Analyzing human factors in road accidents: TRACE WP5 Summary Report

The main objectives of TRACE WP5 'Human factors' deliverables are: i) To support a better standardization of accident analysis in Europe on a scientific background, ii) To provide operational models and methodological classification grids dealing with 'human factors' aspects involved in road accidents, iii) To promote a comprehensive analysis of the involvement of human beings, going further than the usual 'user-orientated causal analysis' often limited at establishing the driver 'at fault' and without searching for the background reasons of the problems met par road users. Such objectives involve analyzing accidents as the symptom of the difficulties met by drivers in certain driving situations, and as a revelatory of their needs in help. Two questions have to be asked in order to progress in the understanding of accident causation: 1) What are precisely and operationally the human failures in accidents? But also: 2) What are the reasons for these human failures? Keeping in mind that these reasons are of multiple natures and combine most of the time to produce the final event. By so doing, the definition of typical scenarios of 'human error' production can open to the definition of more appropriate countermeasures, well fitted to human needs

Which factors and situations for human functional failures? Developing grids for accident causation analysis

This report describes the work undertaken in Task 5.2 of the TRACE project. Human failures are explained by factors characterizing the state of the system and of their interactions. A grid of factors which could lead to these human functional failures is given along with a grid of pre-accident driving situations. In addition to this, an overview is included of the background work undertaken to establish a methodology for classification of these factors and situations. Factors related to the ‘User’, ‘Vehicle’ and ‘Environment’ are described and classifications for use at a ‘descriptive’, ‘generic’ and ‘in-depth’ level are determined, to allow analysis at different levels of detail of accident data. These factors and situations will be used along with the Task 5.1 functional failures to help identify typical failure generating scenarios in Task 5.3, and the subsequent analysis of real world accident data in other work packages in TRACE. They will also be a useful basis for future improvements in the collection of accident causation data, avoiding the common over simplification whereby road users are seen as the main reason for the ‘failure’ in the accident scenario

An analysis of speed related UK accidents using a human functional failure methodology

Accidents involving either illegal or inappropriate speeding play a part in a large proportion of accidents involving cars. The types of typical failure generating scenarios found in car accidents where illegal speeding or inappropriate speeding is contributory are compared using the detailed human functional failure methodology developed in the European TRACE project (TRaffic Accident Causation in Europe), funded by the European Commission. Using on-scene cases from the UK ‘On The Spot’ database (funded by the UK Department for Transport and Highways Agency), a sample of cases where speed is contributory have been analysed. An overview of speeding cases from the 4,000 in-depth cases available in the dataset is also presented. The results highlight not only the differences between inappropriate and illegal speeding cases, but also the differences in the functional failures experienced by both the ‘at fault’ and ‘not at fault’ road users in both types of speed-related accidents. The results form a unique base of knowledge for future work on the human-related issues associated with speeding of both types, for all crash participants. Also considered is how new technologies can address speeding accidents

Trip related factors

WP3 of the European Project TRACE is concerned with Types of Factors to analyse the causation of road traffic accidents from a factors' point of view. In task 3.3 'Trip-related Factors' it was tried to characterise accidents that are caused by certain contributing factors found on a trip level. This was done by applying one statistical method to existing databases of the WP3 Partners on the one hand and on the other hand by performing an in-depth case analysis using the WP5 method. The analysed factors stem from the Human Component of the accident causation classification, namely "alcohol", "vigilance", and "experience", from the Vehicle Component, namely "vehicle condition/maintenance", and from the Environment component, namely "road layout" and "road condition". This selection resulted from the task 3.1 conclusions and feasibility reasons. Due to inhomogeneous results for the databases from Austria, France, Germany, Great Britain, and Spain the detailed results will be pictured in an Internal TRACE Report by Sub-reports of the WP3 Partners, in this task report the main results are discussed with respect to findings and data in other databases available to the TRACE partners as requested from WP8. Both methods applied show that trip-related factors are possible to prevent not on a trip level only, but also from a background level and as well on a level closer to the accident (driving task level). However, only some suggestions are possible to give by these results. A more detailed view for preventing the different accidents that result from trip-related factors is necessary, as shown by the results of BASt with the statistic method, as well as by INRETS with the ultra in-depth WP5 method

Summary report on work package 3 "Types of Factors"

This summary report presents the main results of Work Package 3 "Types of Factors" of the TRACE Project. The work as performed in the tasks 3.1 (accident related factors), 3.2 (sociological and cultural factors), 3.3 (trip-related factors), and 3.4 (driving-task associated factors) and presented in the Deliverables 3.1 to 3.4 and an additional internal TRACE Report (Collection of Sub-Reports for task 3.3) is summarized and discussed. The objective of defining relevant accident related factors first and the objective of analysing traffic accident causation - from a factor's point of view while taking traditional views into account - on different levels - by using statistic methods for existing databases as provided by the Work Package 3 Partners and - by using new (developed in Work Package 5 of the TRACE project) methods on new case analysis in order to gain new knowledge on accident causation was possible to reach. The scope of the identified key aspects as found by the Partners in their work for the relevance in EU27 is discussed. In accordance, even further, appropriate suggestions for prevention of traffic accidents can be derived

Driving task-related factors

Driving task-related factors by definition are ‘directly and causally contributing to the accident occurrence, very specific and detailed, are short-term lasting or dynamic in nature, and refer to the actual conditions of the components’. The aim was to analyse specific driving task-related factors to investigate how these type of factors affect the driver undertaking their tasks within driving. A selection of driving task-related factors were chosen and analysed using two types of analysis; by a statistical method and by an in-depth methodology developed in TRACE. Typical characteristics of these accidents were identified, and for a number of factors, typical failure generating scenarios were also identified. From this, a list of possible countermeasures were defined with the aim of preventing such accidents occurring. These included driver education, in-vehicle technologies and design issues. Finally, benefits and limitations of the analysis undertaken are given, with recommendation for future work on driving task-related factors

Reconsidering accident causation analysis and evaluating the safety benefits of technologies: final results of the TRACE project

The objectives of the EU-funded project TRACE (TRaffic Accident Causation in Europe, 2006-2008) are the up-dating of the etiology of road accidents and the assessment of the safety benefits of promising technology-based solutions. The analyses are based on available, reliable and accessible existing databases (access to which has been greatly facilitated by a number of partners highly experienced in safety analysis, coming from 8 different countries and having access to different kinds of databases, in-depth or regional or national statistics in their own country). Apart from considerable improvements in the methodologies applicable to accident research in the field of human factors, statistics and epidemiology, allowing a better understanding of the crash generating issues, the TRACE project quantified the expected safety benefits for existing and future safety applications. As for existing safety functions or safety packages, the main striking results show that any increment of a passive or active safety function selected in this project produces additional safety benefits. In general, the safety gains are even higher for higher injury severity levels. For example, if all cars were Euro NCAP five stars and fitted with EBA and ESC, compared to four stars without ESC and EBA, injury accidents would be reduced by 47%, all injuries would be mitigated by 68% and severe + fatal injuries by 70%. As for future advanced safety functions, TRACE investigated 19 safety systems. The results show that the greatest additional safety gains potential are expected from intelligent speed adaptation systems, automatic crash notification systems, and collision warning and collision avoidance systems. Their expected benefits (expected reduction in the total number of injured persons if the fleet is 100% equipped) are between 6% and 11%. Safety benefits of other systems are more often below 5%. Some systems have a very low expected safety benefit (around or less than 1%)

Review of current in-vehicle safety systems and related data sources

When considering how safety systems fulfil drivers' needs, leading to an evaluation of overall benefit, it is important to understand the overall functionality of the system, take into account as many design parameters as possible and consider previous evaluation work. The objective of this research is to provide an inventory of in-vehicle technological systems that are present on current production models, using a standard template. A catalogue listing details such as the aim of the system, the functions covered by the system, phase of the accident upon which the system is acting, the level of intervention, technical specifications and previous evaluations is developed for 31 active, passive and integrated safety systems and the example of the Adaptive Cruise Control system is presented in this paper. Moreover, a review of existing identification procedures related to safety systems is carried out, aiming to underline the available information sources that could be used to gather data on safety equipment using a common format, review the variable level of quality and the feasibility and length of time that it would take to collect the data. Results revealed that although there are many different implementations of safety systems with different performance parameters, the development of a safety systems inventory can become a useful tool for analysts to establish a feel for a generic system, project the functionality of such a system onto available accident data and importantly to evaluate if the system really meets drivers' needs. The use of an assembled standard template can further act as a central register, in which analysts can quickly acquire detailed information on the system along with web links to vehicle manufacturer, governmental, safety and research organization websites. Furthermore, two main safety systems data collection methods were identified through the review of different data sources, either using the make/model/ variant approach or the VIN number method, demonstrating the feasibility of recording all active, passive and integrated safety systems implemented within a vehicle to a European wide database. This work has been undertaken in the EC funded DaCoTA project

European road safety and e-safety

The objective of this research is to develop and describe a methodology that allows building the structure of a European Road Safety Observatory (ERSO) that addresses these e-safety issues, identify the nature of the data that has to be stored in such an observatory, in a way that it is easily interpretable and usable, and finally to implement suitable methods for appropriate e-safety data analyses that will assess the most promising technological counter-measures. For this reason, a five-step methodology is developed. The analysis revealed that a well matched statistical analysis model is necessary for quantitative assessment of the e-Safety systems, indicating whether they address the real users’ needs revealed by the causation analysis. The expansion of the current benefits figures to an EU level and the analysis of the interactions between technology-based applications are considered to be the fundamental plinth upon which the relevant structure and data of ERSO are determined