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<p>Many hazardous conditions and environmental factors, such as vehicle collisions, accidents, and natural disasters, can cause vehicle damage. The majority of insurance investigators require a significant amount of time to process claims and recover losses. The aim of this study is to reconstruct a 3D model of vehicle damage using UAVs. The objectives of this study are to determine the best flight design for image acquisition for the 3D model of vehicle damage using UAVs and to evaluate the accuracy of the 3D model of vehicle damage compared to actual measurements. Several flight designs were evaluated in this project to assess the accuracy of the 3D model of vehicle damage using UAVs compared to actual measurements. The selected flight design is the Point of Interest (POI) method at various altitudes and ranges. All of these designs are capable of producing a quality 3D model for the purpose of this investigation. The methodology of this study consists of four phases: preliminary work, data acquisition, data processing, and data analysis. When comparing UAV data with object measurement data, the accuracy of these parameters will be assessed based on their Root Mean Square Error (RMSE) value. In comparison to other data collection methods, such as laser scanning, UAVs are chosen because they collect data more quickly. This study was conducted using six different flight designs, including altitudes of 5&#xa0;m with a range of 5&#xa0;m, 5&#xa0;m with a range of 7&#xa0;m, 7&#xa0;m with a range of 5&#xa0;m, 7&#xa0;m with a range of 7&#xa0;m, 10&#xa0;m with a range of 5&#xa0;m, and 10&#xa0;m with a range of 7&#xa0;m. The best result is achieved with a combination of a 7-meter altitude and a 7-meter range among all flight designs, as it generates the smallest RMSE value of 0.008&#xa0;m. The results of UAV measurements indicate that UAVs can replace object measurements for vehicle damage reconstruction. This option is available for investigators to use, as it produces excellent results and reduces investigation time.</p>

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3D Model Reconstruction of Vehicle Damage Using UAV Photogrammetry

  • 期刊论文

  • 发表日期：

    2026年4月30日

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  • Ammar Muhsin Saharuddin,
  • Khairul Nizam Tahar

摘要

Many hazardous conditions and environmental factors, such as vehicle collisions, accidents, and natural disasters, can cause vehicle damage. The majority of insurance investigators require a significant amount of time to process claims and recover losses. The aim of this study is to reconstruct a 3D model of vehicle damage using UAVs. The objectives of this study are to determine the best flight design for image acquisition for the 3D model of vehicle damage using UAVs and to evaluate the accuracy of the 3D model of vehicle damage compared to actual measurements. Several flight designs were evaluated in this project to assess the accuracy of the 3D model of vehicle damage using UAVs compared to actual measurements. The selected flight design is the Point of Interest (POI) method at various altitudes and ranges. All of these designs are capable of producing a quality 3D model for the purpose of this investigation. The methodology of this study consists of four phases: preliminary work, data acquisition, data processing, and data analysis. When comparing UAV data with object measurement data, the accuracy of these parameters will be assessed based on their Root Mean Square Error (RMSE) value. In comparison to other data collection methods, such as laser scanning, UAVs are chosen because they collect data more quickly. This study was conducted using six different flight designs, including altitudes of 5 m with a range of 5 m, 5 m with a range of 7 m, 7 m with a range of 5 m, 7 m with a range of 7 m, 10 m with a range of 5 m, and 10 m with a range of 7 m. The best result is achieved with a combination of a 7-meter altitude and a 7-meter range among all flight designs, as it generates the smallest RMSE value of 0.008 m. The results of UAV measurements indicate that UAVs can replace object measurements for vehicle damage reconstruction. This option is available for investigators to use, as it produces excellent results and reduces investigation time.