Vessel Route Optimization via Traffic Data Segmentation
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Solution Overview
Problem
Existing methods for determining an optimal route for a vessel face challenges due to the lack of structural data similar to road networks, making it difficult to create a graph for shortest-route calculation algorithms, as ships can travel in any direction and speed across navigable water bodies.
Innovation Solution
A method is developed to generate an optimal route for vessels using vessel traffic data by defining sub-regions with similar characteristics, creating a graph with nodes representing these sub-regions, and assigning edges based on vessel journeys, with weights calculated from average travel time, fuel consumption, and journey frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional road network graph structures are used for vessel routing, then shortest-path algorithms can be applied, but the lack of equivalent structural data for water bodies makes graph creation difficult
Solution Approach 1:
The continuous water body is segmented into discrete grid cells, transforming the unstructured navigation space into a structured graph where each cell becomes a node. This segmentation enables the application of shortest-path algorithms by creating a manageable graph structure from the otherwise continuous and unstructured water environment.
Solution Approach 2:
Vessel traffic data serves as an intermediary to infer navigable routes. Instead of relying on pre-defined road-like structures, the patent uses observed vessel movement patterns as mediators to establish edges between grid cells, effectively creating the graph structure through data-driven inference rather than direct structural mapping.
2Measurement precision
If vessel traffic data is used to create accurate route representations, then routing accuracy improves, but data processing and graph construction time increases
Solution Approach 1:
The patent processes vessel traffic data partially by sampling a representative subset of voyages rather than analyzing every single vessel movement. This partial action approach maintains sufficient routing accuracy while significantly reducing the computational time and resources required for graph construction.
Solution Approach 2:
The graph structure is constructed in advance using historical vessel traffic data before actual routing queries are made. This preliminary action separates the computationally intensive graph building phase from the faster route query phase, allowing accurate routing representations to be prepared beforehand and reused for multiple queries.
Data Source
AI summary
Disclosed herein is a method of determining an optimal route for a vessel based on vessel traffic data. The method comprises receiving vessel traffic data relating to the movement of each of a plurality of vessels in a geographical region and defining sub-regions within the geographical region in which the vessel traffic data has similar characteristics. The method also comprises determining an optimal route for a vessel between two geographical points using a representation of the geographical region. The representation comprises nodes, and each node is associated with a respective defined sub-region.