| 1. |
- Martensen, Heike, et al.
(författare)
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The European Road Safety Decision Support System on Risks and Measures
- 2019
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 125:05, s. 344-351
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Tidskriftsartikel (refereegranskat)abstract
- The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs.
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| 2. |
- van Nes, Nicole, et al.
(författare)
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The potential of naturalistic driving for in-depth understanding of driver behavior: UDRIVE results and beyond
- 2019
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Ingår i: Safety Science. - : Elsevier BV. - 0925-7535 .- 1879-1042. ; 119, s. 11-20
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Tidskriftsartikel (refereegranskat)abstract
- Within the UDRIVE project, a rich cross-European naturalistic driving database was created which includes everyday driving data on car and truck drivers and powered two-wheeler riders. The database provides extensive, reliable insights into driving behavior in real traffic as a foundation for improving the safety and sustainability of European road traffic. This paper discusses the characteristics of the data in the UDRIVE database—elucidating key methodological choices and presenting a selection of results to date. A priority of the study design was obtaining in-depth information on driving behavior, permitting the exploration of diverse research questions. A tailor-made data acquisition system collected very comprehensive data. A total of 287 drivers/riders participated. The sample size restricts the addressable research topics to common behaviors in everyday driving and limits the generalizability of results. However, the data are extensive and promising analyses have already been performed. The results show differences between European countries for distracting activities, seatbelt use, and looking behavior towards cyclists at urban intersections. Moreover, it shows that European drivers engage less in mobile phone use than U.S. drivers. It is likely that European drivers differ in other ways, also—highlighting the dataset's value for developing and implementing targeted safety measures, for the E.U. and its individual countries. Based on the comparison of the different studies, the paper introduces the general conceptual framework for naturalistic driving studies, providing insight in the relation between the scope of a naturalistic driving study and the key methodological choices on sample selection and data acquisition system.
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| 3. |
- Elvik, Rune, et al.
(författare)
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Updated estimates of the relationship between speed and road safety at the aggregate and individual levels
- 2019
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Ingår i: Accident Analysis and Prevention. - : Elsevier Ltd. - 0001-4575 .- 1879-2057. ; 123, s. 114-122
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Tidskriftsartikel (refereegranskat)abstract
- Recent studies of the relationship between the speed of traffic and road safety, stated as the number of fatalities and the number of injury accidents, are reviewed and their results synthesised by means of meta-analysis. All studies were based on data fully or partly for years after 2000. Previously proposed models of the relationship between the speed of traffic and road safety, including the Power Model and an Exponential Model, are supported. Summary estimates of coefficients show that the relationship between speed and road safety remains strong. The Power Model and the Exponential Model both fit the data very well. The relationship between speed and road safety is the same at the individual driver level as at the aggregate level referring to the mean speed of traffic.
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