In the context of this study, different data sources for accident research were examined regarding their possible data access and evaluated concerning the individual quality and extent of the data. Analyses of accidents require detailed and comprehensive information in particular concerning vehicle damages, injury patterns and descriptions of the accident sequence. The police documentation supplies the basic accident statistics and is amended in the context of the forensic treatment by further information, e.g. by medical and technical appraisals and witness questionings. As a new approach to the data acquisition for the analysis of fatal traffic accidents, the information was made usable which was collected by the police and by the investigations of the public prosecutor. The best strategy for obtaining reliable, extensive and complete data consists of combining the information from these two sources: the very complete, but elementary statistic data of the Niedersächsisches Landesamt für Statistik (Lower Saxony State Authority of Statistics), based on the police documentation as well as the very extensive accident information resulting from the investigation documentation of the public prosecutor after conclusion of the procedure, the so-called Court Records. Of all 715 fatal traffic accidents, which happened in the year 2003 in the German State of Lower Saxony, 238 cases were selected by means of a statistically coincidental selective procedure based on a statistically representative manner (every third accident). These cases cover the investigation documents of the 11 responsible public prosecutor- offices, which were requested and evaluated while preserving the data security. Of the 238 cases 202 cases were available, which were individually coded and stored in a data base using 160 variables. Thus a data base of a sample of representative data for fatal accidents in Lower Saxony was set up. The data base contains extensive information concerning general accident data (35 variables), concerning road and road surface data (30 variables), concerning vehicle-specific data (68 variables) as well as concerning personal and injury data (27 variables).
With an ever rising human life expectancy the share of elderly people in society is constantly rising. This leads to the fact that at the same rate the share of people with age related diseases such as dementia and poor eyesight taking part in traffic will rise and therefore traffic accidents caused by this group of people due to the disease will play an ever greater role. This Situation will be among the future challenges of road safety work. At present this study displays specific characteristics of accidents caused by elderly car drivers (aged 65 or higher) based on the analysis of the German In-Depth Accident Study GIDAS. Herein almost 1000 elderly car drivers were identified as accident participants in the years 2008 to 2011. The focus of this study lies on identifying special types of accidents which are caused by elderly drivers and on characterizing these types with the information gathered on scene and by interviewing the participants. The main evidence analyzed is the knowledge about the accident locality, the trajectories of the participants as well as the reasons for the occurrence of the accidents. Furthermore personal information such as the personal condition before the accident and driving purposes is used to identify patterns of contributing circumstances for accidents caused by elderly traffic participants.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.