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TOWARDS A GLOBAL AND HARMONIZED DATABASE FOR INDEPTH ACCIDENT INVESTIGATION IN EUROPE: THE DaCoTA PROJECT

机译:朝向欧洲的印度事故调查全球和统一数据库:Dacota项目

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The aim with this paper is to describe the procedure for the development of a common methodology for research accident investigation and identifying and training new research teams across Europe. In-depth accident investigation has a great potential to provide researchers, car manufacturers and road administrations with valuable information on how and why accidents and injuries occur. The data can be used to determine the issues where efforts must be focused when research studies are conducted, crash protection countermeasures are designed and policy decisions are taken. Existing European databases are mainly focused on regional or specific stakeholder interests due to the lack of an international network, and there are significant differences in the information collected and how the database variables are coded. This lack of harmonisation precludes any detailed global analysis on the whole EU accident situation. The EU co-funded the DaCoTA project - inspired by previous projects like SafetyNet and TRACE - intended to establish a Pan-European In-depth Accident Investigation Network and to create a European database that could include in-depth accident investigation cases from all the European countries. Built on earlier pilot investigations conducted by previous projects, and following consultation with the range of stakeholders, an in-depth accident investigation system has been developed to standardise and harmonise the data to be collected during the investigations. Based on the new methodology, accident investigation teams from across Europe have been trained to systematically produce high quality research data. A comprehensive, secure, web-based database has been created to centralise the information collected and to analyse the results from the cases. To ensure the harmonisation of the data collected, a pilot study and subsequent data quality reviews were performed. The DaCoTA project has developed a harmonised in-depth accident investigation methodology, openly available in an online manual. From 19 European countries, 22 organisations were trained in the DaCoTA accident investigation methodology. The web based database includes over 1,500 variables related to the road, vehicle, road-user, accident reconstruction and injury analysis. Over 450 of these variables are considered as essential "core variables". In total, 99 on-scene and retrospective cases have been collected by 18 accident investigation teams using the standard methodology and these have been uploaded to the database for further analysis. Good relationships have been established between the network teams and their local authorities, including the police and hospitals. In some countries, efforts to obtain the necessary permissions to gain access to the accident scenes and to acquire sensitive medical or forensic data is continued. The DaCoTA project has developed the Pan- European in-depth accident investigation methodology, including a network of investigating teams, providing a viable means for the systematic collection of harmonised in-depth accident data for use by researchers, road and vehicle safety related industries and policy makers.
机译:本文的目的是描述开发研究事故调查和识别和培训欧洲新研究团队的常见方法的程序。深入的事故调查有很大的潜力,可以提供研究人员,汽车制造商和道路管理部门,了解如何以及为什么发生意外和伤害发生的有价值的信息。该数据可用于确定在进行研究研究时必须努力努力的问题,设计了碰撞保护对策,并采取了政策决策。由于缺乏国际网络,现有的欧洲数据库主要集中在区域或特定利益相关者利益上,并且收集的信息存在显着差异以及数据库变量如何编码。这种缺乏统一阻止了对整个欧盟事故情况的任何详细的全局分析。欧盟共同资助了Dacota项目 - 以前的项目,如SafetyNet和Trace,旨在建立一个泛欧的深入事故调查网络,并创建一个可能包括所有欧洲的进一步事故调查案件的欧洲数据库国家。建立在先前项目的早期试点调查,并在与利益相关者的范围进行磋商后,已经制定了深入的事故调查系统,以规范和协调在调查期间收集的数据。根据新方法,欧洲各地的事故调查小组受过培训,以系统地生产高质量的研究数据。已经创建了全面,安全的基于Web的数据库,以集中收集的信息并从案例中分析结果。为确保收集的数据统一,执行试点研究和随后的数据质量审查。 Dacota项目在在线手册中公开提供了齐全的深入事故调查方法。从19个欧洲国家,22个组织培训了Dacota事故调查方法。基于Web的数据库包括与道路,车辆,道路用户,事故重建和伤害分析相关的超过1,500个变量。这些变量中超过450个被认为是必要的“核心变量”。总共有99个现场和回顾性案件已通过使用标准方法的18个事故调查团队收集,并且已上传到数据库以进行进一步分析。网络团队和当地当局之间建立了良好的关系,包括警察和医院。在一些国家,继续努力获得进入事故场景和获取敏感的医疗或法医数据的必要权限。 Dacota项目已经开发了泛欧化的深入事故调查方法,包括调查团队的网络,为研究人员,道路和车辆安全相关行业和车辆安全相关行业和车辆安全相关行业提供了可行的对深入事故数据的可行方法。政策制定者。

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