Objectif
The project objective is to design an accident documentation process for in-depth accident data collection and analysis to be able to asses future developments in traffic safety.
The objectives of ITHACA are to consider theory of accident factors, in particular as they are related to the human factors, in the accident causation process, to define the state of the art (accuracy, consistency of data) and requirements for the use of accident information, to define a new common prototype proforma which can be used by the European Community for in depth accident data collection and to build a prototype expert system for in depth accident investigations concentrating on human factors.
On the basis of literature studies and active accident investigations by police, car/insurance companies and in depth teams a prototype of a new European accident protocol for in depth investigations will be developed, containing road transport informatics (RTI) relevant parameters. Within the parameters the focus lies on human factors and on the precrash phase. Human factors are the main reasons in the accident influence field. The main effort of this project is the development of a knowledge based system (expert system) for accident data analysis.
The project concentrates on in depth investigations with limited accident data collection. It is designed to set up a very small data bank that can be used to illustrate the possibilities of a knowledge based system for the evaluation of safety impacts of new RTI-components.
A prototype was made available on 01/09/92
Information on the accident risk potential of driving tasks and of traffic situations is of great relevance to the development, evaluation and implementation of safety related road transport informatics (RTI) measures. This research was into the design of a European proforma for in depth accident data collection. In depth accident investigations are intended to collect detailed information on factors contributing to accidents via a trained team of experts from different disciplines at the scene of an accident.
We adopted a generic approach of looking at all associated factors and phases of accidents. The emphasis, however, lay on human factors and the precrash phase of the accident. A new prototype accident data collection proforma basedon a multilevel, modular structure for the required variables was proposed. The prototype proforma will serve as a basis for the design of a new panEuropean disaggregate accident data collection proforma.
Many in depth accident studies are carried out in order to reveal not only where the transportation system failed, but also what exactly failed and why parts of the system failed. The aim of this research was to develop a method, supported by a computer expert system, of clarifying the causation of road accidents. The starting point in our study is the system view in which we consider the human operator interacting with the other components such as the environment and the vehicle. In the transportation system all human participants work towards a common goal; to travel from one place to another. This teleological viewpoint can also be found in the task driven approach that we used in the accident analyses.
In order to reach his or her goal and to arrive safely at the place he or she had planned to travel to the road user has to carry out several traffic tasks. Apart from more strategic considerations such as route choice the road user will be concerned with the execution of several manoeuvres during his or her participation in the transportation system. Task analyses prescribe hierarchically ordered rules for carrying out the manoeuvres. These rules (tasks) are incorporated into the expert system and are used by the system as a frame of reference in the analysis of individual accidents.
The first working prototype expert system was limited to the analysis of individual accidents, however, the development of a method for aggregated accident analysis, in which the outcomes of the individual analyses will act as input, is underway.
A new task model was developed to overcome deficiencies in older task models and this new model has become an important part of the developed task driven analysis. The task driven analysis was found to be most fruitful as a method for analyzing accidents at a microscopic level. In task driven analysis risk variables are directly linked with human task performance. With the help of this method, that has been implemented in the protot ype expert system, the relationship between human, vehicle, environment, road factors and the accident can be made clear. These relationships are especially relevant for designers of road transport informatics (RTI) systems who have to know when and how their systems should support the road user in the road traffic system.
The work will encompass the following areas:
- Requirements for in-depth data collection and analysis in view of potential user groups.
- Analysis potential of existing in-depth accident data collection methods.
- Development of a new European proforma in modular structure for in-depth accident investigation.
- A prototype road expert system for road accident data in-depth studies.
Main Deliverables:
Reference proforma for in-depth accident investigation.
Prototype expert system for in-depth accident data analysis.
Champ scientifique (EuroSciVoc)
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CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN. Voir: Le vocabulaire scientifique européen.
- sciences naturelles informatique et science de l'information science des données
- lettres langues et littérature études littéraires
- sciences naturelles informatique et science de l'information intelligence artificielle systèmes experts
- sciences sociales géographie sociale et économique transport
- sciences sociales psychologie psychologie ergonomique
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