Literature DB >> 28262098

Crash data quality for road safety research: Current state and future directions.

Marianna Imprialou1, Mohammed Quddus2.   

Abstract

Crash databases are one of the primary data sources for road safety research. Therefore, their quality is fundamental for the accuracy of crash analyses and, consequently the design of effective countermeasures. Although crash data often suffer from correctness and completeness issues, these are rarely discussed or addressed in crash analyses. Crash reports aim to answer the five "W" questions (i.e. When?, Where?, What?, Who? and Why?) of each crash by including a range of attributes. This paper reviews current literature on the state of crash data quality for each of these questions separately. The most serious data quality issues appear to be: inaccuracies in crash location and time, difficulties in data linkage (e.g. with traffic data) due to inconsistencies in databases, severity misclassification, inaccuracies and incompleteness of involved users' demographics and inaccurate identification of crash contributory factors. It is shown that the extent and the severity of data quality issues are not equal between attributes and the level of impact in road safety analyses is not yet entirely known. This paper highlights areas that require further research and provides some suggestions for the development of intelligent crash reporting systems.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords:  Accident analysis; Accident data; Crash data quality; Crash police reports; Crash severity; Road safety

Mesh:

Year:  2017        PMID: 28262098     DOI: 10.1016/j.aap.2017.02.022

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

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Authors:  Arshad Jamal; Muhammad Tauhidur Rahman; Hassan M Al-Ahmadi; Umer Mansoor
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2.  Associations between vision impairment and driving and the effectiveness of vision-related interventions: protocol for a systematic review and meta-analysis.

Authors:  Helen Nguyen; Gian Luca Di Tanna; Kristy Coxon; Julie Brown; Kerrie Ren; Jacqueline Ramke; Matthew J Burton; Iris Gordon; Justine H Zhang; João M Furtado; Shaffi Mdala; Gatera Fiston Kitema; Lisa Keay
Journal:  BMJ Open       Date:  2020-11-05       Impact factor: 2.692

Review 3.  State-of-the-art review: preventing child and youth pedestrian motor vehicle collisions: critical issues and future directions.

Authors:  Marie-Soleil Cloutier; Emilie Beaulieu; Liraz Fridman; Alison K Macpherson; Brent E Hagel; Andrew William Howard; Tony Churchill; Pamela Fuselli; Colin Macarthur; Linda Rothman
Journal:  Inj Prev       Date:  2020-11-04       Impact factor: 2.399

4.  Validating a Traffic Conflict Prediction Technique for Motorways Using a Simulation Approach.

Authors:  Nicolette Formosa; Mohammed Quddus; Alkis Papadoulis; Andrew Timmis
Journal:  Sensors (Basel)       Date:  2022-01-12       Impact factor: 3.576

  4 in total

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