Mapping patterns and characteristics of fatal road accidents in Israel

Carlo Giacomo Prato, Victoria Gitelman, Shlomo Bekhor

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    This paper intends to provide a broad picture of traffic accidents in Israel by uncovering their patterns and determinants in order to answer an increasing need of designing preventive measures, addressing particular situations and targeting specific social groups with the ultimate objective of reducing the number of traffic fatalities and accidents. The analysis focuses on 1,793 fatal accidents occurred during the four-year period between 2003 and 2006, and applies data mining techniques with the objective of extracting from the data relevant information about accident patterns and major factors without a priori assumptions about the expected outcome of the study. Kohonen neural networks reveal five accident patterns: (i) single-vehicle accidents of young drivers; (ii) multiple-vehicle accidents between young drivers; (iii) accidents involving either motorcycles or bicycles; (iv) accidents where elderly pedestrians crossed in urban areas; (v) accidents where mostly young children and teenagers cross roads in small villages. Feed-forward back-propagation neural networks indicate that demographic characteristics of both victims and drivers are the most relevant determinants, and other significant factors are the road conditions, the accident location in either urban or rural areas, the accident location in either sections or intersections, and the period of the day when the crash occurs.
    Original languageEnglish
    Title of host publicationProceedings of the 12th WCTR Conference
    Publication date2010
    Publication statusPublished - 2010
    Event12th World Conference on Transportation Research - Lisbon, Portugal
    Duration: 11 Jul 201015 Jul 2010
    Conference number: 12
    http://www.wctrs.org/index.php?option=com_content&task=view&id=39&Itemid=60

    Conference

    Conference12th World Conference on Transportation Research
    Number12
    CountryPortugal
    CityLisbon
    Period11/07/201015/07/2010
    Internet address

    Cite this

    Prato, C. G., Gitelman, V., & Bekhor, S. (2010). Mapping patterns and characteristics of fatal road accidents in Israel. In Proceedings of the 12th WCTR Conference
    Prato, Carlo Giacomo ; Gitelman, Victoria ; Bekhor, Shlomo. / Mapping patterns and characteristics of fatal road accidents in Israel. Proceedings of the 12th WCTR Conference. 2010.
    @inproceedings{46044b33bed24c9a8bfcf5814ac731bf,
    title = "Mapping patterns and characteristics of fatal road accidents in Israel",
    abstract = "This paper intends to provide a broad picture of traffic accidents in Israel by uncovering their patterns and determinants in order to answer an increasing need of designing preventive measures, addressing particular situations and targeting specific social groups with the ultimate objective of reducing the number of traffic fatalities and accidents. The analysis focuses on 1,793 fatal accidents occurred during the four-year period between 2003 and 2006, and applies data mining techniques with the objective of extracting from the data relevant information about accident patterns and major factors without a priori assumptions about the expected outcome of the study. Kohonen neural networks reveal five accident patterns: (i) single-vehicle accidents of young drivers; (ii) multiple-vehicle accidents between young drivers; (iii) accidents involving either motorcycles or bicycles; (iv) accidents where elderly pedestrians crossed in urban areas; (v) accidents where mostly young children and teenagers cross roads in small villages. Feed-forward back-propagation neural networks indicate that demographic characteristics of both victims and drivers are the most relevant determinants, and other significant factors are the road conditions, the accident location in either urban or rural areas, the accident location in either sections or intersections, and the period of the day when the crash occurs.",
    author = "Prato, {Carlo Giacomo} and Victoria Gitelman and Shlomo Bekhor",
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    language = "English",
    booktitle = "Proceedings of the 12th WCTR Conference",

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    Prato, CG, Gitelman, V & Bekhor, S 2010, Mapping patterns and characteristics of fatal road accidents in Israel. in Proceedings of the 12th WCTR Conference. 12th World Conference on Transportation Research, Lisbon, Portugal, 11/07/2010.

    Mapping patterns and characteristics of fatal road accidents in Israel. / Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo.

    Proceedings of the 12th WCTR Conference. 2010.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    TY - GEN

    T1 - Mapping patterns and characteristics of fatal road accidents in Israel

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    AU - Gitelman, Victoria

    AU - Bekhor, Shlomo

    PY - 2010

    Y1 - 2010

    N2 - This paper intends to provide a broad picture of traffic accidents in Israel by uncovering their patterns and determinants in order to answer an increasing need of designing preventive measures, addressing particular situations and targeting specific social groups with the ultimate objective of reducing the number of traffic fatalities and accidents. The analysis focuses on 1,793 fatal accidents occurred during the four-year period between 2003 and 2006, and applies data mining techniques with the objective of extracting from the data relevant information about accident patterns and major factors without a priori assumptions about the expected outcome of the study. Kohonen neural networks reveal five accident patterns: (i) single-vehicle accidents of young drivers; (ii) multiple-vehicle accidents between young drivers; (iii) accidents involving either motorcycles or bicycles; (iv) accidents where elderly pedestrians crossed in urban areas; (v) accidents where mostly young children and teenagers cross roads in small villages. Feed-forward back-propagation neural networks indicate that demographic characteristics of both victims and drivers are the most relevant determinants, and other significant factors are the road conditions, the accident location in either urban or rural areas, the accident location in either sections or intersections, and the period of the day when the crash occurs.

    AB - This paper intends to provide a broad picture of traffic accidents in Israel by uncovering their patterns and determinants in order to answer an increasing need of designing preventive measures, addressing particular situations and targeting specific social groups with the ultimate objective of reducing the number of traffic fatalities and accidents. The analysis focuses on 1,793 fatal accidents occurred during the four-year period between 2003 and 2006, and applies data mining techniques with the objective of extracting from the data relevant information about accident patterns and major factors without a priori assumptions about the expected outcome of the study. Kohonen neural networks reveal five accident patterns: (i) single-vehicle accidents of young drivers; (ii) multiple-vehicle accidents between young drivers; (iii) accidents involving either motorcycles or bicycles; (iv) accidents where elderly pedestrians crossed in urban areas; (v) accidents where mostly young children and teenagers cross roads in small villages. Feed-forward back-propagation neural networks indicate that demographic characteristics of both victims and drivers are the most relevant determinants, and other significant factors are the road conditions, the accident location in either urban or rural areas, the accident location in either sections or intersections, and the period of the day when the crash occurs.

    M3 - Article in proceedings

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    ER -

    Prato CG, Gitelman V, Bekhor S. Mapping patterns and characteristics of fatal road accidents in Israel. In Proceedings of the 12th WCTR Conference. 2010