Estimation of the severity of safety critical events

Today, various measures are used to estimate the severity of a traffic conflict. However, these measures are all limited to estimating the crash risk and do not include any estimates of the possible consequences of a potential crash. In accident analysis the estimated severity of the event is related to the outcome of the crash, such as injury levels. This article proposes a new method for estimating the severity of safety critical events based on both an estimate of crash risk and an estimate of possible consequence that, in addition to a measure of safety margins, takes vehicle mass as well as the relative speed of the involved road users into consideration. The article compares the estimated severity of 61 conflicts and 9 accidents of the proposed method with the traffic conflict technique.The results from the severity estimates of our proposed method show a significant difference in the severity levels of events involving vehicles with similar mass compared to critical events involving vehicles with dissimilar mass and events involving pedestrians. The proposed method gives the possibility to compare different conflicts, with regard to severity, with each other regardless of what type of conflict it is, e.g. intersection or rural road, or what kind of road users that are involved.In addition, an event classification, i.e. serious or very serious event, based on the severity estimate of the proposed method, shows promising results indicating that the severities are estimated in a homogenous way. The article concludes that our proposed method of estimating the severity of critical event seems to be able to reflect the dangerousness in a more realistic way than the traffic conflict technique and should facilitate the development of traffic safety analysis methods.     

Safety-in-numbers: Estimates based on a sample of pedestrian crossings in Norway

Safety-in-numbers denotes the tendency for the risk of accident for each road user to decline as the number of road users increases. Safety-in-numbers implies that a doubling of the number of road users will be associated with less than a doubling of the number of accidents. This paper investigates safety-in-numbers in 239 pedestrian crossings in Oslo and its suburbs. Accident prediction models were fitted by means of negative binomial regression. The models indicate a very strong safety-in-numbers effect. In the final model, the coefficients for traffic volume were 0.05 for motor vehicles, 0.07 for pedestrians and 0.12 for cyclists. The coefficient for motor vehicles implies that the number of accidents is almost independent of the number of motor vehicles. The safety-in-numbers effect found in this paper is stronger than reported in any other study dealing with safety-in-numbers. It should be noted that the model explained only 21% of the systematic variation in the number of accidents. It therefore cannot be ruled out that the results are influenced by omitted variable bias. Any such bias would, however, have to be very large to eliminate the safety-in-numbers effect.     

A conceptual framework for road safety and mobility applied to cycling safety

Scientific literature lacks a model which combines exposure to risk, risk, and the relationship between them. This paper presents a conceptual road safety framework comprising mutually interacting factors for exposure to risk resulting from travel behaviour (volumes, modal split, and distribution of traffic over time and space) and for risk (crash and injury risk). The framework's three determinants for travel behaviour are locations of activities; resistances (generalized transport costs); needs, opportunities, and abilities. Crash and injury risks are modelled by the three ‘safety pillars’: infrastructure, road users and the vehicles they use. Creating a link in the framework between risk and exposure is important because of the ‘non-linear relationship’ between them, i.e. risk tends to decrease as exposure increases. Furthermore, ‘perceived’ risk (a type of travel resistance) plays a role in mode choice, i.e. the perception that a certain type of vehicle is unsafe can be a deterrent to its use. This paper uses theories to explain how the elements in the model interact. Cycling is an area where governments typically have goals for both mobility and safety. To exemplify application of the model, the paper uses the framework to link research on cycling (safety) to land use and infrastructure. The model's value lies in its ability to identify potential consequences of measures and policies for both exposure and risk. This is important from a scientific perspective and for policy makers who often have objectives for both mobility and safety.     

Estimating the traffic safety effect of studded tires.

Swedish accident and exposure data from December 1989 to February 1990 are used to estimate the risk of involvement in an accident on a slippery road when using studded tires compared with the risk when driving with summer tires. Two methods have been used, one involving both accident and exposure data, the other using only accident data. Both methods give similar estimates, indicating that studded tires reduce the risk of involvement in slippery road accidents by 20%-50%.     

Overview of critical risk factors in Power-Two-Wheeler safety

Power-Two-Wheelers (PTWs) constitute a vulnerable class of road users with increased frequency and severity of accidents. The present paper focuses of the PTW accident risk factors and reviews existing literature with regard to the PTW drivers’ interactions with the automobile drivers, as well as interactions with infrastructure elements and weather conditions. Several critical risk factors are revealed with different levels of influence to PTW accident likelihood and severity. A broad classification based on the magnitude and the need for further research for each risk factor is proposed. The paper concludes by discussing the importance of dealing with accident configurations, the data quality and availability, methods implemented to model risk and exposure and risk identification which are critical for a thorough understanding of the determinants of PTW safety.     

Measuring accident risk exposure for pedestrians in different micro-environments

Pedestrians are mainly exposed to the risk of road accident when crossing a road in urban areas. Traditionally in the road safety field, the risk of accident for pedestrian is estimated as a rate of accident involvement per unit of time spent on the road network. The objective of this research is to develop an approach of accident risk based on the concept of risk exposure used in environmental epidemiology, such as in the case of exposure to pollutants. This type of indicator would be useful for comparing the effects of urban transportation policy scenarios on pedestrian safety. The first step is to create an indicator of pedestrians’ exposure, which is based on motorised vehicles’ “concentration” by lane and also takes account of traffic speed and time spent to cross. This is applied to two specific micro-environments: junctions and mid-block locations. A model of pedestrians’ crossing behaviour along a trip is then developed, based on a hierarchical choice between junctions and mid-block locations and taking account of origin and destination, traffic characteristics and pedestrian facilities. Finally, a complete framework is produced for modelling pedestrians’ exposure in the light of their crossing behaviour. The feasibility of this approach is demonstrated on an artificial network and a first set of results is obtained from the validation of the models in observational studies.     

Accident sequence precursor analyses for steam generator tube rupture events that actually occurred

Steam generator tube ruptures (SGTRs) at pressurized water reactors are identified as one of the risk significant events in the probabilistic risk assessment studies. In addition, operating experience indicates that SGTRs might result in complex transients, some of which involved additional anomalies such as the delayed recognition of event, resulting in the retarded isolation of the ruptured SG and/or failure to timely equalize the primary and secondary pressures. In order to identify the risk significant anomalies and to obtain generic insights useful for examining alternative mitigation measures for STGR, the present study systematically analyzed ten actual and one potential SGTR events using an accident sequence precursor model consistently. The analysis results show that the SGTR event involving the delayed identification of tube rupture or failure to timely depressurize the reactor could have a relatively high possibility of leading to core damage and would be a significant precursor, though the models and failure probabilities applied might be further examined. This implies the importance of improving the capability to detect SGTR and the operating procedures. It is also shown that some of the other anomalies observed would largely contribute to the possibility of core damage, which points out the need of examining alternative measures for recovering from such conditions.     

Scenario analysis of freight vehicle accident risks in Taiwan

This study develops a quantitative risk model by utilizing Generalized Linear Interactive Model (GLIM) to analyze the major freight vehicle accidents in Taiwan. Eight scenarios are established by interacting three categorical variables of driver ages, vehicle types and road types, each of which contains two levels. The database that consists of 2043 major accidents occurring between 1994 and 1998 in Taiwan is utilized to fit and calibrate the model parameters. The empirical results indicate that accident rates of freight vehicles in Taiwan were high in the scenarios involving trucks and non-freeway systems, while; accident consequences were severe in the scenarios involving mature drivers or non-freeway systems. Empirical evidences also show that there is no significant relationship between accident rates and accident consequences. This is to stress that safety studies that describe risk merely as accident rates rather than the combination of accident rates and consequences by definition might lead to biased risk perceptions. Finally, the study recommends using number of vehicle as an alternative of traffic exposure in commercial vehicle risk analysis. The merits of this would be that it is simple and thus reliable; meanwhile, the resulted risk that is termed as fatalities per vehicle could provide clear and direct policy implications for insurance practices and safety regulations.     

Quantifying safety benefit of winter road maintenance: Accident frequency modeling

This research presents a modeling approach to investigate the association of the accident frequency during a snow storm event with road surface conditions, visibility and other influencing factors controlling for traffic exposure. The results have the premise to be applied for evaluating different maintenance strategies using safety as a performance measure. As part of this approach, this research introduces a road surface condition index as a surrogate measure of the commonly used friction measure to capture different road surface conditions. Data from various data sources, such as weather, road condition observations, traffic counts and accidents, are integrated and used to test three event-based models including the Negative Binomial model, the generalized NB model and the zero inflated NB model. These models are compared for their capability to explain differences in accident frequencies between individual snow storms. It was found that the generalized NB model best fits the data, and is most capable of capturing heterogeneity other than excess zeros. Among the main results, it was found that the road surface condition index was statistically significant influencing the accident occurrence. This research is the first showing the empirical relationship between safety and road surface conditions at a disaggregate level (event-based), making it feasible to quantify the safety benefits of alternative maintenance goals and methods.     

Laws of accident causation

This paper suggests that the influence of a number of important risk factors on road accidents can be described in terms of a few highly general statistical regularities that determine the shape of the relationship between the risk factors and accident occurrence. The statistical regularities are referred to as "laws of accident causation". The following "laws" are proposed: Instances of all these laws, as well as a discussion of to how the laws can be tested empirically, are given. It is hoped that proposing a few basic mechanisms that can summarise the impact of a number of risk factors will stimulate research that may lead to a more general theory of accident causation.     

The impact of young drivers’ lifestyle on their road traffic accident risk in greater Athens area

Young drivers (18–24) both in Greece and elsewhere appear to have high rates of road traffic accidents. Many factors contribute to the creation of these high road traffic accidents rates. It has been suggested that lifestyle is an important one. The main objective of this study is to find out and clarify the (potential) relationship between young drivers’ lifestyle and the road traffic accident risk they face. Moreover, to examine if all the youngsters have the same elevated risk on the road or not. The sample consisted of 241 young Greek drivers of both sexes. The statistical analysis included factor analysis and logistic regression analysis. Through the principal component analysis a ten factor scale was created which included the basic lifestyle traits of young Greek drivers. The logistic regression analysis showed that the young drivers whose dominant lifestyle trait is alcohol consumption or drive without destination have high accident risk, while these whose dominant lifestyle trait is culture, face low accident risk. Furthermore, young drivers who are religious in one way or another seem to have low accident risk. Finally, some preliminary observations on how health promotion should be put into practice are discussed.     

A logical model for quantification of occupational risk

Functional block diagrams (FBDs) and their equivalent event trees are introduced as logical models in the quantification of occupational risks. Although a FBD is similar to an influence diagram or a belief network it provides a framework for introduction in a compact form of the logic of the model through the partition of the paths of the equivalent event tree. This is achieved by consideration of an overall event which has as outcomes the outmost consequences defining the risk under analysis. This event is decomposed into simpler events the outcome space of which is partitioned into subsets corresponding to the outcomes of the initial joint event. The simpler events can be further decomposed into simpler events creating a hierarchy where the events in a given level (parents) are decomposed to a number of simpler events (children) in the next level of the hierarchy. The partitioning of the outcome space is transferred from level to level through logical relationships corresponding to the logic of the model.Occupational risk is modeled trough a general FBD where the undesirable health consequence is decomposed to “dose” and “dose/response”; “dose” is decomposed to “center event” and “mitigation”; “center event” is decomposed to “initiating event” and “prevention”. This generic FBD can be transformed to activity—specific FBDs which together with their equivalent event trees are used to delineate the various accident sequences that might lead to injury or death consequences.The methodology and the associated algorithms have been computerized in a program with a graphical user interface (GUI) which allows the user to input the functional relationships between parent and children events, corresponding probabilities for events of the lowest level and obtain at the end the quantified corresponding simplified event tree.The methodology is demonstrated with an application to the risk of falling from a mobile ladder. This type of accidents has been analyzed as part of the Workgroup Occupational Risk Model (WORM) project in the Netherlands aiming at the development and quantification of models for a full range of potential risks from accidents in the workspace.     

Risk factors for injury accidents among moped and motorcycle riders

Objective

To study and quantify the effect of factors related to the riders of powered two-wheelers on the risk of injury accident involvement.

Methodology

Based on national data held by the police from 1996 to 2005, we conducted a case–control study with responsibility for the accident as the event of interest. We estimated the odds ratios for accident responsibility. Making the hypothesis that the non-responsible riders in the study are representative of all the riders on the road, we thus identified risk factors for being responsible for injury accidents. The studied factors are age, gender, helmet wearing, alcohol consumption, validity of the subject's driving licence and for how long it has been held, the trip purpose and the presence of a passenger on the vehicle. Moped and motorcycle riders are analyzed separately, adjusting for the main characteristics of the accident.

Results

For both moped and motorcycle riders, being male, not wearing a helmet, exceeding the legal limit for alcohol and travelling for leisure purposes increased the risk of accident involvement. The youngest and oldest users had a greater risk of accident involvement. The largest risk factor was alcohol, and we identified a dose–effect relationship between alcohol consumption and accident risk, with an estimated odds ratio of over 10 for motorcycle and moped riders with a BAC of 2 g/l or over. Among motorcycle users, riders without a licence had twice the risk of being involved in an accident than those holding a valid licence. However, the number of years the rider had held a licence reduced the risk of accident involvement. One difference between moped and motorcycle riders involved the presence of a passenger on the vehicle: while carrying a passenger increased the risk of being responsible for the accident among moped riders, it protected against this risk among motorcycle riders.

Conclusion

This analysis of responsibility has identified the major factors contributing to excess risk of injury accidents, some of which could be targeted by prevention programmes.     

Cross-analysis of hazmat road accidents using multiple databases

Road selection for hazardous materials transportation relies heavily on risk analysis. With risk being generally expressed as a product of the probability of occurrence and the expected consequence, one will understand that risk analysis is data intensive. However, various authors have noticed the lack of statistical reliability of hazmat accident databases due to the systematic underreporting of such events. Also, official accident databases alone are not always providing all the information required (economical impact, road conditions, etc.). In this paper, we attempt to integrate many data sources to analyze hazmat accidents in the province of Quebec, Canada. Databases on dangerous goods accidents, road accidents and work accidents were cross-analyzed. Results show that accidents can hardly be matched and that these databases suffer from underreporting. Police records seem to have better coverage than official records maintained by hazmat authorities. Serious accidents are missing from government's official databases (some involving deaths or major spills) even though their declaration is mandatory.     

To what extent can theory account for the findings of road safety evaluation studies?

This paper proposes a conceptual framework that can be used to assess to what extent the findings of road safety evaluation research make sense from a theoretical point of view. The effects of road safety measures are modelled as passing through two causal chains. One of these, termed the engineering effect, refers to the intended effects of a road safety measure on a set of risk factors related to accident occurrence or injury severity. The engineering effect of road safety measures is modelled in terms of nine basic risk factors, one or more of which any road safety measure needs to influence in order to have the intended effect on accidents or injuries. The other causal chain producing the effects of road safety measures is termed the behavioural effect, and refers to road user behavioural adaptations to road safety measures. The behavioural effect is related to the engineering effect, in the sense that certain properties of the engineering effect of a road safety measure influence the likelihood that behavioural adaptation will occur. The behavioural effect of a road safety measure is modelled in terms of six factors that influence the likelihood that behavioural adaptation will occur. The nine basic risk factors representing the engineering effect of a road safety measure, and the six factors influencing the likelihood of behavioural adaptation can be used as checklists in assessing whether or not the findings of road safety evaluation studies make sense from a theoretical point of view. At the current state of knowledge, a more stringent evaluation of the extent to which theory can explain the findings of road safety evaluation studies is, in most cases, not possible.     

Optimal use of warning signs in traffic

The aim of the paper is to develop a model of drivers’ behaviour particularly designed to analyse the safety and total driving cost implications of warning sign installations. One special feature of the model is that it makes a clear distinction between drivers’ perceived risk values at certain speeds and their respective objective values. When focusing on a certain stretch of road only, the paper concludes that warning signs will increase safety and probably reduce total objective driving costs; that is the sum of time costs and objective expected accident costs. Since drivers’ speed will reduce implying higher time costs per distance, the reduction in total objective driving costs will be lower than the reductions in accident costs. The analysis is then extended to comprise the whole road system and using warning signs prior to curves as an example. Besides the driving conditions in different curves, the analysis shows that the optimal number of signs is dependent on the road authorities’ objectives for road traffic and on how drivers form their risk perceptions. Generally speaking, simulations indicate that the safety and economic benefits of warning sign installation are not very high. When considering the whole road system, warning signs seem, however, to have a greater positive impact on total driving costs than on accident costs.     

Disaggregate model of highway accident occurrence using survival theory

The analysis of discrete accident data and aggregate exposure data frequently necessitates compromises that can obscure the relationship between accident occurrence and potential causal risk components. One way to overcome these difficulties is to develop a model of accident occurrence that includes accident and exposure data at a mathematically consistent disaggregate level. This paper describes the conceptual and mathematical development of such a model using principals of survival theory. The model predicts the probability of being involved in an accident at time t given that a vehicle has survived until that time. Several alternative functional forms are discussed including additive, proportional hazards and accelerated failure time models. Model estimation is discussed for the case in which both accident and nonaccident trips are included and for the case with only accident data. As formulated, the model has the distinct advantage of being able to consider accident and exposure data at a disaggregate level in an entirely consistent analytic framework. A conditional accident analysis is undertaken using truck accident data obtained from a major national carrier in the United States. Model results are interpretable and generally reasonable. Of particular interest is that segmenting accidents in several categories yields very different sets of significant parameters. Driver service hours seemed to most strongly effect accident risk: regularly scheduled drivers who take frequent trips are likely to have a reduced risk of an accident, particularly if they have a longer (greater than eight) number of hours off-duty just prior to a trip.     

Use of CCTV to determine road accident factors in urban areas

This paper sets out to assess whether there is a potential use for images collected through the increasingly ubiquitous use of CCTV cameras in urban areas as a means of increasing understanding of the causes of road traffic accidents. Information on causation and contributory factors is essential as a means of understanding why accidents occurred and how the occurrence of similar events may be prevented in the future. CCTV records of accidents could provide an independent perspective on an accident and have the potential to increase both the quality and quantity of information available to the safety researcher.

This study focuses on an area of central Leeds in the UK and shows that an existing CCTV camera system used for urban traffic management reasons has the potential to record around a quarter of the accidents which occur in the area, based on patterns of past occurrence. Most city centres in the UK will have similar camera systems set-up. By the introduction of additional strategically placed cameras and replacement of existing cameras with ones dedicated to accident recording, this figure could be increased substantially.

The paper also considers how effective cameras and video records will be as a means of identifying contributory factor information once an accident is recorded. The contributory factor classification used by a recently introduced system in Britain is assessed in terms of how visible each of the factors is likely to be on video and their relative frequency of occurrence. It is concluded that CCTV has a high potential to provide corroborative evidence about many of the most commonly occurring factors, and to throw further light on accident causation.