Driving-Behavior Scoring for Autonomous Vehicle Wait-Line Mapping
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Solution Overview
Problem
Autonomous vehicles face challenges in determining appropriate stopping or yielding locations at traffic features due to the difficulty in accurately interpreting HD maps, leading to potential safety risks and navigation issues.
Innovation Solution
Systems and methods that process data from actual driving behaviors to determine wait condition information, such as wait lines, associated with traffic features by scoring mapstreams based on adherence to traffic rules, and update maps to indicate these locations, enabling vehicles to navigate safely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HD maps are used to determine traffic feature locations, then navigation precision is improved, but the ability to determine appropriate stopping/yielding locations deteriorates due to map interpretation difficulties
Solution Approach 1:
The patent introduces wait condition information as an intermediary layer between HD map data and vehicle navigation decisions. This intermediary provides explicit stopping/yielding location guidance that bridges the gap between precise traffic feature locations and actionable navigation instructions, resolving the contradiction by making the map data more operationally useful without sacrificing precision
Solution Approach 2:
The system performs preliminary determination of wait conditions and appropriate stopping/yielding locations before the vehicle reaches the traffic feature. By pre-calculating and providing these locations in advance based on HD map data and traffic rules, the system eliminates the real-time decision-making difficulty while maintaining precise location awareness
2Device complexity
If conventional map systems are used, then map data structure is simple, but navigation safety deteriorates due to inability to provide precise stopping/yielding locations
Solution Approach 1:
The patent segments map data into distinct functional layers: basic HD map information, wait condition information, and derived navigation instructions. This segmentation allows the system to maintain simple base map structures while adding safety-critical wait condition data as a separate, manageable layer that explicitly guides stopping/yielding locations without overwhelming complexity
Solution Approach 2:
The system adds a new dimensional layer of wait condition information to the traditional two-dimensional map data. This additional dimension provides vertical depth to the map structure, incorporating safety-critical stopping/yielding location data that transforms flat map information into multi-layered navigation guidance, improving safety without fundamentally redesigning the base map system
Data Source
AI summary
In various examples, determining wait condition information associated with traffic features for autonomous and semi-autonomous systems and applications is described herein. Systems and methods described herein may process data representing actual driving behaviors associated with users of machines in order to determine wait condition information, such as wait lines (e.g., stopping lines, etc.), for traffic features located within an environment. For instance, mapstreams (e.g., drives, etc.) associated with machines navigating approximate to a traffic feature may be scored based at least on whether rules associated with the environment and/or the traffic feature were followed. At least a portion of the mapstreams, such as mapstreams associated with at least a threshold score, may then be used to determine a wait line associated with the traffic feature. Additionally, map data representative of a map may be updated to indicate the location of the wait line within the environment.