Conformal Lane Priority Mapping for Lower-Data Autonomous Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the sheer volume of data they need to process and store, which can limit navigation safety and accuracy, especially when relying on traditional mapping technology.
Innovation Solution
A system and method using a conformal prediction model to predict lane priority by analyzing descriptors of road segments, generating a map with navigational priority indicators, and distributing it to host vehicles for safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used to navigate autonomous vehicles, then comprehensive navigation data can be provided, but the sheer volume of data needed to store and update the map becomes unmanageable
Solution Approach 1:
The patent extracts only the essential navigational elements (lane priorities, geometric definitions, control parameters) from traditional comprehensive maps, storing only what is necessary for autonomous navigation decisions rather than complete map data
Solution Approach 2:
The navigation map is segmented into discrete road segments with specific navigational elements, allowing the system to process and store only relevant portions of navigation data rather than complete map information
2Measurement precision
If comprehensive map data is stored to ensure accurate navigation, then navigation accuracy can be maintained, but the challenges in storing and updating the map become daunting
Solution Approach 1:
The patent applies local quality by defining specific navigational elements (lane priorities, geometric definitions, control parameters) for each road segment, storing detailed information only where needed rather than uniformly across the entire map
3Extent of automation
If vast volumes of navigation data are processed and interpreted, then autonomous navigation capability can be achieved, but the data processing challenges limit and adversely affect navigation performance
Solution Approach 1:
The system performs preliminary actions by pre-defining geometric definitions, control parameters, and navigational priorities for road segments, so that during actual navigation the autonomous vehicle only needs to query and apply pre-processed data rather than processing raw comprehensive map data in real-time
Data Source
AI summary
A system for generating a map for use in navigating a host vehicle relative to a road segment. The system may receive a representation of at least a first lane and a second lane associated with the road segment, provide at least one descriptor associated with the representation of the first lane and at least one descriptor associated with the representation of the second lane as input to a trained model configured to apply a conformal prediction technique to generate an output including an indicator of which of the first lane or the second lane has navigational priority with respect to the other, store in the map an indication of which of the first lane or the second lane has navigational priority based on the output of the trained model, and distribute the map to at least one host vehicle navigation system for use in navigating the host vehicle along the road segment relative to at least one of the first lane or the second lane and further relative to the indicator of which of the first lane or the second lane has navigational priority.