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

Blind spot turning planning method for unmanned vehicles based on partially observable Markov model

A Markov model and vehicle blind zone technology, applied in the field of turning planning in the blind zone of unmanned vehicles, can solve problems such as safety driving hazards of automatic vehicle control systems, and achieve the effects of improving traffic efficiency, speeding up processing speed, and good real-time performance

Active Publication Date: 2022-06-28
TONGJI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in actual intersections, especially in the planning of turning at intersections by unmanned driving systems, the risk of blind spots and the uncertainty of other vehicle intentions often exist at the same time, both of which will pose potential risks to the safe driving of automatic vehicle control systems. harm

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
  • Blind spot turning planning method for unmanned vehicles based on partially observable Markov model
  • Blind spot turning planning method for unmanned vehicles based on partially observable Markov model
  • Blind spot turning planning method for unmanned vehicles based on partially observable Markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0059] The present invention provides a layered algorithm for blind spot intersections of unmanned vehicles based on a partially observable Markov model. Planning and routing. The method can realize the safety and efficiency of unmanned vehicles turning at traffic intersections without signal lights, including:

[0060] Step 1: Obtain the traffic dataset of the current intersection;

[0061] Step 2: The high-level model of turn planning gener...

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 present invention relates to a blind spot turning planning method for unmanned vehicles based on a partially observable Markov model, comprising: step 1: obtaining the traffic data set at the current intersection; step 2: generating a high-level turning planning model based on the traffic data set at the current intersection Alternative path; Step 3: Input the alternative path into the low-level turning planning model based on partially observable Markov model, and output the planned turning path and planning speed in the blind spot of the unmanned vehicle; Step 4: Complete the blind spot turning planning of the unmanned vehicle. Compared with the prior art, the present invention has the advantages of good real-time performance, high security, fast processing speed, good universality and the like.

Description

technical field [0001] The invention relates to the technical field of unmanned vehicles, in particular to a blind-spot turning planning method for an unmanned vehicle based on a partially observable Markov model. Background technique [0002] Autonomous driving is a hot research topic at home and abroad. An unmanned vehicle is an intelligent vehicle that senses the surrounding environment through sensors, combines map information, makes autonomous decisions and plans paths, and controls the vehicle to reach the target location. The purpose of driverless technology is to help drivers reduce onerous driving tasks, improve traffic efficiency, and facilitate people's travel. The International Society of Engineers has published a six-level classification of automation for driverless vehicles, ranging from level 0 (no controls but with active safety systems) to level 5 (no human intervention). At present, the driverless technology of various scientific research institutions and...

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 Patents(China)
IPC IPC(8): B60W60/00
CPCB60W60/0011B60W60/0015B60W2720/106
Inventor 王峻王玥
Owner TONGJI UNIV
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com