Vehicle Accident Damage Estimation Using Onboard Sensor Data
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Solution Overview
Problem
Current methods for assessing vehicle accident damage and insurance risk are inefficient, relying on manual processes that require multiple individuals and lack real-time data, leading to inaccurate and time-consuming damage assessment and insurance premium calculations.
Innovation Solution
A system that utilizes onboard vehicle sensors to detect accidents, analyze damage, and transmit data to a central server for rapid assessment and repair scheduling, while also monitoring driver behavior to adjust insurance premiums based on real-time driving habits and spatially referenced risk parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to assess damage and estimate repair costs, then human judgment and experience can be applied, but the process becomes time-consuming and requires multiple individuals
Solution Approach 1:
The patent replaces manual visual assessment and human judgment with an automated computer-based system that uses sensors, image processing, and algorithms to detect accidents, assess damage, and estimate repair costs. This substitution of mechanical/human processes with automated systems directly resolves the contradiction by providing accurate assessments without the time consumption of manual methods.
Solution Approach 2:
The system enables self-service by allowing the vehicle's own sensors and onboard systems to automatically detect accidents, capture images, and transmit data for assessment. This eliminates the need for multiple human assessors to manually evaluate damage, thereby reducing both time and human resource requirements while maintaining assessment accuracy.
2Measurement precision
If comprehensive data collection from multiple sources is performed, then accurate damage assessment can be achieved, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional system where a single integrated platform performs multiple tasks: accident detection, image capture, data collection from various sensors, damage assessment, and repair cost estimation. This universal system consolidates what would otherwise require multiple separate systems, thereby achieving comprehensive data collection without proportionally increasing system complexity.
Solution Approach 2:
The system merges multiple data collection functions (sensors, cameras, vehicle data systems) into a unified assessment platform. By combining these previously separate functions into one integrated system, the patent achieves comprehensive data collection for accurate assessment while managing complexity through consolidation rather than proliferation of separate systems.
3Productivity
If real-time data transmission to central servers is implemented, then rapid assessment can be achieved, but dependence on communication infrastructure increases
Solution Approach 1:
The system performs preliminary actions by collecting and processing data locally at the accident scene before transmission. Images are captured, sensors are activated, and initial assessment data is gathered on-site. This preliminary local processing ensures that even if communication infrastructure is temporarily unavailable, the essential data collection has already occurred, enabling rapid processing once connectivity is restored.
Solution Approach 2:
The patent uses mobile devices (smartphones, tablets) as intermediaries between the accident scene and central servers. These portable devices can store data locally and transmit it when communication is available, serving as a buffer that maintains system reliability even when direct real-time communication infrastructure is interrupted or unavailable.
4Measurement precision
If traditional insurance premium calculation methods are used, then simplicity is maintained, but accuracy in reflecting individual risk is reduced
Solution Approach 1:
The system implements feedback by continuously collecting actual driving behavior data through sensors and using this information to dynamically adjust insurance premiums. Rather than relying on static historical data, the system provides real-time feedback on driving habits, accident risk, and vehicle usage patterns, enabling accurate, individualized premium calculation that reflects actual risk levels.
Solution Approach 2:
The patent changes the parameters used for premium calculation from traditional demographic and historical factors to real-time sensor data including driving behavior, vehicle performance metrics, and actual usage patterns. This parameter transformation enables more accurate risk assessment by basing premiums on actual observed behavior rather than statistical averages, though it requires a more complex data collection and processing system.
Data Source
AI summary
Described herein is a system and method for predicting the extent and cost of repair resulting from a vehicle accident. The estimates can be based on one or more of in-vehicle sensor measurements during the accident, external observations such as weather and traffic and road conditions, and manually or digitally input accident reports. The gathered information is compared to information in a database from historical accidents and the resulting damage and costs for those. The information is classified according to impact force, direction and location along with the specific type of vehicle. Maintaining and refreshing the information and predictive models in the system is also part of the invention.