Ride Request Filtering for Shared Transport
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Solution Overview
Problem
Existing ride-hailing services face inefficiencies in data traffic and user interactions, as they often require users to receive and evaluate numerous ride requests, leading to unnecessary detours and increased costs.
Innovation Solution
A method and device that assist users of means of transportation in finding suitable passengers by filtering and comparing ride requests with predefined or predicted routes, allowing for automatic decision-making on whether to accept ride requests based on predefined references.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all ride requests are forwarded to the user for evaluation, then the user can make informed decisions about ride-sharing opportunities, but the data traffic and user interaction load increase unnecessarily
Solution Approach 1:
The system performs preliminary filtering of ride requests against the user's predefined route and criteria before forwarding them to the user. This preliminary action eliminates obviously incompatible requests (e.g., requests that diverge significantly from the user's route) before they reach the user's device, reducing data traffic and interaction load while maintaining decision quality for relevant requests.
2Loss of energy
If ride requests are filtered automatically based on predefined references, then unnecessary data traffic is reduced, but the complexity of the filtering system increases
Solution Approach 1:
The system introduces an intermediary filtering layer that automatically compares ride requests against the user's predefined route and criteria. This intermediary component handles the complex filtering logic centrally, preventing obviously incompatible requests from being transmitted to the user's device. The complexity is managed through automated algorithms rather than requiring complex user-side processing or manual evaluation of all requests.
3Measurement precision
If the user manually evaluates each ride request, then precise matching with personal preferences is achieved, but time and user interaction effort are consumed
Solution Approach 1:
The system performs preliminary automated filtering of ride requests against the user's predefined criteria and route before presenting them for evaluation. This preliminary action pre-screens requests to ensure only potentially compatible ones reach the user, maintaining preference matching accuracy while eliminating the need for the user to manually evaluate every incoming request, thus saving time and effort.
4Productivity
If ride requests are automatically accepted based on route matching, then user acceptance rate increases, but the user loses control over ride-sharing decisions
Solution Approach 1:
The system enables the user to define their own preferences and criteria in advance, creating a personalized filtering system that automatically evaluates incoming ride requests against their specifications. This self-service approach allows the user to maintain full control over their preferences while the automated system handles the evaluation and presentation of compatible requests, increasing acceptance rates without sacrificing user autonomy.
Data Source
Figure 1~2
Figure 3
AI summary
An apparatus, a computer program product, a signal sequence, a means of transport and a method for assisting a user (1) of a means of transport (10) in finding a suitable fellow passenger (2) are proposed. The method comprises the steps of: – receiving a ride request comprising a definition of a starting position (3) and of a destination position (4), – automatically comparing the ride request against a predefined route (5) of the means of transport (10) and taking a result of the comparison as a basis for – automatically deciding, on the basis of a predefined reference, whether or not the ride request is made to the user (1).