Ridesharing Detour Candidate Filtering
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Solution Overview
Problem
Current ridesharing platforms face inefficiencies when passenger departure and arrival positions do not match driver routes, leading to no results being returned despite drivers being willing to accommodate detours, and the need to compute numerous detours limits processing power and response time.
Innovation Solution
Generating trip filtering parameters based on driver departure and arrival positions and original routes allows for determining candidate trips for detour computation without actually computing the detour, reducing processing power and improving response time by prefiltering trips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system computes detour routes for all trips in the database to accommodate passengers with non-matching positions, then the system can provide more comprehensive ride-matching results, but the processing power and response time are severely degraded
Solution Approach 1:
The system pre-computes and stores filtering parameters (departure position, arrival position, route geometry) for all trips in the database before receiving passenger requests. When a passenger request arrives, the system quickly filters candidate trips using these pre-computed parameters without computing actual detour routes, thereby maintaining high processing speed while enabling comprehensive matching.
Solution Approach 2:
The system divides the trip-matching process into two stages: (1) a fast filtering stage using pre-computed parameters to identify candidate trips, and (2) a detailed detour computation stage only for the filtered candidates. This segmentation allows the system to handle large databases efficiently by avoiding full detour computation for all trips.
2Measurement precision
If the system computes detour routes for numerous trips to identify acceptable trips for drivers, then the system can ensure accurate route matching, but the processing power is excessively consumed
Solution Approach 1:
The system computes detour routes only for a partial subset of trips that pass the initial filtering stage based on pre-computed parameters. This partial computation approach ensures sufficient matching accuracy for viable candidates while avoiding the excessive processing power consumption that would result from computing detours for all trips in the database.
Solution Approach 2:
The system introduces intermediate filtering parameters (pre-computed departure position, arrival position, and route geometry) that act as mediators between the passenger request and the final detour computation. These intermediaries enable the system to screen out incompatible trips before committing computational resources to detour calculations, thus reducing overall processing power consumption while maintaining accuracy for relevant candidates.
3Device complexity
If the system returns no results when passenger positions do not match driver routes, then the system maintains simple matching logic, but drivers willing to undertake detours are not connected with passengers
Solution Approach 1:
The system pre-computes and stores filtering parameters including departure position, arrival position, and route geometry for all trips. This preliminary preparation enables the system to perform sophisticated matching that considers driver detour willingness without increasing the complexity of the core matching logic, as the pre-computed parameters handle the complexity beforehand.
Solution Approach 2:
The system creates a simplified copy or representation of trip information in the form of filtering parameters that capture essential spatial characteristics without containing the full complexity of route computation. This copying approach allows the matching logic to work with simplified data structures while still enabling sophisticated matching that accounts for driver accommodation of detours.
Data Source
AI summary
A system for and a method of determining that a detoured trip is to be presented to a potential passenger. The method comprises receiving a rideshare request; generating a rideshare request parameter; and accessing, from a database, trip filtering parameters associated with trips. The method further comprises determining that at least one of the trips is a candidate for which a detour route is to be computed based on an analysis of the rideshare request parameter and a corresponding trip filtering parameter associated with the at least one of the trips; causing to compute, for the at least one of the trips determined as being the candidate for which the detour route is to be computed, a detoured trip; and determining that the detoured trip is to be presented to the potential passenger by analyzing the deviation value of the detoured trip and the deviation threshold.