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Road traffic safety framework

Başlık çevirisi mevcut değil.

  1. Tez No: 400771
  2. Yazar: AHMET YILDIZ
  3. Danışmanlar: DR. GEORG HAUGER, DR. GERALD FUTSCHEK
  4. Tez Türü: Doktora
  5. Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2009
  8. Dil: İngilizce
  9. Üniversite: Technısche Unıversıtat Wıen
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: Belirtilmemiş.

Özet

Özet yok.

Özet (Çeviri)

Road safety is an important issue, with the aim to reduce the number of accidents, resulting injuries and fatalities in particular. An important aspect hereby is the condition of the road, because they can cause accidents and can also aggravate the consequences of an accident. In this area of road safety research, computer technologies are currently used only on a small scale. In this work, a road safety framework is introduced that uses methods and technologies from Computer Science to capture relevant data for research and development and to store it effectively, both for administrative as well as research purposes. During data acquisition, the road condition presents the primary source of information. This is captured by performing so-called Road Safety Inspections (RSI), which are generally being carried out manually. During the course of this thesis, a software has been developed to enable computer-aided RSI's, thereby helping to reduce the costs and to provide much more accurate data that is most importantly easy to process. To save this data and to link it to other important data such as weather, accident or trafficconflict data, a Data Warehouse is needed. A Data Warehouse is a database designed for analysis, which is used especially by the industry for market research. The use of a Data Warehouse brings about new opportunities for road safety research, some of which are demonstrated in this thesis using extensive accident data from the U.S.. On the one hand, five well-known hypotheses were examined that made clear the importance of current (updated) data. On the other hand, the existing data was automatically analyzed using a statistical method to obtain previously unknown knowledge, without the need to define a hypothesis prior to the analysis. The thesis concludes with the recommendation that computer scientists and traffic planners should work together, whereas the implementation of the introduced framework is definitely a starting point for such a cooperation.

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