Automated Vehicle Steering Control for Manual to Automated Mode Transition
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Solution Overview
Problem
Existing autonomous vehicle systems face challenges in seamlessly transitioning from manual to automated steering modes, particularly in accurately centering the vehicle within a lane during mode transition, which can result in aggressive vehicle maneuvers.
Innovation Solution
A vehicle steering control system utilizing a combination of sensor systems, including computer-vision, radar, and LIDAR, along with a controller-circuit that employs a feedback control algorithm for initial centering and a neural-network algorithm for maintaining position, allowing smooth transition from manual to automated mode by processing position relationship data to steer the vehicle to the center of the lane.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single control algorithm is used for mode transition, then the system complexity is reduced, but the vehicle centering accuracy deteriorates causing aggressive maneuvers
Solution Approach 1:
The control system is segmented into two distinct modules: a first control algorithm that operates during the transition phase to center the vehicle, and a second control algorithm that maintains lane position after centering. This segmentation allows each algorithm to be optimized for its specific function, resolving the contradiction between system simplicity and centering accuracy.
Solution Approach 2:
The system dynamically switches between control algorithms based on the vehicle's position and transition state. The first algorithm is applied when the vehicle is off-center during mode transition, and the second algorithm takes over when the vehicle reaches the center. This dynamic adaptation enables accurate centering without requiring a permanently complex control system.
2Loss of time
If aggressive steering corrections are applied during mode transition, then the vehicle centers faster, but the ride comfort and safety deteriorate
Solution Approach 1:
The control system continuously monitors vehicle position relative to the lane center and adjusts steering corrections based on feedback. The first control algorithm applies gentle corrections that accumulate to center the vehicle without causing aggressive maneuvers, while the second algorithm maintains position with minimal adjustments. This feedback mechanism resolves the contradiction by achieving centering over an optimized time period without aggressive corrections.
3Stability of the object's composition
If manual control is maintained during transition, then vehicle stability is preserved, but the automated mode cannot be activated
Solution Approach 1:
The system performs preliminary centering action using the first control algorithm before fully activating automated mode. This preliminary action ensures the vehicle is properly positioned and stable when transitioning to automated operation, resolving the contradiction by preparing the vehicle state in advance so that automated activation does not compromise stability.
Data Source
AI summary
A system includes one or more sensor systems, a controller-circuit, a first module, and a second module. The sensor systems are configured to determine position relationship data between a roadway and a host vehicle. The sensor system includes at least one of a computer-vision system, a radar system, and a LIDAR system. The controller-circuit is configured to receive and transform the position relationship data to effect steering control of the host vehicle. The first module is controlled by the controller-circuit to effect the steering control when the steering control transitions from a manual-mode to an automated mode. The second module is controlled by the controller-circuit to effect steering control of the host vehicle after control by the first module and upon meeting a prescribed condition.