Ride Request Matching With Dynamic Time Adjustment
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Solution Overview
Problem
Personal vehicles are used at 5% of their capacity, contributing to 29% of world pollution, primarily due to inefficient usage, with 6.5% annual growth.
Innovation Solution
A computing device adjusts initial times based on historical data to match vehicle requests, providing notifications of changes and updating matches to optimize vehicle usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If personal vehicles are used individually for each request, then service reliability is improved, but vehicle capacity utilization deteriorates (5% utilization rate)
Solution Approach 1:
The system merges multiple ride requests that share common route segments or locations into shared rides. By combining requests with similar destinations or passing through the same areas, the system increases vehicle capacity utilization while still providing reliable service to each passenger through coordinated routing and timing.
Solution Approach 2:
The system enables vehicles to serve multiple functions by handling both shared rides and individual requests through a unified platform. A single vehicle can dynamically switch between serving multiple passengers on a shared route and accommodating individual requests, maximizing overall capacity utilization across the fleet.
2Adaptability or versatility
If more personal vehicles are deployed to meet demand, then service availability is improved, but pollution increases (29% of world pollution)
Solution Approach 1:
By merging multiple requests into shared rides, the system reduces the total number of vehicles needed to serve the same demand. This consolidation maintains service availability for all passengers while decreasing the overall vehicle fleet size, thereby reducing pollution from vehicle operations.
Solution Approach 2:
The system changes the utilization parameter of the vehicle fleet by optimizing route efficiency and passenger loading factors. Through intelligent matching and dynamic routing, vehicles operate at higher capacity rates, reducing the number of vehicles required and consequently lowering pollution emissions.
3Speed
If ride matching is performed without considering time adjustments, then matching speed is improved, but matching accuracy deteriorates
Solution Approach 1:
The system performs preliminary time adjustments by calculating optimal pickup and dropoff times during the matching process. By pre-computing time buffers and synchronization requirements, the system maintains fast matching speed while ensuring accurate timing coordination for shared rides.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor and adjust timing parameters based on real-time conditions. By feeding back timing deviations and recalculating optimal schedules, the system maintains both rapid matching and high timing accuracy for coordinated pickups and dropoffs.
Data Source
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.