Imprialou & Quddus Crash data for road safety research_current state and future directions.pdf (214.53 kB)
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Crash data quality for road safety research: current state and future directions

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journal contribution
posted on 17.03.2017 by Marianna Imprialou, Mohammed Quddus
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.

History

School

  • Architecture, Building and Civil Engineering

Published in

Accident Analysis and Prevention

Volume

130

Issue

September 2019

Pages

84 - 90

Citation

IMPRIALOU, M-I. and QUDDUS, M.A., 2017. Crash data quality for road safety research: current state and future directions. Accident Analysis and Prevention, 130 (September 2019), pp.84-90.

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

22/02/2017

Publication date

2017-03-03

Notes

This paper was published in the journal Accident Analysis and Prevention and the definitive published version is available at http://dx.doi.org/10.1016/j.aap.2017.02.022.

ISSN

0001-4575

Language

en

Exports