Directed Vehicle Path Map Matching for Noisy Road Graphs
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Solution Overview
Problem
Existing map matching technologies struggle to accurately align vehicle trajectory data represented as a directed graph to a digital road topology network due to inherent inaccuracies and noise in the data, complex map data, and computational inefficiencies, particularly when dealing with directed graphs.
Innovation Solution
The method involves aggregating vehicle trajectory data into a directed graph, segmenting it into linear features, and using a path-based map matcher to incorporate context for each feature, extending geometries for improved context where necessary, and aggregating results to generate accurate map matching outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional map matching methods are used to align vehicle trajectory data to digital road topology, then the process can handle basic GPS traces, but accuracy deteriorates due to inherent inaccuracies and noise in raw trajectory data
Solution Approach 1:
The patent segments the vehicle path network into multiple linear features, where each linear feature connects two nodes in the directed graph. This segmentation allows the path-based map matcher to process smaller, more manageable segments individually, improving the ability to handle noise and inaccuracies in each segment while maintaining overall path accuracy.
Solution Approach 2:
The patent performs preliminary aggregation of vehicle trajectory data into a directed graph representation before map matching. This preliminary structuring organizes the noisy raw data into a coherent path network with nodes and edges, making the subsequent map matching process more robust to noise and inaccuracies in the original trajectory data.
2Reliability
If path-based map matching is applied to entire vehicle paths, then context information is preserved, but computational complexity and resource requirements increase significantly
Solution Approach 1:
The patent divides the vehicle path network into multiple linear features connecting nodes in the directed graph. Each linear feature is matched separately using the path-based map matcher, which preserves context information within each segment while reducing the overall computational burden compared to matching the entire path as a single unit.
Solution Approach 2:
The patent applies map matching to each linear feature segment rather than the complete vehicle path. This partial action approach maintains the contextual benefits of path-based matching for each segment while avoiding the excessive computational requirements of processing the entire path, especially for long or complex trajectories.
3Measurement precision
If detailed processing is performed on each trajectory point to improve matching precision, then accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent segments the vehicle path into linear features between nodes in the directed graph. This segmentation reduces the number of points requiring detailed processing while maintaining precision through context-aware matching on each segment, thereby reducing overall processing time compared to detailed processing of every individual trajectory point.
Solution Approach 2:
The patent merges multiple trajectory points between nodes into linear features that represent the overall path segment. This merging reduces the volume of data requiring detailed processing while preserving the essential geometric and contextual information needed for accurate map matching, thus improving the precision-time tradeoff.
4Reliability
If the digital map data is used as-is without preprocessing, then data freshness is maintained, but matching accuracy deteriorates due to potential inaccuracies and outdated information in the map
Solution Approach 1:
The patent performs preliminary aggregation of vehicle trajectory data into a directed graph structure before map matching. This preprocessing step creates a robust representation of the actual vehicle paths that can be more easily aligned with the digital map, compensating for inaccuracies or outdated information in the map data while maintaining the benefits of using current trajectory data.
Data Source
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Figure 3A~3B
AI summary
An approach is provided for map matching a vehicle path network to a road topology network of a digital map. The approach, for instance, involves aggregating vehicle trajectory data into a vehicle path network that is a directed graph comprising a plurality of nodes. The approach also involves segmenting the vehicle path network into a plurality of linear features. Each linear feature of the plurality of linear features connects two nodes of the plurality of nodes in the vehicle path network. The approach further involves using a path-based map matcher to separately match each linear feature by incorporating context of the vehicle path network to a map topology of a digital map to generate map matching results. The approach further involves aggregating the map matching results of each linear feature into an overall map matching result for the directed graph, and providing the overall map matching result as an output.