Context-Based Sensor Data Reduction for Connected Vehicles
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Solution Overview
Problem
Connected vehicles face challenges in efficiently sharing sensor data due to large data volumes, which can overwhelm networks and render data less valuable for real-time applications, necessitating a strategy to reduce data size based on channel load and context.
Innovation Solution
A vehicle system that processes sensor data to generate a reduced data set by considering channel load and context information, using a detected object container forming module to strip down data based on radio channel and location contexts, resulting in a context-based object representation for sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If large volumes of sensor data are collected and transmitted, then comprehensive perception of nearby vehicles is improved, but network load increases and data transmission time increases
Solution Approach 1:
The patent extracts and transmits only the most critical features from sensor data based on context analysis. The system identifies essential object characteristics (position, velocity, acceleration) and omits redundant information, achieving efficient data transmission while maintaining comprehensive perception capabilities.
Solution Approach 2:
The patent applies different data transmission qualities to different objects based on their relevance and context. Critical objects (e.g., vehicles in blind spots) receive higher data fidelity while less critical objects use compressed representations, optimizing network resource allocation.
2Quantity of substance
If data is compressed to reduce transmission size, then network load is reduced, but compression time and computational cost increase
Solution Approach 1:
The patent performs preliminary context analysis and feature selection before data transmission. By pre-identifying which features are essential based on current driving context, the system avoids time-consuming compression algorithms during real-time operation, reducing latency while maintaining data efficiency.
3Measurement precision
If all sensor data features are transmitted, then data accuracy is improved, but transmission latency increases reducing real-time value
Solution Approach 1:
The patent transmits partial data features selectively based on context requirements. Instead of transmitting all sensor data, the system identifies and transmits only the necessary subset of features needed for safe driving decisions, achieving real-time performance while maintaining sufficient accuracy.
4Productivity
If data is stripped to critical components, then transmission efficiency is improved, but information completeness may be reduced
Solution Approach 1:
The patent dynamically adjusts the level of data detail transmitted based on changing driving contexts. As driving conditions evolve, the system adapts which features are transmitted and at what fidelity level, ensuring information completeness is maintained when needed while optimizing transmission efficiency during normal conditions.
Data Source
AI summary
In accordance with one embodiment of the present disclosure, a method includes obtaining, with a sensor of a vehicle, a data set representing an external object, the data set having a first set of features, obtaining, with a receiver of the vehicle, a channel load about a radio frequency through which the data set may be transmitted, obtaining, with an environment sensor of the vehicle, context information about a road on which the vehicle is located, and processing the data set representing the external object based on the channel load and the context information to generate a reduced data set representing the external object, the reduced data set having a second set of features fewer than the first set of features.