Telematics-Based Renter Filtering for Vehicle-Sharing Trust
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Solution Overview
Problem
Conventional vehicle-sharing platforms lack low-level trust mechanisms to enforce personal preferences of vehicle owners, allowing only high-level filtering mechanisms such as overall reviews or ratings, which do not adequately address the need for matching renters with similar driving behaviors.
Innovation Solution
A vehicle-sharing platform predicts user preferences based on telematics data to identify driving behaviors of vehicle owners, setting criteria for eligible renters, and only displays vehicles to those who meet these criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional vehicle-sharing platforms use general reviews and ratings for trust verification, then the platform can operate with basic trust mechanisms, but it cannot generate and enforce personal preferences to allow only specific renters to rent vehicles
Solution Approach 1:
The patent transforms the trust verification mechanism by changing the parameters from general reviews and ratings to specific telematics data parameters such as acceleration, braking, and speed patterns. This allows the system to evaluate and filter renters based on quantifiable driving behavior metrics rather than subjective feedback, enabling owners to set precise preferences for acceptable driving patterns.
Solution Approach 2:
The patent replaces the manual trust verification system (where owners manually review renter profiles and feedback) with an automated telematics-based evaluation system. The vehicle's onboard sensors automatically collect and analyze driving behavior data, substituting human judgment with objective, data-driven assessment of renter compatibility.
2Reliability
If vehicle-sharing platforms require identity verification and general expectations for all renters, then basic trust is established, but personal preferences cannot be enforced to allow only high-trust renters
Solution Approach 1:
The system enables owners to automatically generate their own personal preferences by analyzing their historical telematics data. The platform self-services the preference creation process by comparing owner driving patterns with potential renter patterns, eliminating the need for manual preference setting and reducing operational complexity while maintaining high reliability.
Solution Approach 2:
The system implements continuous feedback loops where telematics data from both owners and renters is constantly monitored and analyzed. This feedback mechanism allows the platform to dynamically adjust and refine preference matching, automatically enforcing personal preferences based on real-time driving behavior analysis rather than static verification processes.
Data Source
AI summary
Embodiments described herein receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by an owner of the vehicle during the period of time; analyze the telematics data to identify driving behavior(s) of the owner during the period of time; predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared; apply the one or more criteria to a potential vehicle renter; and cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.