Adaptive Driver Input Validation for Automated Driving
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current automated driving systems (ADS) face challenges in effectively adapting to driver behavior, particularly in distinguishing valid from erroneous driver inputs, which can lead to inefficient operation and unnecessary warnings, especially for drivers of varying experience levels.
Innovation Solution
A testing system that uses one or more processors and a memory to test driver inputs during manual driving modes, adapting a fixed time interval based on validation criteria to differentiate between valid and erroneous inputs, thereby improving the reliability and responsiveness of ADS modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed time interval is used to validate driver inputs in automated driving systems, then the system operation is simplified and consistent, but the system cannot adapt to varying driver behaviors and experience levels, leading to erroneous warnings and reduced reliability
Solution Approach 1:
The patent implements a dynamic time interval system where the validation time interval is no longer fixed but adapts based on driver behavior patterns. The system continuously learns from driver inputs and adjusts the time interval accordingly, allowing the same system to serve multiple driver types without requiring multiple fixed configurations.
Solution Approach 2:
The system changes the temporal parameter (time interval) dynamically based on observed driver behavior. By modifying this key parameter rather than maintaining a constant value, the system achieves adaptability to different driving styles and experience levels while using the same underlying hardware and software architecture.
2Reliability
If driver input validation uses a fixed time interval, then the system is easier to implement and operate, but it generates erroneous warnings for valid driver inputs and fails to distinguish between accidental and intentional actions
Solution Approach 1:
The system performs preliminary testing and learning during manual driving modes before fully engaging automated driving. This preliminary action allows the system to establish baseline driver behavior patterns and adjust validation parameters in advance, reducing false warnings during automated operation.
Solution Approach 2:
The system implements continuous feedback loops where driver inputs are monitored, analyzed, and used to refine the time interval parameters. This feedback mechanism allows the system to learn from both valid and erroneous inputs, progressively improving validation accuracy while adapting to individual driver characteristics.
Data Source
AI summary
System, methods, and other embodiments described herein relate to improving automated driving by testing for inputs during driving. In one embodiment, a method includes testing an input from a driver in a manual driving mode of a vehicle. The method also includes adapting a fixed time interval on a condition that a test result of the input satisfies criteria used to validate driver inputs. The method also includes monitoring, via an input system of the vehicle, for driver feedback according to the fixed time interval in an automated driving mode.


