Accuracy of Mobile Phone LiDAR on Crashed Vehicles

2025-01-8692

04/01/2025

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
Apple’s mobile phone LiDAR capabilities can be used with multiple software applications to capture the geometry of vehicles and smaller objects. The results from different software have been previously researched and compared to traditional ground-based LiDAR. However, results were inconsistent across software applications, with some software being more accurate and others being less accurate. (Technical Paper 2023-01-0614. Miller, Hashemian, Gillihan, Benes.) This paper builds upon existing research by utilizing the updated LiDAR hardware that Apple has added to its iPhone 15 smartphone lineup. This new hardware, in combination with the software application PolyCam, was used to scan a variety of crashed vehicles. These crashed vehicles were also scanned using a FARO 3D scanners and Leica RTC 360 scanners, which have been researched extensively for their accuracy. The PolyCam scans were compared to FARO and Leica scans to determine accuracy for point location and scaling. Previous research has shown that user variability can be minimal (Technical Paper 2023-01-0614. Miller, Hashemian, Gillihan, Benes), so one user utilized the PolyCam application to document real-world crashed vehicles along with 3D scanners for comparative analysis. The authors found that the PolyCam software presented one data set with results similar to the previously researched software application Recon3D, but there were data sets that were less accurate. The authors believe these inconsistencies need to be evaluated further, but believe the accident reconstruction community, and other forensic disciplines, will continue to find accessibility and usability with PolyCam and other iPhone LiDAR applications that are available.
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DOI
https://doi.org/10.4271/2025-01-8692
Pages
58
Citation
Miller, S., Stogsdill, M., and McWhirter, S., "Accuracy of Mobile Phone LiDAR on Crashed Vehicles," SAE Technical Paper 2025-01-8692, 2025, https://doi.org/10.4271/2025-01-8692.
Additional Details
Publisher
Published
Apr 01
Product Code
2025-01-8692
Content Type
Technical Paper
Language
English