Line-Based Preprocessing for Multimodal Transit Routing
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Solution Overview
Problem
The preprocessing phase of the Trip-Based Public Transit Routing algorithm becomes time-consuming when adding more modes or personalization to the transportation network, particularly due to the increased number of computations required, which hampers efficient real-time updates and multimodal itinerary generation.
Innovation Solution
A line-based preprocessing method is introduced to reduce the number of computations by building a set of feasible transfers based on lines, followed by arrival and change time-based pruning to create a reduced set of transfers, significantly decreasing processing time while ensuring correctness and relevance for optimal path calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the complete set of feasible transfers is built for the Trip-Based Public Transit Routing algorithm, then the correctness of optimal path calculation is ensured, but the preprocessing time increases significantly
Solution Approach 1:
The patent extracts and removes redundant transfers from the complete set of feasible transfers. By identifying and eliminating transfers that cannot contribute to optimal paths (those not satisfying the pruning conditions), the method reduces the transfer set size to approximately 1/5 of the original while preserving all transfers necessary for correct optimal path calculation.
Solution Approach 2:
The patent performs preliminary pruning of the transfer set before the actual routing computation. By pre-identifying and removing redundant transfers using the specified conditions (comparing arrival times and transfer counts), the method prepares an optimized transfer set that speeds up subsequent routing operations without compromising correctness.
2Adaptability or versatility
If more modes and personalization are added to the transportation network, then the versatility and accuracy of itinerary generation is improved, but the number of computations and preprocessing time increase
Solution Approach 1:
The patent extracts only the necessary transfers from the expanded multimodal network. By applying the pruning conditions to filter out redundant transfers even in complex multimodal scenarios, the method maintains versatility across multiple transportation modes while keeping the transfer set size manageable and preprocessing efficient.
Solution Approach 2:
The patent changes the parameter of transfer set size by applying pruning conditions that reduce it to approximately 1/5 of the original. This parameter transformation allows the system to handle multimodal networks with personalization features while maintaining acceptable preprocessing times through significant reduction of the transfer set.
Data Source
AI summary
A method creates a reduced set of feasible transfers T(t, L′) for a trip t of line L, for each target line L′ from a set of all transfers from line L to all other lines, by computing, for each origin line L, feasible transfers between stations of the origin line L and a destination line L′; sorting the computed feasible transfers to create a transfer set T(L); determining, for each trip t of origin line L, and for each transfer in the transfer set T(L), an earliest trip t′ of L′ wherein the transfer is feasible; and adding, for each trip t of origin line L, the determined transfer from t to t′ to the reduced set of feasible transfers T(t, L′) when trip t′ is the only destination trip of the transfers in the reduced set of feasible transfers T(t, L′) passing at the destination station and when it is earlier than all the previous destination trips of the transfers in the reduced set of feasible transfers T(t, L′) passing by the destination station.