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Crash data quality for road safety research: Current state and future directions
Marianna Imprialou1, Mohammed Quddus1
1Transport Studies Group, School of Civil and Building Engineering, Loughborough University, Loughborough LE11 3TU, United Kingdom.
Accident; Analysis and Prevention
|March 7, 2017
Summary
Crash data quality is crucial for road safety research accuracy. This review reveals significant issues in crash location, time, and contributing factors, impacting effective safety countermeasures.
Area of Science:
- Road safety
- Transportation engineering
- Data science
Background:
- Crash databases are essential for road safety research.
- Data quality directly impacts the accuracy of crash analyses and countermeasure design.
- Existing research often overlooks or inadequately addresses data correctness and completeness issues.
Purpose of the Study:
- To review the current literature on crash data quality.
- To assess data quality issues concerning the five Ws (When, Where, What, Who, Why) of crashes.
- To identify critical areas for improving crash reporting systems.
Main Methods:
- Literature review of current research on crash data quality.
- Analysis of data quality issues across different crash report attributes.
- Categorization of quality problems based on the five Ws.
Main Results:
- Significant inaccuracies exist in crash location and time data.
- Data linkage challenges arise from database inconsistencies.
- Misclassification of crash severity, incomplete user demographics, and inaccurate identification of contributing factors are prevalent.
- Data quality issues vary in severity and impact across different attributes.
Conclusions:
- Addressing data quality is paramount for reliable road safety analysis.
- Further research is needed to quantify the impact of data quality issues.
- Development of intelligent crash reporting systems is recommended to enhance data accuracy.
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