Autonomous mobile robot for generating traffic information

Abstract

An autonomous mobile robot for generating traffic information, according to one embodiment of the present invention, comprises: an operation system unit which is responsible for operating the autonomous mobile robot in a driving area corresponding to a shoulder of a road; a position measurement unit for determining the position of the autonomous mobile robot on the basis of GPS on an HD map; a traffic condition determination unit for generating road sensing information which is information on the speed of a plurality of vehicles located in a road area through which vehicles pass on the HD map by using a LiDAR, and determining whether a traffic jam has started in the road area on the basis of the road sensing information and preset conditions; and a communication unit for transmitting location information on a location where the traffic jam has started to a server.

Description

Autonomous mobile robots that generate traffic information

[0001] The present invention relates to an autonomous mobile robot that generates traffic information while autonomously moving on a road on which vehicles travel.

[0002] According to the Korea Expressway Corporation, 1,079 people died in traffic accidents on highways managed by the corporation between 2015 and 2019. Drowsiness and inattention were the most common causes, accounting for 729 fatalities (67.6%). Speeding (11.9%) and jaywalking (3.5%) were also cited as contributing factors.

[0003] Drowsiness and inattention, the leading causes of fatal accidents, often lead to drivers failing to recognize traffic congestion ahead and failing to sufficiently slow down before it occurs, ultimately leading to rear-end collisions. Congestion on highways, national highways, local roads, and other roads can be caused by a variety of factors, including road construction, traffic accidents, and entering and exiting ICs, junctions, and bridges.

[0004] Therefore, in cases where traffic congestion is expected to occur on the road, there is a growing need for autonomous mobile robots that can move to the point where traffic congestion begins and inform following vehicles about the traffic congestion situation.

[0005] In order to solve the above-described problem, the present invention aims to provide an autonomous mobile robot that moves to a point where traffic congestion begins on a road on which vehicles travel and provides information to following vehicles about the traffic congestion situation on the road.

[0006] According to one embodiment of the present invention for achieving the above-described object, an autonomous mobile robot for generating traffic information includes: a driving system unit for driving the autonomous mobile robot in a driving area corresponding to a shoulder of a road; a position measurement unit for determining the location of the autonomous mobile robot based on GPS on an HD map; a traffic situation determination unit for generating road sensing information, which is information on the speeds of a plurality of vehicles located in a road area on which vehicles travel on the HD map, using lidar, and determining whether a traffic jam has started in the road area based on the road sensing information and a preset condition; and a communication unit for transmitting location information on a location where the traffic jam has started to a server.

[0007] Preferably, the traffic situation judgment unit can make a judgment using a plurality of road sensing information generated while moving in the opposite direction of the vehicle's driving direction in the road area from the starting point where the autonomous mobile robot starts operating.

[0008] Preferably, the preset condition may be a condition in which the speed of the plurality of vehicles included in each of the plurality of road sensing information is below a predetermined threshold speed and then exceeds the threshold speed.

[0009] Preferably, the traffic situation judgment unit can scan the road area with a lidar to create a point cluster, and then calculate the speed of the plurality of vehicles based on the distance traveled by the recognized vehicle and the measured time interval based on the point cluster.

[0010] Preferably, the HD map corresponds to the shoulder of the road and may include a driving area, which is an area in which the autonomous mobile robot operates, and a road area, which is an area in which vehicles travel from the shoulder of the road to the center line of the road.

[0011] Preferably, the traffic situation judgment unit generates road sensing information that further includes information on the density of the plurality of vehicles, and when judging whether a traffic jam has started in the road area, it may be further based on the information on the density of the plurality of vehicles.

[0012] Preferably, an alarm unit may be further included to indicate the start of a traffic jam by using a variable guide sign, warning light, or speaker.

[0013] An autonomous mobile robot according to one embodiment of the present invention can move to a point where traffic congestion begins on a road on which vehicles are traveling, and provide guidance to following vehicles about the traffic congestion situation on the road through various means, thereby having the effect of preventing traffic accidents in advance.

[0014] FIG. 1 is a block diagram showing an autonomous mobile robot that generates traffic information according to one embodiment of the present invention.

[0015] FIG. 2 is a block diagram showing an autonomous mobile robot that generates traffic information according to another embodiment of the present invention.

[0016] FIG. 3 is a drawing for explaining an autonomous mobile robot according to one embodiment of the present invention.

[0017] FIG. 4 is a drawing for explaining HDMAP according to one embodiment of the present invention.

[0018] FIG. 5 is a drawing for explaining an operation method of an autonomous mobile robot according to one embodiment of the present invention.

[0019] The present invention is susceptible to various modifications and embodiments. Specific embodiments will be described in detail with reference to the drawings. However, this is not intended to limit the present invention to specific embodiments, but rather to encompass all modifications, equivalents, and alternatives falling within the spirit and technical scope of the present invention. Throughout the description of each drawing, similar reference numerals have been used to designate similar components.

[0020] Terms such as first, second, A, and B may be used to describe various components, but the components should not be limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component. The term "and / or" includes a combination of multiple related description items or any one of multiple related description items.

[0021] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0022] The terminology used in this application is only used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprise" or "have" indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but do not exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0023] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and will not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0024] Throughout the specification and claims, whenever a part is said to include a certain component, this does not mean that it excludes other components, but rather that it may include other components, unless specifically stated otherwise.

[0025] Hereinafter, the present invention will be described with reference to the attached drawings.

[0026] FIG. 1 is a block diagram showing an autonomous mobile robot that generates traffic information according to one embodiment of the present invention.

[0027] Referring to FIG. 1, an autonomous mobile robot (100) that generates traffic information according to one embodiment of the present invention includes a driving system unit (110), a position measurement unit (120), a traffic situation judgment unit (130), and a communication unit (140).

[0028] The operation system unit (110) is responsible for the operation of the autonomous mobile robot (100) in the driving area corresponding to the shoulder of the road.

[0029] At this time, the driving system unit (110) may include basic components necessary for driving on a road, such as a battery, motor, and tires. Furthermore, the driving system unit (110) may further include a camera or lidar, enabling autonomous navigation to the next destination on the road. For example, referring to FIG. 3, an embodiment of an autonomous mobile robot (100) that generates traffic information according to one embodiment of the present invention is illustrated.

[0030] For reference, referring to FIG. 4, the driving area refers to the area where the autonomous mobile robot (100) drives on the road, and may correspond to the shoulder of the road.

[0031] The location measurement unit (120) determines the location of the autonomous mobile robot (100) based on GPS on the HD map.

[0032] That is, the position measurement unit (120) can determine the position of the autonomous mobile robot (100) on the HD map using GPS or high-performance DGPS. More specifically, the position measurement unit (120) can secure the current position of the autonomous mobile robot (100) in the form of longitude and latitude coordinates using GPS or DGPS, and can determine the position of the autonomous mobile robot (100) on the HD map by mapping these coordinates on the HD map.

[0033] The traffic situation judgment unit (130) uses lidar to generate road sensing information, which is information on the speed of multiple vehicles located in a road area where vehicles travel, on an HD map, and determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0034] Here, Lidar is a device that precisely draws the surroundings by emitting laser pulses and measuring the distance to objects by receiving the light that is reflected back from surrounding objects.

[0035] For example, referring to FIG. 4, while the autonomous mobile robot (100) remains in the driving area on the HD map, the traffic situation judgment unit (130) of the autonomous mobile robot (100) can measure the speed of a vehicle located in the road area using lidar to generate road sensing information.

[0036] Meanwhile, a traffic jam refers to a situation in which traffic on a road is congested or delayed, and can mean a situation in which vehicles on the road repeatedly stop and go at a certain speed (e.g., 30 km / h) or remain in one place for a long time.

[0037] In another embodiment, the traffic situation judgment unit (130) can scan a road area with a lidar to create a point cluster, and then calculate the speed of multiple vehicles based on the distance traveled by the recognized vehicle and the measured time interval based on the point cluster.

[0038] For example, the traffic situation judgment unit (130) can scan a road area with a lidar to create a point cluster, and recognize multiple vehicles in the point cluster by utilizing deep learning technology, etc. In addition, the traffic situation judgment unit (130) can scan the road area with a lidar multiple times at a preset cycle, and calculate the average speed of the multiple vehicles by using the distance traveled by each of the multiple recognized vehicles and the scanned time interval.

[0039] In another embodiment, the traffic situation judgment unit (130) can make a judgment using a plurality of road sensing information generated while moving in the opposite direction of the vehicle's driving direction in the road area from the starting point where the autonomous mobile robot (100) begins to operate.

[0040] Here, the starting point from which the autonomous mobile robot (100) begins to operate can be determined as a location adjacent to a predetermined distance from a point where road construction is in progress on a highway, national road, local road, or general road, an entry / exit point of an IC / JC / bridge, or a point where a traffic accident occurred.

[0041] For example, referring to FIG. 5, when an autonomous mobile robot (100) moves sequentially from a starting point (1) adjacent to a point where road construction is in progress to point 2 (2), point 3 (3), and point 4 (4) in the opposite direction of vehicle operation in the road area, the traffic situation judgment unit (130) can generate road sensing information at each of those locations and calculate the speeds of multiple vehicles. That is, the traffic situation judgment unit (130) can generate road sensing information a total of four times and calculate the speeds of multiple vehicles.

[0042] Additionally, the traffic situation judgment unit (130) can use the four road sensing information and preset conditions to determine whether a traffic jam has occurred in a road area. The preset conditions are described in detail in the following embodiments.

[0043] In another embodiment, the preset condition may be a condition in which the speed of a plurality of vehicles included in each of a plurality of road sensing pieces of information is below a predetermined threshold speed and then exceeds the threshold speed.

[0044] For example, referring to FIG. 5, the traffic situation judgment unit (130) can determine that a traffic jam has started in the road area of ​​point 4 (4) when the speed of multiple vehicles included in each of the road sensing information generated at the starting point (1), point 2 (2), and point 3 (3) is below the critical speed and the speed of multiple vehicles included in the road sensing information generated at point 4 (4) exceeds the critical speed.

[0045] At this time, the traffic situation judgment unit (130) may stay at point 4 (4) for a certain period of time and then regenerate road sensing information. In addition, when the speed of multiple vehicles included in the road sensing information becomes lower than the critical speed, the traffic situation judgment unit (130) may transmit a message to the server to convey the information, and then move in the opposite direction of the vehicle driving direction in the road area to determine again whether a traffic jam has started in the road area.

[0046] On the other hand, if the speed of multiple vehicles included in the road sensing information exceeds the threshold speed, the traffic situation judgment unit (130) transmits a message to the server to convey the content, and then moves in the direction of vehicle travel in the road area to determine again whether a traffic jam has started in the road area.

[0047] In another embodiment, the traffic situation judgment unit (130) generates road sensing information that further includes information on the density of multiple vehicles, and when judging whether a traffic jam has started in a road area, it may be further based on the information on the density of the multiple vehicles.

[0048] The traffic situation judgment unit (130) can scan a road area with a lidar to create a point cluster and recognize multiple vehicles in the point cluster by utilizing deep learning technology, etc. In addition, the traffic situation judgment unit (130) can calculate the density of multiple vehicles by counting the number of vehicles located in a certain area of ​​the road area that can be scanned with the lidar. Furthermore, the traffic situation judgment unit (130) can generate road sensing information that further includes information regarding the density of multiple vehicles.

[0049] In addition, the traffic situation judgment unit (130) can further utilize information on the density of multiple vehicles included in the road sensing information to determine whether a traffic jam has started in the road area. For example, if the density of multiple vehicles exceeds a predetermined critical density at the starting point (1), point 2 (2), and point 3 (3), and then falls below the critical density at point 4 (4), the traffic situation judgment unit (130) can determine that a traffic jam has started in the road area at point 4 (4).

[0050] At this time, the traffic situation judgment unit (130) can use the information on the density and speed of multiple vehicles to determine the onset of a traffic jam. For example, the traffic situation judgment unit (130) can determine that a traffic jam has started when the density of multiple vehicles exceeds the critical density at the starting point (1), point 2 (2), and point 3 (3) and then falls below the critical density at point 4 (4), and when the speed of the multiple vehicles falls below the critical speed at the starting point (1), point 2 (2), and point 3 (3) and then exceeds the critical speed at point 4 (4). However, the present invention is not limited to this embodiment, and the traffic situation judgment unit (130) can use the information on the density and speed of multiple vehicles in various forms to determine the onset of a traffic jam.

[0051] Finally, the communication unit (140) transmits location information about the location where the designated state started to the server.

[0052] At this time, the communication unit (140) can transmit location information about the location where the designated state started to the server using a wireless mobile communication means such as 3G, 4G / LTE, 5G, LoRa, etc.

[0053] For example, referring to FIG. 5, when it is determined that a traffic jam has started in the road area of ​​point 4 (4), the communication unit (140) can transmit location information (e.g., longitude / latitude) regarding the location of point 4 (4) to the server.

[0054] Furthermore, the communication unit (140) can transmit information about the location to another autonomous mobile robot (not shown). At this time, the other autonomous mobile robot (not shown) can move in the opposite direction of the vehicle's direction of travel a preset distance from the location and use a variable guide sign, warning light, or speaker to inform that there is a point ahead where a traffic jam begins.

[0055] In another embodiment, the HD map may correspond to the shoulder of a road and include a driving area, which is an area where an autonomous mobile robot (100) operates, and a road area, which is an area where a vehicle travels from the shoulder of the road to the centerline of the road.

[0056] In general, a high definition map (HD map) refers to a high-precision map that can provide autonomous vehicles with detailed road and surrounding terrain information in advance. With an accuracy of within 10 cm, it can include 3D digital data for lane-level information such as road centerlines and boundaries, as well as traffic lights, signs, curbs, road markings, and various structures.

[0057] The HD map used in the present invention includes information on the road boundary line, shoulder, and road centerline, and with reference to FIG. 4, may include a driving area meaning an area corresponding to the shoulder of the road and a road area meaning an area between the shoulder and the road centerline.

[0058] FIG. 2 is a block diagram showing an autonomous mobile robot that generates traffic information according to another embodiment of the present invention.

[0059] Referring to FIG. 2, an autonomous mobile robot (100) that generates traffic information according to another embodiment of the present invention includes a driving system unit (110), a position measurement unit (120), a traffic situation judgment unit (130), a communication unit (140), and an alarm unit (150).

[0060] The operation system unit (110) is responsible for the operation of the autonomous mobile robot (100) in the driving area corresponding to the shoulder of the road.

[0061] The location measurement unit (120) determines the location of the autonomous mobile robot (100) based on GPS on the HD map.

[0062] The traffic situation judgment unit (130) uses lidar to generate road sensing information, which is information on the speed of multiple vehicles located in a road area where vehicles travel, on an HD map, and determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0063] The communication unit (140) transmits location information about the location where the designated state began to the server.

[0064] The alarm unit (150) uses a variable guide sign, warning light, or speaker to notify that a designated traffic situation has begun.

[0065] For example, referring to FIG. 5, when it is determined that a traffic jam has started in the road area of ​​point 4 (4), the alarm unit (150) can use a variable message board (VMS) installed on the autonomous mobile robot (100) to inform the user that a traffic jam has started at a certain distance ahead in the form of text. In addition, the alarm unit (150) can inform the user that a traffic jam has started ahead by emitting or flashing a warning light mounted on the autonomous mobile robot (100). In addition, the alarm unit (150) can inform the user that a traffic jam has started ahead by outputting a voice, warning sound, etc. through a speaker mounted on the autonomous mobile robot (100).

[0066] At this time, referring to FIG. 3, an autonomous mobile robot (100) that generates traffic information according to another embodiment of the present invention can be equipped with a variable guide sign, a warning light, and a speaker.

[0067] The above description is merely an illustrative illustration of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications and variations can be made without departing from the essential characteristics of the present invention. Therefore, the embodiments implemented in the present invention are intended to illustrate rather than limit the technical idea of ​​the present invention, and the scope of the technical idea of ​​the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted by the following claims, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of the rights of the present invention.

Claims

1. The operation system department responsible for the operation of autonomous mobile robots in the driving area corresponding to the shoulder of the road; A position measurement unit that determines the position of the autonomous mobile robot based on GPS on an HD map; A traffic situation judgment unit that generates road sensing information, which is information on the speed of multiple vehicles located in a road area where vehicles travel on the HD map, using lidar, and determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions; and A communication unit that transmits location information about the location where the above-mentioned designated state started to the server; An autonomous mobile robot that generates traffic information, characterized by including:

2. In paragraph 1, The above traffic situation judgment department An autonomous mobile robot that generates traffic information, characterized in that it makes a judgment using a plurality of road sensing information generated while moving in the opposite direction of the vehicle's driving direction in the road area from the starting point where the autonomous mobile robot starts to operate.

3. In paragraph 2, The above preset conditions are An autonomous mobile robot that generates traffic information, characterized in that the speed of the plurality of vehicles included in each of the plurality of road sensing information is below a predetermined threshold speed and then exceeds the threshold speed.

4. In paragraph 1, The above traffic situation judgment department An autonomous mobile robot that generates traffic information, characterized in that it scans the road area with a lidar to generate a point cluster, and then calculates the speed of the plurality of vehicles based on the distance traveled by the recognized vehicle and the measured time interval based on the point cluster.

5. In paragraph 1, The above HD map is A driving area corresponding to the shoulder of the road, which is the area where the autonomous mobile robot operates; and An autonomous mobile robot that generates traffic information, characterized by including a road area, which is an area where vehicles travel from the shoulder of the road to the centerline of the road.

6. In paragraph 1, The above traffic situation judgment department Generate road sensing information that further includes information on the density of the plurality of vehicles, When determining whether a traffic jam has started in the above road area, An autonomous mobile robot that generates traffic information, characterized in that it is further based on information about the density of the plurality of vehicles.

7. In paragraph 1, An alarm unit that uses variable guidance signs, warning lights, or speakers to indicate that a traffic jam is about to begin. An autonomous mobile robot generating traffic information, characterized by further including:

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