Autonomous Vehicle Sensor Streaming for Low-Latency Object Response
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Solution Overview
Problem
Autonomous vehicles face latency issues in processing sensor data due to batch processing methods, which delay reaction times and impact safety, as they wait for entire scenes or multiple objects to be analyzed before making decisions.
Innovation Solution
Implementing a streaming processing system that prioritizes and transfers subsets of sensor data related to high-priority objects or regions of interest ahead of schedule, using a data streaming controller and classification systems to determine priority and interaction classifications, allowing for real-time decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If batch processing methods are used to analyze entire scenes or multiple objects before making decisions, then comprehensive environmental understanding is achieved, but latency increases and reaction times are delayed
Solution Approach 1:
The patent segments sensor data processing by dividing the 360-degree scene into multiple regions of interest (ROIs) and processing them independently through parallel pipelines. Each ROI is identified based on priority criteria (e.g., detected objects, motion activity) and processed separately, allowing high-priority regions to be analyzed and acted upon without waiting for complete scene analysis. This segmentation resolves the contradiction by enabling comprehensive monitoring through multiple focused analyses rather than one monolithic batch process.
Solution Approach 2:
The system performs preliminary identification and prioritization of regions of interest before complete scene analysis is finished. By pre-identifying which regions require immediate attention based on sensor data triggers (object detection, motion changes), the system prepares processing pipelines in advance for these critical areas. This preliminary action allows the vehicle to begin analyzing important regions sooner, reducing overall latency while maintaining comprehensive environmental understanding through subsequent completion of full scene analysis.
2Reliability
If batch processing waits for entire scenes to be analyzed, then complete situational awareness is achieved, but safety response time is reduced
Solution Approach 1:
The patent implements dynamic processing where the system adapts its analysis depth and scope based on real-time conditions. When high-priority objects or regions are detected, the system dynamically allocates more processing resources to those areas while maintaining reduced processing for lower-priority regions. This dynamic approach ensures that safety-critical situations receive immediate attention with thorough analysis, while maintaining overall situational awareness through continuous monitoring of all regions at varying levels of detail.
Solution Approach 2:
The system maintains continuous processing of sensor data through parallel pipelines that operate simultaneously on different regions of interest. Rather than stopping to complete full scene analysis before any response, multiple processing streams continue uninterrupted, with high-priority regions receiving immediate analysis and response while other regions continue being monitored. This continuity ensures both rapid safety responses and sustained situational awareness without interruption.
3Area of stationary object
If all sensor data is processed equally, then complete environmental coverage is maintained, but processing efficiency decreases
Solution Approach 1:
The patent applies local quality by assigning different processing priorities and resource allocations to different regions of the environment based on their importance. High-priority regions (containing detected objects, motion activity, or potential hazards) receive intensive processing with multiple sensor fusion operations and detailed analysis, while low-priority regions receive streamlined processing. This differential approach maintains complete environmental coverage through systematic monitoring of all areas while significantly improving processing efficiency by concentrating computational resources where they are most needed.
Data Source
AI summary
Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.