Heavy-Duty Vehicle Path Following With Adaptive Preview Control
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Solution Overview
Problem
Existing path following methods for heavy-duty vehicles face challenges in maintaining path tracking accuracy and stability, especially at higher speeds, due to lateral instability and rollover issues. Current methods often rely on gain scheduling and internal vehicle models, which can lead to performance degradation and are not easily scalable or adaptable to different vehicle combinations.
Innovation Solution
The proposed method involves a control unit that improves path tracking and lateral stability by incorporating tolerance margins and adjusting the preview distance based on lateral deviation and vehicle speed. This approach relaxes the control objective to utilize available lateral maneuvering room, reducing peak lateral accelerations and jerk, and is designed to operate in real-time without requiring complex gain scheduling or internal vehicle models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pure pursuit path following algorithm is used, then path tracking simplicity is improved, but path tracking accuracy deteriorates at higher speeds
Solution Approach 1:
The patent implements dynamic preview distance adjustment based on vehicle speed and lateral deviation. The preview distance is not fixed but adapts in real-time according to vehicle operating conditions, allowing the pure pursuit algorithm to maintain accuracy across varying speeds without increasing computational complexity or requiring complex gain scheduling.
2Manufacturing precision
If gain scheduling is used to handle various vehicle speeds, then path tracking accuracy is improved, but device complexity increases
Solution Approach 1:
The patent changes the parameter being adjusted from multiple gain parameters (as in gain scheduling) to a single preview distance parameter. This single parameter dynamically adapts to vehicle speed and lateral deviation, achieving speed-adaptive path tracking without the complexity of multiple gain parameters or switching between different controllers.
3Reliability
If model-based motion planning is used, then path following performance is improved, but computational cost increases
Solution Approach 1:
The patent extracts and removes the requirement for internal vehicle models from the path following algorithm. By using pure pursuit with dynamic preview distance adjustment, the system achieves adaptive path following without needing to incorporate complex vehicle dynamics models, thereby reducing computational cost while maintaining performance.
4Device complexity
If fixed preview distance is used, then control simplicity is improved, but adaptability to different speeds deteriorates
Solution Approach 1:
The patent makes the preview distance dynamic rather than fixed. The preview distance automatically adjusts based on vehicle speed and lateral deviation from the reference path, enabling the simple pure pursuit algorithm to adapt to different speeds and driving conditions without increasing control complexity.
Data Source
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AI summary
A method for controlling a heavy-duty vehicle to follow a reference path (P), comprising determining a goal point along the reference path to be used as a steering reference from a vehicle location in vicinity of the path, where the goal point is distanced along the path by a preview distance measured from a reference location associated with the vehicle location, determining a direction w1 of a first flow field associated with the reference path, determining whether a lateral deviation of the vehicle location from the reference path exceeds a threshold lateral deviation, and controlling the vehicle in accordance with the direction w1 of a first flow field if the lateral deviation exceeds the threshold lateral deviation, and otherwise controlling the vehicle in accordance with the direction wpipe of a pipe flow substantially parallel to the reference path or in accordance with an optimization-based path (1302).