Reimagining Auto Insurance with LiDAR: A Review of Applications, Challenges, and Opportunities

Аннотация

The acceptance of LiDAR (Light Detection and Ranging) technology in self-driven vehicles and urban mapping is substantial. In the auto insurance domain, LiDAR’s accurate depth-sensing potential proposes its unexploited opportunity, which can help insurers tremendously. This review paper examines the current use of LiDAR and prospective applications in auto insurance in areas like risk assessment, claim settlements, fraud detection, and driver behavior analysis. We will look into the technological underpinning of LiDAR and its integration challenges, and put forward a hypothetical framework for its acquisition in Insurance processing steps. In conclusion, this paper proposes future research areas and the tactical role of technologies like cloud and AI in implementing LiDAR- collected data in the insurance world. KEYWORDS LiDAR, auto insurance, claims processing, underwriting, fraud detection, telematics, 3D point cloud, cloud computing, AI in insurance 1. INTRODUCTION With the discovery of advanced driver-assistance systems(ADAS), telematics, and artificial intelligence, the auto insurance industry is experiencing swift changes. Among the latest advancements, LiDAR is more impressive in capturing rich 3D spatial data. Commonly used in robotics and autonomous navigation, LiDAR extends novel data information that insurers can utilize for better underwriting, dynamic pricing based on data pointers, and automated claims management. The paper explores the gap between LiDAR’s technical ability and its judicious use in the auto insurance industry. https://www.academicpublishers.org/journals/index.php/ijdsml 250 AMERICAN ACADEMIC PUBLISHER Fig.1 LiDAR in Auto Insurance 1. Literature Review LiDAR improves localization in self-driving cars however, during dynamic motion, MSF (Multi-Sensor Fusion) systems are still susceptible to GPS spoofing. LiDAR inputs can be disregarded in these circumstances, according to MSAF (Motion-Sensitive Analysis Framework), allowing for more successful spoofing. Actual experiments demonstrate that MSAF increases attack effectiveness and success in LiDAR-based systems such as Apollo_MSF and Shenlan_MSF[1]. In the paper, “Autonomous Forklifts: State of the Art—Exploring Perception, Scanning Technologies and Functional Systems—A Comprehensive Review” the author thoroughly examined the importance of sensors and object identification, especially LiDAR, in navigation and safety is highlighted in this study on autonomous forklifts. The increasing usage of LiDAR in auto insurance for risk assessment, accident reconstruction, and improving claims accuracy through accurate environmental awareness is directly supported by its insights into real-time perception and system design[2]. According to the author, high-resolution, three-dimensional flood risk visualization can be improved using LiDAR point cloud data. This technology has a direct bearing on auto insurance, since LiDAR provides accurate environmental context and enhanced communication of hazard exposure, supporting hyperlocal risk assessment, damage prediction, and claims processing, particularly in flood-prone locations.[3] This study[4] compares 2D and 3D burn wound assessments to demonstrate LiDAR's capacity to increase measurement accuracy. Similar LiDAR-driven 3D imaging can improve the assessment of vehicle damage in motor insurance, especially on curved or complicated surfaces. This can result in more accurate claim evaluations and more equitable settlements, particularly after collisions or natural disasters. This study[5] demonstrates that LiDAR-derived digital surface models (DSMs) outperform deep learning in accurately detecting crop damage. In auto insurance, similar DSM-based LiDAR analysis can provide precise post- accident vehicle damage assessments, especially in partial or complex impacts. Combining LiDAR with AI could significantly enhance claim accuracy, fraud detection, and settlement fairness. This study demonstrates[6] how accurate elevation mapping and Web-based visualization of LiDAR-generated 3D https://www.academicpublishers.org/journals/index.php/ijdsml 251 AMERICAN ACADEMIC PUBLISHER building models improve flood damage estimates. By precisely describing environmental damage scenarios, similar LiDAR-driven modeling in auto insurance might enhance post-disaster vehicle and property evaluations, facilitating improved claim validation, underwriting, and risk mapping in flood-prone areas. Following a review of several studies on LiDAR in the auto insurance sector, the main emphasis was on autonomous driving and advanced driver-assistance systems (ADAS). LiDAR makes safer and more accurate navigation possible, especially in difficult situations, by using laser beams to produce a 3D map of the vehicle's surroundings, but it does not focus on correcting insurance pricing, risk assessment, claim settlements, fraud detection, and driver behavior analysis[7]. The goal of this work is to familiarize the insured with the impo