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Estimation control method applied to trajectory control of automatic driving

A trajectory control and control method technology, applied in the field of predictive control of trajectory control, can solve the problems of large tracking error, underutilization of future trajectory information, slow response, etc.

Active Publication Date: 2021-04-09
ZF COMMERCIAL VEHICLE SYSTEMS (QINGDAO) CO LTD
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AI Technical Summary

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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  • Estimation control method applied to trajectory control of automatic driving
  • Estimation control method applied to trajectory control of automatic driving
  • Estimation control method applied to trajectory control of automatic driving

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Embodiment Construction

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

[0078] Such as 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 signals input from the virtual brain controller and the vehicle CAN network in real time;

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

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

[0082] Motion information includes: velocity, acceleration, curvature, and curv...

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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. Firstly, a domain controller receives signals input by a virtual brain controller and a whole vehicle CAN network in real time, then transverse deviation dy and course angle deviation dphi in the signals are filtered and substituted into a dynamic error prediction and estimation model, and new transverse deviation dy, course angle deviation dphi, transverse deviation change rate and course angle deviation change rate are obtained through calculation; the lateral deviation dy, the lateral deviation change rate, the steering angle deviation dphi and the steering angle deviation change rate of future Hp points are estimated according to an estimation model of the deviation dynamic variation; and finally, a steering angle is calculated and input to a steering angle control system in a CAN message form, and a steering control output request needs to be limited by the physical limit of stable operation of the active steering system. According to the invention, the safety and comfort of automatic driving are improved, and the adaptive scene of automatic driving is expanded.

Description

technical field [0001] The invention belongs to the technical field of basic intelligent driving, and in particular relates to a predictive control method applied to trajectory control of automatic driving. Background technique [0002] The environment perception and path planning of the existing unmanned driving system (SAE L4) autonomous driving are all assigned to the virtual brain with powerful computing capabilities. The vehicle controller is responsible for controlling the vehicle's executive agencies—engine, steering system, braking system, etc. to make the car follow the trajectory of the brain. [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 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, sl...

Claims

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Application Information

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IPC IPC(8): B60W30/095
CPCB60W30/0953
Inventor 陈明星
Owner ZF COMMERCIAL VEHICLE SYSTEMS (QINGDAO) CO LTD
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