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The study builds on previous rumble strip safety evaluations by providing some Canadian-specific experience and in the process offering some definitive insights into differences in safety effects between installations on curved and tangent segments. An empirical Bayes before–after study estimated crash modification factors (CMFs) for installing edge line rumble strips (ELRS) and centerline rumble strips (CLRS), separately and in combination, on two-lane rural roads in Ontario. Separate CMFs were estimated for ELRS and CLRS for curved and tangent segments. The estimated CMFs indicate that rumble strips can be beneficial, except for CLRS on curved segments, and especially if applied in combination on tangents. The results also indicate that edge line and dual rumble strips are more effective on curved segments, so priority should be given to their application on such segments. It is noteworthy that dual application is more safety effective than either CLRS or ELRS, for tangents and overall. [ABSTRACT FROM AUTHOR]

• This study explores the applicability of univariate and two-stage approaches for estimating crash frequency by severity. • The prediction accuracies of univariate and two-stage severity distribution function (SDF) methods were found to be similar. • The results highlight the potential of the two-stage SDF approach at least for curved two-lane road sections. • The two-stage SDF approach can be especially a useful method for the all too frequent cases where samples are too small. The Highway Safety Manual (HSM) procedures apply specific safety performance functions (SPFs) and crash modification factors (CMFs) appropriate for estimating the safety effects of design and operational changes to a roadway. Although the applicability of the SPFs and CMFs may significantly vary by crash severity, they are mainly based on total crash counts, with different approaches for estimation of crashes by crash severity. The variety of approaches in the HSM and in the literature in general suggests that there may be no one best approach for all situations, and that there is a need to develop and compare alternative approaches for each potential application. This paper addresses this need by demonstrating the development and comparison of alternative approaches using horizontal curves on two-lane roads as a case study. This site type was chosen because of the high propensity for severe crashes and the potential for exploring a wide range of variables that affect this propensity. To facilitate this investigation, a two-stage modeling approach is developed whereby the proportion of crashes for each severity level is estimated as a function of roadway-specific factors and traffic attributes and then applied to an estimate of total crashes from an SPF. Using Highway Safety Information System (HSIS) curve data for Washington state, a heterogeneous negative binomial (HTNB) regression model is estimated for total crash counts and then applied with severity distribution functions (SDFs) developed by a generalized ordered probit model (GOP). To evaluate the performance of this two-stage approach, a comparison is made with predictions directly obtained from estimated univariate SPFs for crash frequency by severity and also from a fixed proportion method that has been suggested in the HSM. The results revealed that, while the two-stage SDF approach and univariate approach adopt different procedures for model estimation, their prediction accuracies are similar, and both are superior to the fixed proportion method. In short, this study highlights the potential of the two-stage SDF approach in accounting for crash frequency variations by severity levels, at least for curved two-lane road sections, and especially for the all too frequent cases where samples are too small to estimate viable univariate crash severity models. [ABSTRACT FROM AUTHOR]

It is fairly well understood that there is link between pavement friction and safety, or more specifically, the probability of wet-weather skidding crashes. However, robust knowledge on the comparative quantitative effects on safety for specific treatments that improve pavement friction, which can assist pavement engineers in economically justifying and prioritising treatments, is sparse. The large-scale study on which this paper is based aimed to firm up this knowledge for a variety of low-cost treatments and road classes, using state-of-the-art methodology and substantial, high-quality data-sets. This was a retrospective study for pavement safety performance, looking back at crash data before and after treatments was implemented. Both flexible and rigid pavement treatments were analysed and crash modification factors were estimated for several target crash types and road classes. The majority of the friction improvement treatments considered under this effort are typically used for pavement preservation or minor rehabilitation purposes. Although pavement engineers recognise that these treatments generally improve safety, they are not typically installed by highway agencies explicitly for safety improvement objectives. The combined results for most treatment types confirmed nevertheless the safety benefits for wet-road crashes, with a few exceptions. For dry road crashes, there was some evidence of the deleterious effects of speed adaptation to new surfaces in that crashes increased for a few treatments on some road types. [ABSTRACT FROM PUBLISHER]

Crash-based safety performance functions (SPFs) typically cannot account for all design and operational factors that contribute to crash frequency in assessing the safety impacts of these factors. An approach using surrogate safety measures can address this issue, providing these measures can be linked to crashes. This approach was explored by using microsimulation to generate and analyze conflicts for merge areas on Ontario freeways. Crash-conflict integrated SPFs with different time to collision thresholds were then developed and compared. The results of the conflict-based SPFs are in agreement with those from crash-based SPFs developed for the same sample, with logically negative coefficients for acceleration lane length and positive coefficients for traffic volumes. This suggests that the crash-conflict approach is a reasonable substitute for conventional crash prediction models in assessing the safety effects of design changes, especially for those changes that cannot be captured in the conventional models. [ABSTRACT FROM AUTHOR]

Crash Modification Factors (CMFs) are used to represent the effects on crashes of changes to highway design elements and are usually obtained from observational studies based on reported crashes. The design element of interest for this paper is horizontal curvature on rural 2-lane highways. The data for this study came from the Washington State database in the Highway Safety Information System (HSIS). Crash prediction models are developed for curve sections on rural 2-lane highway and the tangent sections up- and down-stream of the curve sections. Different negative binomial models were developed for segments on level grades (<3%), moderate grades (3–6%), and steep grades (>6%) to account for the confounding effects of gradient. The relationships between crashes at different traffic volumes and deflection angles are explored to illustrate how to get estimates of CMFs for increases in the minimum radius, considering the effect of increased tangent length for sharper curves, an effect that is overlooked in the Highway Safety Manual CMF, in addition to the effect of gradient. The results of that exploration indicated that even at different design speeds and deflection angles, the CMF estimates for incremental increases in radius lie within the same range, and that the crash reduction rate (CRR) is higher at segments on higher grades compared to the ones on lower grades. [ABSTRACT FROM AUTHOR]

This study investigates the use of crash prediction models and micro-simulation to develop an effective surrogate safety assessment measure at the intersection level. With the use of these tools, hypothetical scenarios can be developed and explored to evaluate the safety impacts of design alternatives in a controlled environment, in which factors not directly associated with the design alternatives can be fixed. Micro-simulation models are developed, calibrated, and validated. Traffic conflicts in the micro-simulation models are estimated and linked with observed crash frequency, which greatly alleviates the lengthy time needed to collect sufficient crash data for evaluating alternatives, due to the rare and infrequent nature of crash events. A set of generalized linear models with negative binomial error structure is developed to correlate the simulated conflicts with the observed crash frequency in Toronto, Ontario, Canada. Crash prediction models are also developed for crashes of different impact types and for transit-involved crashes. The resulting statistical significance and the goodness-of-fit of the models suggest adequate predictive ability. Based on the established correlation between simulated conflicts and observed crashes, scenarios are developed in the micro-simulation models to investigate the safety effects of individual transit line elements by making hypothetical modifications to such elements and estimating changes in crash frequency from the resulting changes in conflicts. The findings imply that the existing transit signal priority schemes can have a negative effect on safety performance, and that the existing near-side stop positioning and streetcar transit type can be safer at their current state than if they were to be replaced by their respective counterparts. [ABSTRACT FROM AUTHOR]

The combined application of centerline and shoulder rumble strips is intended to reduce the frequency of crashes by alerting drivers that they are about to leave the traveled lane. To date, this combination treatment has not been rigorously evaluated with a multistate database. To fill this void, this study evaluated treated two-lane rural road locations in three states. To account for potential site selection bias, an empirical Bayes (EB) before-after analysis was conducted. The combined results for all states indicate statistically significant crash reductions for all crash types analyzed. The crash type with the smallest crash modification factor (CMF) (i.e., the greatest crash reduction) is head-on with a CMF of 0.632 (i.e., a crash reduction of 36.8%). For run-off-road, head-on, and sideswipe-opposite direction crashes combined (i.e., lane departure crashes), the estimated CMF is 0.733. Benefit:cost (B:C) ratios were estimated to range from 28.2 to 67.7, depending on the treatment cost and service life assumption. [ABSTRACT FROM AUTHOR]

Crash prediction models used to estimate safety of highway segments and intersections are traditionally developed using various traffic volume measures. There are issues with this approach and surrogate safety measures such as conflicts and delays have been proposed to overcome them. This study investigates the statistical relationships between crash frequencies and traffic volume, intersection delay, and simulated conflicts to explore and compare the viability of these models for estimating safety at urban two-way stop controlled intersections. The database used includes 78 three leg and 55 four leg intersections within the city of Toronto, Canada. Crash prediction models were developed and evaluated based on various goodness-of-fit measures. With the developed models, an alternate approach to crash based evaluations of intersection improvements is presented. A case study is developed to investigate and demonstrate the use of the models for estimating the safety impact of implementing a left turn lane on a major approach of an urban three leg stop controlled intersection. This case study and other results confirm the promise of the approach, suggesting that surrogate measures, such as the ones investigated, can capture effects of factors other than traffic volume alone. [ABSTRACT FROM AUTHOR]

Highlights: [•] We investigate fully specified and hierarchical models with crash modification functions (CM-Functions). [•] Both formulations yield reasonable CM-Functions but hierarchical model is better. [•] Hierarchical models provide efficient estimates with conformity and correlations. [•] We fill a methodological void about crash modification factors in the Highway Safety Manual. [ABSTRACT FROM AUTHOR]

Abstract: Despite widespread recognition of operating speed as a key safety-related variable for roundabouts, there is no consensus on the best models for capturing the relationship between crashes and speed, or, for that matter, on how speed can be estimated in situations where it cannot be observed (such as when a roundabout is being designed or redesigned). This paper uses US and Italian roundabout approach-level data to investigate models relating safety to various measures of predicted speed. This is an indirect approach for developing safety models for estimating the effects of design features, the premise being that these features can better predict speed, which, in turn, can be used as a predictor of crash frequency. After exploring various possibilities, the approach average speed (AAS) – defined as the average of entry, upstream circulating and exiting speeds in this study – was found to be the speed measure that best predicts safety. US data were used to develop a Bayesian Poisson-gamma safety model based on predicted AAS with random coefficients and varying dispersion parameter. This model structure was not appropriate for the Italian data used to examine whether the approach could be generalized to data for another country. For that data, a zero-inflated Poisson (ZIP) model was found to be suitable. Notwithstanding the heterogeneity of the model structure, the investigation suggests that the indirect approach for evaluating the safety of a roundabout is a sound one in that it can preserve model parsimony while capturing the effects of design changes that affect safety. [Copyright &y& Elsevier]

The multivariate Poisson log normal (MVPLN) Bayesian method has recently been introduced in road safety analysis mainly for network screening and using different crash severity levels. However, there is little or no research applying MVPLN to different crash types. Besides, only one model structure for the expected crashes of a given severity was investigated in previous MVPLN studies. Another knowledge gap is that this method has not yet been evaluated for before–after treatment effect analysis. The objective of this study was to evaluate the application of MVPLN Bayesian method for before–after road safety evaluation studies. Two groups of unsignalized California intersections, for which a naive before–after comparison shows a significant change in the crash frequency after a hypothetical treatment was assigned, were used to conduct the study. It was found that the crash reduction rates are sensitive to the function form of expected crashes. For each model structure, MVPLN, univariate Poisson log normal (PLN) and Poisson-gamma models provided comparable results while PLN was seen to be superior. Finally, models that consider temporal effects of unobserved latent variables were found to be superior to those that don’t. [ABSTRACT FROM AUTHOR]

Abstract: The empirical Bayes (EB) approach has now gained wide acceptance among researchers as the much preferred one for the before–after evaluation of road safety treatments. In this approach, the before period crash experience at treated sites is used in conjunction with a crash prediction model for untreated reference sites to estimate the expected number of crashes that would have occurred without treatment. This estimate is compared to the count of crashes observed after treatment to evaluate the effect of the treatment. This procedure accounts for regression-to-the-mean effects that result from the natural tendency to select for treatment those sites with high observed crash frequencies. Of late, a fully Bayesian (FB) approach has been suggested as a useful, though complex alternative to the empirical Bayes approach in that it is believed to require less data for untreated reference sites, it better accounts for uncertainty in data used, and it provides more detailed causal inferences and more flexibility in selecting crash count distributions. This paper adds to the literature on comparing the two Bayesian approaches through empirical applications. The main application is an evaluation of the conversion of road segments from a four-lane to a three-lane cross-section with two-way left-turn lanes (also known as road diets). For completeness, the paper also summarizes the results of an earlier application pertaining to the evaluation of conversion of rural intersections from unsignalized to signalized control. For both applications, the estimated safety effects from the two approaches are comparable. [Copyright &y& Elsevier]

Abstract: The objective of the study on which the paper is based was to explore the application of fully Bayesian methods for before–after road safety studies. Several variations of the methodology were evaluated with a simulated dataset in which hypothetical treatments with no safety effect were randomly assigned to high accident locations to mimic the common site selection process in road jurisdictions. It was confirmed that the fully Bayesian method by estimating no safety effect can account for the regression-to-the-mean that results from this biased site selection process. The fully Bayesian method was then applied to California rural intersection data to evaluate the safety effect of conversion from stop to signalized control. The results were then compared with those from the empirical Bayesian method, currently the accepted approach for conducting unbiased before–after evaluations. This comparison was generally favorable in that FB can provide similar results as EB. [Copyright &y& Elsevier]

Abstract: The empirical Bayes (EB) methodology has been applied for over 20 years now in conducting statistically defendable before–after studies of the safety effect of treatments applied to roadway sites. The appeal of the methodology is that it corrects for regression to the mean and traffic volume and other changes not due to the measure. There is, therefore, a natural tendency to put a stamp of approval on any study that uses this methodology, and to assume that the results can then be used in specifying crash modification factors for use in developing treatments for hazardous locations, or in designing new roads using tools such as the interactive highway safety design model (IHSDM). At the other extreme are skeptics who suggest that the increased sophistication and data needs of the EB methodology are not worth the effort since alternative, less complex methods can produce equally valid results. The primary objective of this paper is to capitalize on experience gained from two decades of conducting EB studies around the world to illustrate that the EB methodology, if properly undertaken, produces results that could be substantially different and less biased than those from more conventional types of studies. A secondary objective is to emphasize that caution is needed in assessing the validity of studies undertaken with the EB methodology and in using these results for providing crash modification factors. To this end, a number of issues that are critical to the proper conduct and interpretation of EB evaluations are raised and illustrated based on lessons learned from recent experience with these studies. These include: amalgamating the effects on different crash types; the specification of the reference/comparison groups; and accounting for traffic volume changes. Current and future directions, including the improvements offered by a full Bayes approach, are discussed. [Copyright &y& Elsevier]

Rural two-lane roads generally lack physical measures such as wide medians or barriers to separate opposing traffic flows. As a result, a major crash problem on these roads involves vehicles crossing the centerline and either sideswiping or striking the front ends of opposing vehicles. These types of opposing-direction crashes account for about 20% all fatal crashes on rural two-lane roads and result in about 4500 fatalities annually in the US. The present study evaluated a potential engineering countermeasure for such crashes—installation of rumble strips along the centerlines of undivided rural two-lane roads to alert distracted, fatigued, or speeding motorists whose vehicles are about to cross the centerlines and encroach into opposing traffic lanes. Data were analyzed for approximately 210 miles of treated roads in seven states before and after installation of centerline rumble strips. An empirical Bayes before–after procedure was employed to properly account for regression to the mean while normalizing for differences in traffic volume and other factors between the before and after periods. Overall results indicated significant reductions for all injury crashes combined (14%, 95% confidence interval (95% CI)=5–23%) as well as for frontal and opposing-direction sideswipe injury crashes (25%, 95% CI=6–44%)—the primary target of centerline rumble strips. In light of their effectiveness and relatively low installation costs, consideration should be given to installing centerline rumble strips more widely on rural two-lane roads to reduce the risk of frontal and opposing-direction sideswipe crashes. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]

Conclusions. Results are consistent with numerous international studies and suggest that roundabout installation should be strongly promoted as an effective safety treatment. (Am J Public Health. 2001;91:628-631) [ABSTRACT FROM AUTHOR]

• This study aims to improve the functional forms used to derive CMFs in cross-sectional regression models. • The estimated CMFs are for target crashes for freeway median width used as a case study. • CMFs for a given change in a feature's value depend not only on the amount of the change but also on the original value. • The results highlight the importance of using the functional forms that can capture non-linear effects of road attributes. Crash modification factors (CMFs) for several roadway attributes are based on cross-sectional regression models, in the main because of the lack of data for the preferred observational before-after study. In developing these models, little attention has been paid to those functional forms that reflect the reality that CMFs should not be single-valued, as most available ones are, but should vary with application circumstance. Using a full Bayesian Markov Chain Monte Carlo (MCMC) approach, this study aimed to improve the functional forms used to derive CMFs in cross-sectional regression models, with a focus on capturing the variability inherent in crash modification functions (CMFunctions). The estimated CMFunction for target crashes for freeway median width, used for a case study, indicates that the approach is capable of developing a function that can capture the logical reality that the CMF for a given change in a feature's value depends not only on the amount of the change but also on the original value. The results highlight the importance of using the functional forms that can capture non-linear effects of road attributes for CMF estimation in cross-sectional models. The case study provides credible CMFs for assessing the safety implications of decisions on freeway median width that could be used in improving current design practice. [ABSTRACT FROM AUTHOR]

This paper describes an economical method for obtaining speeds, flows and densities from low quality time-lapse film that is unsuitable for the more common data reduction techniques, most of which require vehicle tracking. The method is developed from some very basic ideas and is illustrated in a description of a recent application--a study involving 16-mm time lapse film coverage of a 1400 m long freeway segment in Toronto, Canada. Average speeds were comparable to those obtained by tracking individual vehicles. [ABSTRACT FROM AUTHOR]

The article presents a study which assess the effects of maintenance treatments aimed at improving pavement condition of roads on road safety and pavement management. The research was made in two-lane rural roads in Ontario. Also cited are the use of the International Roughness Index (IRI) in the study, and the results showing that treatments were effective in reducing crashes, property damage only (PDO) crashes, and fatal plus injury (FI) crashes.

The primary objective of this paper is to provide a statistical relationship between traffic conflicts estimated from microsimulation and observed crashes in order to evaluate safety performance, in particular the effect of countermeasures. A secondary objective is to assess the effect of conflict risk tolerance and number of simulation runs on the estimates of countermeasure effects so obtained. Conflicts were simulated for a sample of signalized intersections from Toronto, Canada, using VISSIM microscopic traffic simulation and several crash–conflict relationships were obtained. A separate sample of treated intersections from Toronto was used to compare countermeasure effects from the integrated crash–conflict expression to a conventional, but rigorous crash-based Empirical Bayes before-and-after analysis that was already done, with the results published, for the same sites and treatment. The countermeasure considered for this investigation involved changing the left turn signal operation for the treated intersection sample from permissive to protected-permissive. The results support the view that countermeasure effects can be estimated reliably from conflicts derived from microsimulation, and more so when a suitable number of simulation runs and conflict tolerance thresholds are used in the crash–conflict relationship. [ABSTRACT FROM AUTHOR]

Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis. [ABSTRACT FROM AUTHOR]

Abstract: Roundabouts may be new builds but often are conversions from existing intersections. When contemplating the later, there is a need to estimate the safety effects of conversions. Several studies have estimated large reductions in crashes and severity; however, these results pertain mainly to conversions from unsignalized intersections. Results for conversions from signalized intersections have been less conclusive or consistent and tend to be somewhat dated. The objective of this study was to fill this void by estimating the safety effectiveness of converting signalized intersections to roundabouts. Several states helped to identify signalized intersections that were converted to roundabouts in the recent past. In total, 28 conversions were identified in the United States. The empirical Bayes (EB) method was employed in an observational before–after study to estimate the safety effects. Data from select states were also used in a cross-sectional analysis to investigate the compatibility of results from cross-sectional and before–after studies. The EB results indicated a safety benefit for converting signalized intersections to roundabouts. There were reductions in both total and injury crashes, with a larger benefit for injury crashes. Further analysis indicated that the safety benefit of roundabouts for total crashes decreased as traffic volumes increase, a result that suggests the need for the development of a crash modification function, a task for which more data would be required. The safety benefit for injury crashes was sustained across all traffic volumes. Both trends were supported by the cross-sectional analysis. Based on the analysis, it appears that roundabouts have the potential to significantly reduce crashes and severity at signalized intersections. A key aspect of the study was the estimation of the standard deviation of the distribution of the CMF in addition to the conventionally estimated standard error of the mean CMF value. For some CMFs, especially the CMFs for total crashes, the standard deviation of the distribution was larger than the standard error of the mean value of the CMF, indicating substantial variation in the treatment effect across sites. [Copyright &y& Elsevier]

Recently, several attempts have been made to develop collision prediction models in which spatial dependency is considered. These models recognize the local nature of spatial data by relaxing the regression analysis assumption that the error terms for each observation are independent. The primary objective of this study is to investigate an alternative technique for capturing the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors. Spatial relationships are incorporated into the full Bayesian semiparametric additive modeling framework through the covariance of the error terms. The secondary objective of this research study is to build on knowledge of comparing the accuracy of full Bayesian models to that of generalized linear and geographically weighted Poisson regression models. The spatial covariates from the full Bayesian semiparametric additive model indicate that collision frequencies in traffic analysis zones are spatially correlated. The results of accuracy comparison indicate that the spatial models perform better than the conventional generalized linear models. However, mixed results are obtained when the FBSA models were compared to the geographically weighted Poisson regression models. [ABSTRACT FROM AUTHOR]

Abstract: A common technique used for the calibration of collision prediction models is the Generalized Linear Modeling (GLM) procedure with the assumption of Negative Binomial or Poisson error distribution. In this technique, fixed coefficients that represent the average relationship between the dependent variable and each explanatory variable are estimated. However, the stationary relationship assumed may hide some important spatial factors of the number of collisions at a particular traffic analysis zone. Consequently, the accuracy of such models for explaining the relationship between the dependent variable and the explanatory variables may be suspected since collision frequency is likely influenced by many spatially defined factors such as land use, demographic characteristics, and traffic volume patterns. The primary objective of this study is to investigate the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression modeling technique. The secondary objective is to build on knowledge comparing the accuracy of Geographically Weighted Poisson Regression models to that of Generalized Linear Models. The results show that the Geographically Weighted Poisson Regression models are useful for capturing spatially dependent relationships and generally perform better than the conventional Generalized Linear Models. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

The article proposes a two-staged modelling approach to identify the association between one vehicle's attributes, as well as roadway engineering, environmental and crash characteristics, and the injury severity of occupants in the partnering vehicle in two-vehicle crashes. The modelling approach uses a bivariate binary probit model, and crash data for Toronto, to first determine the probability of injury and no injury occurring, followed by the use of a bivariate ordered probit model to investigate the conditional probability of the specific severity level. Vehicles in two-vehicle crashes are categorized as “not-at-fault” (NAF) or “at-fault” (AF) and their occupants also categorized as such. The findings demonstrate that the modelling approach used in this study can reveal meaningful insights by improving understanding of how the same attribute could behave differently for NAF and AF vehicles. For example, factors found to be associated with increased probability of more severe injuries of NAF vehicle occupants are inattentive driving, left-turn movement, heavy vehicle type of the AF vehicle, and angle and rear-end impact type; conversely, for AF vehicles, their probability of more severe injury is positively associated with inattentive driving and heavy vehicle type of the NAF vehicle, and angle and approaching impact type. [ABSTRACT FROM AUTHOR]

Ramp-metering, which controls the onramp flow into the freeway, is successful in increasing freeway throughput and reducing overall travel-time. The maximum flow allowed from the onramp during ramp-metering is typically estimated so that the sum of flows from the onramp and mainline do not exceed a predetermined threshold (either the capacity of the downstream section or a threshold based on occupancy at capacity). Recent research has shown that this threshold is probabilistic and the transition from noncongested to congested conditions (i.e., breakdown) occurs stochastically. Also, research has shown that the contribution of the ramp and freeway demands on breakdown is different; 100 additional vehicles arriving from the ramp increase the probability of breakdown more than 100 additional vehicles from the freeway. This fluctuation has been studied through the development of breakdown probability models, which provide the probability of breakdown as a function of the combination of the mainline and ramp flows. The writers' objective was to develop suitable site-specific probability of breakdown models and use them within existing ramp-metering algorithms to evaluate their ability to postpone the breakdown and reduce congestion at freeway facilities with recurring congestion. The writers first develop a process for obtaining breakdown-probability models for existing critical ramps (i.e., those where breakdown starts). Next, the writers propose specific enhancements to existing ramp-metering algorithms that incorporate probability-of-breakdown models. Proposed enhancements are presented for two algorithms, as follows: (1) the Minnesota stratified ramp-metering algorithm (SZM), and (2) the Ontario COMPASS algorithm. Simulation was used to replicate these algorithms and evaluate the proposed enhancements. The results of these experiments showed that the enhancements are effective in postponing congestion at the two sites by 17-35 min. [ABSTRACT FROM AUTHOR]

The term breakdown of flow at a freeway bottleneck location has been used to describe the transition from relatively free-flowing traffic to congestion, often called stop-and-go traffic, but more generally experienced as slow-and-go. The focus of the research presented in this paper was to develop probabilistic models to predict breakdown of flow by using data from five freeway-ramp merging segments. The development of the probabilistic models allows exploration of several issues: the identification of breakdown, the performance measures for the identification of the breakdown, and the breakdown location. The breakdown probability model (BPM) is based on lifetime data analysis statistics. The breakdown probability models can be very useful tools in establishing capacity values, which in turn can be part of the freeway traffic management process. [ABSTRACT FROM AUTHOR]

Abstract: In Europe, approximately 60% of road accident fatalities occur on two-lane rural roads. Thus, research to develop and enhance explanatory and predictive models for this road type continues to be of interest in mitigating these accidents. To this end, this paper describes a novel and extensive data collection and modeling effort to define accident models for two-lane road sections based on a unique combination of exposure, geometry, consistency and context variables directly related to the safety performance. The first part of the paper documents how these were identified for the segmentation of highways into homogeneous sections. Next, is a description of the extensive data collection effort that utilized differential cinematic GPS surveys to define the horizontal alignment variables, and road safety inspections (RSIs) to quantify the other road characteristics related to safety. The final part of the paper focuses on the calibration of models for estimating the expected number of accidents on homogeneous sections that can be characterized by constant values of the explanatory variables. Several candidate models were considered for calibration using the Generalized Linear Modeling (GLM) approach. After considering the statistical significance of the parameters related to exposure, geometry, consistency and context factors, and goodness of fit statistics, 19 models were ranked and three were selected as the recommended models. The first of the three is a base model, with length and traffic as the only predictor variables; since these variables are the only ones likely to be available network-wide, this base model can be used in an empirical Bayesian calculation to conduct network screening for ranking “sites with promise” of safety improvement. The other two models represent the best statistical fits with different combinations of significant variables related to exposure, geometry, consistency and context factors. These multiple variable models can be used, with caution, and in conjunction with results from other studies, to derive accident modification factors for these variables for design applications, and in safety assessment for smaller samples of sites for which these variables can be assembled with relative ease. [Copyright &y& Elsevier]

Abstract: Main objectives: This study was conducted to estimate the costs per crash for three police-coded crash severity groupings within 16 selected crash geometry types and within two speed limit categories (≤45 and ≥50mph). Methods: We merged previously developed costs per victim by abbreviated injury scale (AIS) score into U.S. crash data files that scored injuries in both the AIS and police-coded severity scales to estimate injury costs, then aggregated the estimates into costs per crash by maximum injury severity. Results: The most costly crashes were non-intersection fatal/disabling injury crashes on a road with a speed limit of 50 miles per hour or higher where multiple vehicles crashed head-on or a single vehicle struck a human (over $1.69 and $1.16 million per crash, respectively). The annual cost of police-reported run-off-road collisions, which include both rollovers and object impacts, represented 34% of total costs. Conclusions: This paper provides cost estimates useful for evaluating roadway countermeasures and for designing vehicles to minimize crash harm. It gives unit costs of crashes by type in the coding system used by the police. The costs are in an appropriate form for economic analysis of countermeasures addressing locally defined problems identified by analyzing police crash reports. [Copyright &y& Elsevier]