Transportation Matching GUIs With Dynamic Efficiency Thresholds
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Solution Overview
Problem
Conventional transportation matching systems face inefficiencies due to inflexible operation and resource wastage, particularly in matching provider vehicles with requestors, leading to excessive travel times, duplicate queries, and network bandwidth strain.
Innovation Solution
The efficiency metric matching system provides graphical user interfaces with varying time windows and dynamic threshold provider device efficiency metrics to flexibly select provider devices, allowing for future time window options and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional transportation matching systems immediately match provider devices with requestor devices, then response time is reduced, but provider device efficiency metrics deteriorate due to excessive travel times and resource wastage
Solution Approach 1:
The system dynamically adjusts the threshold provider device efficiency metric based on the future time window selected by the requestor. Instead of using a fixed threshold, the system modifies the threshold in real-time to balance immediate response needs with long-term provider efficiency, allowing flexible matching decisions that adapt to different time window scenarios.
Solution Approach 2:
The system determines a future time window before finalizing the provider-device match. By anticipating the time window in advance and using it to guide the matching process, the system can proactively select provider devices that will be efficient within that window, rather than reactively matching after the fact.
2Device complexity
If conventional systems use fixed matching criteria, then system complexity is reduced, but adaptability deteriorates due to inability to handle varying time windows and provider conditions
Solution Approach 1:
The system changes the threshold provider device efficiency metric parameter dynamically based on the future time window and current provider device conditions. This parameter adjustment allows the system to adapt to varying scenarios without requiring completely different matching algorithms for each situation.
Solution Approach 2:
The system uses a universal matching framework that can handle both immediate matches and future-time-window matches through the same dynamic threshold mechanism. This multi-functional approach allows the system to adapt to different requestor needs while maintaining a consistent core matching process.
3Measurement precision
If conventional systems perform multiple duplicate queries to ensure matching accuracy, then measurement precision is improved, but network bandwidth consumption increases due to excessive digital communications
Solution Approach 1:
The system uses feedback from the determined future time window to guide the provider device selection process. By incorporating time window feedback into the matching criteria, the system achieves accurate matching in a single query rather than requiring multiple duplicate queries, thereby reducing network bandwidth consumption.
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer readable media, and methods that provide graphical user interfaces comprising future transportation options with varying time windows at different transportation values and dynamically analyze the time windows to identify provider devices to fulfill transportation requests based on provider device efficiency metrics. For instance, the disclosed systems can delay selection of a provider device within a future time window utilizing a dynamic threshold provider device efficiency metric. For instance, the disclosed systems can analyze historical distributions of provider devices to generate a transition probability matrix that is utilized to analyze current provider devices and determine a threshold provider device efficiency metric that reflects the likelihood of identifying more efficient matches in the future. The disclosed systems can compare the determined threshold to anticipated efficiency metrics for individual provider devices to generate matches for digital transportation requests.