Automated Vehicle Behavior Mode Control Under Module Failures
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Solution Overview
Problem
Automated vehicles face challenges in managing complex driving situations due to potential module failures, which can compromise safety and reliability.
Innovation Solution
A computer-implemented method and control device enable dynamic reconfiguration by identifying available and reliable modules to take over the functions of failed modules, adjusting boundary conditions, and selecting behavior modes based on module-specific and behavior-mode-specific conditions to ensure resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individual modules are made redundant to ensure system reliability, then the system can withstand module failures, but the device complexity increases due to the need for dynamic reconfiguration and module management
Solution Approach 1:
The system implements dynamic reconfiguration by continuously monitoring module availability and automatically selecting alternative behavior modes when modules fail. The control device adapts the behavior mode based on real-time module status, transforming a static system into a dynamic one that can respond to failures without manual intervention.
Solution Approach 2:
The system is divided into independent modules with clearly defined functions and boundary conditions. Each module can be individually assessed for availability, and the system can selectively activate or deactivate specific modules based on their operational status, enabling granular fault management.
2Reliability
If the system dynamically reconfigures to replace failed modules, then the system maintains operational capability, but the response time increases due to the need to assess module availability and select alternative behavior modes
Solution Approach 1:
Multiple behavior modes are pre-configured with different module assignments and priorities before any failure occurs. When a module fails, the system does not need to create new configurations from scratch but can immediately switch to a pre-prepared alternative behavior mode that has already been validated.
Solution Approach 2:
The system continuously monitors module availability and uses this feedback to automatically select appropriate behavior modes. This closed-loop feedback mechanism enables rapid detection and response to failures, minimizing the time the system spends in a degraded state.
3Speed
If multiple behavior modes are predefined with different module assignments, then the system can quickly switch during failures, but the device complexity increases due to managing multiple behavior modes and their boundary conditions
Solution Approach 1:
The system manages complexity by parameterizing behavior modes through priority values and module availability flags. Instead of hardcoding complex switching logic, the system uses simple parameter comparisons (priority values) and boolean checks (module availability) to determine which behavior mode to activate, making the control logic more manageable.
Solution Approach 2:
The behavior mode selection mechanism serves multiple functions: it handles normal operation, manages failures, optimizes performance, and adapts to different driving conditions. This universal selection framework eliminates the need for separate control logic for each scenario, reducing overall system complexity.
Data Source
AI summary
A computer-implemented method for controlling a vehicle. The method includes: ascertaining which multiple modules from a plurality of modules of the vehicle are ready for use, wherein each module is assigned respective module-specific boundary conditions; using a representation of an environment of the vehicle, ascertaining behavior mode{s), each of which is assigned one or more of the multiple modules and a respective priority and each of which represents respective behavior-mode-specific boundary conditions; for each behavior mode, ascertaining respective control boundary conditions using the module-specific boundary conditions of the module(s) assigned to the behavior mode, and the behavior-mode-specific boundary conditions represented by them; using the control boundary conditions of a selected behavior mode and the one or more modules assigned to the selected behavior mode, generating control parameters for controlling the vehicle according to the selected behavior mode; and controlling the vehicle according to the control parameters.