Automated Vehicle Driving Strategy Validation via External Server
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Solution Overview
Problem
Automated vehicles face challenges in ensuring safe and reliable operation, particularly in complex traffic environments, due to potential errors in detecting surroundings and determining driving strategies, which existing technologies fail to adequately address.
Innovation Solution
The method involves detecting surroundings data using a sensor system, comparing these data and determined object positions/movements with an external server, validating the driving strategy through comparisons, and switching to an emergency strategy if deviations exceed predefined limits, utilizing a blockchain for secure data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated vehicles use sensor systems to detect surroundings and determine driving strategies independently, then operational autonomy is improved, but reliability and safety deteriorate due to potential errors in detection and decision-making
Solution Approach 1:
The patent introduces an external server as an intermediary between automated vehicles and the central cloud infrastructure. This server performs preliminary validation of surroundings data and driving strategies locally before transmitting to the cloud, reducing transmission loads and enabling faster error detection. The server acts as a mediator that enhances safety through distributed validation while maintaining operational autonomy.
Solution Approach 2:
The system performs preliminary validation of surroundings data and driving strategies at the external server before final execution by the automated vehicle. This preliminary action allows potential errors to be detected and corrected in advance, improving reliability without compromising the vehicle's operational autonomy. The validation process checks data plausibility and compares detected situations against known patterns before the vehicle executes driving maneuvers.
2Reliability
If automated vehicles transmit all surroundings data and driving strategies to external servers for validation, then reliability is improved through error detection, but communication load and processing time increase
Solution Approach 1:
The validation process is segmented into multiple levels: local validation by the automated vehicle's own systems, preliminary validation by the external server, and final validation by the central cloud infrastructure. This segmentation allows critical safety checks to be performed locally and preliminarily without requiring all data to be transmitted to the cloud, reducing communication time while maintaining comprehensive error detection capability.
Solution Approach 2:
The external server performs preliminary validation of surroundings data and driving strategies before data is transmitted to the central cloud infrastructure. This preliminary action filters out obviously erroneous data and validates critical parameters in advance, reducing the amount of data requiring full cloud processing and thereby decreasing overall communication and processing time while maintaining high reliability.
3Adaptability or versatility
If automated vehicles operate in complex traffic environments with multiple objects and variables, then adaptability is improved, but the complexity of detecting and measuring surroundings increases
Solution Approach 1:
The external server acts as an intermediary that receives and validates surroundings data from automated vehicles operating in complex traffic environments. It performs preliminary plausibility checks and compares detected objects and situations against known patterns and databases, reducing the measurement and detection burden on individual vehicles while enabling them to handle complex scenarios through validated data from multiple sources.
Data Source
AI summary
A method and a device for operating an automated vehicle. The method includes a step of detecting surroundings data values, a step of determining positions and/or predicted movements of objects in the surroundings of the automated vehicle, a step of carrying out a first comparison of the surroundings data values and/or of the positions and/or of the predicted movements using an external server, a step of determining a driving strategy for the automated vehicle as a function of the positions and/or predicted movements of the objects and as a function of the first comparison, a step of carrying out a second comparison of the driving strategy using the external server, and a step of operating the automated vehicle as a function of the driving strategy and as a function of the second comparison.