Autonomous Vehicle Blockage Arbitration for Persistent Route Obstructions
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately storing and updating blockage information due to the dynamic nature of road conditions, as blockages such as double-parked vehicles are frequently removed, affecting the reliability of routing and maneuver decisions.
Innovation Solution
Implementing a blockage arbitration system that classifies and persists blockage information based on persistence, using sensors like LiDAR to detect and evaluate blockages, and associating them with time values for storage in a map database, allowing for accurate updating and alternate route calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blockage information is stored in the map database, then routing decisions can be informed by historical blockage data, but the blockage information becomes outdated and unreliable when blockages are frequently removed
Solution Approach 1:
The system performs preliminary classification of blockages as persistent or non-persistent before storing them in the map database. This preliminary action ensures that only blockages meeting persistence criteria are stored, preventing outdated information from compromising routing decision reliability.
Solution Approach 2:
The system dynamically updates blockage information by continuously monitoring whether stored blockages still exist in the environment. When a stored blockage is no longer detected, the system removes or updates the blockage information in the map database, ensuring the data remains current and reliable.
2Loss of information
If all detected blockages are stored for routing decisions, then comprehensive blockage coverage is achieved, but non-persistent blockages clutter the map database and reduce navigation efficiency
Solution Approach 1:
The system applies different quality standards to different blockages based on their persistence characteristics. Persistent blockages are stored with high detail in the map database for long-term routing planning, while non-persistent blockages are either excluded or stored with minimal information, optimizing database quality and navigation efficiency.
Solution Approach 2:
The system segments blockage information into distinct categories: persistent blockages suitable for map database storage and non-persistent blockages handled through immediate routing adjustments. This segmentation prevents clutter in the map database while maintaining comprehensive blockage awareness.
3Measurement precision
If the system continuously monitors and updates blockage information, then routing accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The system performs continuous monitoring only for blockages classified as persistent, applying full measurement precision selectively. Non-persistent blockages are detected initially but not subjected to continuous monitoring, reducing computational energy consumption while maintaining routing accuracy for significant obstructions.
Solution Approach 2:
The system performs preliminary classification of blockages to determine persistence before initiating continuous monitoring. This preliminary action filters out non-persistent blockages from continuous tracking, reducing computational overhead while maintaining high detection accuracy for persistent obstacles that require ongoing attention.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables autonomous vehicles to make informed routing decisions by accurately identifying and updating blockage information, improving navigation efficiency and safety by distinguishing between persistent and non-persistent blockages.
Implementation Method 1
using various sensor types, including but not limited to cameras and/or Light Detection and Ranging (LiDAR) sensors disposed on the AV
Data Source
AI summary
The subject disclosure relates to solutions for arbitrating traffic blockages along vehicle routes. In some aspects, the disclosed technology encompasses a method including steps for determining a vehicle route, wherein the vehicle route comprises at least one lane plan to be followed by an autonomous vehicle (AV), identifying a blockage along the vehicle route, analyzing the blockage to determine if the blockage constitutes a persistent blockage, and if the blockage constitutes a persistent blockage, associating a time value with the blockage. Systems and machine-readable media are also provided.


