The effects of roundabouts on traffic safety for bicyclists: an observational study

A before-and-after study was carried out of injury accidents involving bicyclists on 91 roundabouts in Flanders-Belgium. The study design accounted for the effects of general safety trends and regression-to-the-mean, but could not take into account the possibility of specific changes in traffic volume at roundabouts. The conversion of intersections into roundabouts produces a significant 27% increase in the number of injury accidents involving bicyclists on or nearby the roundabouts. The increase is even higher for accidents involving fatal or serious injuries (41-46%). Compared to the proven favourable effects of roundabouts on safety in general, this result is unexpectedly poor. However, the effects of roundabouts on bicycle accidents differ depending on whether these roundabouts are built inside or outside built-up areas. When inside built-up areas, the construction of roundabouts increased the number of injury accidents involving bicyclists by 48%. For accidents causing fatal or serious injuries inside built-up areas, an average increase of 77% was found. However, outside built-up areas the zero-hypothesis of 'no safety effect for bicyclists' cannot be rejected (best estimate: +1% accidents, not significant). Roundabouts that replace traffic signals perform worse when compared to roundabouts at other types of intersections.     

How the choice of safety performance function affects the identification of important crash prediction variables

Across the nation, researchers and transportation engineers are developing safety performance functions (SPFs) to predict crash rates and develop crash modification factors to improve traffic safety at roadway segments and intersections. Generalized linear models (GLMs), such as Poisson or negative binomial regression, are most commonly used to develop SPFs with annual average daily traffic as the primary roadway characteristic to predict crashes. However, while more complex to interpret, data mining models such as boosted regression trees have improved upon GLMs crash prediction performance due to their ability to handle more data characteristics, accommodate non-linearities, and include interaction effects between the characteristics.An intersection data inventory of 36 safety relevant parameters for three- and four-legged non-signalized intersections along state routes in Alabama was used to study the importance of intersection characteristics on crash rate and the interaction effects between key characteristics. Four different SPFs were investigated and compared: Poisson regression, negative binomial regression, regularized generalized linear model, and boosted regression trees. The models did not agree on which intersection characteristics were most related to the crash rate. The boosted regression tree model significantly outperformed the other models and identified several intersection characteristics as having strong interaction effects.     

Causation mechanisms in car-to-vulnerable road user crashes: Implications for active safety systems

Vulnerable road users (VRUs), such as pedestrians and bicyclists, are often involved in crashes with passenger cars. One way to prevent these crashes is to deploy active safety systems that support the car drivers and/or VRUs. However, to develop such systems, a thorough understanding of crash causation mechanisms is required. The aim of this study is to identify crash causation mechanisms from the perspective of the VRUs, and to explore the implications of these mechanisms for the development of active safety systems. Data originate from the European project SafetyNet, where 995 crashes were in-depth investigated using the SafetyNet Accident Causation System (SNACS). To limit the scope, this study analyzed only intersection crashes involving VRUs. A total of 56 VRU crashes were aggregated. Results suggest that, while 30% of the VRUs did not see the conflict car due to visual obstructions in the traffic environment, 70% of the VRUs saw the car before the collision, but still misunderstood the traffic situation and/or made an inadequate plan of action. An important implication that follows from this is that, while detection of cars is clearly an issue that needs to be addressed, it is even more important to help the VRUs to correctly understand traffic situation (e.g., does the driver intend to slow down, and if s/he does, is it to let the VRU cross or for some other reason?). The former issue suggests a role for various cooperative active safety systems, as the obstacles are generally impenetrable with regular sensors. The latter issue is less straightforward. While various systems can be proposed, such as providing gap size estimation and reducing the car speed variability, the functional merits of each such a system need to be further investigated.     

Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway

While rural freeways generally have lower crash rates, interactions between driver behavior, traffic and geometric characteristics, and adverse weather conditions may increase the crash risk along some freeway sections. This paper examines the safety effects of roadway geometrics on crash occurrence along a freeway section that features mountainous terrain and adverse weather. Starting from preliminary exploration using Poisson models, Bayesian hierarchical models with spatial and random effects were developed to efficiently model the crash frequencies on road segments on the 20-mile freeway section of study. Crash data for 6 years (2000–2005), roadway geometry, traffic characteristics and weather information in addition to the effect of steep slopes and adverse weather of snow and dry seasons, were used in the investigation. Estimation of the model coefficients indicates that roadway geometry is significantly associated with crash risk; segments with steep downgrades were found to drastically increase the crash risk. Moreover, this crash risk could be significantly increased during snow season compared to dry season as a confounding effect between grades and pavement condition. Moreover, sites with higher degree of curvature, wider medians and an increase of the number of lanes appear to be associated with lower crash rate. Finally, a Bayesian ranking technique was implemented to rank the hazard levels of the roadway segments; the results confirmed that segments with steep downgrades are more crash prone along the study section.     

Investigating different approaches to develop informative priors in hierarchical Bayesian safety performance functions

The Bayesian inference method has been frequently adopted to develop safety performance functions. One advantage of the Bayesian inference is that prior information for the independent variables can be included in the inference procedures. However, there are few studies that discussed how to formulate informative priors for the independent variables and evaluated the effects of incorporating informative priors in developing safety performance functions. This paper addresses this deficiency by introducing four approaches of developing informative priors for the independent variables based on historical data and expert experience. Merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance information criterion (DIC), R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparison across the models indicated that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. Furthermore, informative priors for the inverse dispersion parameter have also been introduced and tested. Different types of informative priors’ effects on the model estimations and goodness-of-fit have been compared and concluded. Finally, based on the results, recommendations for future research topics and study applications have been made.     

Safety climate and safety performance among construction workers in Hong Kong. The role of psychological strains as mediators

This paper examines relations among safety climate (safety attitudes and communication), psychological strains (psychological distress and job satisfaction), and safety performance (self-reported accident rates and occupational injuries). A questionnaire was administered to construction workers from 27 construction sites in Hong Kong (N = 374, M = 366, F = 8, mean age =36.68 years). Data were collected by in-depth interviews and a survey from February to May 2000. A path analysis using the EQS-5 was employed to test the hypothesized model relating safety climate, safety performance, and psychological strains. The results provide partial support for the model, in that safety attitudes predict occupational injuries, and psychological distress predicts accident rates. Furthermore, psychological distress was found to be a mediator of the relationship between safety attitudes and accident rates. The implications of these results for psychological interventions in the construction industry are discussed.     

Estimating the safety performance of urban road transportation networks

Transportation planning models are typically used to estimate future traffic patterns, peak period traffic, travel time, and various environmental or other related traffic flow characteristics. Unfortunately, traffic safety is seldom, if ever, explicitly considered proactively during the transportation planning process. This omission is attributed to various factors, including the lack of available tools needed to estimate the number of crashes during this process. To help fill this void, the research on which this paper is based aimed, as a primary objective, to develop a tool that would allow the estimation of crashes on digital or coded urban transportation networks during the planning process. The secondary objective of the research was to describe how the predictive models should be applied on these networks and explain the important issues and limitations surrounding their application. To accomplish these objectives, safety performance functions specifically created for this work were applied to two sample digital networks created with the help of EMME/2, a software package widely used in transportation planning. The results showed that it is possible to predict crashes on digital transportation networks, but confirmed the reality that the accuracy of the predictions is directly related to the precision of the traffic flow estimates. The crash predictions are also sensitive to how the digital network is coded, and it is shown how appropriate adjustments can be made.     

Safety performance functions for crash severity on undivided rural roads

The objective of this paper is to explore the effect of the road features of two-lane rural road networks on crash severity. One of the main goals is to calibrate Safety Performance Functions (SPFs) that can predict the frequency per year of injuries and fatalities on homogeneous road segments. It was found that on more than 2000 km of study-road network that annual average daily traffic, lane width, curvature change rate, length, and vertical grade are important variables in explaining the severity of crashes. A crash database covering a 5-year period was examined to achieve the goals (1295 injurious crashes that included 2089 injuries and 235 fatalities). A total of 1000 km were used to calibrate SPFs and the remaining 1000 km reflecting the traffic, geometric, functional features of the preceding one were used to validate their effectiveness. A negative binomial regression model was used. Reflecting the crash configurations of the dataset and maximizing the validation outcomes, four main sets of SPFs were developed as follows: (a) one equation to predict only injury frequency per year for the subset where only non-fatal injuries occurred, (b) two different equations to predict injury frequency and fatality frequency per year per sub-set where at least one fa tality occurred together with one injury, and (c) only one equation to predict the total frequency per year of total casualties correlating accurate percentages to obtain the final expected frequency of injuries and fatalities per year on homogeneous road segments. Residual analysis confirms the effectiveness of the SPFs.     

Exploring the transferability of safety performance functions

Safety performance functions (SPFs), by predicting the number of crashes on roadway facilities, have been a vital tool in the highway safety area. The SPFs are typically applied for identifying hot spots in network screening and evaluating the effectiveness of road safety countermeasures. The Highway Safety Manual (HSM) provides a series of SPFs for several crash types by various roadway facilities. The SPFs, provided in the HSM, were developed using data from multiple states. In regions without local jurisdiction based SPFs it is common practice to adopt national SPFs for crash prediction. There has been little research to examine the viability of such national level models for local jurisdictions. Towards understanding the influence of SPF transferability, we examine the rural divided multilane highway models from Florida, Ohio, and California. Traffic, roadway geometry and crash data from the three states are employed to estimate single-state SPFs, two-state SPFs and three-state SPFs. The SPFs are estimated using the negative binomial model formulation for several crash types and severities. To evaluate transferability of models, we estimate a transfer index that allows us to understand which models transfer adequately to other regions. The results indicate that models from Florida and California seem to be more transferable compared to models from Ohio. More importantly, we observe that the transfer index increases when we used pooled data (from two or three states). Finally, to assist in model transferability, we propose a Modified Empirical Bayes (MEB) measure that provides segment specific calibration factors for transferring SPFs to local jurisdictions. The proposed measure is shown to outperform the HSM calibration factor for transferring SPFs.     

Critical older driver errors in a national sample of serious U.S. crashes

Objective

Older drivers are at increased risk of crash involvement per mile traveled. The purpose of this study was to examine older driver errors in serious crashes to determine which errors are most prevalent.

Methods

The National Highway Traffic Safety Administration’s National Motor Vehicle Crash Causation Survey collected in-depth, on-scene data for a nationally representative sample of 5470 U.S. police-reported passenger vehicle crashes during 2005–2007 for which emergency medical services were dispatched. There were 620 crashes involving 647 drivers aged 70 and older, representing 250,504 crash-involved older drivers. The proportion of various critical errors made by drivers aged 70 and older were compared with those made by drivers aged 35–54.

Results

Driver error was the critical reason for 97% of crashes involving older drivers. Among older drivers who made critical errors, the most common were inadequate surveillance (33%) and misjudgment of the length of a gap between vehicles or of another vehicle’s speed, illegal maneuvers, medical events, and daydreaming (6% each). Inadequate surveillance (33% vs. 22%) and gap or speed misjudgment errors (6% vs. 3%) were more prevalent among older drivers than middle-aged drivers. Seventy-one percent of older drivers’ inadequate surveillance errors were due to looking and not seeing another vehicle or failing to see a traffic control rather than failing to look, compared with 40% of inadequate surveillance errors among middle-aged drivers. About two-thirds (66%) of older drivers’ inadequate surveillance errors and 77% of their gap or speed misjudgment errors were made when turning left at intersections. When older drivers traveled off the edge of the road or traveled over the lane line, this was most commonly due to non-performance errors such as medical events (51% and 44%, respectively), whereas middle-aged drivers were involved in these crash types for other reasons. Gap or speed misjudgment errors and inadequate surveillance errors were significantly more prevalent among female older drivers than among female middle-aged drivers, but the prevalence of these errors did not differ significantly between older and middle-aged male drivers. These errors comprised 51% of errors among older female drivers but only 31% among older male drivers.

Conclusions

Efforts to reduce older driver crash involvements should focus on diminishing the likelihood of the most common driver errors. Countermeasures that simplify or remove the need to make left turns across traffic such as roundabouts, protected left turn signals, and diverging diamond intersection designs could decrease the frequency of inadequate surveillance and gap or speed misjudgment errors. In the future, vehicle-to-vehicle and vehicle-to-infrastructure communications may also help protect older drivers from these errors.     

Development of road safety performance indicators for trauma management in Europe

Trauma management (TM) covers two types of medical treatment: the initial one provided by Emergency Medical Services (EMS) and a further one provided by permanent medical facilities. There is a consensus in the professional literature that to reduce the severity and the number of road crash victims, the TM system should provide rapid and adequate initial care of injury, combined with sufficient further treatment at a hospital or trauma centre. Recognizing the important role of TM for reducing road crash injury outcome, it was decided, within the EU funded SafetyNet project, to develop road safety performance indicators (SPIs) which would characterize the level of TM systems’ performance in European countries and enable country comparisons.     

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components – fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors.     

Prospective safety performance evaluation on construction sites

This paper presents a systematic Structural Equation Modeling (SEM) based approach for Prospective Safety Performance Evaluation (PSPE) on construction sites, with causal relationships and interactions between enablers and the goals of PSPE taken into account. According to a sample of 450 valid questionnaire surveys from 30 Chinese construction enterprises, a SEM model with 26 items included for PSPE in the context of Chinese construction industry is established and then verified through the goodness-of-fit test. Three typical types of construction enterprises, namely the state-owned enterprise, private enterprise and Sino-foreign joint venture, are selected as samples to measure the level of safety performance given the enterprise scale, ownership and business strategy are different. Results provide a full understanding of safety performance practice in the construction industry, and indicate that the level of overall safety performance situation on working sites is rated at least a level of III (Fair) or above. This phenomenon can be explained that the construction industry has gradually matured with the norms, and construction enterprises should improve the level of safety performance as not to be eliminated from the government-led construction industry. The differences existing in the safety performance practice regarding different construction enterprise categories are compared and analyzed according to evaluation results. This research provides insights into cause–effect relationships among safety performance factors and goals, which, in turn, can facilitate the improvement of high safety performance in the construction industry.     

Road safety performance measures and AADT uncertainty from short-term counts

ObjectiveThe objective of this paper is to enable better risk analysis of road safety performance measures by creating the first knowledge base on uncertainty surrounding annual average daily traffic (AADT) estimates when the estimates are derived by expanding short-term counts with the individual permanent counter method.BackgroundMany road safety performance measures and performance models use AADT as an input. While there is an awareness that the input suffers from uncertainty, the uncertainty is not well known or accounted for.MethodThe paper samples data from a set of 69 permanent automatic traffic recorders in Manitoba, Canada, to simulate almost 2 million short-term counts over a five year period. These short-term counts are expanded to AADT estimates by transferring temporal information from a directly linked nearby permanent count control station, and the resulting AADT values are compared to a known reference AADT to compute errors. The impacts of five factors on AADT error are considered: length of short-term count, number of short-term counts, use of weekday versus weekend counts, distance from a count to its expansion control station, and the AADT at the count site.ResultsThe mean absolute transfer error for expanded AADT estimates is 6.7%, and this value varied by traffic pattern group from 5% to 10.5%. Reference percentiles of the error distribution show that almost all errors are between −20% and +30%. Error decreases substantially by using a 48-h count instead of a 24-h count, and only slightly by using two counts instead of one. Weekday counts are superior to weekend counts, especially if the count is only 24 h. Mean absolute transfer error increases with distance to control station (elasticity 0.121, p = 0.001), and increases with AADT (elasticity 0.857, p < 0.001).ImplicationsThese results can support evidence-based risk analysis of road safety performance measures that use AADT as inputs. Analytical frameworks for such analysis exist but are infrequently used in road safety because the evidence base on AADT uncertainty is not well developed.     

Benchmarking road safety of U.S. states: A DEA-based Malmquist productivity index approach

In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of U.S. states in decreasing the number of road fatalities. Even though the national trend in fatal crashes has reached to the lowest level since 1949 (Traffic Safety Annual Assessment Highlights, 2010), a state-by-state analysis and comparison has not been studied considering other characteristics of the holistic national road safety assessment problem in any work in the literature or organizational reports. In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of 50 U.S. states in reducing the number of fatal crashes. The single output, fatal crashes, and five inputs were aggregated into single road safety score and utilized in the DEA-based Malmquist index mathematical model. The period of 2002–2008 was considered due to data availability for the inputs and the output considered. According to the results, there is a slight negative productivity (an average of −0.2 percent productivity) observed in the U.S. on minimizing the number of fatal crashes along with an average of 2.1 percent efficiency decline and 1.8 percent technological improvement. The productivity in reducing the fatal crashes can only be attributed to the technological growth since there is a negative efficiency growth is occurred. It can be concluded that even though there is a declining trend observed in the fatality rates, the efficiency of states in utilizing societal and economical resources towards the goal of zero fatality is not still efficient. More effective policy making towards increasing safety belt usage and better utilization of safety expenditures to improve road condition are derived as the key areas to focus on for state highway safety agencies from the scope of current research.     

Lesson learned from the application of intersection safety devices in Edmonton

The City of Edmonton began its intersection safety device (ISD) program in 2009 with the installation of 50 cameras throughout the city. The ISDs are approach-specific and combine automated enforcement of red-light running and speed violations during the red and green phases of the intersection control. The goal of this study is to evaluate the safety performance of ISDs within the city of Edmonton, Canada and to identify factors that can lead to successful selection of future ISD sites. A before-and-after Empirical Bayes (EB) method is used to account for regression-to-the-mean and other confounding factors. A safety performance function and yearly calibration factors are developed using data from a set of reference intersections within Edmonton. The before-and-after analysis is applied at the overall intersection level and for each approach of the ISD intersections. The results showed significant reductions that ranged from 12% to 25% for total collisions, and from 33% to 43% for angle collisions. No significant reduction was observed for severe collisions at the intersection level, however significant reductions were found at the approach level at locations with a relatively higher collision history. The impact of site selection criteria on collision reduction was also evaluated. Greater reductions were found at sites with a higher collision frequency. Additionally, the impact of intersection characteristics on collision reduction was investigated. Speed limits, presence of separated right turn lane and the number of lanes were found to impact ISD collision reduction.     

Safety performance functions incorporating design consistency variables

Highway design which ensures that successive elements are coordinated in such a way as to produce harmonious and homogeneous driver performances along the road is considered consistent and safe. On the other hand, an alignment which requires drivers to handle high speed gradients and does not meet drivers' expectancy is considered inconsistent and produces higher crash frequency.     

Staying silent about safety issues: Conceptualizing and measuring safety silence motives

Communication between employees and supervisors about safety-related issues is an important component of a safe workplace. When supervisors receive information from employees about safety issues, they may gain otherwise-missed opportunities to correct these issues and/or prevent negative safety outcomes. A series of three studies were conducted to identify various safety silence motives, which describe the reasons that employees do not speak up to supervisors about safety-related issues witnessed in the workplace, and to develop a tool to assess these motives. Results suggest that employees stay silent about safety issues based on perceptions of altering relationships with others (relationship-based), perceptions of the organizational climate (climate-based), the assessment of the safety issue (issue-based), or characteristics of the job (job-based). We developed a 17-item measure to assess these four motives, and initial evidence was found for the construct and incremental validity of the safety silence motives measure in a sample of nurses.     

LNG safety research in the U.S.A.

This paper describes recent LNG safety research activities in the United States. Most of these activities have been sponsored by the U.S. Department of1. Hazard assessment. These are projects aimed at the development of experimental data and analytical models to describe radiation from LNG spill f2. Accident prevention. These are studies directed toward the development of qualification tests and reliable data on the properties and behavior o3. Hazard control. These are projects which address the conceptual design, testing and engineering development of new or improved response technolo