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Methods: The study is based on traffic crash data merged with road maintenance data and annual average daily traffic (AADT) collected in Denmark. We analyzed 3,964 crashes that occurred from 2010 to 2015. A latent class clustering (LCC) technique was used to identify crash clusters with different road and crash characteristics. The distribution of crash severity and estimated road maintenance costs for each cluster was found and cluster differences were compared using the chi-square test. Finally, a map matching procedure was used to identify the geographical distribution of the crashes in each cluster.
Results: Results showed that based on road maintenance levels there was no difference in the distribution of crash severity. The LCC technique revealed 11 crash clusters. Five clusters were characterized by crashes on roads with a poor maintenance level (levels 4 and 3). Only a few of these crashes included a vulnerable road user (VRU) but many occurred on roads without barriers. Four clusters included a large share of crashes on acceptably maintained roads (level 2). For these clusters only small variations in road characteristics were found, whereas the differences in crash characteristics were more dominant. The last 2 clusters included crashes that mainly occurred on new roads with no need for maintenance (level 1). Injury severity, estimated maintenance costs, and geographical location were found to be differently distributed for most of the clusters.
Conclusions: We find that focusing solely on road maintenance and crash severity does not provide clear guidance of how to prioritize between road maintenance efforts from a traffic safety perspective. However, when combined with geographical location and crash characteristics, a more nuanced picture appears that allows consideration of different target groups and perspectives. 相似文献
Methods: An interrupted time series design was used to compare yearly mortality rates due to road traffic accidents in Rio de Janeiro, Brazil, before and after the zero-tolerance drinking and driving law came into effect on June 19, 2008. Yearly mortality rates were compared according to the type of victim: pedestrian, cyclist, motorcyclist, and vehicle occupant. We used the Prais-Winsten procedure of autoregression in the analysis of time series; the outcome of this analysis was the annual percentage change in the rates. Overall and stratified analyses were conducted to investigate whether the zero-tolerance drinking and driving law may have had a distributional effect on mortality rates due to road traffic accidents depending on sex and age group; a significance level of P < .01 was accepted.
Results: From 1999 to 2016, there were 15,629 deaths due to road traffic accidents in Rio de Janeiro. The effect of the zero-tolerance drinking and driving law on overall mortality rates due to road traffic accidents in Rio de Janeiro was not statistically significant. However, among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes and aged ≥20 years, the effect of the zero-tolerance drinking and driving law was to decrease mortality due to road traffic accidents at a yearly rate.
Conclusion: There is evidence of reduced mortality rates due to road traffic accidents among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes aged ≥20 years in the second major Brazilian capital 9 years after the zero-tolerance drinking and driving law was adopted. 相似文献