Traffic-accident data system

SNRA has a Traffic-Accident Data System at its disposal. It is used to store all police-reported traffic crashes on the government and municipal road and street network. The following types of information are stored about each accident ... 

Within aviation, analyzing the exact causes of accidents and incidents is a nontrivial task. Even if detailed flight data from the black box are available, it is usually still difficult to come up with a clear analysis, for the simple reason that the causes of incidents cannot be attributed to a single point of failure of one individual entity. Instead, most incidents in aviation are found to be caused by a complex interplay of processes at various levels of the socio-technical system, involving pilots, air traffic controllers, technical systems, and their interaction. For example the famous accident in 2009 of Air France Flight 447 is stiU under investigation and seems to have been the consequence of a rare combination of factors. On May 31, 2009, this flight disappeared... 

Given the objective of prospective evaluation regarding the overall effectiveness of a measure of active safety representative for a traffic system, the methods discussed above— ranging from analysis of accident data bases to sophisticated case-by-case simulations—do not seem to be adequate. Mass simulations covering all relevant varieties (e.g., due to human behavior) as weU as imcertainties in different situations offer an approach to meet this objective. 

The individual accidents are grouped into so-caUed reference scenarios . Reference scenarios are defined as a limited number of scientifically derived traffic situations that represent a major part of the real traffic system [2]. Basis for the construction of reference scenarios are in this case in-depth accident data. A detailed description of the data sources, the development of the methodology as well as the results can be found in [2 ]. The grouping uses parameters that have a high influence on the genesis of the critical situation and describe the pre-crash phase in a meaningful way. In the case of pedestrian accidents the key criteria are ... 

An important consideration for the process chain is that traffic accidents are statistically rare events and that each accident is a unique event (see Chap. 1). Detailed accident data are available in various databases and are very helpful in determining the potential of safety measures. However, critical traffic situations or near-accidents are not included in any representative databases. Field Operational Tests, like eu-roFOT [22], or Naturalistic Driving Studies, like the 100-Car Naturalistic Driving Study [23], collect data of such events, but often lack representativity for the traffic system as a whole. A possible solution can be provided, for example, by methods such as fault-tree analysis (see [24, 25]) and stochastic simulation. The simulation described in the following is a stochastic simulation, as many of the subprocesses involved include distributed parameters, which are hard to account for, e.g., in a fault-tree analysis. 

Another caveat is the definition of a crash and or injury. For example, one of the more common definitions, used in the U.S. Fatal Analysis System, for a fatal traffic accident is a police-reported crash involving a motor vehicle in transport on a trafficway in which at least one person dies within 30 days of the crash. (NHTSA, 2000). Not all coimtries limit recorded crashes in their data files to ones occurring on public roads (by including crashes off the road... 

Probable interaction effects with other measures can mask the investigated effect To this end, possible confounders have to be known and controlled (e.g., belt-use rates, presence of other systems with similar functions and/or effects) [16, 19]. The control of confounders is only possible, if those are available in the data sets used. Interaction effects and confounders are even harder to control for, if the data cover a large span in time and the internal influences on traffic and/or accidents may change in that period [12],... 

Software is without doubt an important element in our Kves. Software systems are present in air traffic control systems, banking systems, manufacturing, nuclear power plants, medical systems, etc. Thus, software failures can have serious consequences customer annoyance, loss of valuable data in information systems accidents, and so forth, which can result in millions of dollars in lawsuits. Hence, software development needs to be optimized, monitored, and controlled. 

Other users who can use units of this type are the surgery wards in hospitals, the computer units in traffic control and financial institutions, and the systems of emergency lighting in public spaces. Uninterruptible power is needed here to prevent loss of lives, severe accidents, or loss of valuable data that sometimes may not be recoverable. 

The historic overview clearly shows that a wide range of perspectives has been applied in risk assessments for maritime transportation. Most of the work is rooted in the idea that a true, mind-independent risk exists in line with realist perspectives on the continuum of Table 1. Using different modeling approaches, the majority of the methods aim to estimate this true risk. While the use of expert judgment has gained steady support, many of the applications rely heavily on accident and traffic data. Even when judgment is applied, it is considered to be truth-oriented. From the overview, it is also found that constructivist views, where the assessment is seen rather as a reflection of an assessor s interpretation of the system risk, are rare. The uncertainty view, where an assessor expresses his uncertainty about the occurrence of events and consequences, is not found in the application area. 

The FHWA therefore has to rely on a variety of sources of information. First, they have data on accidents obtained from reports filed by attending police officers. Second, they have access to traffic violations written by police officers. Third they have complaints submitted by members of the public. Fourth they have local "intelligence" from their own inspectorate. Fifth, they have some idea of the "profile" of poor carriers such as size, corporate structure, and the type of work they are engaged in. Sixth they have the Safety Audits described earlier in the chapter. Finally there is a system of uniform inspections of vehicles and drivers which are conducted at the roadside. Over one-and-a-half million trucks are inspected each year. Many are conducted at existing weigh stations where all trucks are required to stop when stations are open. Other vehicles are pulled over by specialist officers who patrol in cars. 

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