Real-Time Ride Matching for Ephemeral Shared Transportation
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Solution Overview
Problem
Conventional ride sharing systems rely on static computational models that rigidly apply matching algorithms, leading to inefficiencies such as excessive resource consumption, vague ride-sharing details, and inflexible user interfaces, which waste computing resources and fail to provide accurate and timely shared transportation options.
Innovation Solution
A dynamic transportation sharing system that intelligently matches new requestors with active transportations of existing users based on detected pickup and drop-off locations, providing ephemeral-transportation options in real-time, integrating GPS data for accurate and specific route and cost information, and offering flexible user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a static computational model is used to match shared transportation requests, then the system can provide shared transportation options, but the system consumes excessive computing resources and time to find a match
Solution Approach 1:
The system pre-calculates and stores routing information, cost estimates, and transportation details before a shared ride request is made. When a request arrives, the system only needs to retrieve pre-computed data and perform simple matching, rather than calculating everything from scratch. This preliminary preparation dramatically reduces the computational burden and time required to respond to shared transportation requests.
Solution Approach 2:
The system transitions from a static matching approach to a dynamic one where routing information and cost estimates are updated in real-time based on current conditions. The system can provide accurate, up-to-date information about transportation routes, costs, and availability without requiring excessive computational resources by using dynamic data structures and efficient query mechanisms.
2Loss of information
If a static computational model is used to match shared transportation requests, then the system can identify shared vehicles, but the system provides vague and inaccurate ride-sharing details with little to no information regarding route and estimated time of arrival
Solution Approach 1:
The system pre-computes and stores detailed routing information, estimated times of arrival, and cost estimates for potential shared transportation routes. This preliminary calculation of all possible routes and their associated details allows the system to provide accurate, specific information immediately when a match is made, without needing to calculate these details in real-time.
Solution Approach 2:
The system continuously updates routing information and cost estimates based on real-time data about transportation demand, vehicle availability, and route conditions. This feedback mechanism ensures that the information provided to users remains accurate and current, reflecting the latest conditions in the shared transportation network.
3Measurement precision
If conventional systems provide shared-transportation-match information with historical average-cost estimates, then the system can provide cost information, but the estimates lack accuracy by averaging historical costs
Solution Approach 1:
The system pre-calculates cost estimates for specific routes and shared transportation scenarios based on actual, current conditions rather than historical averages. By computing costs in advance for specific routes and vehicle assignments, the system provides accurate, route-specific cost estimates that reflect current pricing and conditions, eliminating the need for inaccurate historical averaging.
4Ease of operation
If conventional systems use rigid client-device models with siloed interfaces for shared and non-shared transportation, then the system can provide specific transportation options, but the system requires excessive user interactions and wastes computing resources when users need to reconfigure requests
Solution Approach 1:
The system uses a unified client-device model that handles both shared and non-shared transportation requests through the same interface and processing logic. This universal approach allows users to switch between transportation types without needing to navigate separate interface pathways, reducing the number of user interactions required and eliminating the need to cancel and re-submit requests when changing transportation preferences.
Solution Approach 2:
The system provides a dynamic, flexible interface that adapts to user needs in real-time. When users want to change from shared to non-shared transportation or adjust their request parameters, the system dynamically updates the available options and re-calculates matches without requiring users to back out through multiple interface screens or re-submit entire requests, thereby reducing both user interactions and computational waste.
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for detecting a potential (or active) shared transportation request from a new requestor's device and an ongoing (or otherwise active) transportation for an existing requestor by a vehicle and then extemporaneously generating an ephemeral-transportation option for display on the new requestor's device to share the ongoing transportation by the vehicle. For example, the disclosed systems can detect a pickup location and a drop-off location associated with a new requestor and one or more active transportations that correlate with the detected locations. Based on the detected pickup and drop-off locations, the disclosed systems match the new requestor with the active transportation by the vehicle for the existing requestor. The disclosed systems then provide, for display on the new requestor's device, an ephemeral-transportation option for the new requestor to share the active transportation with the existing requestor.