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1.
Accid Anal Prev ; 203: 107643, 2024 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-38781630

RESUMEN

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.


Asunto(s)
Accidentes de Tránsito , Conducción de Automóvil , Seguridad , Humanos , Noruega , Planificación Ambiental
2.
Accid Anal Prev ; 145: 105668, 2020 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-32777559

RESUMEN

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.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Entorno Construido/estadística & datos numéricos , Accidentes de Tránsito/clasificación , Conducción de Automóvil/estadística & datos numéricos , Entorno Construido/clasificación , Humanos , Puntaje de Gravedad del Traumatismo , Heridas y Lesiones/epidemiología
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