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Manual for DREAM version 3.2

Mikael Ljung Aust (Institutionen för tillämpad mekanik, Fordonssäkerhet) ; Azra Habibovic (Institutionen för tillämpad mekanik, Fordonssäkerhet) ; Emma Tivesten (Institutionen för tillämpad mekanik, Fordonssäkerhet) ; Ulrich Sander (Institutionen för tillämpad mekanik, Fordonsteknik och autonoma system) ; Jonas Bärgman (Institutionen för tillämpad mekanik, Fordonssäkerhet) ; Johan Engström (Institutionen för tillämpad mekanik, Fordonssäkerhet)
Göteborg : Chalmers University of Technology, 2012. - 79 s.
[Rapport]

The Driving Reliability and Error Analysis Method (DREAM) is based on the Cognitive Reliability and Error Analysis Method (CREAM; Hollnagel, 1998). CREAM was developed to analyse accidents within process control domains such as nuclear power plants and train operation, and DREAM is an adaptation of CREAM to suit the road traffic domain. The purpose of DREAM is to make it possible to systematically classify and store accident and incident causation information. This means that DREAM, like all other methods for accident/incident analysis, is not a provider but an organiser of explanations. For any of the contributing factor categories available in DREAM to be used, it must be supported by relevant empirical information. DREAM in itself cannot tell us why accidents happen (if it could, we would need neither on-scene investigations nor interviews). DREAM includes three main components: an accident model, a classification scheme and a detailed procedure description which step by step goes through what needs to be done in order to perform a DREAM analysis on an investigated accident/incident. Below, the accident model will be given more detailed descriptions. After this follows a description of the classification scheme, and then comes the analysis process, including example cases and recommendations for how to do the categorisation in certain typical scenarios.

Nyckelord: accident causation, DREAM, driver models, contributing factors



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Denna post skapades 2014-10-24. Senast ändrad 2016-10-18.
CPL Pubid: 204828