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Lane line detection method and device based on neural network, equipment and medium

A lane line detection and neural network technology, applied in biological neural network models, neural architectures, instruments, etc., can solve problems such as data errors and low accuracy of lane lines, reduce errors, improve accuracy and reliability, and improve The effect of efficiency

Pending Publication Date: 2022-07-29
AUTOMOTIVE INTELLIGENCE & CONTROL OF CHINA CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a neural network-based lane line detection method, device, equipment, and readable storage medium, which can solve the problems caused by hardware precision, environmental factors or sensor vibration in the existing lane line detection technology. The data has a large error, which leads to the problem of low accuracy of lane line detection

Method used

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  • Lane line detection method and device based on neural network, equipment and medium
  • Lane line detection method and device based on neural network, equipment and medium
  • Lane line detection method and device based on neural network, equipment and medium

Examples

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no. 1 example

[0049] see figure 1 .

[0050] like figure 1 As shown, this embodiment provides a method for detecting lane lines based on a neural network, which at least includes the following steps:

[0051] S1. Acquire lane line data collected by an autonomous vehicle within a preset period, and generate a lane line data set, where the lane line data set includes at least one set of lane line data;

[0052] S2, inputting the lane line data set into a preset neural network for lane line recognition to obtain an estimated lane line set, where the estimated lane line set includes at least one group of lane lines;

[0053] S3, performing clustering and fusion processing on each group of estimated lane lines in the set of estimated lane lines according to the target clustering algorithm, to obtain the current lane lines after calibration of each group, and generate a set of current lane lines;

[0054] S4. Matching the current lane line set with a preset map to obtain a target map set, wher...

no. 2 example

[0096] see figure 2 .

[0097] like figure 2 As shown, this embodiment provides a device for lane line detection based on a neural network, including:

[0098] A data collection module 100, configured to acquire lane line data collected by the autonomous driving vehicle within a preset period, and generate a lane line data set, wherein the lane line data set includes at least one set of lane line data;

[0099] An estimation module 200, configured to input the lane line data set into a preset neural network for lane line recognition, and obtain an estimated lane line set, where the estimated lane line set includes at least one set of lane lines;

[0100] The calibration module 300 is configured to perform clustering and fusion processing on each group of estimated lane lines in the set of estimated lane lines according to a target clustering algorithm, obtain the current lane lines after calibration of each group, and generate a set of current lane lines;

[0101] A match...

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Abstract

The invention discloses a lane line detection method and device based on a neural network, equipment and a medium, and the method comprises the steps: obtaining lane line data collected by an automatic driving vehicle in a preset period, and generating a lane line data set; inputting the lane line data set into a preset neural network for lane line recognition to obtain an estimated lane line set; performing clustering fusion processing on the estimated lane line set according to a target clustering algorithm to obtain each group of calibrated current lane lines, and generating a current lane line set; matching the current lane line set with a preset map to obtain a target map set; and according to the current lane line set and the target map set, detecting whether the current lane line is an actual lane line of the autonomous vehicle. According to the embodiment of the invention, the neural network is constructed to estimate the acquired lane line data, and map matching and detection are performed after lane line calibration, so that the accuracy and reliability of lane line detection are greatly improved, and the detection error is reduced.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, and in particular, to a method, device, device and readable storage medium for lane line detection based on a neural network. Background technique [0002] At present, one of the main research points of Advanced Driver Assistance Systems (ADAS) is to improve the safety of the vehicle itself or the driving of the vehicle and reduce road accidents. Smart and driverless vehicles are expected to address road safety, traffic issues and passenger comfort. Lane line detection is a complex and challenging task in research tasks for intelligent vehicles or unmanned vehicles. As a main part of the road, the lane line plays a role of providing reference for unmanned vehicles and guiding safe driving. Lane line detection includes road positioning, the relative positional relationship between the vehicle and the road, and the driving direction of the vehicle. [0003] During the pro...

Claims

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Application Information

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IPC IPC(8): G06V20/58G06N3/04G06K9/62G06V10/26G06V10/74G06V10/764G06V10/762G06V10/774G06V10/82G06V10/80
CPCG06N3/045G06F18/22G06F18/23213G06F18/25G06F18/24G06F18/214
Inventor 史帅管越
Owner AUTOMOTIVE INTELLIGENCE & CONTROL OF CHINA CO LTD
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