Managing Node Control of Vehicle Sensor Data by Link Capacity
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Solution Overview
Problem
Existing vehicle-to-vehicle data sharing systems are inefficient and resource-consuming, particularly in platooning scenarios, due to the lack of effective methods for managing sensor data distribution across vehicles with varying processing capabilities and communication links, leading to suboptimal synchronization and delayed reactions.
Innovation Solution
A managing node is introduced to determine the capacity of wireless communication links and data generation rates, selecting between data compression, preprocessing, or transmission of uncompressed data based on these factors to optimize data distribution across vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is transmitted uncompressed between vehicles, then data quality and processing accuracy are improved, but network bandwidth consumption increases and transmission delays worsen
Solution Approach 1:
The system dynamically changes the compression parameter based on link capacity conditions. When link capacity is sufficient, uncompressed or lightly compressed data is transmitted to maintain data quality. When link capacity is limited, compression ratio is increased to reduce bandwidth consumption. This resolves the contradiction by making the data quality parameter adaptive to network conditions.
Solution Approach 2:
The patent implements dynamic adjustment of data transmission parameters based on real-time link capacity assessment. The managing node continuously evaluates wireless link conditions and adjusts compression levels accordingly, transforming a static transmission approach into a dynamic one that balances data quality against bandwidth consumption.
2Loss of energy
If sensor data is compressed before transmission, then network bandwidth consumption is reduced, but data processing time and synchronization delays increase
Solution Approach 1:
The system adjusts compression parameters dynamically based on link capacity. When link capacity is high, compression is minimized or skipped to reduce processing time. When link capacity is low, compression is applied to reduce bandwidth consumption. This resolves the contradiction by making compression intensity adaptive rather than fixed.
Solution Approach 2:
The managing node implements feedback mechanisms to monitor link capacity and adjust compression levels in real-time. This closed-loop control ensures that compression is applied only when necessary, minimizing the impact on processing time while achieving bandwidth savings when network conditions permit.
3Productivity
If each vehicle processes sensor data independently, then processing speed is improved, but system coordination and synchronization deteriorate
Solution Approach 1:
The patent introduces a managing node as an intermediary that coordinates data distribution among vehicles. The managing node assesses link capacities, determines optimal compression levels, and manages the overall data flow. This intermediary structure enables individual vehicles to process data independently while maintaining system-wide synchronization through centralized coordination.
Solution Approach 2:
The system segments the processing function: the managing node handles coordination, link capacity assessment, and compression parameter determination, while individual vehicles handle local data processing and actuation. This segmentation allows parallel processing at the vehicle level while maintaining centralized control for synchronization.
4Stability of the object's composition
If a centralized system manages all sensor data distribution, then synchronization is improved, but system complexity and computational overhead increase
Solution Approach 1:
The managing node serves as a lightweight intermediary that performs only essential coordination functions: link capacity assessment, compression parameter determination, and data distribution management. By limiting the intermediary's responsibilities to these specific tasks, the system achieves synchronization without excessive complexity.
Solution Approach 2:
Individual vehicles perform self-service processing of sensor data locally, executing processing and actuation without requiring centralized intervention. This self-service approach reduces the computational burden on the centralized managing node while maintaining synchronization through pre-coordinated parameters and protocols.
Data Source
AI summary
A managing node for controlling device-to-device communications of sensor data between managed nodes of vehicles, user devices, and/or roadside infrastructure. Operations include determining capacity of wireless communication links of the managed nodes. Operations include determining data generation rate of at least one sensor to be communicated through the wireless communication links. Operations include selecting one of the following based on the capacity of the wireless communication links and the data generation rate: compress data of the at least one sensor before transmission through at least one of the wireless communication links; transmit uncompressed data of the at least one sensor through the at least one of the wireless communication links; and preprocess data of the at least one sensor and transmit the preprocessed data through the at least one of the wireless communication links. Operations include initiating performance of the selection.