V2V Telematics for Grading Non-Subscriber Vehicle Driving Behavior
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Solution Overview
Problem
Current vehicle-based communication systems lack the ability to effectively analyze and grade driving behaviors of non-subscriber vehicles, limiting the collection of data for insurance rating, routing, and car resale value purposes.
Innovation Solution
A vehicle-to-vehicle (V2V) communications system that enables monitoring vehicles to collect and analyze driving data from target vehicles, including speed, position, and driver behavior, using a driving analysis computing device to determine driving behaviors and calculate driver grades, even for vehicles not participating in a telematics program.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle-based communication systems only monitor subscriber vehicles, then data collection is limited and accurate, but the ability to analyze and grade driving behaviors of non-subscriber vehicles is lost
Solution Approach 1:
The monitoring vehicle's telematics system is designed to perform multiple functions: it not only monitors its own subscriber vehicle data but also receives, processes, and analyzes V2V communication data from non-subscriber target vehicles. This universal capability allows the system to grade driving behaviors across all vehicle types regardless of subscription status, resolving the contradiction between measurement precision and adaptability.
2Quantity of substance
If V2V communication data from non-subscriber vehicles is collected, then more comprehensive driving data is available for insurance rating, but data reliability and consistency may be compromised
Solution Approach 1:
The system implements feedback mechanisms where monitoring vehicles continuously receive V2V communications from target vehicles and cross-validate the received data against their own sensor data and historical patterns. This feedback loop enables the system to filter inconsistent or unreliable data while maintaining comprehensive data collection, thus resolving the contradiction between data quantity and reliability.
3Productivity
If comprehensive driving data is collected from all vehicles, then insurance rating and car resale value assessments are improved, but system complexity and processing requirements increase
Solution Approach 1:
The data processing system is segmented into distributed components: each monitoring vehicle independently processes and pre-analyzes V2V data from target vehicles, performing local filtering and initial behavior grading. Only processed and validated data is transmitted to central servers for final insurance rating calculations. This segmentation reduces overall system complexity while maintaining comprehensive assessment capabilities.
Data Source
AI summary
Systems and methods of analyzing a target vehicle based on other vehicles are disclosed. One or more computing devices may receive monitoring vehicle driving data collected from vehicle operation sensors within at least one monitoring vehicle by a telematics device. The one or more computing devices may further receive target vehicle driving data from the telematics device of the at least one monitoring vehicle. The one or more computing devices may determine a driving behavior associated with the target vehicle based on an analysis of the monitoring vehicle driving data and the target vehicle driving data. The one or more computing devices may calculate one or more driver scores based on the driving behavior.