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A Predictive Control Method for Trajectory Control Applied to Autonomous Driving

A trajectory control and control method technology, which is applied in the field of predictive control of trajectory control, can solve the problems of insufficient use of future trajectory information, large steering fluctuations, and large tracking errors, so as to reduce frequent changes in corners, reduce lateral errors, The effect of reducing the number of downtime or performance degradation

Active Publication Date: 2022-07-08
ZF COMMERCIAL VEHICLE SYSTEMS (QINGDAO) CO LTD
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Problems solved by technology

[0003] The traditional control algorithm cannot or does not make full use of the future trajectory information of the brain, and at the same time combines the dynamic information of the whole vehicle to drive the car safely, accurately and comfortably
The traditional control algorithm—PID control algorithm has the problems of large steering fluctuation, large tracking error, slow response and low robustness, and it is difficult to adapt to the complex open road environment

Method used

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  • A Predictive Control Method for Trajectory Control Applied to Autonomous Driving
  • A Predictive Control Method for Trajectory Control Applied to Autonomous Driving
  • A Predictive Control Method for Trajectory Control Applied to Autonomous Driving

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Embodiment Construction

[0077] In order to facilitate those skilled in the art to understand and implement the present invention, the specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments:

[0078] like figure 1 As shown, a predictive control method for trajectory control applied to automatic driving includes the following steps:

[0079] Step 1: The domain controller receives real-time signals from the virtual brain controller and the vehicle CAN network;

[0080] The signals input by the virtual brain controller include the coordinate information of the planned trajectory, the motion information, and the position error between the current vehicle position and the reference trajectory;

[0081] The coordinate signal of the planned trajectory includes: abscissa y, ordinate x and steering angle phi;

[0082] The motion information includes: the speed, acceleration, curvature, and rate of curvature change o...

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Abstract

The invention discloses an estimation control method applied to trajectory control of automatic driving, and belongs to the technical field of basic intelligent driving. First, the domain controller receives the signal input from the virtual brain controller and the vehicle CAN network in real time, then filters the lateral deviation dy and the heading angle deviation dphi in the signal, and substitutes it into the dynamic error prediction estimation model to calculate a new lateral deviation dy and heading angle deviation dphi. Deviation dy, heading angle deviation dphi, lateral deviation change rate and heading angle deviation change rate; predict future H according to the prediction model of the dynamic change of deviation p Lateral deviation dy, lateral deviation change rate, steering angle deviation dphi and steering angle deviation change rate of each point; finally calculate the steering angle and input it to the steering angle control system in the form of CAN message, the steering control output request is subject to the active steering system stabilization Physical limits of operation. The present invention improves the safety and comfort of automatic driving, and expands the adaptation scenarios of automatic driving.

Description

technical field [0001] The invention belongs to the technical field of basic intelligent driving, and in particular relates to an estimation control method applied to trajectory control of automatic driving. Background technique [0002] The environment perception and path planning of the existing unmanned system (SAE L4) autonomous driving are all handed over to the virtual brain with powerful computing power. The vehicle controller is responsible for controlling the car's actuators - engine, steering system, braking system, etc. to make the car track the trajectory of the brain. [0003] The traditional control algorithm cannot or does not fully utilize the future trajectory information of the brain, and at the same time combines the dynamics information of the whole vehicle to drive the car safely, accurately and comfortably. The traditional control algorithm-PID control algorithm has the problems of large steering fluctuation, large tracking error, slow response and low...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60W30/095
CPCB60W30/0953
Inventor 陈明星
Owner ZF COMMERCIAL VEHICLE SYSTEMS (QINGDAO) CO LTD
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