Rental Car Duration Estimation via Multi-Source Accident Data
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Solution Overview
Problem
Current systems lack accuracy in determining the time required for vehicle repair after an accident, which affects the duration of rental car needs, as they do not comprehensively collect and analyze data from both vehicle-based systems and mobile devices, leading to inefficiencies in providing rental car services.
Innovation Solution
A system comprising a mobile computing device inside a vehicle that detects accidents and collaborates with server computers to determine the extent of damage, using data from both vehicle-based systems and mobile devices to calculate a rental car credit amount based on the repair duration, thereby facilitating more accurate rental car provisioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is collected only from vehicle-based systems, then the system complexity is reduced, but the measurement precision of repair time estimation deteriorates
Solution Approach 1:
The patent combines data collection from multiple sources including vehicle-based systems (OBD, sensors) and mobile devices (smartphones with accelerometers, GPS) into a unified data aggregation system. This merging of data sources improves measurement precision for repair time estimation while managing system complexity through standardized data interfaces and centralized processing architecture.
2Measurement precision
If comprehensive data from multiple sources is collected, then the rental car duration calculation accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent introduces a rental car prediction server as an intermediary component that receives data from multiple sources (vehicle systems, mobile devices, repair shop systems) and processes it through standardized algorithms. This intermediary architecture enables comprehensive data collection for accurate rental car duration calculation while managing system complexity by providing a centralized processing layer that abstracts the complexity from individual data sources.
3Productivity
If manual assessment of vehicle damage is used, then the system complexity is reduced, but the productivity of repair coordination deteriorates
Solution Approach 1:
The patent implements automated damage assessment systems that use sensor data from vehicles and mobile devices to self-evaluate the extent of vehicle damage without requiring manual inspection. The system automatically processes collision data, determines damage severity, and generates repair time estimates, thereby improving repair coordination efficiency while managing complexity through algorithmic automation and standardized assessment protocols.
Data Source
AI summary
One or more devices in an accident detection and recovery computing system may be configured to determine that vehicle accidents have occurred, collect and analyze accident characteristics and other related data, and providing customized accident recovery services. Mobile computing devices, alone or in combination with vehicle-based systems and external devices, may detect accidents or receive accident indication data. After determining that an accident has occurred, mobile computing devices and/or vehicle-based systems may be configured to determine accident characteristics, and then determine the damages or potential damages resulting from the accident. With an estimated assessment of damage, an accurate estimated of the amount of time to repair the damaged vehicle may be calculated, thus an automatic determination of the amount of time a user may need a rental car during the vehicle collision repair may occur.