Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Unmanned driving deep reinforcement learning method fused with humanoid driving behaviors

An unmanned driving and reinforcement learning technology, which is applied in the direction of position/direction control, autonomous decision-making process, vehicle position/route/height control, etc., can solve the problem of inability to have decision-making robustness, and achieve improved human-like characteristics , improve the discrete probability and preserve the effect of robustness

Active Publication Date: 2020-09-18
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
View PDF7 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is more focused on realizing functions rather than achieving high driving performance. Due to the uncertainty of the data source of driverless cars, this kind of solution that relies on accurate environmental judgment cannot be robust enough to deal with the real road environment. sex

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
  • Unmanned driving deep reinforcement learning method fused with humanoid driving behaviors
  • Unmanned driving deep reinforcement learning method fused with humanoid driving behaviors
  • Unmanned driving deep reinforcement learning method fused with humanoid driving behaviors

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangements of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0059] The following description of at least one exemplary embodiment is merely illustrative in nature and in no way taken as limiting the invention, its application or uses.

[0060] Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.

[0061] In all examples shown and discussed herein, any specific values ​​should be construed as exemplary only, and not as limitations. Therefore, other instances of the exemplary embodiment may have dif...

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 discloses an unmanned deep reinforcement learning method fused with humanoid driving behaviors. The method comprises the steps of: building a humanoid driving rule through priori knowledge, wherein the humanoid driving rule is used for reflecting the driving logic of a human; and taking the driving of a vehicle as a continuous and stateful process, performing posteriori constraint onan unmanned driving strategy based on the humanoid driving rule constraint, shaping a constraint result into a reward and punishment function, and exploring the unmanned driving strategy meeting a set standard by utilizing deep reinforcement learning. According to the invention, an unmanned driving strategy with humanoid logic can be output, and more excellent control performance and training efficiency are achieved.

Description

technical field [0001] The present invention relates to the technical field of unmanned driving of vehicles, and more specifically, relates to a deep reinforcement learning method for unmanned driving that integrates human-like driving behavior. Background technique [0002] Unmanned driving is an inevitable trend of future vehicle development and an effective way to avoid human driving errors and improve traffic efficiency. The rapid development of existing communication, electronics and computer technologies has laid a solid foundation for the development of unmanned driving technology. The Institute of Electrical and Electronics Engineers (IEEE) predicts that by 2040, 75% of vehicles will be driverless cars. The market growth rate of unmanned vehicles will be 10 times that of other vehicles, and the emergence of unmanned vehicles will reduce the traffic accident rate to 10%. [0003] Among the many tasks faced by artificial intelligence, unmanned driving is a very chall...

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): G05D1/00G06N3/04
CPCG05D1/0088G06N3/045
Inventor 徐坤吕迪李慧云
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products