TITLE:
Evaluating the Accuracy and Reliability of Police-Reported Crash Data: A Comparative Analysis of Crash Reports and Visual Evidence from Crash Videos
AUTHORS:
Adnan Inusah, Jonathan S. Wood, Shauna Hallmark, Guillermo Basulto-Elias
KEYWORDS:
Crash Reporting, Crash Data Accuracy, Video Analytics, Reporting Bias
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.16 No.3,
July
10,
2026
ABSTRACT: Police-reported crash data are essential for transportation safety analysis, but their utility is often hampered by issues including underreporting and inconsistencies. Comparing crash videos with police reports provides a valuable method for identifying these discrepancies and improving data accuracy. This study identifies discrepancies in police reports by comparing them to crash videos. Iowa crash reports were compared to videos from the Iowa Advanced Traffic Management System (ATMS) for 2022. A spatiotemporal matching approach was used. Key crash elements were manually reduced from corresponding videos and compared to those from the corresponding crash reports. The accuracy of each element, along with its 95% confidence interval, was computed. Crash elements observable on-site, such as environmental conditions, light conditions, and vehicle damage, demonstrated high accuracy levels. Elements requiring inference and reliance on witness accounts, such as the manner of crash or collision, the first harmful event, and the sequence of events during the incident, showed lower accuracy and greater variability. The results highlight inconsistencies in derived elements, particularly the major cause of the crash, which relies on the accuracy of the elements it is derived from. These findings underscore the benefit of incorporating video data into crash data workflows to enhance reporting accuracy and reliability. Policymakers and safety professionals can use the insights on these inconsistencies to improve traffic safety measures and make informed decisions. Additionally, outcomes can be used to help train officers in coding crash reports. This study highlights the importance of developing systematic methods to integrate multiple data sources for improved traffic safety analytics.