Autonomous Vehicle Control Transition Strategy
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Solution Overview
Problem
Existing autonomous vehicle systems lack efficient methods for seamlessly transitioning control from autonomous mode to manual mode without interruption, particularly in dynamic driving conditions, and often fail to verify driver intent accurately, leading to potential safety hazards.
Innovation Solution
A computing device within the vehicle monitors various parameters such as speed, steering, braking, and environmental factors to determine the appropriateness of transitioning control to the driver, using thresholds and strategies to ensure safe and efficient handover, including determining the duration and systems to transition, based on driver input and vehicle state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the autonomous vehicle system transitions control to manual mode upon driver input, then driver control is enabled, but the transition may be interrupted or delayed in dynamic driving conditions, creating safety hazards
Solution Approach 1:
The system performs preliminary verification of driver intent by monitoring driver inputs (steering wheel torque, brake pedal position, accelerator pedal position) before executing the control transition. This preliminary action ensures that the driver genuinely intends to take control and reduces the risk of unintended mode switching, thereby improving transition safety while maintaining smooth operation.
Solution Approach 2:
The system continuously monitors vehicle state parameters (speed, acceleration, steering angle) and driver input parameters during the transition process. This feedback mechanism allows the system to adapt the transition strategy in real-time based on dynamic driving conditions, ensuring both smooth transition and high reliability by preventing interruption when unsafe conditions are detected.
2Reliability
If the system monitors multiple parameters (speed, steering, braking, environmental factors) to verify driver intent, then transition safety improves, but system complexity increases
Solution Approach 1:
The computing device leverages existing sensors and control systems already present in the autonomous vehicle for other functions (speed monitoring for cruise control, steering angle sensing for lane keeping, brake monitoring for emergency stopping). By reusing these multi-functional components for driver intent verification, the system achieves high reliability without proportionally increasing device complexity.
Solution Approach 2:
The system combines multiple monitoring functions (speed monitoring, steering input detection, brake pedal position sensing, environmental factor assessment) into a unified control transition decision-making framework. This merging approach consolidates the complexity into a single integrated system rather than requiring separate dedicated sensors and processing units for each parameter, thereby improving verification accuracy while managing overall system complexity.
3Reliability
If the transition strategy adapts to vehicle state (speed, acceleration, steering angle), then transition safety improves, but control complexity increases
Solution Approach 1:
The control transition strategy is designed to be dynamic rather than static. The system adjusts transition parameters (transition duration, rate of control transfer) based on real-time vehicle state (speed, acceleration, steering angle). This dynamic adaptation improves safety by preventing transitions during critical maneuvers while enabling smooth transitions during stable driving conditions. The complexity is managed by using straightforward conditional logic based on pre-defined thresholds for vehicle parameters.
Data Source
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AI summary
Methods and systems for adaptive methods for transitioning control to the driver are described. A computing device controlling a vehicle autonomously may be configured to receive a request for a transition of the vehicle from autonomous mode to manual mode through an indication by the driver. The computing device may determine the state of the vehicle based on parameters related to the autonomous operation of the vehicle. Based on the state of the vehicle and the indication, the computing device may determine instructions corresponding to the transition of control, which may include a strategy for the transition and duration of time corresponding to the transition of control. The computing device may pro vide the instructions to perform the transition of control of the vehicle from autonomous mode to manual mode.