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.     

The impact of climate change on winter road maintenance and traffic accidents in West Midlands, UK

Winter weather can be a significant cause of road traffic accidents. This paper uses UKCIP climate change scenarios and a temporal analogue to investigate the relationship between temperature and severe road accidents in the West Midlands, UK. This approach also allows quantification of the changes in the severity of the winter season over the next century in the region. It is demonstrated that the predicted reduction in the number of frost days should in turn reduce the number of road accidents caused due to slipperiness by approximately 50%. However, the paper concludes by warning against complacency in winter maintenance regimes. A warmer climate may result in budget cuts for highway maintenance which in turn may well reverse declining accident trends.     

A spatially disaggregate analysis of road casualties in England

Spatially disaggregate ward level data for England is used in an analysis of various area-wide factors on road casualties. Data on 8414 wards was input into a geographic information system that contained data on land use types, road characteristics and road casualties. Demographic data on area-wide deprivation (the index of multiple deprivation) for each ward was also included. Negative binomial count data models were used to analyze the associations between these factors with traffic fatalities, serious injuries and slight injuries. Results suggest that urbanized areas are associated with fewer casualties (especially fatalities) while areas of higher employment density are associated with more casualties. More deprived areas tend to have higher levels of casualties, though not of motorized casualties (except slight injuries). The effect of road characteristics are less significant but there are some positive associations with the density of “A” and “B” level roads.     

A full history proportional hazards model for preventive maintenance scheduling

This paper is concerned with the development of a realistic preventive maintenance (PM) scheduling model. A heuristic approach for implementing the semi-parametric proportional-hazards model (PHM) to schedule the next preventive maintenance interval on the basis of the equipment's full condition history is introduced. This heuristic can be used with repairable systems and does not require the unrealistic assumption of renewal during repair, or even during PM. Two PHMs are fitted, for the life of equipment following corrective work and the life of equipment following PM, using appropriate explanatory variables. These models are then used within a simulation framework to schedule the next preventive maintenance interval. Optimal PM schedules are estimated using two different criteria, namely maximizing availability over a single PM interval and over a fixed horizon. History data from a set of four pumps operating in a continuous process industry is also used to demonstrate the proposed approach. The results indicate a higher availability for the recommended schedule than the availability resulting from applying the optimal PM intervals as suggested by using the conventional stationary models. © 1997 John Wiley & Sons, Ltd.     

Probabilistic safety assessment support for the maintenance rule at Duke Power Company

The Nuclear Regulatory Commission (NRC) published the Maintenance Rule on July 10, 1991 with an implementation date of July 10, 1996 [1]. Maintenance rule implementation at the Duke Power Company has used probabilistic safety assessment (PSA) insights to help focus the monitoring of structures, systems and components (SSC) performance and to ensure that maintenance is effectively performed. This paper describes how the probabilistic risk assessment (PRA)¹ group at the Duke Power Company provides support for the maintenance rule by performing the following tasks: (1) providing a member of the expert panel; (2) determining the risk-significant SSCs; (3) establishing SSC performance criteria for availability and reliability; (4) evaluating past performance and its impact on core damage risk as part of the periodic assessment; (5) providing input to the PRA matrix; (6) providing risk analyses of combinations of SSCs out of service; (7) providing support for the SENTINEL program; and (8) providing support for PSA training. These tasks are not simply tied to the initial implementation of the rule. The maintenance rule must be kept consistent with the current design and operation of the plant. This will require that the PRA models and the many PSA calculations performed to support the maintenance rule are kept up-to-date. Therefore, support of the maintenance rule will be one of the primary roles of the PSA group for the remainder of the life of the plant.     

Parents’ perceptions of the family climate for road safety

The current study examined the applicability of the Family Climate for Road Safety Scale (FCRSS; Taubman-Ben-Ari and Katz-Ben-Ami, 2013) to the parents of young drivers. The sample consisted of 549 parents and 234 of their children, all of whom completed the FCRSS. In addition, the parents completed the multidimensional driving style inventory (MDSI; Taubman-Ben-Ari et al., 2004) and provided background data (e.g., age, gender). Confirmatory factor analysis supported a slightly modified structure of the scale for parents. Examination of the correlations revealed significant weak to strong associations between parents’ scores on the various FCRSS dimensions on the one hand, and their self-reported driving styles and offspring’s perceptions of the family climate for safety on the other. The findings indicate that the FCRSS is suitable for use with the parents of young drivers, and that perceptions of the family climate are shared by the two generations. Furthermore, they show that family climate is related to parents’ customary driving behavior, with the careful driving style positively related to the positive dimensions of the FCRSS. The discussion stresses the importance of the parents’ influence on the manner in which their children drive, and the multifaceted nature of this influence. Moreover, it indicates the potential value of the FCRSS, both for research and for designing interventions and measuring their effectiveness.     

Modelling the effects of road traffic safety measures

A model is presented for assessing the effects of traffic safety measures, based on a breakdown of the process in underlying components of traffic safety (risk and consequence), and five (speed and conflict related) variables that influence these components, and are influenced by traffic safety measures. The relationships between measures, variables and components are modelled as coefficients. The focus is on probabilities rather than historical statistics, although in practice statistics may be needed to find values for the coefficients. The model may in general contribute to improve insight in the mechanisms between traffic safety measures and their safety effects. More specifically it allows comparative analysis of different types of measures by defining an effectiveness index, based on the coefficients. This index can be used to estimate absolute effects of advanced driver assistance systems (ADAS) related measures from absolute effects of substitutional (in terms of safety effects) infrastructure measures.     

Proposal for territorial distribution of the 2010 EU road safety target

European Union (EU) road safety policies include reduction in road fatalities by 50% during 2000–2010. The original territorial distribution of this target is uniform, as all the territories have to halve the number of fatalities regardless of their previous record.We propose a simple method of distributing the total effort required to reach the EU target of halving fatalities in a territory in such a way that those areas with a higher proportion of fatalities (relative to their populations) have the highest targets and the sum of all of the areas is the 50% reduction. The distribution function we use here is based on an inverse logarithmic function selected from among several alternative functions analyzed in an initial study. This use of weighted distribution functions has been applied since 2000 by the EU in other policies, such as the use of renewable energies.We applied the proposed distribution function to two territorial aggregation levels in the EUROSTAT Nomenclature of Territorial Units for Statistics (NUTS): NUTS0 for EU-15 and EU-25 Member States, and NUTS3 for the 50 Spanish provinces, comparing the new and old targets with the real achievements for the 2000–2006 period, and new and old targets for the 2000–2010 period.This is a simple proposal for modification of target distribution that can be further improved using other parameters, such as road or weather conditions.     

The use of maintenance indicators to evaluate the effects of maintenance programs on NPP performance and safety

Nuclear Power Plants (NPPs) under commercial operation are under continuous demand to meet higher levels of performance and safety by NPP owners, regulatory authorities and the public in general. Maintenance plays an important role in achieving such a goal, therefore, many programs are being conducted in order to improve their effectiveness. A common link between these programs is the necessity to evaluate how maintenance affects NPP performance and safety. This paper presents the foundation of a methodology for a maintenance evaluation program based on maintenance indicators and how it is applied to monitoring the effectiveness of the maintenance at the Cofrentes NPP. The methodology is general and might be applied in other fields of industrial engineering, particularly in those activities which devote many resources to maintain plant equipment, and also in those with less but very critical maintenance.     

A tool for safety evaluations of road improvements

Road safety impact assessments are requested in general, and the directive on road infrastructure safety management makes them compulsory for Member States of the European Union. However, there is no widely used, science-based safety evaluation tool available. We demonstrate a safety evaluation tool called TARVA. It uses EB safety predictions as the basis for selecting locations for implementing road-safety improvements and provides estimates of safety benefits of selected improvements. Comparing different road accident prediction methods, we demonstrate that the most accurate estimates are produced by EB models, followed by simple accident prediction models, the same average number of accidents for every entity and accident record only. Consequently, advanced model-based estimates should be used. Furthermore, we demonstrate regional comparisons that benefit substantially from such tools. Comparisons between districts have revealed significant differences. However, comparisons like these produce useful improvement ideas only after taking into account the differences in road characteristics between areas. Estimates on crash modification factors can be transferred from other countries but their benefit is greatly limited if the number of target accidents is not properly predicted. Our experience suggests that making predictions and evaluations using the same principle and tools will remarkably improve the quality and comparability of safety estimations.     

Simulation of crash tests for high containment levels of road safety barriers

This paper presents the results of computer simulations of road safety barrier behaviour under vehicle crash conditions for high containment levels as mandated by the European standard EN 1317. Simulations were performed with the explicit finite element code LS-DYNA, running on a multiprocessor computational platform. A very good agreement of simulation and real crash tests results was observed, which in turn justifies the use of computer simulations in the process of development and certification of road safety barriers.     

A Bayesian model for the joint optimization of quality and maintenance decisions

We develop a model for the economic design of a Bayesian control chart for monitoring a process mean. The process may randomly suffer failures that result in a non‐operating state, and thus call for an immediate corrective maintenance action, as well as assignable causes that shift the process mean to an undesirable level. Quality shifts, apart from poorer quality outcome and higher operational cost, also result in higher failure rate. Consequently, their removal, besides improving the outcome quality and reducing the quality‐related cost, is also a preventive maintenance action since it reduces the probability of a failure. The proposed Bayesian model allows the determination of the design parameters that minimize the total expected quality and maintenance cost per time unit. The effectiveness of the proposed model is evaluated through the comparison of its expected cost against the optimum expected cost of the simpler variable‐parameter Shewhart chart. Copyright © 2010 John Wiley & Sons, Ltd.     

On statistical inference in time series analysis of the evolution of road safety

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research.     

An exploratory analysis of models for estimating the combined effects of road safety measures

Road safety programmes consisting of a large number of road safety measures have been developed in many countries. To estimate the effects of such programmes on the number of accidents, models for estimating the combined effects of road safety measures are needed. This paper presents an exploratory analysis of such models. There is very little empirical evidence to support model building. Based on a few studies that have evaluated the effects of multiple road safety measures introduced at the same locations, the paper compares two models. One of the models, the common residuals model, assumes that the (percentage) effect of a road safety measure remains unchanged when it is combined with other road safety measures. The other model, the dominant common residuals model, assumes that the most effective measure in a set of measures has a dominant effect that weakens the effects of other road safety measures it is combined with. Evidence from the few studies that were found is consistent with both these models. A study of the effects of a road safety programme implemented in Victoria, Australia between 1990 and 1996 indicated that the effects of safety measures are weakened when these measures are combined with other road safety measures.     

市政养护施工围栏对安全驾驶的实验研究

目的:近几年随着社会经济的发展,市政养护作业增加,而市政养护部门缺少相关的规范和标准,这造成了养护工作无法有效地正常进行。本研究试图从道路使用者对福州市市政维护的满意程度以及整体状况展开实验调查,为中国的道路养护维修提供有效的客观数据。方法:本研究招募私家车,出租车和公交车司机对市政养护的实际驾驶情景中遇到围栏做出减速、变道的反应时,对围栏的总体满意度以及围栏是否影响驾驶行为等方面进行研究,采用E-prime软件采集数据,结果:发现私家车在遇到施工围栏的减速和变道反应快于出租车和公交车;所有车型司机对于施工作业围栏的满意度只有57%;公交车司机的危险性失误行为低于另外两个车型司机。结论:市政养护施工作业对不同道路使用者的安全驾驶行为产生一定影响。     

A support tool for identifying evaluation issues of road safety measures

The introduction of new technologies in traffic produces a range of unknown deviations in the desired traffic process. These developments require additional ex-ante assessment procedures for measures which will be implemented in the traffic system. In this paper, the HAZOP methodology is applied to road traffic measures to provide scenarios based upon predicted deviations and problems with new, mainly in-vehicle technologies. To make HAZOP applicable for road safety purposes analysis of the expectations of road users is added to the traditional approach. In this paper, some results are shown for speed reduction measures. The dependency of the results on the membership of the HAZOP team and especially the question if a mixture of expertise is required are also discussed.     

The likelihood of achieving quantified road safety targets: A binary logistic regression model for possible factors

In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors – including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target – that contribute to a target’s success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed.     

Simulation of safety: A review of the state of the art in road safety simulation modelling

Recent decades have seen considerable growth in computer capabilities, data collection technology and communication mediums. This growth has had considerable impact on our ability to replicate driver behaviour and understand the processes involved in failures in the traffic system. From time to time it is necessary to assess the level of development as a basis of determining how far we have come. This paper sets out to assess the state of the art in the use of computer models to simulate and assess the level of safety in existing and future traffic systems. It reviews developments in the area of road safety simulation models. In particular, it reviews computer models of driver and vehicle behaviour within a road context. It focuses on stochastic numerical models of traffic behaviour and how reliable these are in estimating levels of safety on the traffic network. Models of this type are commonly used in the assessment of traffic systems for capacity, delay and general performance. Adding safety to this assessment regime may allow more comprehensive assessment of future traffic systems. To date the models have focused primarily on vehicular traffic that is, cars and heavy vehicles. It has been shown that these models have potential in measuring the level of conflict on parts of the network and the measure of conflict correlated well with crash statistics. Interest in the prediction of crashes and crash severity is growing and new models are focusing on the continuum of general traffic conditions, conflict, severe conflict, crash and severe crashes. The paper also explores the general data types used to develop, calibrate and validate these models. Recent technological development in in-vehicle data collection, driver simulators and machine learning offers considerable potential for improving the behavioural base, rigour and application of road safety simulation models. The paper closes with some indication of areas of future development.     

Pedestrian behavior and safety on a two-stage crossing with a center refuge island and the effect of winter weather on pedestrian compliance rate

Despite a burgeoning research effort directed at understanding the effects of age, gender, disability, group size, traffic control condition and street width on pedestrian safety and compliance rate as they cross a signalized intersection, remarkably little is known about the compliance rate at a signal controlled two-stage crossing and how pedestrians react to different weather conditions. The purpose of this study was to determine whether pedestrian behavior becomes more risky in inclement weather through the investigation of street crossing behavior and compliance under different weather and road surface conditions at a busy two-stage crossing. Road crossing behavior was filmed at one eight-lane divided road strip at a downtown site in Toronto metropolitan area. The intersection was filmed unobtrusively from a rooftop by one camera set to record both oncoming near-side traffic and pedestrian movements. Pedestrian behavior and compliance rate were scored for a number of determinants of safe road crossing actions. Overall, the results show that road crossing behavior in inclement weather conditions was less safe than in fine weather. The designs of signal timing and configuration of the center refuge island also adversely influenced pedestrian behavior at this crossing, and adverse weather conditions further exacerbated the noncompliance rate. This paper presents new information on compliance rate at a two-stage crossing that emphasizes the need to consider the influence of traffic signal design and weather conditions on pedestrians’ behavior. More studies are needed to develop traffic control techniques to allow pedestrians to cross wide two-stage crossings in safety.     

A review of the effect of traffic and weather characteristics on road safety

Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research.