Autonomous Vehicle Sensor Reliability Metrics Under Poor Connectivity
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Solution Overview
Problem
Autonomous vehicles face challenges in determining the reliability of sensor data, particularly video data, when connectivity is poor, leading to outdated representations of the environment, which can compromise safety and navigation accuracy.
Innovation Solution
A system that determines a reliability metric based on parameters such as time difference, vehicle speed, distance traveled, and environmental factors, adjusting the display of sensor data accordingly to indicate reliability, and influencing vehicle actions based on this metric.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video data is streamed in real-time with good connectivity, then the video data reliability is high, but the system requires high bandwidth and network resources
Solution Approach 1:
The system dynamically changes transmission parameters based on connectivity conditions. When connectivity is poor, it switches from streaming all video frames to transmitting only key frames or compressed summaries, thereby maintaining acceptable reliability while reducing network resource consumption.
Solution Approach 2:
Instead of transmitting complete video data under all conditions, the system transmits only the necessary portion (key frames or essential information) when connectivity is limited, achieving sufficient reliability with reduced network usage.
2Use of energy by moving object
If video data transmission is restricted due to poor connectivity, then network resources are conserved, but the video data becomes outdated and less reliable
Solution Approach 1:
The system implements feedback mechanisms where the remote system monitors connectivity conditions and sends requests for specific types of video data. The vehicle adjusts its transmission strategy based on these feedback signals, ensuring that the most critical information is transmitted even under resource constraints.
Solution Approach 2:
The system introduces an intermediary processing layer that selectively transmits video information. This intermediary filters and prioritizes video data based on reliability requirements and network conditions, transmitting only essential information when resources are limited.
3Use of energy by moving object
If the system displays outdated video frames to operators, then network bandwidth is reduced, but the operators cannot accurately assess the current environment
Solution Approach 1:
The system extracts and transmits only the most critical environmental information rather than complete video frames. By taking out essential elements (key objects, hazards, navigation-relevant features) from full video data, it reduces bandwidth usage while preserving the information needed for accurate environmental assessment.
Solution Approach 2:
The system applies different quality levels to different portions of video data. Critical regions of the environment receive higher fidelity transmission while less important areas are transmitted at lower resolution or summarized, optimizing bandwidth usage while maintaining operational decision-making accuracy.
Data Source
AI summary
A computer implemented method is provided. The method, comprises: receiving from an autonomous vehicle sensor data, wherein the sensor data is indicative of an environment in which the vehicle is currently located or was previously located. The method further comprises receiving or determining additional data associated with at least one of: the sensor data, the vehicle, or the environment, wherein the additional data is different from the sensor data. The method further comprises displaying, on a display, an output comprising a representation of the sensor data. The method further comprises determining, based at least in part on the additional data, a reliability metric, the reliability metric being indicative of how reliable the sensor data is at representing the environment in which the vehicle is located at a current time. The method further comprises causing the output on the display to be based at least in part on the reliability metric.