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<p>Police accident statistics are an essential basis for road safety work to identify spatial danger spots and for downstream decision-making. Despite their practical importance, however, official (mostly police) statistics on road accidents are criticized as a&#xa0;body of data for road safety work because they only depict a portion of the actual accidents. The systematic recording of accidents in Germany primarily describes accidents involving motor vehicles and fatal accidents, whereby conceptual inadequacies in data collection are partly inherent to the Road Traffic Accident Statistics Act (<i>Straßenverkehrsunfallstatistikgesetz</i>). In contrast, there is no comparably comprehensive and systematic procedure for recording near-misses and potential danger spots, which means that key dangers in road safety work across the board cannot be anticipated. In this article the potential of population-based reporting of danger spots as a&#xa0;supplement to official accident statistics is discussed. Based on a&#xa0;comparison of the results of a&#xa0;face-to-face survey with data from the Accident Atlas (<i>Unfallatlas</i>, 2019–2023) in the vicinity of 13 primary school locations in Dortmund, this study shows that there are both relevant similarities and discrepancies between population-based information on danger spots and police accident statistics. Reports on danger spots from the population are therefore principally plausible and, as a&#xa0;supplement to the official accident statistics, can contribute to improving knowledge and heuristic anticipation of spatial danger spots. Based on these findings, we recommend supplementing municipal road safety work with monitoring measures for reported danger spots, whereby concerted campaigns to report danger spots play an important role in improving data quality. In the long term, binding, possibly legally, specifications of corresponding responsibilities and procedures could contribute to improving systematic data collection.</p>

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Amtliche Verkehrsunfallstatistik im Vergleich mit einer proaktiven Bevölkerungserhebung über wahrgenommene Gefahrenstellen, Beinaheunfälle und Unfälle am Beispiel von Dortmund

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  • 发表日期：

    2026年1月22日

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  • David J. Hölzel,
  • Franziska Jonas,
  • Niklas Artmann,
  • Sophie Boniface,
  • Joachim Scheiner

摘要

Police accident statistics are an essential basis for road safety work to identify spatial danger spots and for downstream decision-making. Despite their practical importance, however, official (mostly police) statistics on road accidents are criticized as a body of data for road safety work because they only depict a portion of the actual accidents. The systematic recording of accidents in Germany primarily describes accidents involving motor vehicles and fatal accidents, whereby conceptual inadequacies in data collection are partly inherent to the Road Traffic Accident Statistics Act (Straßenverkehrsunfallstatistikgesetz). In contrast, there is no comparably comprehensive and systematic procedure for recording near-misses and potential danger spots, which means that key dangers in road safety work across the board cannot be anticipated. In this article the potential of population-based reporting of danger spots as a supplement to official accident statistics is discussed. Based on a comparison of the results of a face-to-face survey with data from the Accident Atlas (Unfallatlas, 2019–2023) in the vicinity of 13 primary school locations in Dortmund, this study shows that there are both relevant similarities and discrepancies between population-based information on danger spots and police accident statistics. Reports on danger spots from the population are therefore principally plausible and, as a supplement to the official accident statistics, can contribute to improving knowledge and heuristic anticipation of spatial danger spots. Based on these findings, we recommend supplementing municipal road safety work with monitoring measures for reported danger spots, whereby concerted campaigns to report danger spots play an important role in improving data quality. In the long term, binding, possibly legally, specifications of corresponding responsibilities and procedures could contribute to improving systematic data collection.