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<p>In order to make road traffic safer and diminish the number of accident injuries and fatalities, there is a growing expectation that road accidents should be explored as thoroughly as possible. To measure the success of such explorations, this paper applies the concept of “assessability” of accidents, which shows how well an accident process can be reconstructed and how surely the liability for an accident can be determined. The success of assessment largely depends on the data available for experts. Although data recording technologies are constantly developing, no method is available to measure how much this technological advancement actually improves accident assessability. In the lack of such a methodology, it is impossible to set the societally most fruitful directions of technical development. The aim of this study is to propose a methodology to quantify how the application of modern data recording technologies increase the assessability of various accident categories, applying an ordered logit regression model. The methodology is demonstrated using accident data collected in Hungary between 1998 and 2022, and the results show that the different accident data recording technologies affect the assessability of various accident categories to differing degrees, which may set the future directions for developing data recording methods in the automotive industry.</p>

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Effects of developing data recording technologies on the reliability of accident reconstruction and liability determination

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月27日

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  • Gábor Vida,
  • Árpád Török

摘要

In order to make road traffic safer and diminish the number of accident injuries and fatalities, there is a growing expectation that road accidents should be explored as thoroughly as possible. To measure the success of such explorations, this paper applies the concept of “assessability” of accidents, which shows how well an accident process can be reconstructed and how surely the liability for an accident can be determined. The success of assessment largely depends on the data available for experts. Although data recording technologies are constantly developing, no method is available to measure how much this technological advancement actually improves accident assessability. In the lack of such a methodology, it is impossible to set the societally most fruitful directions of technical development. The aim of this study is to propose a methodology to quantify how the application of modern data recording technologies increase the assessability of various accident categories, applying an ordered logit regression model. The methodology is demonstrated using accident data collected in Hungary between 1998 and 2022, and the results show that the different accident data recording technologies affect the assessability of various accident categories to differing degrees, which may set the future directions for developing data recording methods in the automotive industry.