Autonomous Vehicle Sensor Data Transfer for Remote Operation
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently transferring driving environment data to remote operation computing systems, particularly in complex environments and varying communication channel conditions, which can impact timely and informed decision-making by remote operators.
Innovation Solution
The method involves using a sensor system with multiple types of sensors to acquire driving environment data and selectively choosing a subset based on environment complexity and communication channel availability, then sending this data to the remote operation computing system for efficient data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensor data is transmitted to the remote operation computing system, then the remote operator has complete information for decision-making, but the data transfer bandwidth and processing load increase significantly
Solution Approach 1:
The patent extracts and transmits only the essential sensor data needed for remote operation decision-making, filtering out redundant information. The system identifies and transmits critical data elements that directly support remote operator decisions while excluding unnecessary data, thereby reducing transfer volume while preserving information completeness.
Solution Approach 2:
The patent applies different data transmission qualities based on local conditions - transmitting high-fidelity sensor data when communication bandwidth is available and low-fidelity or summarized data when bandwidth is constrained. The system adapts the quality and detail level of transmitted information to match current communication channel capabilities and operational needs.
2Measurement precision
If high-resolution sensor data is transmitted continuously, then the remote operator can make accurate decisions, but the communication bandwidth requirement increases
Solution Approach 1:
The patent dynamically adjusts the resolution and detail level of sensor data transmitted based on real-time communication channel conditions and operational context. When bandwidth is abundant, high-resolution data is transmitted; when bandwidth is limited, the system reduces data resolution or transmits only critical changes, thereby maintaining decision-making accuracy while adapting to bandwidth constraints.
Solution Approach 2:
The patent changes key parameters of data transmission including resolution, sampling rate, and compression level based on communication channel availability and environmental complexity. The system monitors channel conditions and adjusts data transmission parameters accordingly, transmitting high-precision data when possible and lower-precision summarized data when necessary.
3Productivity
If a subset of sensors is selected based on environment complexity, then the data transfer efficiency improves, but the system complexity increases
Solution Approach 1:
The patent performs preliminary analysis of the driving environment to identify which sensor data will be most valuable for remote operation decisions before initiating data transmission. The system pre-processes sensor inputs, evaluates environmental complexity, and pre-selects relevant sensor subsets based on predicted operational needs, thereby improving transfer efficiency while keeping the selection logic manageable through rule-based approaches.
4Reliability
If all sensor types are transmitted, then the remote operator has comprehensive situational awareness, but the data processing load at the remote system increases
Solution Approach 1:
The patent extracts and transmits only the critical sensor data necessary for safe remote operation, filtering out redundant or low-value information. The system identifies essential data elements that directly contribute to situational awareness and decision-making while excluding unnecessary sensor outputs, thereby reducing remote processing load while preserving reliability.
Data Source
AI summary
Arrangements relating to the transfer of data from an autonomous vehicle to a remote operation computing system while the autonomous vehicle is operating in a remote operational mode are described. A driving environment of the autonomous vehicle can be sensed using a sensor system to acquire driving environment data. The sensor system includes a plurality of different types of sensors. A driving environment complexity can be determined. The availability of a communication channel between the autonomous vehicle and the remote operation computing system can be determined. A subset of the plurality of different types of sensors can be selected based on the determined driving environment complexity and/or the determined communication channel availability and/or its quality. Driving environment data acquired by the selected subset of the plurality of different types of sensors can be sent to the remote operation computing system.