AI Route Generation Across Gig Platforms for Multi-Trip Planning
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Solution Overview
Problem
Existing systems fail to generate efficient transportation routes that cover multiple trip assignments from different gig platforms simultaneously, lacking the ability to integrate user preferences and historical data for optimized routing.
Innovation Solution
A computer system utilizing AI tools to generate optimal transportation routes by combining trip assignments from multiple gig platforms, considering historical data, user preferences, and real-time contextual information, and providing integrated route instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a driver uses multiple gig platforms simultaneously to accept trip assignments, then earning potential increases, but the ability to generate an optimized route covering all assignments decreases
Solution Approach 1:
The patent combines trip assignments from multiple gig platforms into a single unified route. The system aggregates assignments from different platforms and generates one optimized route that covers all destinations, allowing drivers to work multiple platforms simultaneously while maintaining efficient routing that would otherwise require separate route planning for each platform.
2Adaptability or versatility
If conventional mobile applications are used for each gig platform, then platform-specific trip management is achieved, but integrated route optimization across platforms is lost
Solution Approach 1:
The patent creates a universal route generation system that works across multiple gig platforms. Instead of requiring separate applications for each platform, the system provides a single unified route optimization service that can handle assignments from any platform, reducing the number of applications needed while maintaining platform-specific functionality through integration.
3Ease of operation
If drivers manually manage trips from multiple platforms, then flexibility in platform selection is maintained, but time efficiency and route optimization deteriorate
Solution Approach 1:
The patent performs preliminary route optimization by pre-calculating the most efficient route that covers multiple trip assignments from different platforms before the driver begins their work. The system analyzes all assigned trips and determines the optimal sequence and path in advance, saving the driver time during actual trip execution while maintaining flexibility in platform selection.
Data Source
AI summary
A computer system may be provided. The computer system may include at least one processor. The at least one processor may be programmed to: (a) cause, using an application executing on the user device, the user device to display a plurality of trip assignments, each of the plurality of trip assignments associated with a trip assignment provider device of a plurality of trip assignment provider devices; (b) receive, from the user device, a selection of one or more of the plurality of trip assignments, each of the one or more selected trip assignments including trip information including at least an origin and a destination; (c) generate an optimal route based upon the trip information using an AI model, wherein the AI model is trained using historical trip records including historical trip information associated with historical trips; and (d) cause, using the application, the user device to display the generated route.