steer and brake at approximately the same time prior to the crash.     

Problem driver remediation: a meta-analysis of the driver improvement literature

PROBLEM: Given the public safety risk posed by violation and crash repeaters and the substantial costs for state driver improvement programs, it is important that their effectiveness be scientifically demonstrated and that intervention programs are based on sound research findings. METHOD: Crash and traffic violation standardized effect sizes (d) representing 106 individual interventions were coded from 35 methodologically sound studies and analyzed using meta-analysis. RESULTS: Driver improvement intervention in general was associated with small but significant reductions in both crashes (dw = 0.03) and violations (dw = 0.06). Significant effects were found on both measures for warning letters, group meetings, individual hearings, and license suspense/revocation. Of the driver improvement interventions studied, license suspension/revocation was by far the most effective treatment for both crashes and violations (dw = 0.11 and 0.19). Since one of the objectives of license suspension/revocation is to eliminate driving for the period of suspension, it is possible that much or all of the effect is due to reduced exposure and/or more careful driving during the suspension interval. Results were mixed for other types of interventions, although distributing educational or informational material was not associated with any reductions. Interventions associated with violation reduction tended to also be associated with crash reduction, although the relationship was not very strong (r = .30). DISCUSSION: Although interpretation of the effect size estimates was complicated by almost ubiquitous heterogeneity, the results do suggest an overall positive impact of driver improvement interventions in general. IMPACT ON INDUSTRY: The results support the continued use of driver improvement interventions, chiefly warning letters, group meetings, individual hearings, and especially license suspension/revocation. The results also suggest that court-triggered traffic violator programs are less effective than interventions triggered by drivers license agencies.     

Red light violations at rural and suburban signalized intersections in Jordan

This case study investigated red light violations at rural and suburban signalized intersections in Jordan. Field observations were conducted at 15 signalized intersections located in different Jordanian regions: Amman, Irbid, and Zarqa. The results showed that, out of a total of 1,190 drivers who had a chance for violation, 153 (12.9%) drivers ran red lights. It was found that older drivers have less tendency for running red lights. Based on vehicle type, the analysis showed that truck drivers had the highest violation rate followed by small vehicles and then buses. The Y-shaped intersection had a higher percentage of violations as compared to the T- and cruciform-shaped intersections. The percentage of red light violations was found to be directly proportional to the subjects approach speed and inversely proportional to the conflicting traffic volumes.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

Responsibility of drivers, by age and gender, for motor-vehicle crash deaths

Problem: Motor-vehicle crash rate comparisons by age and gender usually are based on the extent to which drivers in a particular age/gender category are themselves injured or involved in crashes (e.g., the number of 20-year-old females in crashes). Basing comparisons instead on the extent to which drivers in various age/gender groups are responsible for deaths (including themselves) in their crashes is more revealing of their overall contribution to the problem. Methods: Data from the Fatality Analysis Reporting System (FARS, 1996–2000) were used in the analysis, which was based on crashes that involved one or two vehicles only. Drivers in fatal single-vehicle crashes were assumed to have responsibility for the crash. In fatal two-vehicle crashes, driver operator errors reported by police were used to assign crash responsibility. Results: When all crashes were considered, both the youngest and oldest drivers were most likely to be responsible for deaths in their crashes. In two-vehicle crashes, the oldest drivers were more likely than young drivers to be responsible. Young males were more likely than young females to be responsible for crash deaths, whereas females in their 50s and older were more likely than same-age males to be responsible. In terms of responsibility for deaths per licensed driver, young drivers, especially males, had the highest rates because of their high involvement rates and high responsibility rates. The majority of deaths for which young drivers were responsible occurred to people other than themselves, especially passengers in their vehicles, whereas the bulk of the deaths for which older drivers were responsible were their own. Discussion: The results highlight the contribution of young drivers to the motor-vehicle crash problem, the need for measures such as passenger restrictions in graduated licensing systems, and the need for vehicle modifications to better protect older occupants.     

Older drivers’ involvement in fatal RTCs. Do crashes fatal to them differ from crashes involving them but fatal to others?

In several countries, older drivers are disproportionately involved in fatal road traffic crashes (RTCs) for various reasons. This study maps the circumstances of occurrence of crashes involving older drivers that are fatal to either them or other road users and highlights differences between them. Sweden’s national in-depth studies of fatal RTCs archive was used and focus was placed on crashes in which a driver aged 65 years or older was involved between 2002 and 2004 (n = 197). Thirteen driver and crash characteristics were analyzed simultaneously and typical crash patterns (classes) were highlighted. For each pattern, the proportions of crashes fatal to the older driver vs. to someone else were compared. Four patterns were identified: (1) crashes on low-speed stretches, involving left turn and intersections; (2) crashes involving very old drivers and older vehicles, (3) rear-end collisions on high-speed stretches; and (4) head-on and single-vehicle crashes in rural areas. Older drivers dying in the crash were over-represented in classes 2 and 4. The study shows that when older drivers are involved in fatal RTCs, they are often the ones who die (60%). Typical circumstances surrounding their involvement include manoeuvring difficulties, fast-moving traffic, and colliding in an old vehicle. Preventing fatal RTCs involving older drivers requires not only age-specific but also general measures.     

Driver behavior analysis for right-turn drivers at signalized intersections using SHRP 2 naturalistic driving study data

IntroductionUnderstanding driver behavior is important for traffic safety and operation, especially at intersections where different traffic movements conflict. While most driver-behavior studies are based on simulation, this paper documents the analysis of driver-behavior at signalized intersections with the SHRP 2 Naturalistic Driving Study (NDS) data. This study analyzes the different influencing factors on the operation (speed control) and observation of right-turn drivers.MethodA total of 300 NDS trips at six signalized intersections were used, including the NDS time-series sensor data, the forward videos and driver face videos. Different factors of drivers, vehicles, roads and environments were studied for their influence on driver behavior. An influencing index function was developed and the index was calculated for each influencing factor to quantitatively describe its influencing level. The influencing index was applied to prioritize the factors, which facilitates development and selection of safety countermeasures to improve intersection safety. Drivers' speed control was analyzed under different conditions with consideration of the prioritized influencing factors.ResultsVehicle type, traffic signal status, conflicting traffic, conflicting pedestrian and driver age group were identified as the five major influencing factors on driver observation.ConclusionsThis research revealed that drivers have high acceleration and low observation frequency under Right-Turn-On-Red (RTOR), which constituted potential danger for other roadway users, especially for pedestrians.Practical applicationsAs speed has a direct influence on crash rates and severities, the revealed speed patterns of the different situations also benefit selection of safety countermeasures at signalized intersections.     

Collisions involving senior drivers: high-risk conditions and locations

OBJECTIVES: To better understand the characteristics of crashes involving senior drivers 65 and older, studies of these crashes were reviewed. METHODS: The review focused primarily on North American studies published since 1990. Studies point to important differences between the crashes of senior drivers and those of younger drivers. RESULTS. Numerous studies have found that senior drivers' crashes are much more likely than crashes of younger drivers to occur at intersections. Senior drivers have particularly high rates of involvement in intersection crashes when they are turning, and even more so when they are turning left. Senior drivers are more likely than younger drivers to have been at fault in these situations, typically because they failed to yield the right-of-way, disregarded the traffic signal, or committed some other traffic violation. Studies also suggest that the extent of overinvolvement of senior drivers in certain types of crashes generally increases with advancing age. CONCLUSIONS. The extent to which the distinctive characteristics of senior drivers' crashes may be due to changing travel patterns associated with aging, or physical or cognitive impairments related to the aging process, is unclear. Further research is needed to understand the pre-crash circumstances of older drivers' intersection crashes.     

Improvement of the performance of animal crossing warning signs

Introduction: Animal–vehicle collisions (AVCs) can result in serious injury and death to drivers, animals' death, and significant economic costs. However, the cost effectiveness of the majority of AVC mitigation measures is a significant issue. Method: A mobile-based data collection effort was deployed to measure signs under the Utah Department of Transportation's (UDOT) jurisdiction. The crash data were obtained from the UDOT risk management database. ArcGIS was employed to link these two data sets and extract animal-related crashes and signs. An algorithm was developed to process the data and identify AVCs that occurred within sign recognition distance. Kernel density estimation (KDE) technique was applied to identify potential crash hotspots. Results: Only 2% of AVCs occurred within the recognition distance of animal crossing signs. Almost 58% of animal-related crashes took place on the Interstate and U.S. highways, wherein only 30% of animal crossing signs were installed. State routes with a higher average number of signs experienced a lower number of AVCs per mile. The differences between AVCs that occurred within versus outside of sign recognition distance were not statistically significant regarding crash severity, time of crash, weather condition, driver age, vehicle speed, and type of animal. It is more likely that drivers become accustomed to deer crossing signs than cow signs. Conclusions: Based on the historical crash data and landscape structure, with attention given to the low cost safety improvement methods, a combination of different types of AVC mitigation measures can be developed to reduce the number of animal-related crashes. After an in-depth analysis of AVC data, warning traffic signs, coupled with other low cost mitigation countermeasures can be successfully placed in areas with higher priority or in critical areas. Practical applications: The findings of this study assist transportation agencies in developing more efficient mitigation measures against AVCs.     

Analysis of driver injury severity levels at multiple locations using ordered probit models

Problem: The occurrence and outcome of traffic crashes have long been recognized as complex events involving interactions between many factors, including the roadway, driver, traffic characteristics, and the environment. This study is concerned with the outcome of the crash. Method: Driver injury severity levels are analyzed using the ordered probit modeling methodology. Models were developed for roadway sections, signalized intersections, and toll plazas in Central Florida. All models showed the significance of driver's age, gender, seat belt use, point of impact, speed, and vehicle type on the injury severity level. Other variables were found significant only in specific cases. Results: A driver's violation was significant in the case of signalized intersections. Alcohol, lighting conditions, and the existence of a horizontal curve affected the likelihood of injuries in the roadway sections' model. A variable specific to toll plazas, vehicles equipped with Electronic Toll Collection (ETC), had a positive effect on the probability of higher injury severity at toll plazas. Other variables that entered into some of the models were weather condition, area type, and some interaction factors. This study illustrates the similarities and the differences in the factors that affect injury severity between different locations.     

Investigating the self-reported behavior of drivers and their attitudes to traffic violations

IntroductionDriving behavior theoretical models consider attitudes as an important determinant of driver behavior. Moreover, the association between the self-reported tendency to commit violations and accident involvement is widely recognized. This research investigates drivers’ self-reported behavior and attitudes to risky behaviors related to the traffic violations of speeding, drink-driving, and cell phone use using cluster analysis.MethodA sample of 601 Greek drivers participating at the SARTRE 4 pan-European survey is utilized. The analysis identified three clusters of drivers. Drivers in Cluster 1 commit traffic violations more often; drivers in Cluster 2 favor traffic violation countermeasures while having moderate views toward compliance with traffic rules; and drivers in Cluster 3 strongly support traffic violation countermeasures and also have strong views toward compliance with traffic rules. Risky behaviors and related attitudes that differentiate the three distinct groups of drivers (clusters) were determined.ResultsThe findings indicate that differences in attitudes and behaviors may be attributed to factors such as age, gender, and area of residence. The research findings also provided some insight about the current level of drivers’ attitudes to traffic violations, especially those that negatively affect traffic safety. The pattern of their views on violations may form the basis of risk behavior-related interventions tailored to the identified groups, aiming at informing, educating, and raising the awareness of the public.Impact on IndustryAgencies focused on safety interventions could exploit this information in designing and implementing education campaigns, enforcement programs and in defining relevant priorities.     

Association between older driver characteristics, on-road driving test performance, and crash liability

From May 1999, a new system for licensing older drivers was introduced in New Zealand. It included a practical on-road driving test with expanded scope, to be completed every two years from the time the driver turns 80. The relationship between crashes and test performance needed to be studied to inform the debate regarding the testing system. The population studied was all drivers who entered this licensing system during its first three years of operation. They were defined as crash involved if they were involved in an injury crash during the two years following their first licensure under the new system. Logistic regression was used to describe the risk of crash involvement in terms of driving test performance and other driver characteristics. Each driving test failure was associated with a 33% increase in the odds of crash involvement (95% CI 14% to 55%), controlling for age, gender, minor traffic violations, and whether the older driver lived with another licensed driver or not. Minor traffic violations in the two years following the driving test were associated with twice the odds of crash involvement. These results suggest that the new on-road driving test does identify older driver behaviors or limitations that are related to crash liability. It is anticipated that the results presented here will provide essential information for discussing older driver licensing systems, whose impact will grow in importance as the population of drivers ages.     

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

Aims: Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

Methods: A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004–2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

Results: Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

Conclusions: Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.