Method and system for previewing safe path based on CNN and LSTM

A technology of safe path and preview, which is applied to the car that previews the safe path. The field of previewing the safe path based on CNN and LSTM can solve problems such as unsolved problems, and achieve convenient analysis, reduce deviation, and improve driving safety. Effect

Active Publication Date: 2020-12-29
HEFEI UNIV OF TECH
View PDF9 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But this invention also does not solve the technical problem of reducing the deviation between the expected path and the actual path

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and system for previewing safe path based on CNN and LSTM
  • Method and system for previewing safe path based on CNN and LSTM
  • Method and system for previewing safe path based on CNN and LSTM

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] A detailed description will be given below in conjunction with the accompanying drawings.

[0056] In the prior art, due to the large deviation between the expected path and the actual path, the driving safety of the driver needs to be improved. The invention determines the steering wheel angle applied by the driver to the car through the preset road trajectory and expected vehicle speed information, thereby determining the driving path of the driver. The LSTM is used to continuously adjust the internal weights of the neural network, thereby reducing the deviation between the expected path and the actual path, and obtaining a good preview path following the driver model.

[0057] The present invention is the method and the system of preview safe path based on CNN and LSTM, also can be a kind of long short-term memory network (LSTM, Long Short-Term Memory) driver model preview path optimization method, can also be a A method and system for establishing a driver followin...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a method and a system for previewing a safe path based on a CNN (Convolutional Neural Network) and an LSTM (Long Short Term Memory). The method at least comprises the following steps: predicting an ideal steering wheel rotation angle of an initial driver following model based on expected vehicle speed information and expected path information; optimizing the ideal steeringwheel rotation angle into an actual steering wheel rotation angle based on vehicle motion information fed back by a vehicle model; and optimizing vehicle attitude information based on the actual steering wheel rotation angle information and fitting to obtain expected path information by the vehicle model. According to the method and the system, through a preset road track and expected vehicle speed information, the steering wheel rotation angle applied to the vehicle by the driver is decided, so that the driving path of the driver is decided. and internal weight of a neural network is continuously adjusted through LSTM, so that deviation between an expected path and an actual path is reduced, and a good driver preview following model for preview path following is obtained.

Description

technical field [0001] The present invention relates to the technical field of intelligent driving, in particular to a method and system for previewing safe paths based on CNN and LSTM. The invention also relates to the technical field of automobiles, and relates to an automobile that previews a safe path. Background technique [0002] Path tracking is one of the cores of the underlying control of autonomous driving, and its performance determines the safety and stability of the vehicle. In the field of path tracking research, the more commonly used methods are: PID, driver preview model, model predictive control (Model Predictive Control, MPC) and so on. Among them, the PID algorithm has a simple structure, but it is difficult to adjust the parameters, and the fixed parameters cannot be used for complex and changeable driving conditions. Model predictive control can cope with different working conditions, but it has high requirements for the vehicle model and a large amoun...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): B60W30/12B60W40/105B60W10/20B60W50/00
CPCB60W30/12B60W40/105B60W10/20B60W50/00B60W2050/0043B60W2520/10B60W2710/20
Inventor 张良饶泉泉续秋锦祁永芳李鑫孙克
Owner HEFEI UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap