Online Route Graph Generation Using Steepest Descent Optimization
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Solution Overview
Problem
Existing methods for generating route graphs from trajectory data are inefficient for online processing, as they require batch processing and do not account for the order of trajectory data addition, leading to suboptimal cost optimization and increased computational complexity.
Innovation Solution
The implementation of a steepest descent method for online processing, which focuses on optimizing the cost of route graphs by selectively rerouting trajectories and updating the graph structure based on differences between the current and previous graph states, using a Delaunay graph and Voronoi diagram to reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If batch processing is used to generate route graphs from trajectory data, then the graph structure can be extracted with clustering, but the processing efficiency is low and cannot handle online processing requirements
Solution Approach 1:
The patent segments the trajectory data processing into incremental updates rather than batch processing. Each new trajectory data piece is processed individually to update the route graph, enabling online processing. The route graph is divided into existing structures and new elements to be added, allowing efficient incremental construction.
Solution Approach 2:
The patent implements a dynamic route graph that can be updated in real-time as new trajectory data arrives. The graph structure adapts dynamically by adding new nodes and edges only where necessary, rather than reconstructing the entire graph batch-wise. This dynamic update mechanism significantly improves processing efficiency for online applications.
2Device complexity
If the route graph is updated by processing each trajectory data piece sequentially from an empty graph, then the graph can be built incrementally, but the computational complexity increases and cost optimization becomes suboptimal
Solution Approach 1:
The patent performs preliminary actions by maintaining an existing route graph structure that can serve as a foundation for new updates. Instead of starting from an empty graph, the system leverages the pre-established graph structure and only processes new elements, reducing computational complexity while maintaining optimization quality.
Solution Approach 2:
The patent extracts only the necessary new elements (nodes and edges) from incoming trajectory data that are not already present in the existing route graph. This selective extraction approach minimizes computational complexity by avoiding redundant processing of existing graph structures while preserving cost optimization through careful selection of new elements to add.
3Reliability
If all trajectory data is processed to ensure complete graph coverage, then the route graph comprehensively represents all trajectories, but the processing time and computational resources increase significantly
Solution Approach 1:
The patent applies local quality by processing only the specific portions of trajectory data that differ from the existing route graph structure. Instead of uniformly processing all trajectory data, the system identifies and processes only the local differences (new nodes and edges), maintaining complete graph coverage where needed while reducing processing time through selective local updates.
Data Source
AI summary
An apparatus acquires a first piece of trajectory information from among plural pieces of trajectory information, and acquires a first planar graph from among one or more planar graphs. The apparatus generates a second planar graph, based on the first planar graph and plural pieces of position information included in the first piece of trajectory information, and extracts, from among the plural pieces of trajectory information, second pieces of trajectory information indicating trajectories passing a difference portion between the first and second planar graphs. For each of candidate graphs each obtained by excluding a reduction set of edges from the second planar graph, the apparatus calculates optimality of the each candidate graph with which an addition set of trajectories indicated by the first and second pieces of trajectory information are associated, and outputs one of the candidate graphs determined based on the calculated optimality.