Helen Fagerlind

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.

On scene injury severity prediction (OSISP) algorithm for car occupants

Many victims in traffic accidents do not receive optimal care due to the fact that the severity of their injuries is not realized early on. Triage protocols are based on physiological and anatomical criteria and subsequently on mechanisms of injury in order to reduce undertriage. In this study the value of accident characteristics for field triage is evaluated by developing an on scene injury severity prediction (OSISP) algorithm using only accident characteristics that are feasible to assess at the scene of accident. A multivariate logistic regression model is constructed to assess the probability of a car occupant being severely injured following a crash, based on the Swedish Traffic Accident Data Acquisition (STRADA) database. Accidents involving adult occupants for calendar years 2003-2013 included in both police and hospital records, with no missing data for any of the model variables, were included. The total number of subjects was 29128, who were involved in 22607 accidents. Partition between severe and non-severe injury was done using the Injury Severity Score (ISS) with two thresholds: ISS>8 and ISS>15. The model variables are: belt use, airbag deployment, posted speed limit, type of accident, location of accident, elderly occupant (>55 years old), sex and occupant seat position. The area under the receiver operator characteristic curve (AUC) is 0.78 and 0.83 for ISS>8 and ISS>15, respectively, as estimated by 10-fold cross-validation. Belt use is the strongest predictor followed by type of accident. Posted speed limit, age and accident location contribute substantially to increase model accuracy, whereas sex and airbag deployment contribute to a smaller extent and seat position is of limited value. These findings can be used to refine triage protocols used in Sweden and possibly other countries with similar traffic environments.

The development of a European fatal accident database

A lack of representative European accident data to aid the development of safety policy, regulation and technological advancement is a major obstacle in the European Union. Data are needed to assess the performance of road and vehicle safety and also to support the development of further actions by stakeholders. A recent analysis conducted by the European Transport Safety Council identified that there was no single system in place that could meet all of the needs and that there were major gaps including in-depth crash causation information. This paper describes the process of developing a data collection and analysis system designed to partly fill these gaps. A project team with members from seven countries was set up to devise appropriate variable lists to collect fatal crash data, using retrospective detailed police reports (n = 1300), under the following topic levels: accident, road environment, vehicle and road user. The typical level of detail recorded was a minimum of 150 variables for each accident. The project will enable multidisciplinary information on the circumstances of fatal crashes to be interpreted to provide information on a range of causal factors and events surrounding the collisions. This has major applications in the areas of active safety systems, infrastructure and road safety, as well as for tailoring behavioural interventions.

Single-Vehicle Collisions in Europe: Analysis Using Real-World and Crash-Test Data

Many European road casualties result from vehicles leaving the road, often impacting roadside obstacles. As part of the European Commission-funded project RISER (Roadside Infrastructure for Safer European Roads), several activities were undertaken to collate the type of real world crash data which is needed to understand single vehicle crash situations and relate this to crash-test data mandated in the European Union. Accident data were collected and used to create databases exclusively for single-vehicle collisions on major rural roads, simulation software was used to further understand impacts with roadside structures, and an inventory of crash-test data was collected for impacts with poles and safety barriers. The combination of accident data, simulations and crash-test data has provided a unique insight into the characteristics of single-vehicle collisions, helping those involved in the design and evaluation of the roadside environment to understand them better and make recommendations for consideration when drafting design guidelines.

Fatal intersection crashes in Norway: Patterns in contributing factors and data collection challenges

Fatal motor vehicle intersection crashes occurring in Norway in the years 2005-2007 were analyzed to identify causation patterns among their underlying contributing factors, and also to assess if the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to do causation pattern analysis. 28 fatal accidents were analyzed. Causation charts of contributing factors were first coded for each driver in each crash using the Driving Reliability and Error Analysis Method (DREAM). Next, the charts were aggregated based on a combination of conflict types and whether the driver was going straight or turning. Analysis results indicate that drivers who were performing a turning maneuver in these crashes faced perception difficulties and unexpected behavior from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers who were going straight on the other hand had less perception difficulties but largely expect any turning drivers to yield, which led to either slow reaction or no reaction at all. In terms of common contributing factors, those often pointed to in literature as contributing to fatal crashes, e.g. high speed, drugs and/or alcohol and inadequate driver training, contributed in 12 of 28 accidents. This confirms their prevalence, but also shows that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, there was an asymmetry in terms of reported obstructions to view due to signposts and vegetation. These were frequently reported as contributing for turning drivers, but rarely reported as contributing for their counterparts in the same crashes. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver held legally liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator approach needs to be addressed to avoid future bias in crash investigation reports.

Prehospital transportation decisions for patients sustaining major trauma in road traffic crashes in Sweden

ABSTRACT Objective: The objective of this study was to evaluate the proportion and characteristics of patients sustaining major trauma in road traffic crashes (RTCs) who could benefit from direct transportation to a trauma center (TC). Methods: Currently, there is no national classification of TC in Sweden. In this study, 7 university hospitals (UHs) in Sweden were selected to represent a TC level I or level II. These UHs have similar capabilities as the definition for level I and level II TC in the United States. Major trauma was defined as Injury Severity Score (ISS) > 15. A total of 117,730 patients who were transported by road or air ambulance were selected from the Swedish TRaffic Accident Data Acquisition (STRADA) database between 2007 to 2014. An analysis of the patient characteristics sustaining major trauma in comparison with patients sustaining minor trauma (ISS < 15) was conducted. Major trauma patients transported to a TC versus non-TC were further analysed with respect to injured body region and road user type. Results: Approximately 3% (n = 3, 411) of patients sustained major trauma. Thirty-eight percent of major trauma patients were transported to a TC, and 62% were transported to a non-TC. This results in large proportions of patients with Abbreviated Injury Scale (AIS) 3+ injuries being transported to a non-TC.  The number of AIS 3+ head injuries for major trauma patients transported to a TC versus non-TC were similar, whereas a larger number of AIS 3+ thorax injuries were present in the non-TC group. The non-TC major trauma patients had a higher probability of traveling in a car, truck, or bus and to be involved in a crash in a rural location. Conclusions: Our results show that the majority of RTC major trauma patients are transported to a non-TC. This may cause unnecessary morbidity and mortality. These findings can guide the development of improved prehospital treatment guidelines, protocols and decision support systems.

A test-based method for the assessment of pre-crash warning and braking systems

In this paper, a test-based assessment method for pre-crash warning and braking systems is presented where the effectiveness of a system is measured by its ability to reduce the number of injuries of a given type or severity in car-to-car rear-end collisions. Injuries with whiplash symptoms lasting longer than 1 month and MAIS2+ injuries in both vehicles involved in the crash are considered in the assessment. The injury reduction resulting from the impact speed reduction due to a pre-crash system is estimated using a method which has its roots in the dose-response model. Human-machine interaction is also taken into account in the assessment. The results reflect the self-protection as well as the partner-protection performance of a pre-crash system in the striking vehicle in rear-end collisions and enable a comparison between two or more systems. It is also shown how the method may be used to assess the importance of warning as part of a pre-crash system.

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures. Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ⩾ 16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC). Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks. Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.

A methodology for improving structural robustness in frontal car-to-car crash scenarios

There has been significant development in passenger car crashworthiness over the last few decades. However, real-world crashes often occur in scenarios dissimilar to laboratory barrier crash set-ups. Further knowledge is required on how different impact scenarios affect vehicle structural response and occupant injury risk in real-world scenarios. This study introduces a methodology for assessing crash configuration parameters that influence the structural response in car-to-car frontal collisions by using finite element models of two identical vehicles. The crash configuration parameters included in this study were initial velocities, oblique angle and lateral offset distance. An evaluation was made in terms of passenger compartment intrusion and crash pulse severity. Special focus was directed towards investigating whether these input parameters can be used to define incompatible scenarios, i.e. where the structural response in one vehicle is significantly different compared to the other vehicle. Results indicate that collision scenarios with large overlap as extreme in terms of crash pulse severity, and incompatible car-to-car crash scenarios were found at small overlap and an oblique angle of 15°. An outlook for future model and method validation work is described.

PW 2207 The hidden figures of major road trauma crashes

Major trauma (MT) from road traffic crashes is a great burden to global health. Analyses of MT using hospital-based samples are normally selected at the patient level using an Injury Severity Score (ISS) above 12 or 15, and in-hospital fatalities. This likely underestimates the number of injured people requiring medical care from MT crashes. The objective was to determine the true number of people injured in MT crashes in Sweden. Data from April 2011 to March 2017 was retrieved from the Swedish Traffic Accident Data Acquisition (STRADA) which is a matched hospital and police national database. First, MT patients were selected from emergency department (ED) data where at least one patient was transported by ambulance with an ISS >12 or died in hospital. Then, matched individuals in the same MT crashes were added to the sample. The sample was based on 2,542 MT patients from 2444 road crashes. An additional 1012 non-MT patients or fatalities were presented to the ED’s. Of these ED patients, 884 (87.4%) were transported by ambulance and 488 (48.2%) were admitted to hospital. The police reported 1,383 MT crash participants beyond those presenting to the ED. In total, there were 4937 road users exposed to a MT crash. The burden of MT crashes on the society and the health care system is much larger when including all road users from these crashes. The matched crash data revealed an increase of ED presentations by 39.8% and ambulance transportations by 34.8%. To understand the full extent of MT crashes, governments need to provide better opportunities for data linkage across authorities to better guide crash and injury prevention.