| 1. |
- Fagerlind, Helen, 1975, et al.
(författare)
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Development of an In-depth European Accident Causation Database and the Driving Reliability and Error Analysis Method, DREAM 3.0
- 2008
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Ingår i: 3rd International Conference ESAR (Expert Symposium on Accident Research). - Hannover, Tyskland.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The SafetyNet project was formulated in part to address the need for safety oriented European road accident data. One of the main tasks included within the project was the development of a methodology for better understanding of accident causation together with the development of an associated database involving data obtained from on-scene or “nearly on-scene” accident investigations. Information from these investigations was complemented by data from follow-up interviews with crash participants to determine critical events and contributory factors to the accident occurrence. A method for classification of accident contributing factors, known as DREAM 3.0, was developed and tested in conjunction with the SafetyNet activities. Collection of data and case analysis for some 1 000 individual crashes have recently been completed and inserted into the database and therefore aggregation analyses of the data are now being undertaken. This paper describes the methodology development, an overview of the database and the initial aggregation analyses.
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| 2. |
- Ljung Aust, Mikael, 1973, et al.
(författare)
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Accident investigations for active safety at CHALMERS - new demands require new methodologies
- 2007
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Ingår i: Vehicle System Dynamics. - : Informa UK Limited. - 1744-5159 .- 0042-3114. ; 45:10, s. 881-894
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Tidskriftsartikel (refereegranskat)abstract
- In order to develop efficient active safety systems, knowledge about what causes traffic accidents is required. One way to gather such knowledge is through traffic accident investigations. For the needs of active safety, most current accident investigation methodologies do not provide a sufficiently detailed or theoretically anchored analysis. Therefore, new studies need to be carried out using new theoretical frameworks and analysis methods. At CHALMERS, a new methodology called driving reliability and error analysis method has been developed and tried out during recent years. The methodology, as described and exemplified, shows good promise of meeting the needs of active safety accident investigation projects. Results from studies using the methodology also imply consequences for how benefit estimation of new active safety systems should be carried out.
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| 3. |
- Sandin, Jesper, 1975-
(författare)
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Aggregating Case Studies of Vehicle Crashes by Means of Causation Charts : An Evaluation and Revision of the Driving Reliability and Error Analysis Method
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- There is a need for increased knowledge about causes to motor-vehicle crashes and their prevention. Multidisciplinary in-depth case studies can provide detailed causation data that is otherwise unattainable. Such data might allow the formulation of hypotheses of causes and causal relationships for further study. By converting the data into causation charts that are aggregated, common causation patterns would give greater weight to such hypotheses. However the charts must first be compiled by means of a systematic analysis method, which requires three parts; a model, a classification scheme and a classification method.Four general accident models were evaluated and found inadequate to form the basis for a causation analysis method. This was primarily because the models in practice treat road-users, vehicles and traffic environment as separate components, but also due to the focus on events immediately prior to the crash and either static, sequential, or absent modelling of interaction.Two studies were carried out to evaluate whether case files could be aggregated by means of charts that had been compiled with the Driving Reliability and Error Analysis Method (DREAM). In DREAM, contributory factors (genotypes) are systematically analysed, classified and linked in a single chart for each driver that illustrate the causes of a critical event (phenotype). In the first study, case files from 38 single-vehicle crashes were examined to distinguish crashes with similar circumstances. Four types of loss of vehicle control were identified, for which the associated DREAM charts were aggregated. The results revealed common patterns within the types, as well as different patterns between them. The second study focused on 26 intersection crashes. Based on the most common violations at intersections, six risk situations were defined, and the DREAM charts associated with each risk situation were aggregated. A common pattern in each of two risk situations indicated that drivers with and without the right of way had not seen the other vehicle due to distractions and/or sight obstructions. A frequently occurring pattern for the drivers with the right of way was that they had not expected another vehicle to cross their path. The absence of clear patterns in three risk situations was a result of a low number of charts and rather unique circumstances in these cases. Parts of the aggregated charts contained an unexpectedly large variation, identified as a consequence of inconsistently compiled charts.Prior the final study assessing intercoder agreement, DREAM was revised into a new version based on the experience from the latter aggregation study. A total of seven investigators from four European countries compiled seven DREAM charts for each driver involved in four types of accidents. The results indicated that the intercoder agreement for genotypes ranged from 74% to 94% with an average of 83%, while it for phenotypes ranged from 57% to 100% with an average of 78%. This acceptable level of agreement is expected to rise with enhanced training. The present thesis thus shows that DREAM is a highly promising method for the compilation of causation charts. Future studies are expected to benefit from aggregating DREAM charts when formulating hypotheses of general causes and causal relationships as a subject for further research, as well as to identify alternative countermeasure strategies.
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| 4. |
- Sandin, Jesper, 1975
(författare)
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An analysis of common patterns in aggregated causation charts from intersection crashes
- 2009
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 41:3, s. 624-632
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Tidskriftsartikel (refereegranskat)abstract
- intersection crashes are a major traffic problem. Greater knowledge of causation is required in order to prevent them with the implementation of active safety measures. Causation charts were aggregated to establish whether common patterns of interlinked factors could be found. The data used comprised causation charts for 52 drivers involved in 26 in-depth investigated urban intersection crashes. The charts were compiled by means of the Driving Reliability and Error Analysis Method (DREAM) version 2.1, in which contributing factors are systematically analysed, classified and linked in a causation chart. The charts were aggregated for six defined risk situations, four for drivers without the right of way and two for those with the right of way. in two risk situations, one for drivers with and one for the drivers without the right of way, common patterns showed that the drivers had not seen the other vehicle due to distractions and/or sight obstructions. A frequently occurring pattern for the drivers with the right of way was that they had not expected another vehicle to cross their path. The absence of clear patterns in three risk situations for the drivers without the right of way was due to the low number of charts and rather unique circumstances. Parts of the aggregated charts showed an unwarranted variation, identified as a consequence of inconsistent charts. The present study shows that the rather unique approach of aggregating causation charts has potential, provided that the charts are consistent. (C) 2009 Elsevier Ltd. All rights reserved.
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| 5. |
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| 6. |
- Sandin, Jesper, 1975
(författare)
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DREAM: A Method for Understanding the Causation of Single-Vehicle Crashes
- 2006
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- When conducting in-depth causation studies, it is essential that the analysis method can both define and classify contributing factors and be able to analyse how these factors may interact to produce a critical event. These issues are highly influenced by the underlying theory, e.g. the accident model. Consequently, the first study in this thesis surveyed the characteristics of four general accident models, i.e. sequential models, epidemiological models, energy transfer models and systemic models. Based on the accident model survey, this thesis investigated the characteristics of accident models applied in five previous accident causation studies, three statistical studies and two case studies. In the investigation, it was found that the statistical studies had not defined an accident model. This together with other methodological deficiencies resulted in the misleading conclusion that human factors are responsible for up to 70-95% of traffic accidents. The two case studies defined detailed accident models, forming the base for their causation analysis methods. However, because of an implemented driver model based on the information-processing concept, the accident models received features resembling the disadvantages of sequential accident models. As a result, every accident was analysed and explained always using the same structure of causation. Further, the results in the form of case reports provided limited possibilities to compare similar accidents and see common causation characteristics, e.g. through comparing contributory factors and their interactions.In the second study of this thesis, a promising method for analysing causation, Driving Reliability and Error Analysis Method (DREAM), was presented and demonstrated in an in-depth investigation of 38 single-vehicle crashes (SVCs). DREAM is based on the principles of systemic accident models. Consequently, DREAM consists of a factor and a linkage structure that is flexible enough to analyse the various types of causation factors that together may contribute to an accident. The result of a DREAM analysis is illustrated as an accident pattern for each accident case. The individual SVCs were compared to distinguish cases with similar crash circumstances. As a result, causation patterns were combined into four scenarios that demonstrate the most frequently occurring factors and links. The four scenarios described in greater detail the factors that contribute to accidents characterised by road departure, slipperiness, excessive speed or excessive driver manoeuvres. Because of the flexible structure, the sequence of a DREAM analysis may first appear abstract and therefore difficult to immediately understand. Consequently, there is a risk that analysts with different competence may produce diversified results. However, this risk will likely be reduced with more distinct factor definitions, education and experience.
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| 7. |
- Sandin, Jesper, 1975, et al.
(författare)
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Understanding the causation of single-vehicle crashes: a methodology for in-depth on-scene multidisciplinary case studies
- 2007
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Ingår i: International Journal of Vehicle Safety. - 1479-3105 .- 1479-3113. ; 2:3, s. 316-333
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of the interaction between and consequences of causation factors is essential when designing active safety measures. There is frequently a lack of adequate details in the area of causation, especially pertaining to Single-Vehicle Crashes (SVCs). This study describes the in-depth and on-scene investigations of 38 SVCs that took place in Gothenburg, Sweden. The causation factors involved were analysed using the Driving Reliability and Error Analysis Method (DREAM). The 38 SVCs were grouped into four scenarios. In the first scenario, vehicles drifted out of lane due to driver fatigue, sleepiness or distraction. In the second, an undetectable reduction in road friction caused experienced drivers to lose control in curves. Loss of control in curves was also a factor in scenario three, partly due to high speed. In this scenario, drivers overestimated their driving skills or had limited experience of the vehicle or the curve. In the final scenario, alarmed drivers lost control as a result of excessive steering-wheel manoeuvres. This study demonstrates a methodology that can be used to explain how a combination of factors may increase the risk of SVCs.
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| 8. |
- WALLÉN WARNER, HENRIETTE, 1972, et al.
(författare)
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Dream 3.0. Documentation of references supporting the links in the classification scheme
- 2008
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Both the Driving Reliability and Error Analysis Method (DREAM; Ljung, 2002) and theSafetyNet Accident Causation System (SNACS; Ljung, 2006) have been successfully used astools for accident analysis in Sweden as well as in other European countries. While the drivervehicle/traffic environment-organisation triad are used as frames of reference and theContextual Control Model (COCOM; Hollnagel, 1998) is used to organise human cognition,the links in the classification schemes have not been established by referring to literature. Theaim of this literature review is therefore to investigate the empirical support for the links inthe classification scheme of DREAM 3.0 (an updated version of DREAM/SNACS).
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| 9. |
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