Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

A Real-time Recognition Method of Surrounding Vehicle Behavior Based on Kinematics Prediction and Compensation Mechanism

A technology of compensation mechanism and identification method, applied in traffic control systems, traffic control systems, instruments and other directions of road vehicles, which can solve the problems of intelligent vehicles with little practical significance, incomplete historical information, and lack of real-time identification and applicability. , to achieve the effect of short calculation time of probability speculation, enhanced applicability and accuracy, and enhanced real-time recognition

Active Publication Date: 2021-08-17
JIANGSU UNIV
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing hot spot feature conversion method only uses the historical location information of surrounding vehicles, and the recognition is often completed after the behavior has been basically completed. At this time, the recognition result has little practical significance for intelligent vehicles, and lacks real-time recognition and applicability.
In addition, in the initial stage of the execution of a certain surrounding vehicle behavior, the recognition accuracy is generally low due to the incomplete historical information of the behavior in the observation sequence and the interference of the previous vehicle behavior information.

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
  • A Real-time Recognition Method of Surrounding Vehicle Behavior Based on Kinematics Prediction and Compensation Mechanism
  • A Real-time Recognition Method of Surrounding Vehicle Behavior Based on Kinematics Prediction and Compensation Mechanism
  • A Real-time Recognition Method of Surrounding Vehicle Behavior Based on Kinematics Prediction and Compensation Mechanism

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be further described below in conjunction with drawings and embodiments.

[0040] Such as figure 1 Shown, implementation of the present invention comprises as follows:

[0041] Step1: The typical behavior of Zhouche and the definition of hot zone

[0042] The typical behaviors of surrounding vehicles are classified into maneuvers, which are left lane change, right lane change, and lane keeping. For vehicles, my country’s expressway is a two-way three-lane type. Taking this as an example, the road is divided into five hot spots in combination with the lane line and the shoulder position, and each area has a corresponding hot spot value, which is A, B, C, D, E. Among them, let the lane width be L. Let the area A be between the left shoulder and L / 4 on the right side of the centerline of the left lane, and area B between the L / 4 on the right side of the centerline of the left lane and L / 4 on the left side of the centerline of the middle lane. ...

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 a real-time identification method of surrounding vehicle behavior based on kinematics prediction and compensation mechanism, including: typical behavior of surrounding vehicles and hot zone definition: classifying the typical behavior of surrounding vehicles, combining lane lines and road shoulder positions, Divide into 5 hotspot areas; offline training of hidden Markov vehicle behavior recognition model: establish discrete hidden Markov model DHMM for each maneuver class, and use EM algorithm to train each DHMM model to obtain the best DHMM model group; Establish a vehicle trajectory prediction kinematics model: The vehicle trajectory prediction kinematics model can predict the trajectory and generate the position sequence information of the vehicle for the next 3 time steps; online real-time recognition: the obtained vehicle history 5 time step position sequence and the predicted vehicle future 3 The time-step position sequence is transformed into an 8-time-step hotspot sequence, which is input to the trained hidden Markov vehicle behavior recognition model, and the surrounding target vehicle behavior is obtained by forward calculation and recognition.

Description

technical field [0001] The invention belongs to the technical field of intelligent driving, and in particular relates to a method for real-time recognition of surrounding vehicle behavior based on a kinematics prediction and compensation mechanism. Background technique [0002] Nowadays, whether it is advanced driver assistance systems or fully autonomous vehicles, scholars in various fields have aroused extensive research interests. There is no doubt that automotive intelligence has become one of the most important trends and trends in the development of the automotive industry. In addition, the 5G communication era is coming, and our country is one of the leaders leading this era. The V2X communication of 5G Internet of Vehicles based on D2D technology has an air interface delay of about 1ms and an end-to-end delay of milliseconds. Accurately obtain the status information of surrounding vehicles in real time under the scene. At this stage, the biggest challenge for us to...

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): G08G1/017G06F30/20
CPCG08G1/017G06F30/20
Inventor 蔡英凤邰康盛王海陈小波李祎承刘擎超
Owner JIANGSU UNIV
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
Eureka Blog
Learn More
PatSnap group products