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Automatic driving control method, automatic driving device and computer storage medium

A technology of automatic driving control and computer program, applied in the fields of automatic driving device, automatic driving control, and computer storage media, can solve the problems of poor real-time decision-making, limited parallelism, and low parallel efficiency, so as to improve real-time performance and utilization rate , to ensure the effect of safety

Active Publication Date: 2022-02-18
SANY SPECIAL PURPOSE VEHICLE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For massive computing tasks, the current autonomous driving decision-making system has limited parallelism, and there are a large number of vacant computing resources in actual computing. The actual parallel efficiency is very low, and the real-time decision-making is poor.

Method used

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  • Automatic driving control method, automatic driving device and computer storage medium
  • Automatic driving control method, automatic driving device and computer storage medium
  • Automatic driving control method, automatic driving device and computer storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] Such as figure 1 As shown, in one embodiment of the present invention, a kind of automatic driving control method is provided, comprising:

[0043] S102, acquiring real-time road environment information;

[0044] S104, generating an event flow according to a preset reasoning rule base and real-time road environment information;

[0045] S106, generating multiple inference events according to the event flow;

[0046] S108, establishing a directed acyclic graph model in real time according to multiple reasoning events and a preset reasoning rule base;

[0047] S110, outputting a security operation sequence according to the directed acyclic graph model and the preset reasoning rule base;

[0048] S112, delivering the safety operation sequence to the transmission system.

[0049] The automatic driving control method provided in this embodiment first acquires real-time road environment information when performing automatic driving control on a vehicle. Among them, real-...

Embodiment 2

[0055] Such as figure 2 As shown, in one embodiment of the present invention, a kind of automatic driving control method is provided, comprising:

[0056] S202, acquiring real-time road environment information;

[0057] S204, matching the real-time road environment information with the preset road environment information;

[0058] S206. Generate an event stream according to the first inference rule information;

[0059] S208, generating multiple inference events according to the event flow;

[0060] S210. Obtain a partial order relationship among multiple inference events according to the second inference rule information;

[0061] S212, establishing a partial order graph according to the partial order relationship;

[0062] S214, establishing a directed acyclic graph model according to the partial order graph;

[0063] S216. Execute multiple inference events according to the DAG model and the third inference rule information;

[0064] S218, outputting a security operat...

Embodiment 3

[0072] Such as image 3 As shown, in one embodiment of the present invention, a kind of automatic driving control method is provided, comprising:

[0073] S302, acquiring real-time road environment information;

[0074] S304, matching the real-time road environment information with the preset road environment information;

[0075] S306. Generate an event flow according to the first inference rule information;

[0076] S308, generating multiple inference events according to the event flow;

[0077] S310. Obtain a partial order relationship among multiple inference events according to the second inference rule information;

[0078] S312. Establish a partial order graph according to the partial order relationship;

[0079] S314, adding a real-time constraint to the partial sequence diagram;

[0080] S316, establishing a directed acyclic graph model according to the partially ordered graph;

[0081] S318. Detect whether multiple reasoning events satisfy the real-time constrain...

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Abstract

The invention provides an automatic driving control method, an automatic driving device and a computer storage medium. Among them, the automatic driving control method includes: obtaining real-time road environment information, generating an event flow according to the preset reasoning rule base and real-time road environment information; generating multiple reasoning events according to the event flow; Establish a directed acyclic graph model; output a safe operation sequence according to the directed acyclic graph model and a preset reasoning rule base; transfer the safe operation sequence to the transmission system. The automatic driving control method provided by the present invention constructs a directed acyclic graph model and solves it according to the inference events and the preset inference rule library, so that multiple inference events can be calculated in parallel at a higher degree of parallelism, making full use of the computing resources of the system , and reduce the repeated execution of reasoning operations, thereby improving the decision-making efficiency of automatic driving.

Description

technical field [0001] The present invention relates to the technical field of vehicle control, in particular to an automatic driving control method, an automatic driving device and a computer storage medium. Background technique [0002] In related technologies, the automatic driving decision-making system generally uses a linear model or a relatively modular parallel model, and sequentially imposes traffic rule constraints, path constraints, and speed constraints on automatic driving to obtain an automatic driving decision that meets the requirements. With the rapid development of urban traffic, the road conditions will become more and more complex, and the calculation amount of the corresponding program will increase rapidly. For massive computing tasks, the current autonomous driving decision-making system has limited parallelism, and there are a large number of vacant computing resources in actual computing. The actual parallel efficiency is very low, and the real-time ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60W60/00G06N5/04
CPCB60W60/0015G06N5/04
Inventor 胡文彪贺志国
Owner SANY SPECIAL PURPOSE VEHICLE CO LTD