Overlap-Aware Avoidance Area Ranking for Autonomous Vehicle Routing
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Solution Overview
Problem
Large-scale mapping operations face challenges in efficiently updating avoidance areas on high-definition maps due to the rapid establishment of inconsistencies, leading to suboptimal routing for autonomous vehicles, as current statistical approaches are computationally cumbersome and impractical.
Innovation Solution
A computing system that identifies and prioritizes avoidance areas based on their network effects by grouping them according to their impact on routing metrics, using a recursive influence evaluation algorithm to generate a ranking that optimizes resource allocation for remapping, thereby improving trip routing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If statistical approaches are used to prioritize avoidance areas, then routing efficiency can be improved, but computational complexity becomes cumbersome and impractical
Solution Approach 1:
The patent segments the operational area into multiple grid cells, with each cell containing avoidance areas. This segmentation allows the system to process and prioritize avoidance areas in smaller, manageable units rather than treating the entire map as a single complex structure, thereby improving routing efficiency while keeping computational complexity tractable.
Solution Approach 2:
The patent changes the parameter representation by using grid cell indices and avoidance area identifiers instead of complex statistical models. The system evaluates parameters such as grid cell coordinates, avoidance area counts, and route impact metrics to prioritize remapping, transforming the problem from a computationally cumbersome statistical approach to a more efficient parameter-based evaluation.
2Reliability
If more avoidance areas are established on the map, then safety is improved, but route length and cost increase
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously evaluates the impact of avoidance areas on routing metrics. By analyzing how avoidance areas affect route length, cost, and travel time, the system prioritizes remapping of avoidance areas that have the greatest negative impact on routing efficiency. This feedback loop allows the system to maintain safety by keeping avoidance areas on the map while minimizing their detrimental effects on route planning.
3Ease of manufacture
If random selection of avoidance areas is used for remapping, then simplicity is maintained, but routing efficiency is not optimized
Solution Approach 1:
The patent applies preliminary action by pre-evaluating and prioritizing avoidance areas before remapping operations. The system calculates priority scores for each avoidance area based on their impact on routing metrics, so that when remapping resources are allocated, they are directed to the most impactful areas first. This preliminary prioritization ensures that routing efficiency is optimized without requiring complex real-time decision-making during remapping operations.
Data Source
AI summary
A computing system that analyzes the network effects of avoidance areas on autonomous vehicle routing is described herein. The computing system includes a data store that comprises a set of avoidance areas through which the autonomous vehicle is prohibited from being routed. A grouping system identifies groups of avoidance areas. A graph construction system constructs a graph representation of the avoidance area groups. A ranking algorithm is evaluated over the graph representation to generate a ranking of the avoidance area groups by relative impact on routing metrics for routes through an operational area of the autonomous vehicle. A mapping vehicle can be dispatched to resolve avoidance areas in avoidance area groups indicating in the ranking as having a greater impact on routing metrics than other avoidance area groups.