Autonomous Vehicle Query Relaxation for Connected Graph Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manually searching for desirable query conditions in connected graphs for autonomous vehicle navigation is challenging due to large search spaces and computationally intensive processes, leading to wasted user time and effort.
Innovation Solution
A computer-implemented method for relaxing queries on a connected graph by identifying relaxed query sets that broaden query criteria based on user-defined constraints, using algorithms to score and select query sets that maximize connected component size, thereby automating the identification of query relaxations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual searching for query conditions is performed in connected graphs, then navigation accuracy can be maintained, but user time and effort are significantly wasted
Solution Approach 1:
The system pre-computes and stores optimal query conditions and relaxed query sets in the connected graph database before actual navigation queries are made. This preliminary preparation allows the system to quickly retrieve pre-analyzed navigation paths without requiring users to manually search through large search spaces during actual use, thus maintaining accuracy while reducing time loss.
Solution Approach 2:
The system automatically generates and evaluates relaxed query sets without requiring manual user intervention. The autonomous vehicle navigation system performs self-service by autonomously determining optimal query conditions, evaluating connected components, and selecting navigation paths based on pre-computed relaxed query sets, eliminating the need for users to manually search through numerous query conditions.
2Adaptability or versatility
If relaxed query sets are generated to broaden search criteria, then navigation range is improved, but computational overhead increases
Solution Approach 1:
The system generates relaxed query sets by selectively relaxing only certain query criteria rather than all criteria. This partial relaxation approach allows the system to expand navigation range in specific directions where flexibility is beneficial, while maintaining strict criteria in other areas, thus achieving improved adaptability without proportionally increasing computational overhead across the entire search space.
Solution Approach 2:
The system divides the query relaxation process into discrete, manageable relaxed query sets, each targeting specific navigation scenarios. By segmenting the overall search problem into multiple focused relaxed query evaluations, the computational overhead is distributed and managed more efficiently, allowing the system to achieve broader navigation range without being overwhelmed by a single exhaustive search.
3Productivity
If automated query relaxation algorithms are implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system implements a universal query relaxation framework that handles multiple navigation scenarios and query types through a single automated algorithmic approach. This multi-functional system can evaluate different relaxed query sets for various navigation contexts (different vehicle types, environments, and requirements) using the same core methodology, thereby improving trip planning productivity across diverse applications without proportionally increasing system complexity for each specific case.
Data Source
AI summary
A computer-implemented method for relaxing queries on a queried connection graph can include obtaining, by a computing system including one or more computing devices, a connected graph. The computer-implemented method can include evaluating, by the computing system, a first set of connected components of the connected graph with respect to a first query set. The first query set can include one or more query criteria. The query criteria can include one or more attributes associated with operating an autonomous vehicle. The computer-implemented method can include determining, by the computing system, one or more relaxed query sets based at least in part on the first query set. The computer-implemented method can include evaluating, by the computing system, a second set of connected components of the connected graph with respect to the one or more relaxed query sets, the connected graph being associated with autonomous vehicle operation within a geographic area.