Automatic driving method and system of deep learning based on traffic element visual enhancement

An autonomous driving and visual enhancement technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as insufficient attention, safety accidents in autonomous vehicles, and inability to achieve autonomous driving capabilities.

Active Publication Date: 2020-12-01
GUANGZHOU AUTOMOBILE GROUP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the existing deep learning automatic driving methods directly use the original image as the input of the deep learning network, resulting in the network not paying enough attention to traffic elemen

Method used

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  • Automatic driving method and system of deep learning based on traffic element visual enhancement
  • Automatic driving method and system of deep learning based on traffic element visual enhancement
  • Automatic driving method and system of deep learning based on traffic element visual enhancement

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Embodiment Construction

[0069] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0070] Such as figure 1 As shown, it shows a schematic diagram of the main flow of an embodiment of an automatic driving method based on deep learning of traffic element visual enhancement provided by the present invention, combined with Figure 2 to Figure 3 As shown, in this embodiment, the method includes the following steps:

[0071] Step S10, collect the driving environment data of the current vehicle through the vehicle-mounted camera; in one example, use a camera installed at the front of the vehicle to collect the driving environment data. A collection frequency (such as 30Hz) for collection;

[0072] Step S11, using the sensory neural network to identify traffic elements in the collected driving environment data, and visually enhancing the identified tr...

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Abstract

The invention discloses an automatic driving method of deep learning based on traffic element visual enhancement. Vehicle driving data is obtained through a vehicle-mounted camera; traffic elements such as vehicles, pedestrians, traffic lights, lane lines, stop lines and the like in the image are identified by utilizing the established perception neural network; visual enhancement is carried out on traffic elements in an image through different color blocks, then the enhanced image serves as input and is imported into a pre-determined and trained deep learning neural network model, and an expected steering wheel angle, accelerator opening and brake force are outputted so as to control a vehicle to achieve automatic driving. The invention further discloses a corresponding system. The attention of the deep learning automatic driving system to the key road traffic elements can be increased, and thus the safety, reliability and robustness of automatic driving are effectively improved.

Description

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Claims

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Application Information

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Owner GUANGZHOU AUTOMOBILE GROUP CO LTD
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