KR20170017189A

KR20170017189A - Switching driving view screen utilizing the Internet of Things and method of manufacturing

Info

Publication number: KR20170017189A
Application number: KR1020150110750A
Authority: KR
Inventors: 김태일; 조태엽
Original assignee: 김태일; 조태엽
Priority date: 2015-08-05
Filing date: 2015-08-05
Publication date: 2017-02-15

Abstract

The present invention enables a driver to easily recognize vehicles around a drivers vehicle by providing a driving screen at a view downward from an upper side to make the driver recognize information about the vehicles around the drivers vehicle at a look while the driver performs other tasks in case an autonomous vehicle is widely used by enabling the driver to recognize unexpected accidents, which are caused by a fact that a viewing angle of the people is limited and, especially, a fact that people is unable to recognize except for a spot where the people looks in concentration, better. To this end, the present application is to claim patents about a method for displaying the information about the vehicles and objects around the drivers vehicle on a screen and a method and an algorithm for indicating a risk degree of the movable object around the vehicle applied to the drivers vehicle with colors.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a driving-time conversion screen,

The present invention provides a screen for easily recognizing the position of a nearby vehicle in a backward and lane change situation or an unmanned driving situation by introducing AVHS, A monitoring program and a location detection method that provide a single view of threats to be performed.

The effective field of view of a person is shown in Fig. Due to this limited visibility, the driver will focus on the front or rearview mirror depending on the direction in which the driver is going in the current driving situation. In such a situation, if an unexpected situation occurs in another place where the driver is unconscious, the driver experiences an unexpected accident.

Due to the effective view of such a person, there is a blind spot generated by the rearview mirror even in the lane changing and backward parking situations.

On December 23, 2014, Google unveiled a self-driving vehicle that recognizes and drives lane alone without people. In addition to Google, vehicle makers are also preparing to commercialize autonomous vehicles. However, due to the limitation that it is impossible to forecast all kinds of unexpected situations and situations of accidents, autonomous driving vehicles, which are scheduled to be commercialized, are intended to be driven by drivers capable of driving.

However, in the automatic driving situation by the self-driving vehicle, the driver can see other tasks other than driving. If the driver suddenly starts driving by the signal of the vehicle in a situation where the driver can not grasp the driving situation around him, he needs rather the recognition time.

Based on this point, the present invention provides a monitor and a method for providing a driver, who is aboard the autonomous vehicle, to easily recognize the location information of the nearby vehicle and the threat given to the traveling vehicle at a glance.

Herein, the term 'driving vehicle' refers to one vehicle in which a driver drives a vehicle equipped with the result of the present invention, and 'peripheral vehicle' refers to a driving vehicle in the vicinity of a driving vehicle, Means all of the vehicles except for.

It is not possible to check the object information located in various directions at the same time with the naked eye of the person and the braking distance according to the exact distance and speed change with other objects can not be accurately calculated and at the time of commercialization of the autonomous vehicle, Allows you to check nearby vehicle information at a glance while doing other tasks.

By changing the view of the driver's view from the sky instead of the sight of the person watching only one direction due to the effect of the effective field of view, the position information of the surrounding vehicle and the degree of threat to the moving vehicle can be calculated, Let's do it.

Due to the present invention, when the vehicle is in a lane change state, the speed difference between the vehicle and the next lane vehicle is analyzed. When the vehicle is safe, the vehicle is marked as "green ", and the driver recognizes the exact position and speed difference of the lane lane. Do.

In the backward situation, the driver can easily recognize the surrounding vehicle, lane, and object information, and can accurately park the vehicle at a desired position.

In the autonomous driving situation, the driver can easily grasp the position of nearby vehicles and the threat level of the surrounding vehicles expressed by rust, yellow, and red by looking at the moment of the moment while looking at the urgent work.

Figure 1 Figure 1 shows an illustration of the effective field of view of a person
(Drawing source: 'Understanding of people,
http://cms.cku.ac.kr/user/sylee/class/HCD/human_1.htm)
2 is a conceptual view showing a position where a distance sensor and a camera are attached;
FIG. 3 is a view showing a state in which a perceived situation is detected through the distance sensor of the traveling vehicle
FIG. 4 is a view showing a screen in which the lane information and the sign information recognized through the camera of the driving vehicle are added to the screen of three degrees
FIG. 5 is a view showing a screen in which a screen of a driving vehicle is synthesized with a screen of 4 degrees of a peripheral vehicle using a program calculated by the present invention
6 is a diagram illustrating a process for deriving a screen of 5 degrees
7 is a diagram showing a process for deriving a screen of 5 degrees (continued)
FIG. 8 shows a screen in which the degree of threat of the surrounding vehicle to the traveling vehicle is expressed in color and applied to 5 degrees
9 is a diagram showing a process of recognizing information of a nearby vehicle and classifying it as a forward,
10 is a diagram showing a process of dividing the degree of threat of the vehicle on the side of the vehicle by color,
11 is a diagram showing a process of dividing the degree of threat posed by the vehicle ahead of the vehicle into a color,
12 is a diagram showing a process of dividing the degree of threat of the rearward vehicle on the traveling vehicle by a color,

The vehicle to which this system is applied has eight sensors (S101) and four cameras (S102). Each position is in accordance with the position shown in Fig.

Among them, the sensor recognizes an object existing in 3D around the vehicle (Fig. 3), and the camera recognizes two-dimensional information such as lane and milestone (Fig. 4). However, in the result drawn through this process (FIG. 4), there is a blind spot S104 for the object located on the rear side of the effective range of the camera and the sensor (S103). This blind spot retrieves the information of other vehicles through the Internet. Through the Internet, the driving vehicle recognizes whether nearby vehicles use the same system. If the same system is used, (FIG. 5).

This process is shown in FIGS. 6 to 7, and information on the vehicle and the lane in the blind spot S104 of the driving vehicle can also be obtained through this process. In this respect, it can be said that it is superior to the way in which the person directly confirms it with the naked eye.

This process is repeated to derive the screen of Fig. However, it is difficult for the user to easily recognize the change of the situation with such a simple screen.

Therefore, the degree of threat to be imposed by the surrounding vehicles is analyzed and expressed in colors to the surrounding vehicles. This process is shown in FIGS. 9 to 12. FIG.

First, the position of the surrounding object recognized as 'vehicle' is grasped through FIG. If the vehicle is on the side, it enters the algorithm of (A). If the vehicle is in the front (B) and if it is in the rear, it enters the algorithm of (C). If this process is repeated and all of the information of the perceived object is recognized, the algorithm is terminated. This process is illustrated in FIG.

When a vehicle traveling in a lane that is not the same as the traveling vehicle is recognized, the state of FIG. 10 is entered. The side vehicle is expressed in yellow and red depending on the situation when approaching the traveling vehicle. Also, if the vehicle on the side of the vehicle is distant from the vehicle being driven, the vehicle is regarded as a problem-free vehicle even if the lane change is made and is expressed in green.

When the vehicle is located in front of the traveling vehicle, the state shown in FIG. 11 is entered. In such a situation, if the vehicle ahead is approaching the driving vehicle, it is yellow. If the vehicle is suddenly stopped, it is expressed in red, thereby informing the driver of an emergency.

When the vehicle is located behind the traveling vehicle, the state shown in FIG. 12 is entered. In such a situation, when the rear vehicle approaches the driving vehicle, it is yellow, and when the vehicle accelerates rapidly, it expresses in red and informs the driver of the emergency.

When this process is completed, the screen of FIG. 5 recognizes the threat level of the surrounding vehicle and switches to the screen of FIG.

S101 Position of the sensor attached to the vehicle
S102 Position of the camera attached to the vehicle
S103 Sensor and camera recognition range
S104 Sensor and camera blind spots

Claims

Screen method that expresses the surrounding situation of the driving vehicle from the sky

The method according to claim 1, wherein the information of the screen of the neighboring vehicle is taken and synthesized to the blind spot of the existing screen

The method according to claim 1, further comprising the steps of: expressing a degree of threat to the traveling vehicle

An algorithm that implements the expression scheme of claim 3