Transit Routing System Precomputing Transfer Patterns
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Solution Overview
Problem
Conventional public transportation trip planning systems face increased computation time and resource demands due to the growing complexity of routes resulting from expanded infrastructure and transfer options, leading to longer wait times for users to receive optimal route information.
Innovation Solution
A public transit travel planning system that preprocesses transit information to determine optimal transfer patterns prior to query time, using a transit graph and associated tables to calculate and store the best routes between transit stations, allowing for minimal computation during user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional transit planning systems analyze various routes at query time to determine optimal paths, then route optimization accuracy is improved, but query processing time increases dramatically
Solution Approach 1:
The system pre-processes transit information and pre-calculates optimal transfer patterns between all pairs of transit stations before query time. This preliminary computation stores routing data in advance, so when a user query is received, the system can quickly retrieve pre-computed results rather than analyzing all possible routes in real-time, thus resolving the contradiction between route optimization accuracy and query processing time
Solution Approach 2:
The invention extracts and separates the computationally intensive route analysis from the query processing step. By taking out the route optimization calculation and performing it in advance during system initialization or data updates, the actual user queries only need to retrieve and display pre-computed routing information, eliminating the time penalty while preserving optimization accuracy
2Adaptability or versatility
If the public transportation infrastructure expands and more transfer options are added, then system versatility and route options are improved, but computation time and resource demands increase
Solution Approach 1:
The system handles infrastructure expansion and increased route options by pre-processing all transit data during system initialization or when schedule changes occur. This allows the system to accommodate any number of transfer options and route variations without impacting real-time query performance, as all computational work is completed in advance
Solution Approach 2:
The invention segments the routing problem into discrete transfer patterns between station pairs. Each transfer pattern is independently pre-calculated and stored, allowing the system to efficiently handle expanded infrastructure by simply adding more pre-computed patterns rather than re-analyzing the entire network for each query
Data Source
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AI summary
A public transit travel planning system and methodology that uses an extensive preprocessing approach of transit information prior to query time on order to determine optimal public transit routes for journeys. At query time, since the transit information has already been processed by the system, very little computation is needed in order to fulfill the query. The system then provides users with public transit directions in response to the queries for public transit journeys.