Node Arrangement for Quasi-Optimal Route Search
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Solution Overview
Problem
Existing automatic driving techniques often result in wide random sampling regions, leading to the search for routes with poor quasi-optimality due to the inclusion of unnecessary nodes, which can cause zigzag paths and increased processing time.
Innovation Solution
An information processing device that selectively arranges nodes in specific regions around obstacles, using a potential field to define risk areas and optimize route search, thereby reducing the number of nodes and improving route efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If random sampling is performed in a wide region to search for routes, then the coverage of possible paths is improved, but the route optimality deteriorates and processing time increases
Solution Approach 1:
The patent applies local quality by differentiating node arrangement density based on spatial location. Nodes are arranged densely in regions close to the vehicle and sparsely in distant regions. This localized differentiation allows comprehensive local route optimization while reducing overall computational burden, resolving the contradiction between search coverage and route optimality.
Solution Approach 2:
The search space is segmented into multiple regions based on distance from the vehicle (e.g., first region within first distance, second region within second distance greater than first distance). Each region has different node arrangement densities. This segmentation enables targeted computational resources allocation, improving route optimality in critical near regions while maintaining adequate coverage in far regions.
2Manufacturing precision
If nodes are arranged densely in the sampling region to improve route precision, then the route optimality is improved, but the processing time and computational load increase
Solution Approach 1:
The patent implements local quality by setting different node arrangement densities for different spatial regions. High-density node arrangement is applied only in regions close to the vehicle where precise route optimization is most critical, while lower density is used in distant regions. This resolves the contradiction by concentrating computational resources where they provide maximum benefit.
Solution Approach 2:
The patent applies partial action by not uniformly distributing nodes throughout the entire search space. Instead, nodes are concentrated in specific regions (particularly near the vehicle) where they provide the most value for route optimization. This partial focus achieves sufficient route optimality without the excessive processing time required for uniform dense arrangement across all regions.
3Adaptability or versatility
If nodes are arranged in a wide sampling region, then the route search coverage is improved, but the number of unnecessary nodes increases causing zigzag paths
Solution Approach 1:
The patent applies local quality by varying node arrangement characteristics based on regional importance. In regions close to the vehicle, nodes are arranged with higher density and specific orientation constraints to prevent zigzag paths. In distant regions, fewer nodes are arranged with more flexibility. This localized approach maintains search coverage while reducing overall complexity.
Solution Approach 2:
The search space is segmented into multiple distance-based regions, each with different node arrangement rules. This segmentation allows the system to apply appropriate complexity levels to different parts of the search space, maintaining adequate coverage in all regions while avoiding unnecessary complexity in regions where high precision is less critical.
Data Source
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AI summary
According to an arrangement, an information processing device (20) includes a first arrangement unit (20E), a second arrangement unit (201), and a search unit (20J). The first arrangement unit (20E) arranges a node (N1) in a first region (44) not interfering with an object (12) on a scheduled traveling route (30). The second arrangement unit (201) arranges the node (N2) in a second region (46) around an interference region (42) interfering with the object (12). The search unit (20J) searches for a route (60) going through a plurality of nodes (N1, N2) and having a moving cost from a first point to a second point on the scheduled traveling route (30) equal to or smaller than a threshold.