Assessing the risk of Car Crashes in Road Networks

Diego Zappa, Riccardo Borgoni, Andrea Gilardi

Risultato della ricerca: Contributo in libroChapter

Abstract

Worldwide thousands of people die annually in highway-related crashes and millions are injured. By 2030 highway-related crashes will be the 5-th leading cause of death in the world according to the WHO (Mannering and Bhat, 2014). The statistical analysis of accident data has historically been fundamental to develop road-safety policies aiming at saving lives and reducing injuries severity. In the absence of detailed driving-related data (such as acceleration and braking) and crash-related data (such as those made available from vehicle black-boxes) that would help improve the identification of cause and effect relationships, a large majority of research has addressed the problem in terms of understanding the factors that affect the frequency of crashes, i.e. the number of crashes occurring in some geographical space over some specified time periods.[...]
Lingua originaleEnglish
Titolo della pubblicazione ospiteNew Economic & Statistical Perspectives on Urban and Territorial Themes (NESPUTT 2019). Book of Short Papers and Proceedings
EditorMichelangeli Alessandra Borgoni Riccardo
Pagine1-4
Numero di pagine4
Stato di pubblicazionePubblicato - 2020

Keywords

  • Spatial data
  • Zero inflated regression model

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