Vehicle Trajectory Planning With Yaw-Rate Delay Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing trajectory planning systems for vehicles face challenges in accurately following a target curvature due to numerous changing and unknown factors, such as road surface conditions and tire characteristics, leading to delays and imprecisions in steering angle selection.
Innovation Solution
A trajectory planning system that measures actual curvature based on current yaw rate, determines target yaw rates, and uses a steering system with variables to compensate for delays through a parameter estimator and preview estimator, which recursively estimates delays and sets steering variables in advance to achieve precise trajectory control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a steering system with electronic steering axes is used to follow the target curvature, then the vehicle can implement predefined trajectories, but delays and imprecisions occur in obtaining the target curvature in the actual curvature due to changing factors such as road surface conditions and tire characteristics
Solution Approach 1:
The system calculates a preview time based on the estimated delay between target and actual yaw rates, then determines steering variables in advance for a future point in time. This preliminary action compensates for the inherent delays in the steering system by proactively adjusting steering angles before the delay would cause trajectory deviation.
Solution Approach 2:
The system recursively estimates the delay between target and actual yaw rates using sensor measurements of actual curvature and yaw rate, combined with target trajectory information. This feedback mechanism continuously adapts the preview time calculation to current system conditions, improving trajectory tracking precision despite varying road and tire characteristics.
2Adaptability or versatility
If steering variables are adjusted in real-time to follow the target trajectory, then the vehicle can adapt to changing conditions, but the changing and unknown factors such as road surface nature and tire contact make it difficult to select the correct steering angle
Solution Approach 1:
The system uses sensor systems to measure actual curvature and yaw rate, then recursively estimates the delay parameter based on the difference between target and actual vehicle response. This feedback loop continuously adapts to changing road surface conditions and tire characteristics, maintaining steering angle precision despite environmental variations.
Solution Approach 2:
The system determines the preview time and steering variables autonomously based on measured actual curvature, estimated delay parameters, and target trajectory information. The trajectory planning system self-adjusts to changing conditions without requiring external intervention or manual calibration for different road and tire combinations.
3Device complexity
If the steering system directly implements the target curvature from memory, then the system structure remains simple, but the sequence is subject to numerous changing factors that make reliable definition difficult across the entire functional range
Solution Approach 1:
The system calculates preview time and determines steering variables in advance for future time points, compensating for delays before they affect trajectory accuracy. This preliminary calculation approach maintains relatively simple system structure while significantly improving reliability across the entire functional range of trajectory control.
Solution Approach 2:
The system dynamically adjusts the preview time based on recursively estimated delay parameters that adapt to current operating conditions. This dynamic adjustment allows the steering control system to maintain reliability across varying speeds, road conditions, and tire characteristics without requiring a fundamentally complex system architecture.
Data Source
AI summary
A trajectory planning system for a vehicle includes a sensor system for measuring an actual curvature on the basis of a respective current yaw rate, a memory containing a target trajectory with target curvatures, wherein the trajectory planning system determines target yaw rates from the target curvature, and a steering system that uses steering variables to obtain target curvatures in actual curvatures. The system determines a respective first actual derivative of the measured respective current actual yaw rate over time and a respective first target derivative of the respective current target yaw rate over time. A correlator determines a respective current delay on the basis of the respective first actual derivatives and the respective first target derivatives in a current yaw rate segment, and a parameter estimator recursively estimates the delay between the target yaw rate and the actual yaw rate on the basis of respective current delay inputs.