Lane Path Control Using Real-Time Understeer Gradient Updates
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Solution Overview
Problem
Existing autonomous and semi-autonomous vehicles struggle to maintain precise lane centering during turns due to unpredictable changes in understeer gradient caused by factors like load variations, which are not accounted for in real-time, leading to potential off-centering and discomfort for occupants.
Innovation Solution
A method and device that continuously update the understeer gradient in real-time by tracking and storing state variables during vehicle movement, adjusting the steering angle to account for load changes and other factors, ensuring smooth path control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the understeer gradient is determined using a fixed nominal value, then the control system is simple, but the vehicle path control precision deteriorates when load conditions change
Solution Approach 1:
The understeer gradient is transformed from a fixed static parameter to a dynamic parameter that is continuously updated based on real-time vehicle state variables. The system determines the understeer gradient by processing state variables (lateral acceleration, steering angle, vehicle speed) during actual vehicle operation, allowing the parameter to adapt dynamically to changing load conditions and road situations.
Solution Approach 2:
The system implements a feedback mechanism where the understeer gradient is continuously determined from measured state variables and used to adjust the path control. The control unit processes current and historical state variables to update the understeer gradient value, which then feeds back into the path control calculation, creating a closed-loop system that automatically compensates for load variations.
2Measurement precision
If the understeer gradient is updated in real-time during vehicle movement, then the path control precision is improved, but the device complexity increases
Solution Approach 1:
The control system performs self-calibration by automatically determining the understeer gradient from its own operational data. The system uses state variables already being collected for other control functions (lateral acceleration, steering angle, speed) to compute the understeer gradient without requiring external calibration equipment or additional complex sensors, making the system self-sufficient.
Solution Approach 2:
The system performs preliminary determination of the understeer gradient using stored values from previous sampling increments before finalizing the control command. By accumulating and processing state variable data over multiple sampling periods, the system prepares an accurate understeer gradient value in advance, smoothing out transient variations and providing a more reliable basis for path control.
3Speed
If the understeer gradient is determined from instantaneous state variables, then the response to load changes is fast, but the control stability deteriorates due to noise and fluctuations
Solution Approach 1:
The system performs preliminary processing of state variables over multiple sampling increments before determining the understeer gradient. By accumulating data from current and previous sampling periods and applying smoothing calculations, the system filters out transient noise and fluctuations while maintaining the ability to respond to genuine load changes, thus stabilizing the control output.
Solution Approach 2:
The understeer gradient determination is performed continuously across multiple sampling increments rather than as discrete instantaneous measurements. The system maintains a continuous calculation process that uses both current and historical state variable data, ensuring smooth transitions and continuous adaptation without abrupt changes, thereby maintaining control stability.
Data Source
AI summary
A method for controlling in real time the path of a motor vehicle travelling in a traffic lane includes detecting a corner in the traffic lane, then, when the vehicle enters the corner, determining first and second quantities for a plurality of successive sampling increments, based on state variables characteristic of the movement of the vehicle, determining a first stored value dependent on the first quantity determined in the current sampling increment and one of the preceding sampling increments, determining a second stored value dependent on the second quantity determined in the current sampling increment and one of the preceding sampling increments, saving the first and second stored values determined for each sampling increment, then, when the vehicle exits the corner determining a value of the understeer gradient depending on the saved first and second stored values, and determining a command for the vehicle based on the understeer gradient.