Dynamic Origin-Destination Matrix Estimation for Multi-Goal Trips
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Solution Overview
Problem
Existing transportation forecasting systems fail to accurately generate origin-destination matrices, particularly in agglomeration areas with dense public transportation networks, as they struggle to account for multi-goal trips, leading to inaccurate evaluation and planning of transportation systems.
Innovation Solution
A method and system that dynamically updates origin-destination matrices by acquiring validation sequences from travelers, identifying subsequences as valid transfer trips, and recognizing multi-goal trips through intermediate destinations, incorporating this information to refine the matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If previous methods are used to generate origin-destination matrices from real-time information, then the matrices can be produced, but they fail to reproduce the observed traffic flows due to not accounting for multi-goal trips
Solution Approach 1:
The patent segments the trip identification process into multiple components: validating individual trip segments, identifying transfer trips, and detecting multi-goal trips. By dividing the complex origin-destination matrix generation into these manageable segments, the system can accurately reproduce observed traffic flows while accounting for multi-goal trips that previous methods missed.
2Measurement precision
If the system tries to identify all possible trips including multi-goal trips, then the accuracy improves, but the complexity of the system increases
Solution Approach 1:
The patent applies preliminary action by first validating individual trip segments before combining them into transfer trips and multi-goal trips. This step-by-step preliminary processing reduces system complexity by breaking down the identification task into manageable stages, where each stage builds upon the previous one, ultimately achieving accurate traffic flow reproduction without overwhelming computational complexity.
3Productivity
If real-time information is used to generate dynamic origin-destination matrices, then the planning becomes more relevant, but the methods fail to identify transfer trips with multiple goals
Solution Approach 1:
The patent implements feedback by using observed traffic flows to validate and refine the origin-destination matrix generation process. By comparing the generated matrices against actual observed traffic patterns, the system continuously improves its ability to identify multi-goal trips and transfer trips, ensuring that real-time information is effectively utilized while capturing the full complexity of traveler behavior.
Data Source
AI summary
A method and system are disclosed for dynamically estimating an origin-destination matrix. An origin-destination matrix is initialized with a set of origin stops and destination stops. Validation sequences are acquired for a set of travelers on a transportation system which include a plurality of the origin stops and respective timestamps. Corresponding destination stops may be known or inferred. For each validation sequence, a set of subsequences is generated, each including a respective one of the origin stops and the associated timestamp. Subsequences which, in combination, constitute a valid transfer trip are identified. For a combination of subsequences constituting a valid transfer trip, the method includes determining whether the valid transfer trip is a multi-goal trip for which there is least a first destination stop with an intermediate goal and a second destination stop with a final goal. The origin-destination matrix is updated, based on the determination.