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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: 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]

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 © 2012 Elsevier Ltd. All rights reserved.)

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 © 2012 Elsevier Ltd. All rights reserved.)

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 4,500 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.

This paper presents estimates for both the economic and comprehensive costs per crash for three police-coded severity groupings within 16 selected crash types and within two speed limit categories (or=50 mph). The economic costs are hard dollar costs. The comprehensive costs include economic costs and quality of life losses. We merged previously developed costs per victim keyed on the Abbreviated Injury Scale (AIS) into US crash data files that scored injuries in both the AIS and police-coded severity scales to produce per crash estimates. 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.