Dataset Information

Probabilistic model data of spatial-dependent crashes for ranking risk of road segments.

ABSTRACT: This article presents the databases analyzed and used to evaluate the risk of segment-based roads resulting from traffic crashes for three main motorways in UK from 2010 to 2014. The raw database is collection to many partial data for variables related to compute the crashes rates for each segment. These data were used to develop and select the best Bayesian probabilistic model presented in our research article (Kadhem et al., 2018) [1]. The data provided in this article would be an important source for studies that require evaluating statistical models and also to improve and develop the plans of traffic safety.

SUBMITTER: Kadhem SK

PROVIDER: S-EPMC6926288 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Probabilistic model data of spatial-dependent crashes for ranking risk of road segments.

Kadhem Safaa K SK Hewson Paul P

Data in brief 20191209

This article presents the databases analyzed and used to evaluate the risk of segment-based roads resulting from traffic crashes for three main motorways in UK from 2010 to 2014. The raw database is collection to many partial data for variables related to compute the crashes rates for each segment. These data were used to develop and select the best Bayesian probabilistic model presented in our research article (Kadhem et al., 2018) [1]. The data provided in this article would be an important so ...[more]

PMID: 31890806

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Project description:BACKGROUND:Distracted driving attributable to the performance of secondary tasks is a major cause of motor vehicle crashes both among teenagers who are novice drivers and among adults who are experienced drivers. METHODS:We conducted two studies on the relationship between the performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes. To facilitate objective assessment, accelerometers, cameras, global positioning systems, and other sensors were installed in the vehicles of 42 newly licensed drivers (16.3 to 17.0 years of age) and 109 adults with more driving experience. RESULTS:During the study periods, 167 crashes and near-crashes among novice drivers and 518 crashes and near-crashes among experienced drivers were identified. The risk of a crash or near-crash among novice drivers increased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval [CI], 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), sending or receiving text messages (odds ratio, 3.87; 95% CI, 1.62 to 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), looking at a roadside object (odds ratio, 3.90; 95% CI, 1.72 to 8.81), or eating (odds ratio, 2.99; 95% CI, 1.30 to 6.91). Among experienced drivers, dialing a cell phone was associated with a significantly increased risk of a crash or near-crash (odds ratio, 2.49; 95% CI, 1.38 to 4.54); the risk associated with texting or accessing the Internet was not assessed in this population. The prevalence of high-risk attention to secondary tasks increased over time among novice drivers but not among experienced drivers. CONCLUSIONS:The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Highway Traffic Safety Administration.).

Project description:OBJECTIVE:Single vehicle run-off crashes in urban areas constitute a growing problem that deserves more attention from authorities and researchers. This study aims to detect geometric road design risk factors characterizing places where urban run-off crashes might happen. METHODS:A case-control study was performed in the urban area of Valladolid (Spain) with data corresponding to a four-year period. Logistic regression models were used to analyze data, considering different variables related to design parameters in the models: type of intersection, radius of curvature, width of the pavement, width of the traffic lane, number of lanes for traffic in the same direction, direction of the traffic, length of the previous straight section, distance to the previous traffic light, slope, and finally, priority regulation. Two different scenarios were investigated: intersections and curves. RESULTS:The Adjusted Odds-Ratio of a run-off crash was five times higher in double direction roads with median strip than in one-way urban roads, for both curves and intersections, and almost nine times higher on road sections with previous straight lengths greater than 500 meters. Specific risk factors for intersections are "number of lanes for traffic in the same direction" (the odds of a run-off crash are more than five times higher on a road with two or more lanes), "length of preceding straight section" (the odds on road sections with lengths greater than 500 meters are more than nine times that of road sections with a length of less than 150 meters). For curves, specific factors are "width of the traffic lane" (the odds of a run-off crash on curves with lanes wider than 3.75m are more than six times higher) and "priority regulation" (the odds of a run-off crash increases more than twelve times on road sections with traffic light regulation over those without any regulation). CONCLUSIONS:The current study identifies urban road configurations that might require redesigning with the aim of decreasing the odds of a run-off crash, or the implementation of passive protective systems to mitigate their consequences. Specifically, intersections in two direction roads with median strip, more than two lanes per direction and a long preceding straight section, as well as curves with wide lanes and traffic light regulation, are the places that require attention.

Project description:PurposeAn average of 611 deaths and over 47,000 bicyclists are injured in traffic-related crashes in the United States each year. Efforts to increase bicycle safety are needed to reduce and prevent injuries and fatalities, especially as trends indicate that ridership is increasing rapidly. The objective of this study was to evaluate the effect of bicycle-specific roadway facilities (e.g., signage and bicycle lanes) in reducing bicycle crashes.MethodsWe conducted a case site-control site study of 147 bicycle crash-sites identified from the Iowa Department of Transportation crash database from 2007 to 2010 and 147 matched non-crash sites. Control sites were randomly selected from intersections matched to case sites on neighborhood (census block group) and road classification (arterial, feeder, collector, etc.). We examined crash risk by any on-road bicycle facility present and by facility type (pavement markings--bicycle lanes and shared lane arrows, bicycle-specific signage, and the combination of markings and signage), controlling for bicycle volume, motor vehicle volume, street width, sidewalks, and traffic controls.ResultsA total of 11.6% of case sites and 15.0% of controls had an on-road bicycle facility. Case intersections had higher bicycle volume (3.52 vs. 3.34 per 30 min) and motor vehicle volume (248.77 vs. 205.76 per 30 min) than controls. Our results are suggestive that the presence of an on-road bicycle facility decreases crash risk by as much as 60% with a bicycle lane or shared lane arrow (OR=0.40, 95% CI=0.09-1.82) and 38% with bicycle-specific signage (OR=0.62, 95% CI=0.15-2.58).ConclusionsInvestments in bicycle-specific pavement markings and signage have been shown to be beneficial to traffic flow, and our results suggest that they may also reduce the number of bicycle-motor vehicle crashes and subsequent injuries and fatalities. As a relatively low-cost traffic feature, community considerations for further implementation of these facilities are justified.

Dataset Information

Probabilistic model data of spatial-dependent crashes for ranking risk of road segments.

Publications

Probabilistic model data of spatial-dependent crashes for ranking risk of road segments.

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