Geo-fence Activation for Vehicle Location Data Collection
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Solution Overview
Problem
Current insurance policy determination methods rely on average historical driving habits, which may not accurately reflect individual driver behavior, leading to inadequate coverage.
Innovation Solution
Implementing a system that uses onboard GPS signals to monitor a vehicle's location and activate geo-fences around areas of actuarial significance, collecting data on vehicle movements to adjust insurance policy parameters in real-time, such as premium, deductible, and policy limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If average historical driving habits data is used to determine insurance policy parameters, then insurance companies can establish baseline coverage, but the policy parameters do not accurately reflect individual driver behavior and location-specific risks
Solution Approach 1:
The system pre-configures geo-fence boundaries around areas of actuarial significance before the vehicle enters them. These geo-fences are established in advance based on historical data and risk assessment, allowing the system to automatically trigger data collection when the vehicle approaches or enters these pre-defined zones, thereby improving measurement precision without requiring continuous monitoring of all locations
Solution Approach 2:
The monitoring system automatically activates and deactivates geo-fences based on the vehicle's location data without requiring manual intervention. The system self-manages the collection and transmission of location information, adjusting policy parameters automatically based on accumulated data, thus reducing operational complexity while improving assessment accuracy
2Loss of information
If continuous location monitoring is implemented to capture individual driving habits, then personalized insurance policies can be created, but data collection costs and system resource consumption increase
Solution Approach 1:
Instead of continuous monitoring, the system periodically collects location data at intervals or when specific events occur (entering or exiting geo-fenced areas). The monitoring activates in periodic cycles or triggered by geo-fence boundary events, capturing essential driving behavior information while significantly reducing energy consumption compared to uninterrupted tracking
Solution Approach 2:
The system focuses data collection efforts on specific locations of actuarial significance rather than uniformly monitoring all areas. By concentrating monitoring resources on geo-fenced zones where driving behavior has insurance relevance, the system achieves complete information about risk-relevant behavior while minimizing energy expenditure in low-priority areas
3Adaptability or versatility
If real-time policy parameter adjustment is implemented based on location data, then insurance coverage accuracy improves, but system complexity and computational requirements increase
Solution Approach 1:
The system implements a feedback mechanism where location data collected from the vehicle is transmitted to the insurance company, which then adjusts policy parameters and transmits updated parameters back to the vehicle's onboard system. This closed-loop feedback enables real-time adaptability of insurance coverage to individual driving behavior while distributing computational complexity between the vehicle's monitoring system and the insurance company's processing infrastructure
Data Source
AI summary
Activating geo-fence boundaries and collecting location data. At least some of the illustrative embodiments are methods including: activating a geo-fence for a pre-determined area responsive to an event related to a vehicle; receiving Global Positioning System (GPS) signals indicative of a location of the vehicle, the receiving by an onboard device coupled to the vehicle; detecting that the vehicle has crossed the geo-fence; creating a data set comprising data regarding locations of the vehicle with respect to the geo-fence; determining a parameter associated with an existing insurance policy based on the data set.