Tire Recommendation Using Trip Speed to Match Driving Patterns
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Solution Overview
Problem
Existing tire proposal systems fail to consider the traveling pattern of a vehicle when selecting a suitable tire, leading to inappropriate tire recommendations for users.
Innovation Solution
A tire proposal system that calculates the average vehicle speed based on mileage and driving time for each trip, determining the traveling pattern and recommending tires that prioritize either fuel efficiency and riding quality for low-speed trips or high-speed stability for high-speed trips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a tire is selected based only on vehicle information (manufacturer, model, year, grade, number) without considering traveling pattern, then the selection process is simple and quick, but the proposed tire may not be appropriate for the actual usage conditions
Solution Approach 1:
The system collects and stores traveling pattern information (mileage and driving time) in advance before tire selection is needed. This preliminary data collection enables the system to automatically determine appropriate tire types without requiring users to manually input usage patterns during the selection process, thus maintaining ease of operation while improving adaptability
Solution Approach 2:
The system introduces traveling pattern information as an intermediary factor between vehicle information and tire selection. By calculating average vehicle speed from mileage and driving time data, the system creates a bridge that translates raw usage data into meaningful tire type recommendations, resolving the contradiction between simple selection process and appropriate tire matching
2Adaptability or versatility
If the system calculates average vehicle speed and analyzes trip data to determine traveling pattern, then tire recommendations become more accurate for usage conditions, but the processing complexity and data requirements increase
Solution Approach 1:
The system transforms raw traveling data (mileage and driving time) into a meaningful parameter (average vehicle speed) that directly indicates traveling pattern. By changing the data representation from multiple raw parameters to a single derived parameter, the system achieves accurate tire recommendations without proportionally increasing processing complexity
Solution Approach 2:
The system applies different tire type recommendations based on local characteristics of traveling patterns. Instead of a single complex analysis for all vehicles, it identifies specific speed ranges (high-speed vs. low-speed traveling patterns) and applies appropriate tire type rules locally, simplifying the overall processing while maintaining accuracy
Data Source
AI summary
A tire proposal system that proposes a tire of a vehicle to a user includes a processing unit that proposes an appropriate tire that is a tire appropriate for the vehicle based on a mileage and a driving time of each trip of the vehicle. With such processing, the appropriate tire is proposed to the user considering a traveling pattern (usage tendency) of the vehicle, which can be grasped from the mileage and the driving time of the each trip of the vehicle, thereby a tire appropriate for the traveling pattern of the vehicle can be proposed to the user as the appropriate tire.