Jesper Sandin

An analysis of common patterns in aggregated causation charts from intersection crashes

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.

Understanding the Causation of Single-Vehicle Crashes: A Methodology for In-Depth On-Scene Multidisciplinary Case Studies

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.

Accident investigations for active safety at CHALMERS - new demands require new methodologies

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.

Accident models for modern road traffic: changing times creates new demands

The purpose of this study is to develop accident models that can be applied to modern road traffic. Several criteria are proposed that a model suitable for the conditions of modern road traffic should fulfill. Four commonly applied general accident models are reviewed, and found to be inadequate in relation to the criteria. Also, the consequences of an underlying structural problem in all four model types, which is the result of regarding the human as a system component, are discussed. To remedy the discovered problems, it is argued that traffic safety should make use of the developments that have been made in the field of industrial safety. Several suggestions are proposed for how a new model could be developed, based on experiences from industrial safety.