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Bypass lanes are a low-cost measure to increase capacity at unsignalized T-junctions without left-turn lanes that allow through-traffic to pass left-turning vehicles on the right. There is very limited knowledge about the safety effects of bypass lanes. We found six previous studies that could be summarized by means of meta-analysis, and the results show an average accident reduction of 10 percent. However, the results from previous studies are inconsistent and may be biased. Therefore, the present study has estimated safety effects of by-pass lanes in Norway, based on a sample of 2,227 T-junctions (incl. 94 with bypass-lanes) for which relevant data was available for a period of up to 10 years. We developed accident prediction models and conducted before-after analyses. The accident prediction models show that junctions with bypass lanes have 82 percent more accidents than junctions without bypass lanes, when controlling for endogeneity. Endogeneity occurs when the implementation of a measure is conditional on the frequency of crashes, as has been the case with bypass lanes. The before-after analysis shows that average accident numbers decrease after the installation of bypass lanes. However, when controlling for regression-to-the-mean (RTM), average accident numbers increase. RTM means that accident numbers would have been likely to decrease even without any measure because they had been exceptionally high in the before period. The control for potential biases in our study is likely to contribute to the discrepancy between results from our study and previous studies, most of which have not controlled for the same potential biases. We conclude therefore that bypass lanes, although favorable for capacity, are likely to be unfavorable for safety when compared to other unsignalized T-junctions without left-turn lanes. Unfavorable safety effects may partly be due to site specific conditions, such as road alignment and sight conditions, that contribute to rear-end collision risk or inappropriate driver behavior. However, this does not necessarily mean that bypass lanes never should be used. For example, at junctions where a bypass lane may solve capacity problems, and where site-specific conditions are favorable, bypass lanes may still be an acceptable solution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: The objective of this study was to summarize existing knowledge on the association between driving under the influence of alcohol and road safety outcomes and to assess factors that may explain why these estimates vary., Methods: Based on studies of the association between blood alcohol concentration (BAC) levels and crashes, we used multilevel metaregression to calculate summary effects of BAC level and analyze potential moderators of the association., Results: Based on 60 studies and 393 effect estimates, we found that BAC level, outcome severity, use of hospital data, and geographical region contributed to heterogeneity in results., Conclusion: The effect of BAC on crash and injury risk and culpability is stronger at higher BAC levels and for more serious outcomes. The relationship between BAC level and outcome is approximately exponential. The relationship is stronger in studies from Nordic countries than in studies from other countries, possibly because of the relatively low level of drunk driving in these countries. Studies based on hospital data and studies using non-crash-involved control groups find smaller effects on average.

The present study has investigated the relationship between traffic volume and crash numbers by means of meta-analysis, based on 521 crash prediction models from 118 studies. The weighted pooled volume coefficient for all crashes and all levels of crash severity (excluding fatal crashes) is 0.875. The most important moderator variable is crash type. Pooled volume coefficients are systematically greater for multi vehicle crashes (1.210) than for single vehicle crashes (0.552). Regarding crash severity, the results indicate that volume coefficients are smaller for more fatal crashes (0.777 for all fatal crashes) than for injury crashes but no systematic differences were found between volume coefficients for injury and property-damage-only crashes. At higher levels of volume and on divided roads, volume coefficients tend to be greater than at lower levels of volume and on undivided roads. This is consistent with the finding that freeways on average have greater volume coefficients than other types of road and that two-lane roads are the road type with the smallest average volume coefficients. The results indicate that results from crash prediction models are likely to be more precise when crashes are disaggregated by crash type, crash severity, and road type. Disaggregating models by volume level and distinguishing between divided and undivided roads may also improve the precision of the results. The results indicate further that crash prediction models may be misleading if they are used to predict crash numbers on roads that differ from those that were used for model development with respect to composition of crash types, share of fatal or serious injury crashes, road types, and volume levels., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: The aim of the present study was to investigate the relationship between bicycle helmet use and safety behavior at signalized intersections. Two hypotheses were investigated: The first states that bicycle helmet use leads to risker behavior because of the increased sense of protection (risk compensation), the other states that helmeted cyclists have a general inclination toward safer behavior (safety package) and that helmet use is one of several behaviors for improving safety., Method: Based on video recordings of 1031 cyclists at 12 signalized intersections in Denmark, two indicators of risky behavior were compared between helmeted and unhelmeted cyclists: Speed and time after the onset of yellow at which the cyclists crossed the stop line. Linear regression models were developed with gender, type of bicycle, and intersection characteristics as predictor variables, in addition to helmet use., Results: Helmeted and unhelmeted cyclists do not differ in how many seconds after the onset of yellow they cross the stopping line. This is consistent with the absence of both risk compensation and safety package, alternatively with a general inclination of helmeted cyclists toward safer behavior which is about offset by risk compensation. Helmeted cyclists had higher speed on average, which indicates that risk compensation may occur. However, the higher speed may also be due to the generally better fitness of helmeted cyclists which is likely to result from larger cycling volumes. Moreover, the effect of helmet use on speed may be overestimated because of a lack of control for potential confounding variables. The results show further that, regardless of helmet use, before-red (lights on a separate bicycle signal shift to red before the main signal) is related to later crossings of the stop lane after the onset of yellow and that cyclists stop earlier on average at intersections with right-turn signals., Conclusions: The results do not provide support for the position that promoting or mandating bicycle helmet use will have adverse safety effects because of more risky behavior among helmeted cyclists.