Ride Request Matching With Dynamic Time Adjustment for Carpooling
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Solution Overview
Problem
Personal vehicles are underutilized, contributing significantly to pollution and traffic congestion due to inefficient usage, with 5% capacity utilization and 1.4 billion vehicles globally experiencing 6.5% annual growth.
Innovation Solution
A system and method for request matching using a computing device to adjust initial times based on historical data, match requests, and provide notifications for optimal vehicle sharing, including adjusting times for flight delays, pick-up delays, and location changes, and canceling or maintaining matches between requests based on updated times and location identifiers, and providing notifications for optimal vehicle sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If personal vehicles are used individually, then each user has direct control and convenience, but vehicle capacity utilization is low (5%) and pollution increases
Solution Approach 1:
The patent merges multiple individual vehicle requests into shared ride arrangements by matching users with similar routes and timing. The system combines separate transportation demands into consolidated trips, increasing overall vehicle utilization while maintaining individual user convenience through automated matching and coordination.
Solution Approach 2:
The vehicle serving system enables vehicles to serve multiple functions and multiple users sequentially or simultaneously. A single vehicle can serve different users on different routes or time slots, transforming the vehicle from a single-user tool to a multi-user resource, thereby improving capacity utilization without sacrificing individual access.
2Adaptability or versatility
If more personal vehicles are manufactured to meet growing demand, then individual mobility options increase, but global vehicle density increases by 6.5% annually and pollution worsens
Solution Approach 1:
The system enables users to independently manage their own transportation needs through automated matching algorithms. Users input their requirements, and the system automatically finds compatible ride-sharing opportunities, eliminating the need for additional vehicles while maintaining mobility options through self-organized carpooling.
Solution Approach 2:
The system changes the utilization parameter of existing vehicles from 5% to potentially 50% or higher through intelligent matching. By altering how existing vehicle resources are allocated and shared across multiple users and time periods, the system provides enhanced mobility options without increasing the total quantity of vehicles.
3Ease of operation
If vehicle usage continues at current rates, then individual transportation needs are met, but transportation contributes 29% of world pollution with 54% from vehicle usage
Solution Approach 1:
The patent combines multiple individual trips into shared transportation events, reducing the total number of vehicles on the road. By merging demand from multiple users into single vehicle trips, the system maintains transportation accessibility for all users while proportionally reducing per-capita pollution emissions through consolidated travel.
4Measurement precision
If the system adjusts times based on historical data, then matching accuracy improves, but system complexity increases
Solution Approach 1:
The system performs preliminary data collection and historical analysis in advance to establish baseline patterns for trip timing and duration. By pre-processing historical data and creating reference profiles before actual matching occurs, the system achieves high matching accuracy while keeping real-time processing complexity manageable through prepared reference information.
Solution Approach 2:
The system uses historical data as feedback to continuously refine matching algorithms and improve time predictions. By analyzing past matching outcomes and actual trip behaviors, the system learns and adjusts its parameters, achieving increasing accuracy over time while the feedback loop automates the complexity management through iterative optimization.
Data Source
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AI summary
A computing device receives a first request that includes a first identifier of a first provider object, and a first location identifier, and adjusts a first initial time associated with the first provider object, determining a first adjusted time. The computing device matches the first request with a second request based on the first adjusted time and the first location identifier, the second request associated with: a second initial time or a second adjusted time; and a second location identifier. The computing devices notifies respective communication devices of the match, accordingly, later determines that the first initial time has changed, and updates the first adjusted time to a first updated adjusted time. When the requests no longer match, the computing devices cancels the match, matches the first request with a third request based on the first updated adjusted time and the first location identifier, and notifies respective communication devices accordingly.