Autonomous Vehicle Control Device Failure Model Switching
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Solution Overview
Problem
Existing driver assistance systems for autonomous driving fail to effectively manage motor vehicles in situations where components are damaged or malfunctioning, as they rely on standard control models that do not account for changed vehicle dynamics, potentially leading to inadequate control behavior.
Innovation Solution
A control device with a failure regulator model that switches from a standard controller model to a failure controller model based on detected component failures, adapting actuating signals to account for the changed behavior of inoperable components, allowing for safe maneuvering of the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a standard controller model is used for autonomous driving, then the control device can operate normally under standard conditions, but it cannot appropriately respond to failure situations such as component damage or malfunction
Solution Approach 1:
The control device dynamically switches between a standard controller model for normal operation and a failure regulator model for failure situations. This dynamic adaptation allows the system to adjust its control behavior based on the operational state, improving reliability in failure conditions while maintaining standard functionality.
Solution Approach 2:
The failure regulator model changes the control parameters and actuating signals to account for altered vehicle dynamics caused by component failures. By modifying the controller model parameters specifically for failure situations, the system achieves appropriate control behavior when vehicle characteristics change due to damage or malfunction.
2Reliability
If the control device uses a standard controller model that assumes proper vehicle operation, then the control algorithm is simpler, but the control behavior becomes inadequate when vehicle components are damaged
Solution Approach 1:
The controller is segmented into distinct models: a standard controller model for normal operation and a failure regulator model for failure situations. This segmentation allows each model to be optimized for its specific operational context, improving reliability in failure conditions while keeping the overall system manageable through modular design.
Solution Approach 2:
The failure regulator model is prepared in advance for specific failure situations such as tire blowouts or aquaplaning. By pre-configuring the alternative controller model with knowledge of potential failure modes, the system can immediately switch to appropriate control behavior without complex real-time analysis, balancing reliability with controlled complexity.
Data Source
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AI summary
The invention relates to a method for autonomously driving a motor vehicle (10) using a control device (22), wherein the control device (22) is coupled to vehicle components (11, 12, 13) for longitudinal control and/or lateral control of the motor vehicle (10), and provides a controller unit (26) for generating control signals (23) for the vehicle components (11, 12, 13) based on a controller model (27, 30). According to the invention, the control device (22) provides a failure controller model (30), via which a failure situation (34) is modelled, in which at least one of the vehicle components (11, 12, 13) is non-functional, and a failure signal (29) signalling the failure situation (34) is received from a detection unit (28) during a driving of the motor vehicle (10), and, depending on the failure signal (29), in the controller unit (26), a standard controller model (27) which assumes that the vehicle components (11, 12, 13) are functional is switched to the failure controller model (30), and the motor vehicle (10) is manoeuvred into a safe state (36) by means of the switched controller unit (26) by generating the control signals (23).