When may road fatalities start to decrease?

Introduction

The comparative analysis of macroscopic trends in road safety has been a popular research topic. The objective of this research is to propose a simple and, at the same time, reliable multiple regime model framework for international road safety comparisons, allowing for the identification of slope changes of personal risk curves and respective breakpoints.

Method

The trends of road traffic fatalities in several EU countries have been examined through the temporal evolution of elementary socioeconomic indicators, namely motorized vehicle fleet and population, at the country level.

Results

Piece-wise linear regression models have been fitted, using a methodology that allows the simultaneous estimation of all slopes and breakpoints. The number and location of breakpoints, as well as the slope of the connecting trends, vary among countries, thus indicating different road safety evolution patterns.

Impact on industry

Macroscopic analysis of road accident trends may be proved beneficial for the identification of best examples and the implementation of appropriate programmes and measures, which will lead to important benefits for the society and the economy through the reduction of road fatalities and injuries. Best performing countries and the related programmes and measures adopted may concern several safety improvements at the processes of the road, the vehicle and the insurance industries.

Conclusions

Lessons from the analysis of the past road safety patterns of developed countries provide some insight into the underlying process that relates motorization levels with personal risk and can prove to be beneficial for predicting the road safety evolution of developing countries that may have not yet reached the same breakpoints. Furthermore, the presented framework may serve as a basis to build more elaborate models, including more reliable exposure indicators (such as vehicle-km driven).     

Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies

Introduction

Fatalities from traffic accidents in less-motorized societies are an important global issue. We aimed to characterize the geographic differences of fatalities in such societies to facilitate the development of targeted interventions.

Method

This study linked police reports, hospital data, and vital registration data from Taiwan with special reference to accident factors in pre-hospital deaths and medical care in hospital deaths.

Results

A higher percentage of pre-hospital deaths were observed following rural as compared to urban traffic accidents. The deaths due to rural accidents can be attributed to lower use of restraints (i.e., helmets or seat belts), lower percentage of motorcyclists, and more highway accidents. A higher percentage of victims in rural accidents were transported to distant medical centers rather than to local hospitals.

Conclusion

Specific interventions, such as intelligent emergency medical systems, campaigns for helmets and seat belt usage, enforcement of helmets and seat belt use, and speed control measures should be targeted to rural areas.

Impact on industry

Cooperation between the vehicle industry and emergency medical providers in rural traffic accident rescue teams may decrease the numbers of deaths in these regions.     

Efficacies of roadway safety improvements across functional subclasses of rural two-lane highways

Introduction

Highway crash occurrence is a leading cause of unnatural deaths, and highway agencies continually seek to identify engineering measures to reduce crashes and to assess the efficacy of such measures. Most past studies on the effectiveness of roadway improvements in terms of crash reduction considered all rural two-lane sections as a single category of roads. However, it may be hypothesized that the differences in the mobility and accessibility characteristics that are reflected in (and due to) the different design standards between different functional subclasses in the rural two-lane highway system can lead to differences in efficacies of safety improvements at these subclasses. This paper investigates the efficacy of roadway improvements, in terms of crash reduction, at the various subclasses of rural two-lane highways.

Methods

An empirical analysis of safety performance at each of the three subclasses of rural two-lane highways was carried out using the negative binomial modeling technique. For each subclass, crash prediction models were developed separately for the three levels of crash severity: property-damage only, injury, and fatal/injury. The crash factors that were considered include lane width, shoulder width, pavement surface friction, pavement condition, and horizontal and vertical alignments. After having developed the safety performance functions, the effectiveness (in terms of the extent of crash reduction, for different levels of crash severity) of highway safety enhancements at each highway subclass were determined using the theoretical concepts established in past literature. These enhancements include widening lanes, widening shoulders, enhancing pavement surface friction, and improving the vertical or horizontal alignment.

Results and Conclusion

The study found that there is empirical evidence to justify the decomposition of the family of rural two-lane roads into its constituent subclasses for purposes of analyzing the effectiveness of safety enhancement projects and thus to avoid underestimation or overestimation of benefits of safety improvements at this class of highways.     

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

Introduction

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN).

Method

It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators’ values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN.

Conclusions

It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model.

Impact on Industry

The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model.     

What is the potential of trauma registry data to be used for road traffic injury surveillance and informing road safety policy?

Introduction

Information from hospital trauma registries is increasingly being used to support injury surveillance efforts. This research examines the potential of using trauma registry data for road traffic injury surveillance for different types of road users in terms of both the information collected and how representative trauma data are compared to two population-based road traffic injury data collections.

Methods

The three data collections were assessed against recommended variables to be collected for injury surveillance purposes and the representativeness of the distribution of road traffic-related injury data from the trauma registry was compared to hospital admission and road traffic authority data collections.

Results

Data from the trauma registry was largely not representative of the distribution of age groups or activities compared to the two population-based collections, but was representative for gender for some road user groups to at least one population-based data collection.

Conclusions

Trauma data could be used to supplement information from population-based data collections to inform road safety efforts.

Impact on Industry

Road safety policy makers should be aware of the potential and the limitations of using trauma registry data for road traffic injury surveillance.     

Survival risk factors for fatal injured car and motorcycle drivers in single alcohol-related and alcohol-unrelated vehicle crashes

Introduction

A high percentage of drivers who die as a result of a single vehicle crash are under the influence of alcohol. We aimed to better understand the prevalence of these fatalities and the ratio of death to injuries based on various risk factors. We focused on alcohol-related and -unrelated single-vehicle crashes to investigate the influence of such risk factors on the time until death for car and motorcycle drivers.

Methods

We combined data from national police reports and a vital registration database in Taiwan. Survival analysis using Cox regression models was used to identify the risk factors of time until death.

Results

Overall, nearly 60% of car driver fatalities and 40% of motorcycle driver fatalities involved the consumption of alcohol. Survival analysis of single-vehicle crashes suggested that the traffic island separation between a car moving at a higher speed and motorcycle traffic resulted in a higher risk of death over time for motorcycle drivers who consumed alcohol. The factors attributed to a higher risk of death over time for motorcycle drivers were older age, crashing into trees, night-time driving, driving on curved roads, and driving on local roads. Driving without restraints and driving on roads with higher speed limits attributed to a higher risk of death over time for car drivers.

Conclusions

The factors that influence the risk of death over time in a motor-vehicle accident involving alcohol depended on different elements, which should each be considered when attempting to reduce this risk.

Impact on Industry

More efforts should be made to investigate the various risk factors in areas with large motorcycle populations.     

Severity models of cross-median and rollover crashes on rural divided highways in Pennsylvania

Introduction

Crossover and rollover crashes in earth-divided, traversable medians on rural divided highways can lead to severe injury outcomes. This study estimated severity models of these two crash types. Vehicle, driver, roadway, and median cross-section design data were factors considered in the models. A unique aspect of the data used to estimate the models were the availability of median cross-slope data, which are not commonly included in roadway inventory data files.

Methods

A binary logit model of cross-median crash severity and a multinomial logit model of rollover crash severity were estimated using five years of data from rural divided highways in Pennsylvania.

Results

The highest probability of a fatal or major injury in cross-median and rollover crashes was found to occur in cases when a driver was not wearing a seatbelt. While flatter cross-slopes and narrower medians were associated with more severe cross-median crash outcomes, steeper cross-slopes and narrower medians significantly increased rollover crash severity outcomes. The presence of horizontal curves was associated with increased probabilities of high-severity outcomes in a median rollover crash.

Impact on Industry

Modeling results in this study confirmed that cross-median and median rollover crash severity outcomes are associated with median cross-section design characteristics. Based on the estimated models, it appears that flatter and narrower medians lead to more severe injury outcomes in cross-median crashes. Steeper median cross-slopes and narrower medians were associated with higher probabilities of more severe outcomes in median rollover crashes. The results presented in this study suggest that there is a trade-off between median cross-section design and cross-median and rollover crashes in earth-divided, traversable medians on rural divided highways. While the severity models can be included in a framework to develop design guidance in relation to this trade-off, models of crash frequency should also be considered.     

Social desirability effects in driver behavior inventories

Problem

The use of lie scales to control for common method variance in driver behavior inventories has been very limited. Given that such questionnaires often use self-reported safety variables as criteria, and have social implications, the risk of artefactual associations is high.

Method

A questionnaire containing scales from several well known driver inventories that have been claimed to predict traffic accident involvement was distributed three times to a group of young drivers in a driver education program, as well as a random group twice. The Driver Impression Management scale (DIM) was used to control for socially desirable responding.

Results

For all behavior scales, the correlation with the DIM scale was substantial. If a scale correlated with self-reported crashes, the amount of predictive power was more than halved when social desirability was controlled for. Results were similar for both samples and all waves. The predictive power of the behavior scales was not increased when values were averaged over questionnaire waves, as should have been the case if the measurement and predictive power were valid. Results were similar for self-reported penalty points. The present results indicate that even the most well-known and accepted psychometric scales used in driver research are susceptible to social desirability bias.

Discussion

As social desirability is only one of a number of common method variance mechanisms that can create artefactual associations, and the great popularity of the self-report methodology, the problem for traffic research is grave.

Impact on industry

Organizations that fund traffic safety research need to re-evaluate their policies regarding what methods are acceptable. The use of self-reported independent and dependent variables can lead to directly misleading results, with negative effects on traffic safety.     

Effect of enhanced seat belt reminders on driver fatality risk

Objective

Enhanced seat belt reminders in automobiles have been shown to increase belt use rates by approximately 3 percentage points. The objective of this study was to estimate the effect of enhanced seat belt reminders on driver fatality risk.

Method

Data included all passenger vehicle driver deaths and vehicle registration counts in the United States for calendar years 2000-2007. Driver fatality rates per vehicle registration per year were compared for otherwise identical vehicle models with and without enhanced seat belt reminders.

Results

Driver fatality rates were 6% lower for vehicles with enhanced seat belt reminders compared with vehicles without enhanced belt reminders. After adjusting for vehicle age differences, the estimated effect of enhanced belt reminders on driver fatality risk ranged from a 9% reduction for General Motors vehicles to a 2% increase for Honda vehicles. Combining all manufacturers, enhanced belt reminders reduced fatality risk by approximately 2%. Although not statistically significant, the 2% reduction in fatality risk agrees with what should be expected from a 3 percentage point increase in seat belt use rates.

Conclusions

Enhanced seat belt reminders have raised driver belt use rates and reduced fatality rates, but more aggressive systems may be needed for some drivers. It can be inferred that nonfatal injury rates also have been reduced.

Impact on Industry

Manufacturers should be encouraged to put enhanced seat belt reminders on all vehicles as soon as possible.     

A Bayesian assessment of the effect of highway bypasses in Iowa on crashes and crash rate

Introduction

A common contention is that the construction of highway bypasses negatively impacts the economy of local communities by reducing pass-by traffic for businesses. However, as access to specific business' account records is limited, this impact is difficult to quantify. Another common contention is that bypasses contribute to a reduction in overall crashes in the community and in the surrounding areas. Even though a large number of bypasses have been constructed in the State of Iowa over the past several years, their actual impact in terms of traffic safety has not been quantified.

Objectives

This study seeks answers to the following questions: (a) Are bypasses in Iowa associated with a reduction in crash frequencies and crash rates on the bypassed highway? (b) Do bypasses in Iowa introduce a reduction of overall crash frequencies and rates or do they merely shift crashes from the highways through the communities to the bypasses with no significant overall reduction?

Method

We obtained crash information from the Iowa DOT at 19 sites on which a bypass was constructed sometime during the past 23 years. We also obtained the same information at six sites used as comparison sites on which no bypasses were constructed at least until 2005. We them employed a Bayesian approach to estimating the association between the construction of the bypass and crash rates, while also accounting for other factors.

Results

The construction of bypasses in Iowa is associated with a significant increase in traffic safety both on the main road through town and on the combined main road and bypass roadway.     

Driving self-restriction in high-risk conditions: how do older drivers compare to others?

Introduction

Many older drivers self-restrict or avoid driving under high-risk conditions. Little is known about the onset of driving self-restrictions or how widespread self-restrictions are among drivers of all ages.

Methods

The Second Injury Control and Risk Survey (ICARIS-2) was a nationwide cross-sectional, list-assisted random-digit-dial telephone survey from 2001 to 2003. National prevalence estimates and weighted percentages of those reporting driving self-restrictions were calculated. Multivariable logistic regression was used to explore associations between specific self-restrictions and age group, adjusting for other personal characteristics.

Results

More than half of all drivers reported at least one driving self-restriction. The most commonly reported restriction was avoidance of driving in bad weather (47.5%), followed by at night (27.9%) and on highways or high-speed roads (19%). A greater percentage of young adult women (18-24 years) reported self-restricting in bad weather compared to women in other age groups, and the percentage of drivers self-restricting at night, in bad weather, and on highways or high-speed roads increased steeply after age 64. We found that women, those in low income groups, and those who had driven low annual mileage were more likely to self-restrict.

Conclusions

In addition to assessing self-restrictions among older drivers, a new finding from our study is that self-restrictions are also quite prevalent among younger age groups. Driving self-restrictions may be better understood as a spectrum across ages in which drivers’ reasons for restriction change.

Impact on industry

Future research on the ability of driving self-restrictions to reduce actual crash risk and prevent injuries is needed.     

Case-control and cross-sectional methods for estimating crash modification factors: comparisons from roadway lighting and lane and shoulder width safety effect studies

Problem

While observational before-after studies are considered the industry standard for developing crash modification factors (CMFs), there are practical limitations that may preclude their use in highway safety analysis. There is a need to explore alternative methods for estimating CMFs.

Method

This paper employs case-control and cross-sectional analyses to estimate CMFs for fixed roadway lighting and the allocation of lane and shoulder widths.

Results

Based on the case-control method, the CMF for intersection lighting is 0.886, while the cross-sectional study indicates a CMF of 0.881. The CMFs developed for lane and shoulder widths are also similar when comparing the two methods.

Conclusions

This paper suggests that case-control and cross-sectional studies produce consistent results if care is taken in the study design and model development.

Impact on industry

Case-control and cross-sectional studies may provide a viable alternative to estimate CMFs when a before-after study is impractical due to data restrictions.     

Injury severity analysis of accidents involving young male drivers in Great Britain

Introduction

Young male drivers are over-represented in traffic accidents; they were involved in 14% of fatal accidents from 1991 to 2003 while holding only 8% of all drivers licenses in the UK. In this study, a subset of the UK national road accident data from 1991 to 2003 has been analyzed. The primary aim is to determine how to best use monetary and progressive resources to understand how road safety measures will reduce the severity of accidents involving young male drivers in both London and Great Britain.

Method

Ordered probit models were used to identify specific accident characteristics that increase the likelihood of one of three categorical outcomes of accident severity: slight, serious, or fatal.

Results

Characteristics found to lead to a higher likelihood of serious and fatal injuries are generally similar across Great Britain and London but are different from those predicted to lead to a higher likelihood of slight injuries. Those characteristics predicted to lead to serious and fatal injuries include driving in darkness, between Friday and Sunday, on roads with a speed limit of 60 mph, on single carriageways, overtaking, skidding, hitting an object off the carriageway, and when passing the site of a previous accident. Characteristics predicted to lead to slight injuries include driving in daylight, between Monday and Thursday, on roads with a speed limit of 30 mph or less, at a roundabout, waiting to move, and when an animal is on the carriageway.

Impact on Industry

These results aid the selection of policy options that are most likely to reduce the severity of accidents involving young male drivers.     

Re-education of young driving offenders; Effects on self-reports of driver behavior

Introduction

Offending drivers are often re-educated, but these courses have seldom been shown to have any safety effects.

Method

An on-line improvement course for offending drivers below the age of 25 was evaluated with several driver inventories.

Results

The drivers reported higher levels of aggression, stress, sensation seeking, drunk driving, and driving violations, six months after the course than before. However, these levels were lower than those of controls, indicating that the initially low levels for the education group were due to socially desirable responding, as measured by a lie scale, an effect that waned after the course.

Discussion

The results can be interpreted as a positive effect of the education, although this conclusion is tentative and not in agreement with all effects in the data.

Impact on industry

The results are in disagreement with previous evaluation studies using the same or similar instruments, and show the need to include controls for social desirability in self-report studies.     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

The accident-exposure association: self-reported versus recorded collisions

Problem

It has been claimed that exposure to risk of road traffic accidents (usually conceptualized as mileage) is curvilinearly associated with crashes (i.e., the increase in number of crashes decreases with increased mileage). However, this effect has been criticized as mainly an artifact of self-reported data.

Method

To test the proposition that self-reported accidents create part of the curvilinearity in data by under-reporting by high-accident drivers, self-reported and recorded collisions were plotted against hours of driving for bus drivers.

Results

It was found that the recorded data differed from self-reported information at the high end of exposure, and had a more linear association with the exposure measure as compared to the self-reported data, thus supporting the hypothesis.

Discussion

Part of the previously reported curvilinearity between accidents and exposure is apparently due to biased methods. Also, the interpretation of curvilinearity as an effect of exposure upon accidents was criticized as unfounded, as the causality may just as well go the other way. Impact on industry: The question of how exposure associates with crash involvement is far from resolved, and everyone who uses an exposure metric (mileage, time, induced) should be careful to investigate the exact properties of their variable before using it.     

A reporting guide for studies on individual differences in traffic safety

Problem

Studies on individual differences in traffic safety report differently on their methodologies, and use different statistics, and these are therefore difficult to compare and meta-analyze.

Method

Based upon a previous, extensive review and meta-analysis of the traffic safety literature, several recommendations are made about what features of the methodology of studies on individual differences (including evaluations) in safety need to be reported to facilitate interpretation and meta-analysis. Similarly, some basic types of statistical values are recommended.

Impact on Industry

The accumulation of knowledge about individual differences in traffic safety would be facilitated if scientific authors and journals adhered to these guidelines.     

A classification tree based modeling approach for segment related crashes on multilane highways

Introduction

This study presents a classification tree based alternative to crash frequency analysis for analyzing crashes on mid-block segments of multilane arterials.

Method

The traditional approach of modeling counts of crashes that occur over a period of time works well for intersection crashes where each intersection itself provides a well-defined unit over which to aggregate the crash data. However, in the case of mid-block segments the crash frequency based approach requires segmentation of the arterial corridor into segments of arbitrary lengths. In this study we have used random samples of time, day of week, and location (i.e., milepost) combinations and compared them with the sample of crashes from the same arterial corridor. For crash and non-crash cases, geometric design/roadside and traffic characteristics were derived based on their milepost locations. The variables used in the analysis are non-event specific and therefore more relevant for roadway safety feature improvement programs. First classification tree model is a model comparing all crashes with the non-crash data and then four groups of crashes (rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes) are separately compared to the non-crash cases. The classification tree models provide a list of significant variables as well as a measure to classify crash from non-crash cases. ADT along with time of day/day of week are significantly related to all crash types with different groups of crashes being more likely to occur at different times.

Conclusions

From the classification performance of different models it was apparent that using non-event specific information may not be suitable for single vehicle/off-road crashes.

Impact on Industry

The study provides the safety analysis community an additional tool to assess safety without having to aggregate the corridor crash data over arbitrary segment lengths.     

Increasing self-awareness among older drivers: The role of self-screening

Introduction

Self-screening by older drivers has shown considerable promise for increasing self-awareness about functional abilities associated with safe driving. The purpose of this study was to improve upon existing self-screening instruments by focusing entirely on “health concerns” that affect driving - that is, the symptoms that people experience due to medical conditions and the medications used to treat them - rather than the medical conditions or medications themselves.

Method

A computer-based, easy-to-use self-screening instrument for older drivers was developed to provide individualized feedback intended to increase self-awareness about declines in driving-related abilities, as well as suggestions for behavioral changes or safety tips to maintain safe driving, further evaluation from a physician/health professional, and vehicle modifications to help compensate for driving-related declines.

Results

This paper describes the development of the self-screening instrument and summarizes findings relative to increasing self-awareness among older drivers. This research represents an important first step in improving self-awareness among older drivers through self-screening.     

Acciphilia on the road: An analysis of severe collisions

Introduction

Although prior studies of road traffic accidents have found between-group differences in risk, little attention has been given to the encounter between drivers involved in severe collisions.

Method

The present study empirically evaluates two different possible causes of "social accidents," which are defined as collisions between two or more drivers where some faulty social interaction might be assumed, and which are the most prevalent cause of road injuries. The analyses use merged Israeli collision records from 1983 to 2004 with data from two national censuses, thus providing an unprecedented empirical basis to study the social foundations of car accidents. The data are used to adjudicate between two alternative hypotheses: the heterogeneity hypothesis (socially different drivers tend to collide) versus the homogeneity hypothesis (socially similar drivers tend to collide).

Results

Multivariate analyses provide preliminary support for the latter hypothesis. Given an accident, there are more collisions among drivers from the same broad educational group, and the factors that influence this correlation are independent of geography. The paper thus leads to the idea that severe collisions reflect a sociological or ecological process that is akin to acciphilia.

Impact on Industry

The preliminary findings suggest that variation between drivers may be preferable to similarity, since apparently there is a greater tendency toward collisions between similar drivers.