Automated Ridesharing Matching via Mobility Status Detection
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Solution Overview
Problem
Current ridesharing solutions require proactive searching by drivers or passengers, and lack automation in matching travel partners, especially for those traveling similar routes or using public transportation, which can lead to inefficiencies and increased costs.
Innovation Solution
An automated system that uses mobile devices to detect a user's pre-travel stage by analyzing acceleration data and location, predicting future travels based on patterns, and suggesting ride-sharing options with potential partners through a database query, without requiring users to enter specific route and travel time details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated matching system is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system automatically detects user travel intentions through mobility status monitoring and location tracking, performs database queries for matching partners, and generates ride-sharing suggestions without requiring user initiation. The mobile device autonomously monitors acceleration data, determines pre-stage conditions, and executes the complete matching workflow, enabling self-service operation that improves productivity while managing complexity through automation.
Solution Approach 2:
The patent replaces manual proactive searching and partner selection with an automated computational system. Instead of users actively seeking travel companions through electronic billboards or social networks, the system uses mobile device sensors, location services, and database queries to automatically identify and suggest matching partners, substituting mechanical user actions with automated digital processes.
2Ease of operation
If proactive searching is required, then ease of operation is worsened, but extent of automation is reduced
Solution Approach 1:
The system performs preliminary detection of user travel intentions by monitoring mobility status and location data before the user actively searches for partners. By identifying pre-stage conditions in advance and pre-querying the database for potential matches, the system prepares ride-sharing suggestions proactively, eliminating the need for users to initiate searches and significantly improving ease of operation while maximizing automation.
Solution Approach 2:
The system continuously monitors user mobility status and location data, providing feedback loops that detect when users are in pre-stage conditions for travel. This feedback mechanism triggers automatic database queries and suggestion generation, creating a responsive automated system that operates based on real-time user state detection rather than requiring manual user initiation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides convenient and cost-effective ride-sharing suggestions to users at the right time, reducing transportation costs, pollution, and traffic congestion, while minimizing processing power consumption on mobile devices.
Implementation Method 1
determining a mobility status for the user, the mobility status determined at least from acceleration readings taken by a mobile device associated with the user
Implementation Method 2
the location indication is optionally determined using information associated with a source selected from the group consisting of: Global Positioning System data; a base station of a Wi-Fi network to which the device is connected; and a base station of a cellular network to which the mobile device is connected
Data Source
AI summary
A method, computer product and computerized system, the method comprising: obtaining travel information regarding at least one future travel for a user, the travel information comprising at least source, destination and travel start time for the at least one travel; determining a location indication and a mobility status for the user, the mobility status determined at least from acceleration readings taken by a mobile device associated with the user; based on the future travel information, mobility status and location indication, determining that the user is in a pre-stage for the at least one future travel; querying a database for a travel partner matching the user and the future travel; and issuing a suggestion to the user to at least partially share a ride from the source to the destination with the travel partner.