The influence of the infrastructure characteristics in urban road accidents occurrence

This paper summarizes the result of a study regarding the creation of tools that can be used in intervention methods in the planning and management of urban road networks in Portugal.     

Predicting the number of accidents at a road junction

We consider a model, within a Bayesian framework, which can be used to predict the number of accidents occurring at a road junction in a given period of time. The predictions are based on measurements of the traffic flows as well as on covariates which describe important features of the junctions. Various approximate and estimative methods, which use Gibbs sampling, posterior normality and Laplace approximations, are considered and compared. Procedures to assess the importance of the different covariates through the use of the Kullback-Leibler measure of divergence are also developed.     

Measuring the safety effect of road measures at junctions

The effects of road measures implemented at main road junctions in 1984–1986 were studied on the basis of police-reported accidents that had occurred at the junctions in 1983–1987. The data were obtained from an extensive junction inventory performed by the District Offices of the Finnish National Road Administration in 1988. A total of 325 three-arm and 298 four-arm junctions were included in the study. The number and type of accidents were studied at each junction both before and after the implementation of the measure. The effects of the measure were determined by comparing the observed number of accidents after the measure with the number that would have been expected to occur at the junction if the measure had not been implemented. The expected number of accidents was calculated on the basis of the observed number of accidents in the before period and the expected number of accidents as predicted by an accident model, utilizing at the same time the information on the variation of the number of accidents at similar junctions revealed by the model. Likelihood functions determined for the effects of the measures were used for studying the accuracy of the estimates of the effects. The likelihood functions can also be utilized later when new before-and-after studies are performed. Road lighting, stop signs, signal control, and lowering of the speed limit value were found to decrease the number of accidents. Through-flow junction widenings, additional lanes for turning vehicles, and road widenings, however, did not seem to affect the safety at junctions to any marked extent. If we had not accounted for the regression-to-the-mean effect, these measures would have seemed to have a positive effect on safety. The study method also enabled us to quantify the regression-to-the-mean effect. The magnitude of the regression effect was on average 20%, i.e. the number of accidents would have decreased by 20% at the junctions studied even if the measures had not been implemented. The magnitude of the regression-to-the-mean varied greatly between the different measures.     

Analysis of traffic accidents at urban intersections in Riyadh

Previous studies have shown that intersection-related accidents account for about 50% of all accidents registered annually in Riyadh, the capital of the Kingdom of Saudi Arabia (KSA). More than half of these accidents are classified as severe. In this study, an attempt was made to investigate traffic accidents that occurred at both intersections and non-intersection sites. The goal was to analyze the nature of such accidents to determine their characteristics so that remedies could be sought or at least future research could be suggested. For this purpose, a sample of 1774 reported accidents was collected in a systematic random manner for the period 1996-1998 (651 severe accidents (accidents resulting in at least one personal injury or fatality) and 1123 property-damage-only (PDO) accidents). Conditional probability and contingency table analyses were used to make inferences from the data. The study found that improper driving behavior is the primary cause of accidents at signalized urban intersections in Riyadh; running a red light and failing to yield are the primary contributing causes. The analysis indicates that there is an urgent need to review existing intersection geometry along with the traffic control devices installed at these sites. In addition, public education campaigns and law enforcement strategies are urgently needed.     

Powered two-wheelers road accidents and their risk perception in dense urban areas: Case of Paris

For a few years, the use of powered two-wheelers has taken off in Paris. It then became critical for the City of Paris to understand both the mechanisms leading to traffic accidents involving at least one powered two-wheelers user and the perception of their risk when riding in dense urban areas. In so doing, two studies were carried out along similar lines so that their results could be compared. The first study focused on the perception of situations where accidents are most likely to occur. The second one was an analysis of police reports of accidents involving at least one powered two-wheelers and the drawing-up of prototypical accident scenarios. Comparing the results of the two studies revealed a gap between perceived and objective risks of these users. In fact, they rather fear the situations during which a car driver is changing lanes, while accidents involving them occur more often when a car driver turns (right, left or U). Knowledge of this dissonance in terms of awareness of road risks for powered two-wheelers and equally, other road users, will give the City of Paris food for thought. The promising results of this study have encouraged the City of Paris to extend it to other types of users, such as cyclists or elderly pedestrians.     

A mixed logit analysis of motorists’ right-of-way violation in motorcycle accidents at priority T-junctions

Research suggested that motorists’ right-of-way (ROW) violation in automobile-motorcycle gap-acceptance accidents at priority (i.e., stop-/yield-controlled) T-intersections has been a safety concern to motorcyclists. This study examines the characteristics of automobile-motorcycle gap-acceptance accidents that occurred at such locations. British Stats19 accident injury database during 1991-2005 are examined in detail. Automobile-motorcycle gap-acceptance accidents are classified into three crash scenarios: approach-turn, angle crossing, and angle merging crashes. Mixed (random parameters) logit models are estimated to investigate the contributory factors to motorists’ ROW violation in these three crash types. Crash features are also compared among gap-acceptance accidents and other crash scenarios. The methodological approach adopted allows for the individuals within the observations to have different parameter estimates as opposed to a single parameter representing all observations (i.e., accounts for unobserved heterogeneity potentially relating to roadway/environmental characteristics, and motorist behaviours). It was found that motorcycles’ ROW was more likely to be violated on non-built-up roads, and in diminished light conditions, with non-uniform effects across the observations. Elderly/female motorists appeared to be over-represented in gap-acceptance crashes. Implications of the findings are discussed.     

Signals are informative but slow down responses when drivers meet bicyclists at road junctions

Three experiments used a laboratory analogue to the task of driving to look at drivers’ responses to encounters with a bicyclist at a T-junction. In particular, a comparison was made between the bicyclist indicating an upcoming turn with an arm signal, an informal signal of intent, or no signal. Overall, arm signals worked relatively well to inform drivers of the bicyclist's intentions and were easier to perceive than informal signals. It was also found that simple failures to react to the bicyclist in time were more common at shorter thinking times whereas incorrect positive responses were unaffected by thinking time. Most interestingly, these experiments showed that arm signals often slowed down the participants’ decision-making processes, leading to a lower probability of their stopping in time when the bicyclist was at risk. Moreover, the same was true for informal signals in which there was eye-contact between the bicyclist and the participant. It is suggested that these effects come about because both arm signals and eye-contact are communicative acts and therefore invoke extra stages of involuntary cognitive processing in the drivers, thereby slowing their reactions.     

Suggestions for an improved system for statistical data about road accidents and road traffic

Data information systems for road accidents and road traffic must satisfy high standards of relevance and quality. The general outline of an improved system for collecting road accident data is given. The system is characterized by the use of statistical sampling methods. The police, the insurance companies and the hospitals are recommended as sources of information about the total accident population. A statistical sample of all identified accidents is then investigated in more detail by special local investigation groups. A hypothetical numerical example is given to show how the suggested system would work in practise. Road accident data should not be isolated from road traffic data. An improved system for collecting information on road traffic is also discussed. This consists of a basic system (founded on statistical sampling methods) for estimation of the total volume of traffic and a few other essential variables such as the volume divided into speed and vehicle types.     

Modeling vehicle accidents and highway geometric design relationships

The statistical properties of four regression models—two conventional linear regression models and two Poisson regression models—are investigated in terms of their ability to model vehicle accidents and highway geometric design relationships. Potential limitations of these models pertaining to their underlying distributional assumptions, estimation procedures, functional form of accident rate, and sensitivity to short road sections, are identified. Important issues, such as the treatment of vehicle exposure and traffic conditions, and data uncertainties due to sampling and nonsampling errors, are also discussed. Roadway and truck accident data from the Highway Safety Information System (HSIS), a highway safety data base administered by the Federal Highway Administration (FHWA), have been employed to illustrate the use and the limitations of these models. It is demonstrated that the conventional linear regression models lack the distributional property to describe adequately random, discrete, nonnegative, and typically sporadic vehicle accident events on the road. As a result, these models are not appropriate to make probabilistic statements about vehicle accidents, and the test statistics derived from these models are questionable. The Poisson regression models, on the other hand, possess most of the desirable statistical properties in developing the relationships. However, if the vehicle accident data are found to be significantly overdispersed relative to its mean, then using the Poisson regression models may overstate or understate the likelihood of vehicle accidents on the road. More general probability distributions may have to be considered.     

Establishing relationships between mechanical properties of aluminium alloys and optimised friction stir welding process parameters

Friction stir welding (FSW) is a solid state welding process for joining aluminium alloys and is employed in aerospace, rail, automotive and marine industries. In FSW, the base metal properties such as yield strength, hardness and ductility control the plastic flow of the material under the action of a rotating non-consumable tool. The FSW process parameters such as, the tool rotational speed, the welding speed and the axial force play a major role in deciding the weld quality. In this investigation, FSW joints were made using six different grades of aluminium alloys (AA1100, AA2219, AA2024, AA6061, AA7039, and AA7075) using different levels of process parameters. Macrostructural analysis was carried out to identify the feasible working range of process parameters. The optimal welding conditions to attain maximum strength for each alloy were identified using Response Surface Methodology (RSM). Empirical relationships were established between the base metal mechanical properties of aluminium alloys and optimised FSW process parameters. These relationships can be effectively used to predict the optimised FSW process parameters from the known base metal properties (yield strength, elongation and hardness).     

Estimating the number of accidents at intersections from a knowledge of the traffic flows on the approaches

The increase in the number of accidents at intersections, relative to non-junction accidents, may be explained by the basic fact that an increase in the number of vehicles on the road is generally accompanied by an increase in the number of collisions, which rise at a faster rate than single-vehicle accidents. Generally, more than 50% of the collisions occur at intersections. Data from a number of countries studied support the above statement and show that over the years, the number of intersection accidents has increased at a faster rate than other accidents. The study includes a statistical analysis of the general trends in the number of intersection accidents, their severity, and an analysis of types of accidents at intersections. A model was developed which enables the estimation of the expected number of accidents at individual intersections. It was found that vehicle exposure can be used as the basis for estimation. The exposure, denned as the number of occasions for accidents, was calculated through the sum of the products of flow at the 24 points where vehicle paths cross or merge. This measure of exposure, expressed as a traffic flow index, showed good correlation with the number of accidents. On the assumption that the number of accidents at an intersection, in a given time interval, is Poisson distributed, significance tests were made comparing the actual number of accidents with the expected according to the vehicle exposure index. Such comparisons are useful in the determination of accident “black spots”.     

Mortality from road traffic accidents in Switzerland: longitudinal and spatial analyses

Road traffic accidents (RTA) are an important cause of premature death. We examined socio-demographic and geographical determinants of RTA mortality in Switzerland by linking 2000 census data to RTA mortality records 2000–2005 (ICD-10 codes V00–V99). Data from 5.5 million residents aged 18–94 years, 1744 study areas, and 1620 RTA deaths were analyzed, including 978 deaths (60.4%) in motor vehicle occupants, 254 (15.7%) in motorcyclists, 107 (6.6%) in cyclists, and 259 (16.0%) in pedestrians. Weibull survival models and Bayesian methods were used to calculate hazard ratios (HR), and standardized mortality ratios (SMR) across study areas.Adjusted HR comparing women with men ranged from 0.04 (95% CI 0.02–0.07) in motorcyclists to 0.43 (95% CI 0.32–0.56) in pedestrians. There was a u-shaped relationship with age in motor vehicle occupants and motorcyclists. In cyclists and pedestrians, mortality increased after age 55 years. Mortality was higher in individuals with primary education (HR 1.53; 95% CI 1.29–1.81), and higher in single (HR 1.24; 95% CI 1.05–1.46), widowed (HR 1.31; 95% CI 1.05–1.65) and divorced individuals (HR 1.62; 95% CI 1.33–1.97), compared to persons with tertiary education or married persons. The association with education was particularly strong for pedestrians (HR 1.87; 95% CI 1.20–2.91). RTA mortality increased with decreasing population density of study areas for motor vehicle occupants (test for trend p < 0.0001) and motorcyclists (p = 0.0021) but not for cyclists (p = 0.39) or pedestrians (p = 0.29). SMR standardized for socio-demographic and geographical variables ranged from 82 to 190.Prevention efforts should aim to reduce inequities across socio-demographic and educational groups, and across geographical areas, with interventions targeted at high-risk groups and areas, and different traffic users, including pedestrians.     

ADHD and relative risk of accidents in road traffic: A meta-analysis

The present meta-analysis is based on 16 studies comprising 32 results. These studies provide sufficient data to estimate relative accident risks of drivers with ADHD. The overall estimate of relative risk for drivers with ADHD is 1.36 (95% CI: 1.18; 1.57) without control for exposure, 1.29 (1.12; 1.49) when correcting for publication bias, and 1.23 (1.04; 1.46) when controlling for exposure. A relative risk (RR) of 1.23 is exactly the same as found for drivers with cardiovascular diseases. The long-lasting assertion that “ADHD-drivers have an almost fourfold risk of accident compared to non-ADHD-drivers”, which originated from Barkley et al.’s study of 1993, is rebutted. That estimate was associated with comorbid Oppositional Defiant Disorder (ODD) and/or Conduct Disorder (CD), not with ADHD, but the assertion has incorrectly been maintained for two decades. The present study provides some support for the hypothesis that the relative accident risk of ADHD-drivers with comorbid ODD, CD and/or other conduct problems, is higher than that of ADHD-drivers without these comorbidities. The estimated RRs were 1.86 (1.27; 2.75) in a sample of ADHD-drivers in which a majority had comorbid ODD and/or CD compared to 1.31 (0.96; 1.81) in a sample of ADHD-drivers with no comorbidity. Given that ADHD-drivers most often seem to drive more than controls, and the fact that a majority of the present studies lack information about exposure, it seems more probable that the true RR is lower rather than higher than 1.23. Also the assertion that ADHD-drivers violate traffic laws more often than other drivers should be modified: ADHD-drivers do have more speeding violations, but no more drunk or reckless driving citations than drivers without ADHD. All accident studies included in the meta-analysis fail to acknowledge the distinction between deliberate violations and driving errors. The former are known to be associated with accidents, the latter are not. A hypothesis that ADHD-drivers speed more frequently than controls because it stimulates attention and reaction time is suggested.     

Disabilities caused by road traffic accidents and their relation to severity scores

The disabilities incurred by 2502 road accident patients admitted in three separate years to an Accident Hospital have been analysed. There were about equal numbers of disabled among pedestrians, motorcyclists and vehicle occupants. This corresponds to the high relative frequency and severity of injuries among motorcyclists. Most of the serious disabilities were caused by head or lower limb injuries. Different severities of disability were not closely correlated with Abbreviated Injury Scale (AIS), (ISS) or (PI) scores or with treatment periods but useful threshold values are described which separate groups with high and low rates of disability. For given severities of injury, disabilities were less severe among young casualties. Comparisons with other studies show rather wide variations in estimates of the incidence of slight disabilities. There is fair agreement with the present findings that serious disabilities occur in about 3% of inpatient hospital cases or in about 1% of total casualties.     

Overdispersion in modelling accidents on road sections and in empirical bayes estimation

In multivariate statistical models of road safety one usually finds that the accident counts are ‘overdispersed’. The extent of the overdispersion is itself subject to estimation. It is shown that the assumption one makes about the nature of overdispersion will affect the maximum likelihood estimates of model parameters. If one assumes that the same overdispersion parameter applies to all road sections in the data base, then, the maximum likelihood estimate of parameters will be unduly influenced by very short road sections and insufficiently influenced by long road sections. The same assumption about the overdispersion parameter also leads to an inconsistency when one estimates the safety of a road section by the Empirical Bayes method. A way to avoid both problems is to estimate an overdispersion parameter (φ) that applies to a unit length of road, and to set the overdispersion parameter for a road section of length L to φL. How this would change the estimates of regression parameters for road section models now in use requires examination. Safety estimation by the Empirical Bayes method is altered substantially.     

Speed, speed limits and road traffic accidents under free flow conditions

The relationship between various measures of traffic speed, under free flow conditions, and accident rate is investigated for two groups of sites, one in the Tyne and Wear county of the UK and the other in Bahrain. The effect of speed limits on traffic speed is estimated for both groups of sites. In Bahrain, there is statistically significant evidence of an association between mean speed and accident rate. In Tyne and Wear the statistical evidence is weaker, and points to a stronger relationship between accidents and the variability of traffic speeds. In both areas, there is an apparent decrease in accident rate if the percentage of heavy vehicles increases, with the speed distribution held constant. In both areas the effect of speed limits is to reduce the mean speed of traffic by at least one quarter. Higher speeds are associated with longer trips.     

The effect of road and environmental characteristics on pedestrian hit-and-run accidents in Ghana

The number of pedestrians who have died as a result of being hit by vehicles has increased in recent years, in addition to vehicle passenger deaths. Many pedestrians who were involved in road traffic accident died as a result of the driver leaving the pedestrian who was struck unattended at the scene of the accident. This paper seeks to determine the effect of road and environmental characteristics on pedestrian hit-and-run accidents in Ghana. Using pedestrian accident data extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana, a binary logit model was employed in the analysis. The results from the estimated model indicate that fatal accidents, unclear weather, nighttime conditions, and straight and flat road sections without medians and junctions significantly increase the likelihood that the vehicle driver will leave the scene after hitting a pedestrian. Thus, integrating median separation and speed humps into road design and construction and installing street lights will help to curb the problem of pedestrian hit-and-run accidents in Ghana.