KR102637515B1 - Vehicle and controlling method for the same - Google Patents

Abstract

By using a bimodal lidar, data is provided from surrounding vehicles and combined to provide environmental information around the vehicle, accurately recognizing the surrounding environment that could not be recognized due to being obscured by other vehicles and buildings, and controlling vehicles and vehicles that enable efficient autonomous driving. Provides a method.
A vehicle according to one aspect of the disclosed invention includes a Lidar sensor that collects first point data about objects around the vehicle; a communication unit that receives position information and second point data from outside the vehicle; And a control unit that generates environmental information around the vehicle by matching the first point data transmitted by the lidar sensor and the second point data transmitted by the communication unit to the position information.

Description

Vehicle and vehicle control method {VEHICLE AND CONTROLLING METHOD FOR THE SAME}

The disclosed invention relates to a vehicle that recognizes the surrounding environment and a method of controlling the vehicle.

Vehicles provide safety services to drivers and passengers. For example, the vehicle supplements the driver's visual information and calculates the distance to the vehicle ahead. Safety services begin with the stage of detecting surrounding vehicles and objects and recognizing the vehicle's own location. The vehicle uses various vehicle sensors to detect the surrounding environment.

A vehicle radar sensor or Lidar sensor may be installed in the vehicle. Automotive radar sensors and lidar sensors each provide information about the environment around the vehicle when the vehicle is driving.

Among them, lidar sensors play a key role in autonomous driving of vehicles. Specifically, lidar sensors provide information about the vehicle's surrounding environment as point data.

Meanwhile, lidar sensors used in research on autonomous driving are expensive sensors that rotate 360 degrees or output 3D images. However, these expensive lidar sensors are not suitable for durability, mass production, and design, and the OEM (Original Equipment Manufacturing) method has the problem of significantly increasing costs.

In order to solve this problem, the disclosed invention uses a bimodal lidar to receive data from surrounding vehicles and combines them to provide environmental information around the vehicle, accurately recognizing the surrounding environment that could not be recognized because it was obscured by other vehicles and buildings, and efficiently Provides vehicles capable of autonomous driving and vehicle control methods.

A vehicle according to one aspect of the disclosed invention includes a Lidar sensor that collects first point data about objects around the vehicle; a communication unit that receives position information and second point data from outside the vehicle; And a control unit that generates environmental information around the vehicle by matching the first point data transmitted by the lidar sensor and the second point data transmitted by the communication unit to the position information.

The control unit may synchronize the first point data and the second point data based on the position information.

The control unit may perform corner matching to modify the surrounding position of the vehicle based on the first and second point data.

The control unit may perform the corner matching when either the first point data or the second data exceeds a preset angle.

The control unit may perform straight line matching to modify the first point data or the second point data based on the position information.

The control unit may modify the position information based on the rotation speed included in the first point data and the second point data.

Based on the position information, the control unit may match the position information, excluding point data located outside the lane in which the vehicle is traveling, among the first point data or the second point data.

After generating the environment information, the control unit may generate the environment information by modifying the excluded point data again based on the rotation speed included in the first point data and the second point data.

After matching the position information, the control unit may review consistency of environmental information around the vehicle.

The communication unit may transmit the first point data collected by the lidar sensor to the outside of the vehicle.

A method for controlling a vehicle according to another aspect of the disclosed invention includes collecting first point data about objects around the vehicle; receive position information and second point data from outside the vehicle; It includes; generating environmental information around the vehicle by matching the first point data transmitted by the lidar sensor and the second point data transmitted by the communication unit to the position information.

The generating may include generating environmental information around the vehicle by synchronizing the first point data and the second point data based on the position information.

The generating may include generating environmental information around the vehicle by performing corner matching to modify the surrounding location of the vehicle based on the first and second point data.

The generating may further include performing the corner matching to generate environmental information around the vehicle when either the first point data or the second data exceeds a preset angle. there is.

The generating may include generating environmental information around the vehicle by performing straight line matching to modify the first point data or the second point data based on the position information.

The generating may include generating the environment information in which the position information is modified based on the rotation speed included in the first point data and the second point data.

The generating is to generate environment information by matching the position information, based on the position information, excluding point data located outside the lane in which the vehicle is traveling, among the first point data or the second point data. May include ;.

The generating includes generating the environment information and then modifying the excluded point data again based on the rotation speed included in the first point data and the second point data to generate the environment information; More may be included.

After matching the position information, reviewing the consistency of environmental information around the vehicle may be further included.

It may further include transmitting the first point data collected by the lidar sensor to the outside of the vehicle.

The vehicle and vehicle control method according to the disclosed embodiment uses a bimodal lidar, receives lidar sensor data from surrounding vehicles, combines this, and provides information on the vehicle's surrounding environment, thereby providing information on the vehicle's surroundings, surroundings that could not be recognized due to being obscured by other vehicles and buildings. It accurately recognizes the environment and enables efficient autonomous driving.

1 is an exterior view of a vehicle according to an embodiment.
Figure 2 is an example diagram illustrating sensing values output from a lidar sensor included in a vehicle.
Figure 3 is a control block diagram of a vehicle according to one embodiment.
Figure 4 is a diagram for explaining point data collected by lidar sensors of a vehicle and surrounding vehicles.
Figure 5 is a diagram for explaining an operation of a control unit matching position information and point data according to an example.
FIG. 6 is a diagram for explaining a point data synchronization operation according to an example.
7 to 10 are diagrams for explaining an operation of a control unit matching point data according to an example.
Figure 11 is a diagram for explaining the operation of matching position information and point data of the lidar sensor.
Figure 12 is a flowchart for explaining the operation of a vehicle according to an example.

The objectives, specific advantages and novel features of the present invention will become more apparent from the following detailed description and preferred embodiments taken in conjunction with the accompanying drawings. In this specification, when adding reference numbers to components in each drawing, it should be noted that identical components are given the same number as much as possible even if they are shown in different drawings. Additionally, in describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the gist of the present invention, the detailed description will be omitted. In this specification, terms such as first and second are used to distinguish one component from another component, and the components are not limited by the terms.

FIG. 1 is an exterior view of a vehicle according to an embodiment, and FIG. 2 is an example diagram illustrating sensing values output from a lidar sensor included in the vehicle.

Referring to FIG. 1, the vehicle 100 according to one embodiment includes a proximity sensor that detects objects or other vehicles on the front, side, or rear of the vehicle 100, and a rain sensor that detects whether or not there is precipitation or the amount of precipitation. May include devices.

The proximity sensor includes a lidar sensor (Lidar, 120), and a plurality of each may be provided in the vehicle 100 as needed. In FIG. 1, three lidar sensors 120 are shown to be installed on the front of the vehicle 100, but the location and number of lidar sensors 120 are not limited to this.

Meanwhile, a radar sensor refers to a detection sensor that irradiates electromagnetic waves (e.g. radio waves, microwaves, etc.) to an object and receives electromagnetic waves reflected from the object to determine the distance, direction, altitude, speed, etc. of the object. do.

In comparison, the lidar sensor 120 radiates a laser beam (e.g., infrared, visible light, etc.) having a shorter wavelength than the electromagnetic wave irradiated by the radar sensor to the object, and receives the light reflected from the object to determine the distance between the object and the object. , refers to a detection sensor that can determine direction, altitude, speed, etc. That is, the lidar sensor 120 can generate a pulse signal with a higher energy density and shorter period than a radar sensor, and has higher azimuth resolution and distance resolution than a radar sensor.

The system related to the lidar sensor 120 may include a transmitter that transmits a laser, a detector that detects the reflected and returned laser, a processor that collects and processes the signal transmitted by the detector, and the lidar sensor described in the disclosed invention. (120) can collectively refer to these system configurations.

The lidar sensor 120 can be divided into a Time-Of-Flight (TOF) method and a Phase-shift method depending on the modulation method of the laser signal.

The TOF method measures the distance to surrounding objects by emitting a pulse signal from a laser and measuring the time it takes for reflected pulse signals from objects within the measurement range to arrive at the receiver.

The phase-shift method calculates time and distance by emitting a laser beam that is continuously modulated with a specific frequency and measuring the amount of phase change in the signal reflected back from an object within the measurement range.

The laser light source of the disclosed lidar sensor has a specific wavelength or a variable wavelength in the wavelength range from 250 nm to 11 μm, and a small, low-power semiconductor laser diode can be used as the light source.

Referring to FIG. 2, the lidar sensor 120 according to an embodiment may output location information of an object Ob on the front of the vehicle 100 as point data Di.

Specifically, the lidar sensor 120 may output point data (Di) corresponding to each light reflected from the front of an object (hereinafter referred to as an object) due to the characteristic of using light.

As shown in FIG. 2, the number of point data collected by the lidar sensor 120 may vary depending on the degree of irradiation by the laser light source. Accordingly, the point data shown in FIG. 4 and below represent a cluster of collected point data Di, and are briefly shown to explain the disclosed invention.

Meanwhile, the lidar sensor 120 may be based on Laser Rangefinder technology that measures the distance by measuring the reception time of a laser beam reflected from an object.

Furthermore, the lidar sensor 120 collects a large amount of point-cloud, or point data, through point-scanning based on laser rangefinder technology, or collects laser reflected from a wide-angle flash-laser through a multi-array receiving element. , 3D images can also be realized.

However, the lidar sensor 120 that implements 3D images is expensive, and has problems in that it is not realistically suitable for OEM-type vehicle manufacturing in terms of durability, mass production, and design.

Therefore, the vehicle 100 according to an embodiment of the disclosed invention may include a lidar sensor 120 with a limited number of channels capable of collecting point data as shown in FIG. 2, and accurately recognizes the surrounding environment. The point data required for this is solved by sharing external point data collected by lidar sensors of surrounding vehicles.

Meanwhile, the disclosed invention does not necessarily limit the channel of the lidar sensor 120. It is sufficient as long as the disclosed vehicle 100 can recognize the surrounding environment by combining data collected by lidar sensors installed in surrounding vehicles, and there is no limitation.

Figure 3 is a control block diagram of a vehicle according to one embodiment.

Referring to FIG. 3, a vehicle 100 according to an embodiment of the disclosed invention includes a communication unit 110, a lidar sensor 120, and a control unit 130.

The communication unit 110 receives various information from outside the vehicle 100, for example, pedestrians 40, surrounding vehicles 50, and the communication network 60. Additionally, the communication unit 110 may transmit point data collected by the lidar sensor 120 of the vehicle 100 to the surroundings of the vehicle 100.

The technology of the communication unit 110 for sending and receiving various information is called V2X communication.

Here, V2X communication refers to a system in which the vehicle 100 becomes the subject and shares information with other portable terminals, communication networks, or vehicles, and refers to communication technology between the vehicle and all interfaces.

Specifically, the forms of V2X include communication between vehicles and mobile media devices (Vehicle-to-Nomadic devices, V2N), communication between vehicles and vehicles (Vehicle-to-Vehicle, V2V), and communication between vehicles and infrastructure (Vehicle-to-Infrastructure, V2I) may be included. The communication between the pedestrian 40 and the communication unit 110 shown in FIG. 3 refers to V2N, the communication between the surrounding vehicle 50 and the communication unit 110 refers to V2V, and the communication between the communication network 60 and the communication unit 110 refers to V2I. means.

The V2X communication used by the disclosed communication unit 110 may use VANET (Vehicular Adhoc Networks) network technology.

Here, VANET is a form of MANET (Mobile Ad-hoc Networks) and refers to wireless communication used in each node of a network that moves at high speed.

If general MANET technology is used as a communication technology for the vehicle 100, network disconnections may occur frequently because the network nodes (each vehicle) move. Additionally, because the vehicle 100 can move at high speed, the network link connection time is shortened and the packet loss rate is high, so the overall network connection state may be unstable.

Therefore, VANET uses shorter channel bandwidth than existing MANET (e.g. WiFi). For example, the standard channel bandwidth of WiFi is 20 MHz. In comparison, VANET networks can use 10 MHz as channel bandwidth. In this way, VANET can reduce the effect of selective fading of frequency by reducing the channel bandwidth and performing V2X communication.

Additionally, VANET can also perform fast communication by performing communication by omitting the main authentication process before establishing communication with another AP (Access Point) of V2X.

Meanwhile, the network technology mentioned above is only an example of the wireless communication technology used by the disclosed communication unit 110, and the disclosed communication unit 110 is capable of performing communication technology capable of communicating with the surroundings of the vehicle 100. Any device is sufficient and there are no limitations.

Referring again to FIG. 3, the communication unit 110 receives various information from the pedestrian 40, surrounding vehicles 50, and the communication network 60.

Specifically, the information received by the communication unit 110 is not only point data information received from lidar sensors of surrounding vehicles, but also position information including GPS (Global Positioning System), the current location of the vehicle 100, and map information surrounding the current location. can be received together. Various information received by the communication unit 110 is transmitted to the control unit 130, and the control unit 130 generates information about the surrounding environment of the vehicle 100 based on this information.

Meanwhile, the information transmitted by the communication unit 110 to the control unit 130 is transmitted through a wired network in the vehicle such as CAN (Controller Area Network), LIN (Local Interconnect Network), MOST (Media Oriented System Transport), or Bluetooth. ), etc., and there are no restrictions.

As described above, the lidar sensor 120 uses a laser to output the position of the object, that is, lidar point data (Di) and speed, as sensing values.

Here, the speed includes longitudinal speed and lateral speed based on the front of the vehicle 100. Additionally, the lidar sensor 120 may output the rotational speed at which the vehicle 100 rotates about the theta (Z) axis as a sensing value.

Specifically, the behavior of the vehicle 100 is the front of the vehicle, that is, linear motion forward and backward in the Rotational movement around each axis can be expressed in 6-axis degrees of freedom.

Here, the X-axis rotational movement is called Roll, the Y-axis rotational movement is called Pitch, and the Z-axis rotational movement is called Yaw, and the angle per second of Yaw, that is, the rotational speed, is called Yaw rate. The yaw rate can be generated by the driver operating the steering wheel in the driving vehicle 100, and the lidar sensor 120 can output the yaw rate based on the reflection time of the laser beam.

The lidar sensor 120 transmits speed information including the output yaw rate and reflected and collected point data to the control unit 130.

The control unit 130 generates information on the surrounding environment of the vehicle 100 based on the position information and point data transmitted by the communication unit 110 and the lidar sensor 120.

Here, the control unit 130 uses point data collected by the lidar sensor 120 (first point data) and point data transmitted by the communication unit 110 (second point data) to generate environmental information around the vehicle 100. requires. That is, the second point data refers to the point data of the lidar sensor that the communication unit 110 receives from vehicles surrounding the vehicle 100.

First, the control unit 130 synchronizes the point data collected by the lidar sensor based on the position information of each vehicle transmitted from the communication unit 110. Here, the point data may be point data collected by the lidar sensor 120 installed in the vehicle 100, or may be point data transmitted by vehicles around the vehicle 100 through the communication unit 110. Therefore, the control unit 130 separates or synchronizes the point data.

Afterwards, the control unit 130 excludes point data located outside the lane among the point data and corrects the positions of surrounding vehicles based on point data with high reliability (hereinafter referred to as corner matching). Afterwards, the control unit 130 corrects the point data with a strong straight line component to match the positions of surrounding vehicles (hereinafter referred to as straight line matching) and stores the twisted angle (hereinafter referred to as rotation speed) of the lidar sensor receiving each synchronized point data. And, based on rotation speed, etc., data on points outside the vehicle previously excluded are corrected.

Finally, the control unit 130 matches information around the vehicle 100 based on the matched data. A detailed description related to this will be described later with reference to FIG. 4 and below.

Meanwhile, the control unit 130 is a processor that can control the communication unit 110 and the lidar sensor 120 in addition to generating surrounding environment information. Additionally, the control unit 130 can be integrated with a storage medium capable of storing data, and can be integrated into a system on chip (SOC) built into the vehicle 100. However, since there is not only one system-on-chip built into the vehicle 100, but there may be multiple, the system-on-chip is not limited to being integrated into only one system-on-chip.

The vehicle 100 according to the disclosed example may include other modules or components not described, and is not limited.

Figure 4 is a diagram for explaining point data collected by lidar sensors of a vehicle and surrounding vehicles. Specifically, Figure 4a (hereinafter Figure 4a) is a diagram for explaining the laser emitted by the lidar sensor 120 of each vehicle 100, and Figure 4b (hereinafter Figure 4b) shows the control unit 130 controlling the lidar sensor 120. This is a diagram to explain the output received from the point data sensed by the sensor 120.

Referring to FIG. 4A, the vehicle 100 is traveling on the road with three vehicles in front of the vehicle 100 and one vehicle in the rear (hereinafter referred to as surrounding vehicles).

The vehicle 100 and surrounding vehicles according to an embodiment of the disclosed invention may include a lidar sensor 120 that can be mass-produced. as I mentioned before. The lidar sensor 120 detects an object by emitting a short-wavelength laser to the surrounding area. However, the lidar sensor 120 that can be mass-produced refers to a sensor that can collect point data within the range of several channels, as shown in FIG. 4A.

The lidar sensors 120 of the vehicle 100 and surrounding vehicles shown in FIG. 4A may be installed on the front, and in this case, the point data about surrounding objects collected by the lidar sensor 120 of each vehicle 100 is It can only be limited.

For example, the lidar sensor 120 installed in the disclosed vehicle 100 may collect only point data for three vehicles running in front of the vehicle 100. If only point data collected in this way is used, environmental information around the vehicle 100 may be different from the actual environment. Accordingly, the disclosed vehicle 100 shares point data collected by lidar sensors installed in surrounding vehicles.

Each point data and figure shown in FIG. 4A separately displays lidar sensors of the vehicle 100 and surrounding vehicles.

Meanwhile, the lidar sensor 120 installed in the vehicle 100 can collect point data using the three vehicles located in front of the driving lane as objects. However, since each vehicle is driving, the collected point data may be distorted due to vibration or steering of the steering wheel.

If there is no distortion in the point data collected by the vehicle 100 for the vehicle in front traveling in the same lane as the vehicle 100, the point data that runs parallel to the rear of the vehicle in front should be displayed. However, because it is collected while driving, the point data may be distorted as shown in FIG. 4B.

Therefore, the control unit 130 corrects the point data that may be distorted and generates accurate environmental information. A detailed description related to this will be described later with reference to FIGS. 6 to 11.

Meanwhile, lidar sensors installed on vehicles around the vehicle 100 may collect point data about buildings or structures outside the lane. The point data collected in this way is shared through the communication unit 110 of the vehicle 100, and can be delivered in the form of point data displayed on the outside of the lane as shown in FIG. 4B.

Figure 5 is a diagram for explaining an operation of a control unit matching position information and point data according to an example.

Specifically, FIG. 5A refers to data that synchronizes the point data shown in FIG. 4B with the position information of the vehicle 100.

As mentioned above, the vehicle 100 may obtain position information where the vehicle 100 is currently located and location information of surrounding vehicles using GPS or the like. Thereafter, the control unit 130 may generate data as shown in FIG. 5A by combining each point data collected in FIG. 4B with position information.

Meanwhile, the control unit 130 corrects point data or position information that may be distorted as shown in FIG. 5B. That is, 5b shows the result of matching the data in 5a.

Specifically, the control unit 130 receives point data from other nearby vehicles and matches each data to generate accurate surrounding information. As mentioned above, data collected from each vehicle may be distorted, and the control unit 130 sets reliability for each data and matches the distorted information, thereby generating surrounding information similar to reality. A detailed description of the matching performed by the control unit 130 will be described later with reference to FIG. 6 and below.

FIG. 6 is a diagram for explaining a point data synchronization operation according to an example.

Referring to FIG. 6, first, the control unit 130 distinguishes from which vehicle each point data was collected.

As mentioned above, the control unit 130 receives point data from lidar sensors installed in surrounding vehicles through the communication unit 110. Additionally, the control unit 130 may collect point data about surrounding objects from the lidar sensor 120 installed in the vehicle 100. Therefore, the control unit 130 performs synchronization to determine which vehicle the collected point data was received from.

Thereafter, the control unit 130 may match the point data based on the current position information of the vehicle 100.

When the communication unit 110 receives point data, location information of each vehicle for which point data has been collected can also be received. Accordingly, the control unit 130 can generate position information together with the location of the vehicle 100 received from GPS, etc., and synchronize the point data with each vehicle as shown in FIG. 6.

Meanwhile, the figure in FIG. 6 is only an example to explain synchronization, and there is no limitation.

7 to 10 are diagrams for explaining an operation of a control unit matching point data according to an example. To avoid redundant explanation, they are explained together below.

Referring to FIG. 7, the control unit 130 excludes data on points outside the lane from the synchronized data. In autonomous driving, surrounding data outside the lane may be of relatively low importance. Therefore, the control unit 130 temporarily excludes point data for objects outside the lane as shown in FIG. 7 and performs the following matching.

Figure 8 is a diagram related to corner matching performed by the control unit 130.

After excluding data on points outside the lane, the control unit 130 may perform corner matching to move the position of the vehicle around the vehicle 100, as shown in FIG. 8 .

Specifically, point data on surrounding vehicles located in the lane next to the lane in which the vehicle 100 is traveling may be collected in the form of a cluster including a certain angle. Corner-shaped point data containing a certain angle has a high probability of matching the location of the actual object. Therefore, the control unit 130 corrects the positions of surrounding vehicles according to the cluster of point data formed at the corner.

Referring to FIG. 8, the positions of vehicles surrounding the vehicle 100 are modified to match the corner-shaped point data.

Figure 9 is a diagram related to straight line matching performed by the control unit 130.

Referring to FIG. 9 , the control unit 130 may perform straight line matching to modify point data in the form of a straight line according to the position of the vehicle around the vehicle 100.

Specifically, among the collected point data, straight-line clusters may have lower reliability than the positions of surrounding vehicles. This is because there is a high probability that straight point data will be distorted due to the vibration of the collecting lidar sensor 120.

Therefore, the control unit 130 can modify the point data in the form of a straight line to match the position of the vehicle, as shown in FIG. 9. Referring to FIG. 9 , point data is modified according to the position information of surrounding vehicles located in front of the vehicle 100 in the driving lane of the vehicle 100.

Figure 10 is a diagram for explaining the operation of the control unit 130 that performs matching of data on points outside the lane.

After performing the corner matching and straight line matching described in FIGS. 8 and 9, the control unit 130 modifies the point data located outside the lane except in FIG. 7. This matching can be performed based on the yaw rate of each vehicle.

The 3D information displayed on each vehicle in FIG. 10 is an arbitrary representation of Roll, Pitch, and Yaw described in FIG. 3. Here, th may mean theta, that is, Yaw rate, and may be a standard for judging the rotation speed of each vehicle.

Referring to FIG. 10, the control unit 130 may modify a cluster of inclined point data among point data outside the lane based on 3D information of each vehicle. That is, if the rotation speed of each vehicle is not 0, the point data collected from that vehicle may be distorted, so the point data outside the inclined lane can be modified based on the rotation speed of the control unit 130.

Figure 11 is a diagram for explaining the operation of matching position information and point data of the lidar sensor.

The control unit 130 may match surrounding environment information based on the point data and position information modified in FIG. 10 . Here, matching means that the control unit 130 re-positions surrounding buildings and surrounding vehicles based on the modified point data.

For example, point data overlapping with the positions of surrounding vehicles or buildings modified during the matching process may be deleted as shown in FIG. 10 .

Afterwards, the control unit 130 can use the matched information as surrounding environment information.

Meanwhile, the operation of the control unit 130 described above is only an example of the disclosed invention, and the matching operation performed by the control unit 130 may vary and is not limited.

Figure 12 is a flowchart for explaining the operation of a vehicle according to an example.

First, the lidar sensor 120 installed in the vehicle 100 can collect point data (300).

In the disclosed invention, a mass-producible lidar sensor 120 can be installed in the vehicle 100, and the lidar sensor 120 according to one example has only channels within a few ranges and can collect point data.

Therefore, it is not possible to accurately collect environmental information around the vehicle 100 with only the point data collected by the lidar sensor 120, and the vehicle 100 does not receive additional point data through V2X communication performed by the communication unit 110. You can.

The communication unit 110 receives position information of the vehicle 100 and point data collected by lidar sensors installed in surrounding vehicles (310).

Here, the communication unit 110 can receive position information including GPS information collected from satellites and additional point data transmitted through V2V communication from surrounding vehicles. That is, the control unit 130 can share point data and position information with surrounding vehicles.

Afterwards, the control unit 130 of the vehicle 100 matches the position information and the point data of the lidar sensor (330).

As mentioned above, the control unit 130 can modify collected data according to a preset process based on reliability. A detailed description related to this will be described in detail later in FIG. 13.

The control unit 130 generates environmental information of the vehicle 100 based on the matched data (340).

The environmental information generated in this way can be used for autonomous driving of the vehicle 100 or displayed to the driver through an AVN device, etc.

Figure 13 is a flowchart for explaining the operation of matching point data with position information.

Referring to FIG. 13, the control unit 130 synchronizes the point data of the lidar sensor received from each vehicle (400).

As mentioned in FIG. 6 , the communication unit 110 may receive point data from vehicles surrounding the vehicle 100 . The control unit 130 checks from which vehicle the point data transmitted by the communication unit 110 was transmitted. Afterwards, the control unit 130 synchronizes each vehicle and the point data based on the position information transmitted by the communication unit 110.

The control unit 130 excludes point data located outside the lane from the synchronized point data (410).

Afterwards, the control unit 130 performs corner matching on the remaining point data (420).

As mentioned in FIG. 7, corner matching means modifying position information based on point data. That is, the control unit 130 that performs corner matching trusts the point data cluster with a preset angle or more than the position information of surrounding vehicles and matches the position information to the point data.

The control unit 130 performs straight line matching (430).

As mentioned in FIG. 8, straight line matching is a low evaluation of the reliability of point data formed by a straight line and means modifying the position of the point data to the position of surrounding vehicles based on position information. That is, the control unit 130 modifies the point data formed in a straight line according to the positions of surrounding vehicles.

The control unit 130 matches point data outside the excluded lane (440).

As mentioned in FIG. 9, the control unit 130 regenerates and modifies the out-of-lane point data excluded in step 410 based on the location of the vehicle moved by straight line matching and the yaw rate of each vehicle included in the position information. do.

Afterwards, the control unit 130 matches surrounding objects based on the matched point data and position information and generates surrounding environment information (450).

The control unit 130 reviews the matched surrounding environment information (460).

As an example of consistency review, the control unit 130 may delete point data remaining redundant with position information during the matching process.

In summary, the vehicle 100 according to the disclosed example does not use an expensive lidar sensor, but uses a lidar sensor 120 that can collect surrounding point data through several channels, and other necessary information is stored in the vehicle. (120) Supplemented through position information and point data received from surrounding vehicles. The vehicle 100 disclosed based on this can generate accurate surrounding environment information by matching various collected data and matching each piece of information.

100: vehicle,
110: Ministry of Communications,
120: lidar sensor

Claims (20)

Lidar sensors that collect first-point data about objects around the vehicle;
a communication unit that receives position information and second point data from outside the vehicle; and
A control unit that generates environmental information around the vehicle by matching the first point data transmitted by the lidar sensor and the second point data transmitted by the communication unit to the position information,
The control unit,
Based on the position information, match the position information excluding point data located outside the lane in which the vehicle is traveling among the first point data or the second point data,
After generating the environmental information, the vehicle generates the environmental information by modifying the excluded point data again based on the rotational speed included in the first point data and the second point data. According to clause 1,
The control unit,
A vehicle that synchronizes the first point data and the second point data based on the position information. According to clause 1,
The control unit,
A vehicle performing corner matching to modify a peripheral position of the vehicle based on the first and second point data. According to clause 3,
The control unit,
A vehicle that performs the corner matching when a cluster of point data of either the first point data or the second data exceeds a preset angle. According to clause 1,
The control unit,
A vehicle that performs straight line matching to modify the first point data or the second point data based on the position information. According to clause 1,
The control unit,
A vehicle that corrects the position information based on the rotational speed included in the first point data and the second point data. delete delete According to clause 1,
The control unit,
A vehicle that checks the consistency of environmental information around the vehicle after matching the position information. According to clause 1,
The Department of Communications,
A vehicle that transmits the first point data collected by the lidar sensor to the outside of the vehicle. Collect first point data about objects around the vehicle;
receive position information and second point data from outside the vehicle;
Generating environmental information around the vehicle by matching the first point data and the second point data to the position information,
The above generates,
Based on the position information, generate environment information by matching the position information, excluding point data located outside the lane in which the vehicle is traveling, among the first point data or the second point data, and generating the environment information. and then generating the environment information by modifying the excluded point data again based on the rotation speed included in the first point data and the second point data. According to clause 11,
The above generates,
Based on the position information, synchronizing the first point data and the second point data to generate environmental information around the vehicle. According to clause 11,
The above generates,
Based on the first and second point data, performing corner matching to modify the surrounding position of the vehicle to generate environmental information around the vehicle. According to clause 13,
The above generates,
If a cluster of point data of either the first point data or the second data exceeds a preset angle, performing the corner matching to generate environmental information around the vehicle; A method of controlling a vehicle further comprising: . According to clause 11,
The above generates,
Based on the position information, performing straight line matching to modify the first point data or the second point data to generate environmental information around the vehicle. According to clause 11,
The above generates,
A method of controlling a vehicle including generating the environment information in which the position information is modified based on a rotation speed included in the first point data and the second point data. delete delete According to clause 11,
After matching the position information, reviewing consistency of environmental information around the vehicle. According to clause 11,
A method of controlling a vehicle further comprising transmitting the first point data collected by the lidar sensor to the outside of the vehicle.

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