Autonomous Vehicle Control Transition via Operator Intent Detection
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Solution Overview
Problem
Autonomous vehicles face challenges in determining whether human operator inputs to vehicle components, such as steering wheel, brake pedal, and accelerator pedal, are intentional or inadvertent, which affects the control of vehicle operations during autonomous driving.
Innovation Solution
The vehicle computer system monitors and analyzes data from various sensors and data collectors to determine the intent behind operator inputs, using predefined parameters and rules to decide whether to modify or ignore these inputs, and communicates with a remote server for additional data and instructions to manage vehicle operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle computer system monitors and analyzes sensor data to determine operator intent, then the reliability of autonomous driving systems is improved, but the device complexity increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring sensor data and pre-establishing parameters that indicate intentional versus inadvertent inputs. The computer is configured with predefined conditions and thresholds before operation, allowing it to quickly assess operator intent without complex real-time analysis, thus improving reliability while managing complexity.
Solution Approach 2:
The vehicle computer system acts as an intermediary between the operator inputs and the autonomous driving control. It mediates by analyzing sensor data through predefined parameters and rules, translating raw input signals into determined operator intent, which then guides whether to modify or ignore the inputs. This intermediary layer improves system reliability through structured analysis while containing complexity within the mediation logic.
2Speed
If the system uses predefined parameters and rules to assess operator inputs, then the response time to operator inputs is improved, but the adaptability to different driving scenarios decreases
Solution Approach 1:
The system applies dynamics by making the assessment parameters adjustable based on driving conditions. The computer can modify the thresholds and parameters for determining intentional inputs depending on the current driving scenario, vehicle state, and environmental conditions. This allows fast response through predefined rules while maintaining adaptability through dynamic parameter adjustment.
Solution Approach 2:
The system changes parameters based on driving scenarios by adjusting the thresholds and criteria for assessing operator intent. Different driving conditions (e.g., highway vs. city driving, weather conditions, traffic density) trigger different parameter sets, enabling the system to respond quickly with appropriate sensitivity levels for each scenario, thus balancing response speed with adaptability.
3Ease of operation
If the vehicle computer modifies control based on determined intentional inputs, then the ease of operation is improved, but the loss of information about autonomous system state increases
Solution Approach 1:
The system implements feedback by continuously monitoring the autonomous vehicle's operational state and using this information to inform the assessment of operator inputs. The computer considers the current autonomous control context when determining whether an input is intentional, ensuring that modifications to control are made with full awareness of the system state. This feedback loop maintains information awareness while enabling easy operator override when truly intentional.
Data Source
AI summary
Instructions are provided to at least one vehicle control for autonomous operation of a vehicle. A change in position is detected of at the least one vehicle control. A determination is made whether to modify operation of the vehicle at least in part according to the change in position of the at least one vehicle control. The autonomous operation of the vehicle is modified according to the change in position.