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At least 19 recordsLinked to original sources
PubMed2002

An alternative accident prediction model for highway-rail interfaces.

Safety levels at highway/rail interfaces continue to be of major concern despite an ever-increasing focus on improved design and appurtenance application practices. Despite the encouraging trend towards improved safety, accident frequencies remain high, many of which result in fatalities. More than half of these accidents occur at public crossings, where active warning devices (i.e. gates, lights, bells, etc.) are in place and functioning properly. This phenomenon speaks directly to the need to re-examine both safety evaluation (i.e. accident prediction) methods and design practices at highway-rail crossings. With respect to earlier developed accident prediction methods, the Peabody Dimmick Formula, the New Hampshire Index and the National Cooperative Highway Research Program (NCHRP) Hazard Index, all lack descriptive capabilities due to their limited number of explanatory variables. Further, each has unique limitations that are detailed in this paper. The US Department of Transportation's (USDOT) Accident Prediction Formula, which is most widely, also has limitations related to the complexity of the three-stage formula and its decline in accident prediction model accuracy over time. This investigation resulted in the development of an alternate highway-rail crossing accident prediction model, using negative binomial regression that shows great promise. The benefit to be gained through the application of this alternate model is (1) a greatly simplified, one-step estimation process; (2) comparable supporting data requirements and (3) interpretation of both the magnitude and direction of the effect of the factors found to significantly influence highway-rail crossing accident frequencies.

Accidents, Traffic↗
PubMed2006

Temporal transferability and updating of zonal level accident prediction models.

This paper examines the temporal transferability of the zonal accident prediction models by using appropriate evaluation measures of predictive performance to assess whether the relationship between the dependent and independent variables holds reasonably well across time. The two temporal contexts are the years 1996 and 2001, with updated 1996 models being used to predict 2001 accidents in each traffic zone of the City of Toronto. The paper examines alternative updating methods for temporal transfer by imagining that only a sample of 2001 data is available. The sensitivity of the performance of the updated models to the 2001 sample size is explored. The updating procedures examined include the Bayesian updating approach and the application of calibration factors to the 1996 models. Models calibrated for the 2001 samples were also explored, but were found to be inadequate. The results show that the models are not transferable in a strict statistical sense. However, relative measures of transferability indicate that the transferred models yield useful information in the application context. Also, it is concluded that the updated accident models using the calibration factors produce better results for predicting the number of accidents in the year 2001 than using the Bayesian approach.

Accidents, Traffic↗
PubMed2004

Sources of error in road safety scheme evaluation: a method to deal with outdated accident prediction models.

This paper considers the errors that arise in using outdated accident prediction models in road safety scheme evaluation. Methods to correct for regression-to-mean (RTM) effects in scheme evaluation normally rely on the use of accident prediction models. However, because accident risk tends to decline over time, such models tend to become outdated and the estimated treatment effect is then exaggerated. A new correction procedure is described which can effectively eliminate such errors.

Accidents, Traffic↗
PubMed1996

Accident prediction models for roads with minor junctions.

The purpose of this study was to develop and validate a method for predicting expected accidents on main roads with minor junctions where traffic counts on the minor approaches are not available. The study was based on data for some 3800 km of highway in the U.K. including more than 5000 minor junctions. The highways consisted of both single and dual-carriageway roads in urban and rural areas. Generalized linear modelling was used to develop regression estimates of expected accidents for six highway categories and an empirical Bayes procedure was used to improve these estimates by combining them with accident counts. Accidents on highway sections were shown to be a non-linear function of exposure and minor junction frequency. For the purposes of estimating expected accidents, while the regression model estimates were shown to be preferable to accident counts, the best results were obtained using the empirical Bayes method. The latter was the only method that produced unbiased estimates of expected accidents for high-risk sites.

Accidents, Traffic↗
PubMed2003

Accident prediction models for urban roads.

This paper describes some of the main findings from two separate studies on accident prediction models for urban junctions and urban road links described in [Uheldsmodel for bygader-Del1: Modeller for 3-og 4-benede kryds. Notat 22, The Danish Road Directorate, 1995; Uheldsmodel for bygader- Del2: Modeller for straekninger. Notat 59, The Danish Road Directorate, 1998] (Greibe and Hemdorff, 1995, 1988). The main objective for the studies was to establish simple, practicable accident models that can predict the expected number of accidents at urban junctions and road links as accurately as possible. The models can be used to identify factors affecting road safety and in relation to 'black spot' identification and network safety analysis undertaken by local road authorities. The accident prediction models are based on data from 1036 junctions and 142 km road links in urban areas. Generalised linear modelling techniques were used to relate accident frequencies to explanatory variables. The estimated accident prediction models for road links were capable of describing more than 60% of the systematic variation ('percentage-explained' value) while the models for junctions had lower values. This indicates that modelling accidents for road links is less complicated than for junctions, probably due to a more uniform accident pattern and a simpler traffic flow exposure or due to lack of adequate explanatory variables for junctions. Explanatory variables describing road design and road geometry proved to be significant for road link models but less important in junction models. The most powerful variable for all models was motor vehicle traffic flow.

Accidents, Traffic↗
PubMed2006

Sensitivity analysis of an accident prediction model by the fractional factorial method.

Sensitivity analysis of a model can help us determine relative effects of model parameters on model results. In this study, the sensitivity of the accident prediction model proposed by Zegeer et al. [Zegeer, C.V., Reinfurt, D., Hummer, J., Herf, L., Hunter, W., 1987. Safety Effect of Cross-section Design for Two-lane Roads, vols. 1-2. Report FHWA-RD-87/008 and 009 Federal Highway Administration, Department of Transportation, USA] to its parameters was investigated by the fractional factorial analysis method. The reason for selecting this particular model is that it incorporates both traffic and road geometry parameters besides terrain characteristics. The evaluation of sensitivity analysis indicated that average daily traffic (ADT), lane width (W), width of paved shoulder (PA), median (H) and their interactions (i.e., ADT-W, ADT-PA and ADT-H) have significant effects on number of accidents. Based on the absolute value of parameter effects at the three- and two-standard deviation thresholds ADT was found to be of primary importance, while the remaining identified parameters seemed to be of secondary importance. This agrees with the fact that ADT is among the most effective parameters to determine road geometry and therefore, it is directly related to number of accidents. Overall, the fractional factorial method was found to be an efficient tool to examine the relative importance of the selected accident prediction model parameters.

Accidents, Traffic↗
PubMed1996

A comprehensive methodology for the fitting of predictive accident models.

Recent years have seen considerable progress in techniques for establishing relationships between accidents, flows and road or junction geometry. It is becoming increasingly recognized that the technique of generalized linear models (GLMs) offers the most appropriate and soundly-based approach for the analysis of these data. These models have been successfully used in the series of major junction accident studies carried out over the last decade by the U.K. Transport Research Laboratory (TRL). This paper describes the form of the TRL studies and the model-fitting procedures used, and gives examples of the models which have been developed. The paper also describes various technical problems which needed to be addressed in order to ensure that the application of GLMs would produce robust and reliable results. These issues included: the low mean value problem, overdispersion, the disaggregation of data over time, allowing for the presence of a trend over time in accident risk, random errors in the flow estimates, the estimation of prediction uncertainty, correlations between predictions for different accident types, and the combination of model predictions with site observations. Each of these problems has been tackled by extending or modifying the basic GLM methodology. The material described in the paper, then, constitutes a comprehensive methodology for the development of predictive accident models.

Accidents, Traffic↗
PubMed1993

Models for predicting accidents at junctions where pedestrians and cyclists are involved. How well do they fit?

The coefficient of determination, R2, i.e. the squared correlation coefficient between observed and fitted values, is often used as a measure of how well a model predicts the number of accidents at road junctions, for instance. The purpose of this article is to show that the R2 values obtained in different studies are rarely comparable with each other and that a prediction model can be "nearly perfect" even if the coefficient of determination is small. Another purpose of the article is to present some results of interest from a practical viewpoint in regard to accidents where pedestrians and cyclists are involved. Empirical R2 values for models predicting accidents at junctions where pedestrians or cyclists are involved are compared with the maximal R2 values that could possibly be obtained. The latter can be calculated both theoretically and with the aid of simulation. How the maximal R2 value depends on the average accident level and the relative dispersion of the expected values for the studied junctions is also shown theoretically. The results obtained show how difficult it can be to determine whether and how far the number of accidents is influenced by additional factors, over and above the traffic flows, which describe the design in greater detail.

Accidents, Traffic↗
PubMed1976

Predicting accident frequency in children.

The concept of "accident proneness" is frequently discussed and rarely documented. We predicted that children who take more risks as judged by their behavior in gym class, or who have more stressful life changes as determined by their score on a Social Readjustment Rating Questionnaire (SRRQ), would be more likely to injure themselves. 103 junior high school boys were rated for these factors, and then followed for injuries by weekly telephone calls for five months. Boys having high SRRQ scores had significantly more accidents than those with low scores; risk-taking levels were not predictive. In this study, children undergoing stressful changes in their lives were more susceptible to accidents.

Accident Proneness↗
PubMed2005

Accident prediction model for railway-highway interfaces.

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.

Accidents↗
PubMed1996

Predicting accidents at work with measures of locus of control and job hazards.

This study was conducted to assess the predictive ability of measures of locus of control and job hazards in involvement in accidents in the workplace. The locus of control scale consisted of 24 items while the job hazards were a measure of the probability of no involvement in an accident. A logistic regression model was 89% accurate in classifying subjects by involvement in an accident as measured by workers' compensation claims.

Accidents, Occupational↗
PubMed1989

Suicide? Accident? Predictable? Avoidable? The psychological autopsy in jail suicides.

The psychological autopsy is a timely adjunct to the suicide detection and prevention efforts emerging in many jails. These efforts can only be enhanced by a thorough review of what went right or wrong for a particular inmate. Conducted in a nonthreatening spirit of peer review, the psychological autopsy can provide staff with closure and new knowledge which will allow them to proceed more effectively and confidently in safeguarding other inmates.

Cause of Death↗
PubMed1997

The Chernobyl accident: predicting cardio-vascular disease in the ex-workers.

This paper describes a computer package that has been used to predict the likelihood of the onset of cardiovascular diseases in these patients who were former workers (liquidators) on the Chernobyl site in the Ukraine, Chernobyl being the place where the Nuclear Power Station was destroyed when the atomic reactor got out of control and spread radiation over a very wide area both on the ground and into the atmosphere. The programme predicts the future morbidity in those patients with an accuracy of 90%.

Adult↗
PubMed2004

Prediction of accidents at full green and green arrow traffic lights in Switzerland with the aid of configuration-specific features.

In this study it was endeavored to predict full green and green arrow accidents at traffic lights, using configuration-specific features. This was done using the statistical method known as Poisson regression. A total of 45 sets of traffic lights (criteria: in an urban area, with four approach roads) with 178 approach roads were investigated (the data from two approach roads was unable to be used). Configuration-specific features were surveyed on all approach roads (characteristics of traffic lanes, road signs, traffic lights, etc.), traffic monitored and accidents (full green and green arrow) recorded over a period of 5 consecutive years. It was demonstrated that only between 23 and 34% of variance could be explained with the models predicting both types of accidents. In green arrow accidents, the approach road topography was found to be the major contributory factor to an accident: if the approach road slopes downwards, the risk of a green arrow accident is approximately five and a half times greater (relative risk, RR = 5.56) than on a level or upward sloping approach road. With full green accidents, obstructed vision plays the major role: where vision can be obstructed by vehicles turning off, the accident risk is eight times greater (RR = 8.08) than where no comparable obstructed vision is possible. From the study it emerges that technical features of traffic lights are not able to control a driver's actions in such a way as to eradicate error. Other factors, in particular the personal characteristics of the driver (age, sex, etc.) and accident circumstances (lighting, road conditions, etc.), are likely to make an important contribution to explaining how an accident occurs.

Accidents, Traffic↗
PubMedDate not supplied

Mechanisms of motor vehicle accidents that predict major injury.

OBJECTIVE: To assess whether prehospital triage guidelines, based on mechanistic criteria alone, accurately identify victims of motor vehicle accidents (MVA) with major injury. METHODS: Retrospective analysis of the Royal Melbourne Hospital trauma database. Mechanisms analysed were those outlined by the American College of Surgeons Committee on Trauma and Advanced Trauma Life Support/Early Management of Severe Trauma prehospital triage guidelines. RESULTS: There were 621 MVA analysed, 253 with major injury (40.7%). Multivariate logistic regression indicated prolonged extrication time (P < 0.0001), cabin intrusion (P = 0.047), high speed (P = 0.003) and ejection from vehicle (P = 0.04) were statistically associated with major injury. Vehicle rollover and fatality in the same vehicle were not statistically associated with major injury. CONCLUSIONS: These data suggest that existing guidelines for the prehospital triage of MVA victims, based on mechanistic criteria alone may need revision.

Accidents, Traffic↗
PubMed1992

The OPQ: a proposed instrument for predicting poisoning accident recurrence in young children.

A 26-item self-report questionnaire for parents/guardians was constructed for potential use with first-exposure childhood poisoning victims to predict high risk for subsequent poisoning episodes. Data were obtained from 185 subjects served by 1 of 5 US regional poison control centers. The resulting device was labeled the OPQ. Its retrospective validity (R = 0.71) and test-retest reliability (0.81) are viewed as sufficient. The test itself, with accompanying scoring key and norms, are provided here in the hope that other clinicians and researchers will join in subjecting the OPQ to prospective validity studies and other forms of Scale refinement.

Child, Preschool↗
PubMed2004

Models relating traffic safety with road environment and traffic flows on arterial roads in Addis Ababa.

This paper presents the study carried out to develop accident predictive models based on the data collected on arterial roads in Addis Ababa. Poisson and negative binomial regression methods were used to relate the discrete accident data with the road and traffic flow explanatory variables. Significant accident predictive models were found with a number of significant explanatory variables. The results show that the existing inadequate road infrastructure and poor road traffic operations are the potential contributors of this ever-growing challenge of the road transport in Addis Ababa. The results also indicate that improvements in roadway width, pedestrian facilities, and access management are effective in reducing road traffic accidents.

Accidents, Traffic↗