KR20230129076A - Method and apparatus for preventing collision with overloaded vehicle - Google Patents

Abstract

The present invention relates to a method for preventing an overloaded vehicle collision and an apparatus thereof. The method for preventing the overloaded vehicle collision according to one embodiment of the present invention comprises: determining whether a front vehicle is an overloaded autonomous vehicle; receiving, in a case of the overloaded autonomous vehicle, GPS information and autonomous vehicle specification information from the front vehicle; generating a virtual vehicle corresponding to the front vehicle based on the GPS information and the autonomous vehicle specification information; determining an inter-vehicle distance to the front vehicle based on the virtual vehicle; and controlling to prevent the collision with the front vehicle based on the determined inter-vehicle distance with the front vehicle. Provided is the forward collision preventing apparatus to prevent the collision with the front vehicle.

Description

Method and apparatus for preventing collision of an overloaded vehicle {METHOD AND APPARATUS FOR PREVENTING COLLISION WITH OVERLOADED VEHICLE}

The present embodiments are applicable to autonomous vehicles in all fields, and more specifically, for example, may be applied to various systems for inducing collision avoidance of an autonomous vehicle in response to a front vehicle loaded with overloaded cargo. .

The American Society of Automotive Engineers, SAE (Society of Automotive Engineers), subdivides autonomous driving levels into six levels, from level 0 to level 5, for example, as follows.

Level 0 (No Automation) is a stage in which the driver controls and takes responsibility for everything in driving. The driver drives all the time, and the system of the self-driving vehicle performs only auxiliary functions such as emergency notification. The subject of driving control is human, and the responsibility for variable detection and driving while driving is also at the human level.

Level 1 (Driver Assistance) is a stage of assisting the driver through adaptive cruise control and lane keeping functions. By activating the system, it assists the driver by maintaining the speed and distance of the autonomous vehicle, and keeping the lane. The subject of driving control lies with the human and the system, and the responsibility for detecting variables that occur during driving and driving is all at the human level.

Level 2 (partial automation) is a stage in which the autonomous vehicle can simultaneously control the steering and acceleration/deceleration of the autonomous vehicle with a human for a certain period of time under specific conditions. Steering on gentle curves and assisted driving to maintain a distance from the car in front are possible. However, variable detection and driving responsibility while driving are at the human level, and the driver always needs to monitor the driving situation, and the driver must immediately intervene in driving situations that the system does not recognize.

Level 3 (conditional automation) is a level in which the system takes charge of driving in sections under specific conditions, such as highways, and the driver intervenes only in case of danger. Driving control and detecting variables while driving are handled by the system, and unlike Level 2, the above monitoring is not required. However, if the system requirements are exceeded, the system requests the driver's immediate intervention.

At level 4 (high automation), autonomous driving is possible on most roads. Both driving control and driving responsibility lie with the system. Driver intervention is unnecessary on most roads except in restricted situations. However, since driver intervention may be requested under specific conditions such as bad weather, a driving control device through a human is required.

Level 5 (full automation) is a stage in which a driver is not required and driving is possible with only passengers. The occupant only inputs the destination, and the system takes care of driving in all conditions. At level 5, control devices for steering, acceleration, and deceleration of autonomous vehicles are unnecessary.

Recently, autonomous vehicles to which a smart cruise control (SCC) system is applied are increasing.

A smart cruise control system is a system for controlling an autonomous vehicle to maintain an inter-vehicle distance by measuring an inter-vehicle distance with a vehicle in front using a radar.

However, even when the front vehicle is a large truck and an autonomous vehicle with illegally modified rear safety plates, the distance between vehicles cannot be accurately measured.

If the distance between vehicles cannot be accurately measured, the smart cruise control system may brake the autonomous vehicle closer to the vehicle in front than expected, and in severe cases, a collision with the vehicle in front may occur.

For these reasons, when an error occurs in the inter-vehicle distance with the preceding vehicle, a method of preventing a collision with the preceding vehicle by correcting the error is required.

In order to solve the above-mentioned problems, an embodiment of the present invention receives location and specification information of an overloaded vehicle and implements a virtual vehicle for the overloaded vehicle in an autonomous vehicle through the corresponding information to prevent collision with a preceding vehicle. It is intended to provide a front collision avoidance device that prevents

The problems to be solved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below. You will be able to.

An overloaded vehicle collision prevention method according to any one of the embodiments of the present invention for solving the above problems is to determine whether a front vehicle is an overloaded autonomous driving vehicle, and if the overloaded autonomous vehicle is the front vehicle receiving GPS information and autonomous vehicle specification information from the GPS information and autonomous vehicle specification information, generating a virtual vehicle corresponding to the preceding vehicle based on the GPS information and autonomous vehicle specification information, and based on the virtual vehicle, a head-to-head distance to the preceding vehicle. and controlling to prevent a collision with the preceding vehicle based on the determined inter-vehicle distance with the preceding vehicle.

According to the embodiment, determining whether the front vehicle is an overloaded autonomous vehicle detects a headway distance to the front vehicle based on a radar, determines whether the detected headway distance information is constant, and determines whether the detected headway distance information and determining that the preceding vehicle is an overloaded self-driving vehicle when is not constant.

According to the embodiment, determining whether the front vehicle is an overloaded self-driving vehicle is performed by receiving rear image data of the front vehicle based on a camera, and comparing the rear image with pre-stored rear view data of the autonomous vehicle to recognize an overloaded cargo. and determining the front vehicle as an overloaded autonomous vehicle when recognizing the overloaded cargo.

According to an embodiment, determining the headway distance to the preceding vehicle based on the virtual vehicle includes calculating a distance from the self-driving vehicle to a rear bumper of the virtual vehicle as the headway distance.

According to an embodiment, determining the inter-vehicle distance to the preceding vehicle based on the virtual vehicle includes determining whether distance data actually sensed through a radar and distance data based on the virtual vehicle match.

According to the embodiment, determining the inter-vehicle distance to the front vehicle based on the virtual vehicle determines the actually sensed distance data to the front vehicle when the actually sensed distance data and the distance data based on the virtual vehicle match. It includes judging by the distance to the rear bumper of the vehicle.

According to the embodiment, the controlling to prevent a collision with the preceding vehicle based on the inter-vehicle distance to the preceding vehicle includes controlling to prevent a collision with the preceding vehicle based on distance data based on the virtual vehicle. .

According to an embodiment, determining the inter-vehicle distance to the preceding vehicle based on the virtual vehicle is determined when the actually sensed distance data and the distance data based on the virtual vehicle do not match, the actually sensed distance data and the distance data based on the virtual vehicle. Among the distance data based on the virtual vehicle, data close to the self-driving vehicle is determined as an inter-vehicle distance corresponding to the overloaded cargo.

According to the embodiment, the controlling to prevent a collision with the preceding vehicle based on the inter-vehicle distance with the preceding vehicle includes controlling to prevent a collision with the preceding vehicle based on the inter-vehicle distance corresponding to the overloaded cargo. do.

According to any one of the embodiments of the present invention, an overloaded vehicle collision avoidance device capable of preventing an accident with an autonomous vehicle because a vehicle in front of the autonomous vehicle is not properly recognized due to an overloaded vehicle loaded with overloaded cargo is provided do.

According to any one of the embodiments of the present invention, there is a technical effect of providing an anti-collision device capable of accurately predicting the existence and movement path of surrounding self-driving vehicles.

The effects obtainable in the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. will be.

1 is an overall block diagram of an autonomous driving control system to which an autonomous driving device according to one of the embodiments of the present invention can be applied.
2 is an exemplary view showing an example in which an autonomous driving device according to any one of the embodiments of the present invention is applied to an autonomous vehicle.
3 is a diagram illustrating an example of a case where an autonomous vehicle cannot accurately measure an inter-vehicle distance to a vehicle in front according to an embodiment of the present invention.
4 is a view for explaining a front collision avoidance device according to any one of the embodiments of the present invention.
5 and 6 are views for explaining a collision avoidance situation with an overloaded cargo vehicle based on a virtual vehicle according to embodiments of the present invention.
7 is a flowchart showing a method for preventing an autonomous vehicle from colliding with an overloaded vehicle of an autonomous vehicle according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a certain component is said to "include", it means that it may further include other components without excluding other components unless otherwise stated.

1 is an overall block diagram of an autonomous driving control system to which an autonomous driving device according to one of the embodiments of the present invention can be applied. 2 is an exemplary view showing an example in which an autonomous driving device according to any one of the embodiments of the present invention is applied to an autonomous vehicle.

First, with reference to FIGS. 1 and 2 , the structure and function of an autonomous driving control system (eg, an autonomous vehicle) to which the autonomous driving device according to the present embodiments can be applied will be described.

As shown in FIG. 1 , an autonomous vehicle 1000 operates through a driving information input interface 101, a driving information input interface 201, a passenger output interface 301, and an autonomous vehicle control output interface 401. It can be implemented around the autonomous driving integrated control unit 600 that transmits and receives data necessary for autonomous driving control of the autonomous vehicle. However, the autonomous driving integrated controller 600 may also be referred to as a controller, a processor, or simply a controller in this specification.

The autonomous driving integrated control unit 600 may obtain driving information according to a driver's manipulation of the user input unit 100 through the driving information input interface 101 in the autonomous driving mode or the manual driving mode of the autonomous vehicle. As shown in FIG. 1, the user input unit 100 includes a driving mode switch 110 and a control panel 120 (eg, a navigation terminal mounted on an autonomous vehicle, a smartphone or tablet PC owned by a passenger, etc.) ), and thus the driving information may include driving mode information and navigation information of the autonomous vehicle.

For example, the driving mode of the autonomous vehicle (ie, autonomous driving mode/manual driving mode or sports mode/eco mode/ Safe Mode/Normal Mode) may be transmitted to the autonomous driving integrated control unit 600 through the driving information input interface 101 as the driving information.

In addition, navigation information such as the passenger's destination input by the passenger through the control panel 120 and the route to the destination (the shortest route or preferred route selected by the passenger among the candidate routes to the destination) is driving information. It can be transmitted to the autonomous driving integrated control unit 600 through the input interface 101 .

Meanwhile, the control panel 120 may be implemented as a touch screen panel that provides a user interface (UI) for a driver to input or modify information for autonomous driving control of an autonomous vehicle. In this case, the aforementioned driving mode switch 110 may be implemented as a touch button on the control panel 120 .

In addition, the autonomous driving integrated control unit 600 may obtain driving information indicating a driving state of the autonomous vehicle through the driving information input interface 201 . The driving information includes the steering angle formed by the occupant operating the steering wheel, the stroke of the accelerator pedal or the brake pedal formed by depressing the accelerator or brake pedal, and the behavior formed in the autonomous vehicle, such as vehicle speed, acceleration, and yaw. , pitch and roll, etc. may include various information representing the driving state and behavior of the autonomous vehicle, and each driving information, as shown in FIG. It can be detected by the driving information detection unit 200 including a (pedal travel sensor) 220, a vehicle speed sensor 230, an acceleration sensor 240, and a yaw/pitch/roll sensor 250.

Furthermore, the driving information of the autonomous vehicle may include location information of the autonomous vehicle, and the location information of the autonomous vehicle may be obtained through a Global Positioning System (GPS) receiver 260 applied to the autonomous vehicle. Such driving information may be transmitted to the autonomous driving integrated control unit 600 through the driving information input interface 201 and used to control driving of the autonomous vehicle in an autonomous driving mode or a manual driving mode.

In addition, the autonomous driving integrated control unit 600 may transmit driving state information provided to passengers in the autonomous driving mode or the manual driving mode of the autonomous vehicle to the output unit 300 through the passenger output interface 301 . That is, the self-driving integrated control unit 600 transmits the driving state information of the autonomous vehicle to the output unit 300 so that the driver can autonomously drive the autonomous vehicle based on the driving state information output through the output unit 300. state or manual driving state may be checked, and the driving state information may include various information indicating the driving state of the autonomous vehicle, such as the current driving mode, shift range, and vehicle speed of the autonomous vehicle.

In addition, when it is determined that a driver needs to be warned in the autonomous driving mode or manual driving mode of the autonomous vehicle along with the driving state information, the autonomous driving integrated control unit 600 sends warning information through the passenger output interface 301. It is transmitted to the output unit 300 so that the output unit 300 outputs a warning to the driver. In order to audibly and visually output such driving state information and warning information, the output unit 300 may include a speaker 310 and a display device 320 as shown in FIG. 1 . At this time, the display device 320 may be implemented as the same device as the aforementioned control panel 120 or may be implemented as a separate and independent device.

In addition, the autonomous driving integrated control unit 600 transmits control information for driving control of the autonomous vehicle in the autonomous driving mode or manual driving mode of the autonomous vehicle through the autonomous vehicle control output interface 401 to the lower level applied to the autonomous vehicle. It can be transmitted to the control system 400. As shown in FIG. 1 , the sub-control system 400 for driving control of an autonomous vehicle may include an engine control system 410, a braking control system 420, and a steering control system 430, and autonomous driving. The integrated control unit 600 may transmit engine control information, braking control information, and steering control information as the control information to each lower control system 410, 420, and 430 through the autonomous vehicle control output interface 401. Accordingly, the engine control system 410 may increase or decrease fuel supplied to the engine to control vehicle speed and acceleration of the autonomous vehicle, and the braking control system 420 may control the braking force of the autonomous vehicle for autonomous driving. Braking of the vehicle may be controlled, and the steering control system 430 may control steering of the autonomous vehicle through a steering device (eg, a motor driven power steering (MDPS) system) applied to the autonomous vehicle.

As described above, the autonomous driving integrated control unit 600 of the present embodiment provides driving information according to the driver's manipulation and driving information representing the driving state of the autonomous vehicle through the driving information input interface 101 and the driving information input interface 201. may be acquired, and driving state information and warning information generated according to the autonomous driving algorithm may be transmitted to the output unit 300 through the occupant output interface 301, and control information generated according to the autonomous driving algorithm may be transmitted to the driver output interface 301. It can be transmitted to the lower control system 400 through the vehicle control output interface 401 and operated to control the driving of the autonomous vehicle.

On the other hand, in order to ensure stable autonomous driving of an autonomous vehicle, it is necessary to continuously monitor the driving state by accurately measuring the driving environment of the autonomous vehicle and control the driving according to the measured driving environment. As shown in FIG. 1, the autonomous driving device includes a sensor unit for detecting objects around the autonomous vehicle, such as surrounding autonomous vehicles, pedestrians, roads, or fixed facilities (eg, traffic lights, milestones, traffic signs, construction fences, etc.) 500) may be included.

As shown in FIG. 1 , the sensor unit 500 may include one or more of a lidar sensor 510, a radar sensor 520, and a camera sensor 530 to detect surrounding objects outside the self-driving vehicle. .

The lidar sensor 510 can detect surrounding objects outside the self-driving vehicle by transmitting a laser signal to the surroundings of the self-driving vehicle and receiving a signal that is reflected and returned to the object. A surrounding object located within a set distance, a set vertical field of view, and a set vertical field of view may be detected. The lidar sensor 510 may include a front lidar sensor 511, an upper lidar sensor 512, and a rear lidar sensor 513 installed on the front, top, and rear of the autonomous vehicle, respectively. The installation location and the number of installations are not limited to specific embodiments. A threshold value for determining the validity of the laser signal reflected by the corresponding object and returned may be stored in advance in a memory (not shown) of the autonomous driving integrated control unit 600, and the autonomous driving integrated control unit 600 is a lidar sensor. The location (including the distance to the object), speed, and direction of movement of the object may be determined by measuring the time for the laser signal transmitted through 510 to be reflected by the object and return.

The radar sensor 520 can detect surrounding objects outside the self-driving vehicle by radiating electromagnetic waves around the self-driving vehicle and receiving a signal reflected back by the object, and a set distance predefined according to the specification. , it is possible to detect surrounding objects located within the range of the set vertical angle of view and the set horizontal angle of view. The radar sensor 520 includes a front radar sensor 521, a left radar sensor 521, a right radar sensor 522, and a rear radar sensor 523 installed on the front, left side, right side, and rear of the autonomous vehicle, respectively. However, the installation location and number of installations are not limited to specific embodiments. The autonomous driving integrated control unit 600 determines the location (including the distance to the corresponding object), speed, and direction of movement of the object through a method of analyzing the power of electromagnetic waves transmitted and received through the radar sensor 520. can do.

The camera sensor 530 may detect surrounding objects outside the self-driving vehicle by capturing an image around the self-driving vehicle, and detect surrounding objects located within a range of a preset distance, a set vertical angle of view, and a set horizontal angle of view according to the specifications thereof. can be detected.

The camera sensors 530 include a front camera sensor 531, a left camera sensor 532, a right camera sensor 533, and a rear camera sensor 534 installed on the front, left side, right side, and rear of the autonomous vehicle, respectively. However, the installation location and number of installations are not limited to specific embodiments. The self-driving integrated controller can determine the location (including the distance to the object), speed, and direction of movement of the object by applying predefined image processing to the image captured through the camera sensor 530. there is.

In addition, an internal camera sensor 535 for capturing an image inside the self-driving vehicle may be mounted at a predetermined location (eg, a rear view mirror) inside the autonomous vehicle, and the autonomous driving integrated control unit 600 may be equipped with an internal camera sensor A guide or warning may be output to the occupant through the above-described output unit 300 by monitoring the occupant's behavior and condition based on the image obtained through step 535.

In addition to the lidar sensor 510, the radar sensor 520, and the camera sensor 530, the sensor unit 500 may further include an ultrasonic sensor 540 as shown in FIG. 1, along with autonomous driving. Various types of sensors for detecting objects around the vehicle may be further employed in the sensor unit 500 .

FIG. 2 shows that a front lidar sensor 511 or a front radar sensor 521 is installed on the front of an autonomous vehicle, and a rear lidar sensor 513 or a rear radar sensor 524 is installed to help understand the present embodiment. The front camera sensor 531, the left camera sensor 532, the right camera sensor 533, and the rear camera sensor 534 are installed at the rear of the driving vehicle, respectively, on the front, left side, right side, and rear side of the autonomous vehicle. Although an installed example is shown, as described above, the installation position and number of installations of each sensor are not limited to a specific embodiment.

Furthermore, the sensor unit 500 detects the occupant's vital signs (eg, heart rate, electrocardiogram, respiration, blood pressure, body temperature, brain wave, blood flow (pulse wave), blood sugar, etc.) It may further include a biosensor for processing, and the biosensors may include a heart rate sensor, an electrocardiogram sensor, a respiration sensor, a blood pressure sensor, a body temperature sensor, an electroencephalogram sensor, a photoplethysmography sensor, and a blood sugar sensor. can

Finally, the sensor unit 500 additionally adds a microphone 550, and the internal microphone 551 and the external microphone 552 are used for different purposes.

The internal microphone 551 may be used, for example, to analyze the voice of a passenger in the autonomous vehicle 1000 based on AI or to immediately respond to a direct voice command.

On the other hand, the external microphone 552 can be used, for example, to respond appropriately to safe driving by analyzing various sounds generated from the outside of the autonomous vehicle 1000 with various analysis tools such as deep learning.

For reference, the symbols shown in FIG. 2 may perform the same or similar functions as those shown in FIG. 1, and FIG. 2 shows the relative positional relationship of each component compared to FIG. Based on) was illustrated in more detail.

3 is a diagram illustrating an example of a case where an autonomous vehicle cannot accurately measure an inter-vehicle distance with a vehicle in front according to an embodiment of the present invention.

Referring to FIG. 3, the front vehicle 3000 is a trailer loaded with overloaded cargo, and in the measurement of the vehicle-to-vehicle distance of the existing autonomous vehicle 1000, the radar detects the rear of the autonomous vehicle 1000 or the wheel portion of the trailer. to measure the distance between vehicles. Therefore, the smart cruise control system of the self-driving vehicle 1000 may have an error at the time of braking the self-driving vehicle 1000, resulting in a poor inter-vehicle distance.

In particular, if the height of the front vehicle 3000 is high or the loaded cargo protrudes from the rear, the loaded cargo of the front vehicle 3000 protrudes outside the autonomous vehicle 1000 using only the radar and camera in the self-driving vehicle 1000. In this case, there was a problem that the exact distance could not be set.

That is, since the radar of the self-driving vehicle 1000 repeatedly measures the distance from the end of an object protruding from the overloaded cargo of the front vehicle 3000 or to the rear bumper of the front vehicle 3000, the reliability of the vehicle-to-vehicle distance is low and accurate A situation in which the target is not detected has occurred.

4 is a view for explaining a front collision avoidance device according to any one of the embodiments of the present invention.

Referring to FIG. 4 , the collision avoidance device 2000 may include a communication unit 2100 and 2100, a sensor unit 2200, a loaded cargo detection unit 2300, a headway distance calculation unit 2400, and a processor unit 2500. can

The communication unit 2100 (2100) may communicate with an external autonomous vehicle 1000 for collision avoidance control of the autonomous vehicle 1000 according to the present invention. For example, the communication unit 2100 (2100) may receive GPS information and specification information of the autonomous vehicle 1000 from an external autonomous vehicle 1000. The communication unit 2100 (2100) may transmit and receive data with the external self-driving vehicle 1000 through V2V communication.

The sensor unit 2200 may include a driving information detection unit 2210 and an object recognition unit 2220.

The driving information detection device 2210 may include a vehicle speed sensor, a steering angle sensor, and a positioning sensor. The vehicle speed sensor senses the driving speed of the autonomous vehicle 1000, the steering angle sensor senses a steering angle formed by adjusting a steering wheel, and the positioning sensor may include a Global Positioning System (GPS) receiver. There is, through which the GPS coordinates of the self-driving vehicle 1000 can be obtained.

The object recognizing unit 2220 is for recognizing an object around the autonomous vehicle 1000 and may include at least one of a camera sensor, a radar sensor, and a LIDAR sensor.

The camera sensor can capture an image around the self-driving vehicle 1000 and detect surrounding objects outside the self-driving vehicle 1000, located within a predefined set distance, set vertical angle of view and set horizontal angle of view range according to its specifications. It can detect nearby objects.

The camera sensors may include a front camera sensor, a left camera sensor, a right camera sensor, and a rear camera sensor installed on the front, left side, right side, and rear side of the autonomous vehicle 1000, respectively. It is not limited to a specific embodiment. The processor unit 2500 of the self-driving vehicle 1000 applies predefined image processing to an image captured through a camera sensor, thereby determining the location (including the distance to the corresponding object), speed, and direction of movement of the object. etc. can be judged.

In addition, an internal camera sensor for capturing an image of the inside of the self-driving vehicle 1000 may be mounted at a predetermined location (eg, a rear view mirror) inside the self-driving vehicle 1000, and the processor of the self-driving vehicle 1000 The unit 2500 may output a guide or warning to the occupant through an output unit in the self-driving vehicle 1000 by monitoring the behavior and condition of the occupant based on the image acquired through the internal camera sensor.

The radar sensor can detect surrounding objects outside the self-driving vehicle 1000 by radiating electromagnetic waves around the self-driving vehicle 1000 and receiving a signal reflected back by the object, and is predefined according to its specifications. It is possible to detect surrounding objects located within the set distance, set vertical angle of view and set horizontal angle of view. The radar sensors may include a front radar sensor, a left radar sensor, a right radar sensor, and a rear radar sensor installed on the front, left side, right side, and rear side of the autonomous vehicle 1000, respectively, but the installation location and number of installations may vary. It is not limited to a specific embodiment. The processor unit 2500 of the self-driving vehicle 1000 analyzes the power of electromagnetic waves transmitted and received through the radar sensor to determine the location of the object (including the distance to the object), speed, and direction of movement. can judge

The lidar sensor can detect surrounding objects outside the self-driving vehicle 1000 by transmitting a laser signal to the surroundings of the self-driving vehicle 1000 and receiving a signal reflected back by the object, and according to its specifications, in advance. A surrounding object located within a defined set distance, a set vertical field of view, and a set horizontal field of view may be detected. The lidar sensor is a front and upper part of the self-driving vehicle 1000. and a front lidar sensor, an upper lidar sensor, and a rear lidar sensor installed on the rear side, but the installation position and number of the lidar sensors are not limited to a specific embodiment. The laser signal reflected from the corresponding object and returned A threshold value for determining the validity of may be previously stored in a memory (not shown) of the processor unit 2500 of the autonomous vehicle 1000, and the processor unit 2500 of the autonomous vehicle 1000 is The location (including the distance to the object), speed, and direction of movement of the object can be determined by measuring the time for the laser signal transmitted through the sensor to be reflected by the object and return.

In addition to the camera sensor, radar sensor, and lidar sensor, the object recognizer 2220 may further include an ultrasonic sensor, and various types of sensors for detecting objects around the self-driving vehicle 1000 may recognize objects. It may be further employed in section 2220.

The loaded cargo detector 2300 may detect a loading rate of the autonomous vehicle 1000 . Also, the loaded cargo detector 2300 may detect a loading rate of the front vehicle 3000 . Information on the load factor of the front vehicle 3000 may be acquired through the communication unit 2100 (2100).

On the other hand, the loaded cargo detection unit 2300 may convert the data of the rear view of the vehicle into big data in advance and store it. The loaded cargo detection unit 2300 detects the protruding loaded cargo when an object protrudes or is hidden from the rear of the autonomous vehicle 1000 in the image of the front vehicle 3000 received from the camera of the autonomous vehicle 1000. can

The head-to-head distance calculation unit 2400 provides information on at least one of the head-to-head distance with the vehicle in front, the relative speed with the vehicle in front, or the speed of the vehicle in front 3000 from a radar or an optical camera mounted on the autonomous vehicle 1000. Acquire

The radar or optical camera measures information on at least one of a relative speed with the preceding vehicle or the speed of the preceding vehicle 3000 and a head-to-head distance with the preceding vehicle in real time. The radar or optical camera may periodically or non-periodically measure information on at least one of the relative speed with the preceding vehicle or the speed of the preceding vehicle 3000 and the inter-vehicle distance with the preceding vehicle. For example, the radar may measure information on at least one of the relative speed with the preceding vehicle or the speed of the preceding vehicle 3000 and the distance between the vehicle and the preceding vehicle once per cycle with a period of 50 ms.

The headway distance calculation unit 2400 acquires information on at least one of the relative speed with the preceding vehicle or the speed of the preceding vehicle 3000 and the headway distance with the preceding vehicle must be installed in the autonomous vehicle 1000. It is not limited to acquisition from a radar or optical camera, and may be obtained from various sensors installed in the self-driving vehicle 1000.

The headway distance calculation unit 2400 determines whether the front vehicle 3000, which is a measurement target, is the same in a radar or an optical camera. That is, when the radar measures information on at least one of the relative speed with the preceding vehicle or the speed of the preceding vehicle 3000 once per cycle and the distance between the vehicle in front and the preceding vehicle, the self-driving vehicle that is the subject of measurement in the previous cycle It is determined whether 1000 and the self-driving vehicle 1000, which is a current measurement target, are the same.

If the front vehicle 3000 is not the same, the measurement target of the radar or optical camera is changed, resulting in a discontinuity between the head-to-head distance and the relative speed. Therefore, calculating the head-to-head distance by setting a physical limit is rather an erroneous value. can be calculated.

The processor unit 2500 may determine whether the preceding vehicle 3000 is an overloaded vehicle. The processor unit 2500 detects the front vehicle 3000 traveling on the road in front of the self-driving vehicle 1000 and the loaded cargo of the front vehicle 3000 based on the detection data of the camera received from the sensor unit 2200. can do.

The processor unit 2500 may determine whether the loaded cargo protrudes from the rear of the front vehicle 3000 by comparing the detected loaded cargo of the front vehicle 3000 with previously stored data. At this time, the processor unit 2500 may receive data stored by converting the data of the rear view of the vehicle into big data from the memory unit (not shown). The rear view of the vehicle is a typical truck shape, but may include a case where objects of the loaded cargo protrude or are obscured from the rear.

The processor unit 2500 may determine that the front vehicle 3000 is an overloaded self-driving vehicle 1000 when loaded cargo protrudes from the rear of the front vehicle 3000 .

The processor unit 2500 may detect an inter-vehicle distance to the preceding vehicle 3000 based on the radar. Also, the processor unit 2500 may calculate the distance to the preceding vehicle 3000 based on radar detection data received from the sensor unit 2200 . Thereafter, the processor unit 2500 may determine whether the sensed headway distance information is constant.

When the detected headway distance information is not constant, the processor unit 2500 may determine the front vehicle 3000 as the overloaded autonomous vehicle 1000 . At this time, the processor unit 2500 may receive rear image data of the front vehicle 3000 based on the camera. The processor unit 2500 may recognize an overloaded cargo by comparing the rear image with preset rear view data of the self-driving vehicle 1000 . When recognizing the overloaded cargo, the processor unit 2500 may determine the front vehicle 3000 as the overloaded autonomous vehicle 1000 .

In the case of the overloaded autonomous vehicle 1000, the processor unit 2500 may receive GPS information and specification information of the autonomous vehicle 1000 from the front vehicle 3000.

The processor unit 2500 may receive GPS information and specification information of the autonomous vehicle 1000 from the preceding vehicle 3000 from the communication units 2100 and 2100 . Depending on the embodiment, the processor unit 2500 continuously measures the distance to the preceding vehicle 3000 repeatedly and abnormally, through the communication unit 2100 (2100), the preceding vehicle 3000 ) and V2V communication, GPS information and information on specifications of the self-driving vehicle 1000 may be received.

The processor unit 2500 may generate a virtual vehicle corresponding to the preceding vehicle 3000 based on the GPS information and the specification information of the autonomous vehicle 1000 .

The processor unit 2500 may determine an inter-vehicle distance to the preceding vehicle 3000 based on the virtual vehicle. Then, the processor unit 2500 may calculate the distance from the autonomous vehicle 1000 to the rear bumper of the virtual vehicle as the headway distance.

The processor unit 2500 may determine whether distance data actually sensed through a radar and distance data based on the virtual vehicle match.

When the actually sensed distance data and the distance data based on the virtual vehicle match, the processor unit 2500 may determine the actually sensed distance data as the distance to the rear bumper of the front vehicle 3000 .

Meanwhile, when the actual sensed distance data and the distance data based on the virtual vehicle do not match, the processor unit 2500 selects one of the actual sensed distance data and the distance data to the rear bumper of the front vehicle 3000. Data close to the autonomous vehicle 1000 may be determined as an inter-vehicle distance corresponding to an overloaded cargo.

The processor unit 2500 may control to prevent a collision with the preceding vehicle 3000 based on the determined inter-vehicle distance with the preceding vehicle 3000.

The processor unit 2500 may control to prevent a collision with the preceding vehicle 3000 based on the distance data based on the virtual vehicle. Also, the processor unit 2500 may control to prevent a collision with the preceding vehicle 3000 based on the inter-vehicle distance with the preceding vehicle 3000.

Meanwhile, the processor unit 2500 may control to prevent a collision with the preceding vehicle 3000 based on the vehicle-to-vehicle distance corresponding to the overloaded cargo.

5 and 6 are views for explaining a collision avoidance situation with an overloaded cargo vehicle based on a virtual vehicle according to embodiments of the present invention.

Referring to FIG. 5 , a front vehicle 3000 travels in the same direction as the autonomous vehicle 1000, the autonomous vehicle 1000 is located behind the front vehicle 3000, and a load loaded on the front vehicle 3000 This is a state in which the overloaded cargo protrudes to the rear.

The self-driving vehicle 1000 may detect a distance to the preceding vehicle 3000 through a radar and a camera. At this time, when the self-driving vehicle 1000 detects the distance to the front vehicle 3000 through the radar, the distance to the rear bumper of the front vehicle 3000 or the tip of the protruding object of the overloaded cargo can be repeatedly measured. can At this time, the self-driving vehicle 1000 may measure the distance from the tip of an object protruding from the front vehicle 3000 or the rear bumper of the front vehicle 3000 based on the radar detection data received from the sensor unit 2200. can Therefore, when the self-driving vehicle 1000 repeatedly measures the distance to the preceding vehicle 3000, the reliability of the distance to the preceding vehicle 3000 may be low, and thus an accurate target may not be detected.

When the distance between the self-driving vehicle 1000 and the preceding vehicle 3000 is repeatedly and fraudulently measured through the radar, the self-driving vehicle 1000 may receive GPS information and specification information of the self-driving vehicle 1000 through V2V communication with the preceding truck.

In addition, the self-driving vehicle 1000 analyzes the image of the front vehicle 3000 through the camera, and when an object protrudes or is covered, GPS information and the self-driving vehicle 1000 specification information are obtained through V2V communication with the front truck. can receive In this case, the self-driving vehicle 1000 may determine that the front vehicle 3000 is an overloaded autonomous vehicle 1000 by analyzing pre-stored rear view data of the vehicle.

Referring to FIG. 6 , the autonomous vehicle 1000 may measure an inter-vehicle distance with the vehicle 3000 in front. At this time, when the front vehicle 3000 is an overloaded vehicle, the self-driving vehicle 1000 recognizes the inter-vehicle distance to the end of the overloaded cargo of the overloaded vehicle as the first inter-vehicle distance 6100, and The vehicle-to-vehicle distance to the end is recognized as the second vehicle-to-vehicle distance 6200 .

When the autonomous vehicle 1000 is repeatedly measured as the first headway distance 6100 and the second headway distance 6200 with the preceding vehicle 3000, the GPS position received from the preceding vehicle 3000 and autonomous driving The virtual vehicle 4000 may be implemented through the vehicle 1000 specifications. The autonomous vehicle 1000 may measure the vehicle-to-vehicle distance to the rear bumper of the virtual vehicle 4000 as the third vehicle-to-vehicle distance 6300 .

Thereafter, the autonomous vehicle 1000 may recognize a headway distance matching the third headway distance 6300 among the first headway distance 6100 and the second headway distance 6200 as actual headway data.

Accordingly, the autonomous vehicle 1000 may determine the second headway distance 6200 as the headway distance where the actual distance data and the virtually implemented distance data match. Accordingly, the second inter-vehicle distance 6200 may be recognized as an actual distance to the rear bumper of the preceding vehicle 3000 .

Thereafter, the autonomous vehicle 1000 may recognize the first headway distance 6100 measured closer among the first headway distance 6100 and the second headway distance 6200 as the end portion of the loaded cargo.

Thereafter, the autonomous vehicle 1000 may perform a forward collision avoidance operation based on the first headway distance 6100 . In this case, the self-driving vehicle may perform forward collision avoidance operation based on the distance based on the radar periodically determining that other distance data moving at the same speed as the front vehicle 3000 is an overloaded cargo.

FIG. 7 is a flowchart showing a method for preventing collision of an autonomous vehicle 1000 with an overloaded vehicle of the autonomous vehicle 1000 according to an embodiment of the present invention.

First, the self-driving vehicle 1000 according to an embodiment of the present invention may calculate an actual headway distance to the preceding vehicle 3000 based on detection information received from the radar (S101).

After step S101, the self-driving vehicle 1000 may determine whether an accurate target is detected based on the actual vehicle-to-vehicle distance. The autonomous vehicle 1000 may determine whether the calculated inter-vehicle distance maintains a constant distance (S102).

After the step S102, when the autonomous vehicle 1000 determines that an accurate target is not being detected, it may determine whether the preceding vehicle 3000 is an overloaded vehicle through a camera (S103).

After the step S103, the autonomous vehicle 1000 may receive GPS information and specifications of the autonomous vehicle 1000 from the preceding vehicle 3000 when the preceding vehicle 3000 is an overloaded autonomous vehicle 1000 (S104 ). For example, GPS information may include GPS information, and specification information of the self-driving vehicle 1000 may include full width and electric length information of the self-driving vehicle 1000 .

After the step S104, the autonomous vehicle 1000 may create a virtual vehicle 4000 corresponding to the preceding vehicle 3000 based on the received GPS information and the specifications of the autonomous vehicle 1000 (S105).

After step S105, the self-driving vehicle 1000 may calculate an inter-vehicle distance with the created virtual vehicle 4000 (S106).

After the step S106, the autonomous vehicle 1000 may determine the inter-vehicle distance with the overloaded cargo based on the actual inter-vehicle distance and the virtual vehicle inter-vehicle distance (S107).

After the step S107, the self-driving vehicle 1000 may perform a forward collision avoidance operation based on an inter-vehicle distance after overloading (S108).

That is, the technical idea of the present invention can be applied to the entire self-driving vehicle 1000 or only to some components inside the self-driving vehicle 1000. The scope of the present invention should be determined according to the matters described in the claims.

As another aspect of the present invention, the operation of the above-described proposal or invention is implemented, implemented, or implemented by a "computer" (a comprehensive concept including a system on chip (SoC) or a microprocessor) It may also be provided as executable code or an application that stores or includes the code, a computer-readable storage medium, or a computer program product, which also falls within the scope of the present invention.

Detailed descriptions of the preferred embodiments of the present invention disclosed as described above are provided to enable those skilled in the art to implement and practice the present invention. Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art will understand that the present invention can be variously modified and changed without departing from the scope of the present invention. For example, those skilled in the art can use each configuration described in the above-described embodiments in a way of combining each other.

Accordingly, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

1000: autonomous vehicles
2000: anti-collision devices
2100: Ministry of Communications
2200: sensor unit
2300: loaded cargo detection unit
2400: Inter-vehicle distance calculation unit
2500: processor unit
3000: front vehicle

Claims (20)

In the overload vehicle collision prevention method,
Determine whether the preceding vehicle is an overloaded autonomous vehicle,
In the case of the overloaded autonomous vehicle, receiving GPS information and autonomous vehicle specification information from the preceding vehicle;
Creating a virtual vehicle corresponding to the preceding vehicle based on the GPS information and the autonomous vehicle specification information;
determining an inter-vehicle distance with the preceding vehicle based on the virtual vehicle;
Controlling to prevent a collision with the preceding vehicle based on the determined inter-vehicle distance with the preceding vehicle
How to avoid collisions with overloaded vehicles. According to claim 1,
Determining whether the front vehicle is an overloaded autonomous vehicle
Detecting an inter-vehicle distance with the preceding vehicle based on a radar;
determining whether the detected headway distance information is constant;
When the detected headway distance information is not constant, determining the preceding vehicle as an overloaded autonomous vehicle
How to avoid collisions with overloaded vehicles. According to claim 2,
Determining whether the front vehicle is an overloaded autonomous vehicle
Receiving rear image data of the front vehicle based on the camera;
Recognizing overloaded cargo by comparing the rear image with pre-stored data of the back of the autonomous vehicle,
Including determining the front vehicle as an overloaded autonomous vehicle when recognizing the overloaded cargo
How to avoid collisions with overloaded vehicles. According to claim 3,
Determining the head-to-head distance with the preceding vehicle based on the virtual vehicle
Calculating a distance from the autonomous vehicle to a rear bumper of the virtual vehicle as an inter-vehicle distance
How to avoid collisions with overloaded vehicles. According to claim 4,
Determining the head-to-head distance with the preceding vehicle based on the virtual vehicle
Determining whether distance data actually sensed through a radar and distance data based on the virtual vehicle match
How to avoid collisions with overloaded vehicles. According to claim 5,
Determining the head-to-head distance with the preceding vehicle based on the virtual vehicle
When the actually sensed distance data and the virtual vehicle-based distance data match, determining the actually sensed distance data as a distance to a rear bumper of the preceding vehicle.
How to avoid collisions with overloaded vehicles. According to claim 6,
Control to prevent a collision with the preceding vehicle based on the inter-vehicle distance with the preceding vehicle
Controlling to prevent a collision with a front vehicle based on distance data based on the virtual vehicle
How to avoid collisions with overloaded vehicles. According to claim 5,
Determining the head-to-head distance with the preceding vehicle based on the virtual vehicle
When the actual sensed distance data and the distance data based on the virtual vehicle do not match,
Determining data close to the autonomous vehicle among the distance data actually sensed and the distance data based on the virtual vehicle as an inter-vehicle distance corresponding to an overloaded cargo
How to avoid collisions with overloaded vehicles. According to claim 8,
Control to prevent a collision with the preceding vehicle based on the inter-vehicle distance with the preceding vehicle
Controlling to prevent a collision with a front vehicle based on an inter-vehicle distance corresponding to the overloaded cargo
How to avoid collisions with overloaded vehicles. In a computer readable storage medium,
the storage medium stores at least one program code containing instructions that, when executed, cause at least one processor to perform operations;
The above actions are:
Determine whether the preceding vehicle is an overloaded autonomous vehicle,
In the case of the overloaded autonomous vehicle, receiving GPS information and autonomous vehicle specification information from the preceding vehicle;
Creating a virtual vehicle corresponding to the preceding vehicle based on the GPS information and the autonomous vehicle specification information;
determining an inter-vehicle distance with the preceding vehicle based on the virtual vehicle;
Controlling to prevent a collision with the preceding vehicle based on the determined inter-vehicle distance with the preceding vehicle
storage medium. A communication unit for receiving GPS information and autonomous vehicle specification information from a preceding vehicle;
a sensor unit including a driving information detection unit and an object recognition unit;
Loaded cargo detection unit for detecting the cargo loaded on the front vehicle;
an inter-vehicle distance calculation unit that calculates a distance to the preceding vehicle; and
It is determined whether the preceding vehicle is an overloaded self-driving vehicle, and if the vehicle is an overloaded self-driving vehicle, GPS information and self-driving vehicle specification information are received from the preceding vehicle, and based on the GPS information and autonomous vehicle specification information, the front Creating a virtual vehicle corresponding to the vehicle, determining an inter-vehicle distance with the preceding vehicle based on the virtual vehicle, and controlling to prevent a collision with the preceding vehicle based on the determined inter-vehicle distance with the preceding vehicle configured to include a processor unit
Overload vehicle anti-collision device. According to claim 11,
the processor unit
Detecting an inter-vehicle distance with the preceding vehicle based on a radar;
determining whether the detected headway distance information is constant;
When the detected headway distance information is not constant, configured to determine the preceding vehicle as an overloaded autonomous vehicle
Overload vehicle anti-collision device. According to claim 12,
the processor unit
Receiving rear image data of the front vehicle based on the camera;
Recognizing overloaded cargo by comparing the rear image with pre-stored data of the back of the autonomous vehicle,
When recognizing the overloaded cargo, configured to determine the front vehicle as an overloaded autonomous vehicle
Overload vehicle anti-collision device. According to claim 13,
the processor unit
configured to calculate a distance from the autonomous vehicle to a rear bumper of the virtual vehicle as an inter-vehicle distance
Overload vehicle anti-collision device. According to claim 14,
the processor unit
Is configured to determine whether the distance data actually sensed through the radar and the distance data based on the virtual vehicle match
Overload vehicle anti-collision device. According to claim 15,
the processor unit
When the actually sensed distance data and the distance data based on the virtual vehicle match, the actually sensed distance data is configured to determine the distance to the rear bumper of the preceding vehicle.
Overload vehicle anti-collision device. According to claim 16,
the processor unit
configured to prevent a collision with a vehicle in front based on distance data based on the virtual vehicle
Overload vehicle anti-collision device. According to claim 15,
the processor unit
When the actual sensed distance data and the distance data based on the virtual vehicle do not match,
It is configured to determine data close to the autonomous vehicle among the actually sensed distance data and the distance data based on the virtual vehicle as an inter-vehicle distance corresponding to an overloaded cargo.
Overload vehicle anti-collision device. According to claim 18,
the processor unit
configured to prevent a collision with a vehicle in front based on an inter-vehicle distance corresponding to the overloaded cargo
Overload vehicle anti-collision device. In autonomous vehicles,
At least one or more sensors for detecting the front vehicle and the loaded cargo of the front vehicle; and
It is determined whether the preceding vehicle is an overloaded self-driving vehicle, and if the vehicle is an overloaded self-driving vehicle, GPS information and autonomous vehicle specification information are received from the preceding vehicle, and the preceding vehicle is detected based on the GPS information and autonomous vehicle specification information. A processor for generating a virtual vehicle corresponding to the virtual vehicle, determining an inter-vehicle distance with the preceding vehicle based on the virtual vehicle, and controlling a collision with the preceding vehicle to be prevented based on the determined inter-vehicle distance with the preceding vehicle. Including an overload vehicle anti-collision device configured to include a unit,
self-driving vehicle.