Road Layout Indexing for Autonomous Vehicle Simulation
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Solution Overview
Problem
Existing systems for autonomous vehicles face inefficiencies in querying and processing high-definition maps with highly detailed geometric information, particularly in static road layouts, which are crucial for precise driving scenarios and simulation-based testing.
Innovation Solution
A scenario query engine is implemented with topological and geometric indexing components to facilitate fast and structured queries on static road layouts, using in-memory indices to efficiently locate road structure elements that satisfy geometric and topological queries, enabling efficient route planning and simulation testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-definition maps with highly detailed geometric information are used, then measurement precision and manufacturing precision are improved, but device complexity and query processing time increase
Solution Approach 1:
The patent segments the road layout into multiple indexed structures: a topological index representing road network connectivity as a graph, and geometric indexes representing spatial relationships. This segmentation allows the system to handle detailed geometric information by organizing it into manageable, query-optimized structures that separate topological and geometric processing concerns.
Solution Approach 2:
The patent introduces intermediary indexing structures between the detailed road layout data and the query processing layer. The topological index and geometric indexes act as mediators that translate high-detail geometric data into query-friendly representations, enabling efficient retrieval without processing the entire detailed map for each query.
2Measurement precision
If detailed road layout queries are processed, then measurement precision is improved, but query processing time increases
Solution Approach 1:
The patent performs preliminary indexing of road layouts into topological and geometric indexes before queries are received. This pre-processing organizes the detailed geometric data into structured representations that can be quickly queried, avoiding the need to scan the entire detailed road layout for each query and significantly reducing query processing time.
Solution Approach 2:
The patent creates indexed copies of road layout data in specialized structures (topological index and geometric indexes) that are optimized for query processing. These indexes are derived from the original detailed road layout but are structured differently to enable fast retrieval, allowing the system to answer queries using the indexed copies rather than the full detailed data.
3Productivity
If comprehensive road layout indexing is implemented, then query efficiency is improved, but device complexity increases
Solution Approach 1:
The patent divides the indexing system into separate, specialized components: a topological index for network structure queries and geometric indexes for spatial queries. This segmentation allows each index to be optimized for its specific function, improving query efficiency while keeping the overall system manageable through modular architecture.
Solution Approach 2:
The patent designs the indexing system to serve multiple query types through a unified approach. The topological index and geometric indexes work together to support various query operations (finding road elements, calculating distances, determining connectivity), making the indexing system multi-functional and reducing the need for separate specialized systems for different query types.
Data Source
AI summary
A computer system comprising: computer storage configured to store a static road layout; a topological indexing component configured to generate an in-memory topological index of the static road layout, the topological index in the form of a graph of nodes and edges, wherein each node corresponds to a road structure element of the static road layout, and the edges encode topological relationships between the road structure elements; a geometric indexing component configured to generate at least one in-memory geometric index of the static road layout for mapping geometric constraints to road structure elements of the static road layout; and a scenario query engine configured to receive a geometric query, search the geometric index to locate at least one static road element satisfying one or more geometric constraints of the geometric query, and return a descriptor of the at least one road structure element(s), wherein the scenario query engine is configured to receive a topological query comprising a descriptor of at least one road element, search the topological index to locate the corresponding node(s), identify at least one other node satisfying the topological query based on the topological relationships encoded in the edges of the topological index, and return a descriptor of the other node(s) satisfying the topological query.