Traffic information generation system and method using autonomous mobile robot

Abstract

A traffic information generation system using an autonomous mobile robot according to an embodiment of the present invention comprises: an autonomous mobile robot for, on the basis of road sensing information which is information on the speed of a plurality of vehicles located in a road area where the vehicles travel and a preconfigured condition, determining whether a traffic congestion state has begun in the road area, and transmitting position information on a position where the traffic congestion state has begun; a server for receiving the position information and transmitting a guide request for requesting a guide for the position where the traffic congestion state has begun, the position being included in the position information; and a guide robot for guiding that the traffic congestion state begins from a position spaced a preconfigured distance ahead from the autonomous mobile robot, in response to the guide request.

Description

Traffic information generation system and method using autonomous mobile robots

[0001] The present invention relates to a traffic information generation system and method using an autonomous mobile robot that determines traffic conditions while 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] Accordingly, in cases where traffic congestion is expected to occur on a road, there is an increasing need for a traffic information generation system and method using an autonomous mobile robot that moves to the point where traffic congestion begins and informs following vehicles about the traffic congestion situation on the road.

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

[0006] In order to achieve the above-described object, a traffic information generation system using an autonomous mobile robot according to one embodiment of the present invention comprises: an autonomous mobile robot that determines whether a traffic jam has started in a road area on which vehicles travel based on road sensing information, which is information about the speeds of a plurality of vehicles located in the road area, and a preset condition, and transmits location information about a location where the traffic jam has started; a server that receives the location information and transmits a guidance request that requests guidance about a location where the traffic jam has started, which is included in the location information; and a guidance robot that, in response to the guidance request, provides guidance that a traffic jam has started ahead at a location a preset distance away from the autonomous mobile robot.

[0007] Preferably, the autonomous mobile robot operates in a driving area corresponding to the shoulder of a road, determines a location based on GPS on an HD map, and then uses lidar to generate road sensing information, which is information on the speed of a plurality of vehicles located in a road area on which vehicles travel, on the HD map, and determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0008] Preferably, the autonomous mobile robot 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 to operate.

[0009] 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.

[0010] Preferably, the autonomous mobile robot 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 vehicles and the measured time interval based on the point cluster.

[0011] Preferably, the HD map may include a driving area corresponding to the shoulder of a road and an area where the autonomous mobile robot operates; and a road area, which is an area where vehicles travel from the shoulder of the road to the centerline of the road.

[0012] Preferably, the autonomous mobile robot generates road sensing information that further includes information on the density of the plurality of vehicles, and when determining 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.

[0013] Preferably, the guide robot can use a variable guide sign, warning light, or speaker to indicate that there is a point ahead where a designated traffic jam begins.

[0014] In addition, a method for generating traffic information using an autonomous mobile robot according to an embodiment of the present invention for achieving the above-described object includes a step of the autonomous mobile robot determining whether a traffic jam has started in a road area on which the vehicle travels based on road sensing information, which is information about the speeds of a plurality of vehicles located in the road area, and a preset condition; a step of the autonomous mobile robot transmitting location information about a location where the traffic jam has started; a step of the server receiving the location information and transmitting a guidance request requesting guidance about a location where the traffic jam has started, which is included in the location information; and a step of the guidance robot, in response to the guidance request, guiding that a traffic jam has started ahead at a location a preset distance away from the autonomous mobile robot.

[0015] Preferably, the autonomous mobile robot operates in a driving area corresponding to the shoulder of a road, determines a location based on GPS on an HD map, and then uses lidar to generate road sensing information, which is information on the speed of a plurality of vehicles located in a road area on which vehicles travel, on the HD map, and determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0016] A traffic information generation system and method using an autonomous mobile robot according to one embodiment of the present invention has the effect of preventing traffic accidents in advance by having the autonomous mobile robot move to a road where a traffic jam has occurred and inform following vehicles about the traffic jam situation on the road through various means.

[0017] FIG. 1 is a block diagram showing a traffic information generation system using an autonomous mobile robot according to one embodiment of the present invention.

[0018] FIG. 2 is a flowchart illustrating a method for generating traffic information using an autonomous mobile robot according to one embodiment of the present invention.

[0019] FIG. 3 is a drawing for explaining an autonomous mobile robot according to one embodiment of the present invention.

[0020] FIG. 4 is a drawing for explaining HDMAP according to one embodiment of the present invention.

[0021] FIG. 5 is a drawing for explaining an operation method of an autonomous mobile robot according to one embodiment of the present invention.

[0022] FIG. 6 is a drawing for explaining the positions of an autonomous mobile robot and a guide robot according to one embodiment of the present invention.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Hereinafter, the present invention will be described with reference to the attached drawings.

[0030] FIG. 1 is a block diagram showing a traffic information generation system using an autonomous mobile robot according to one embodiment of the present invention.

[0031] Referring to FIG. 1, a traffic information generation system using an autonomous mobile robot according to one embodiment of the present invention includes an autonomous mobile robot (110), a server (120), and a guide robot (130).

[0032] An autonomous mobile robot (110) determines whether a traffic jam has started in a road area based on road sensing information, which is information about the speed of multiple vehicles located in a road area where vehicles travel, and preset conditions, and transmits location information about the location where the traffic jam has started.

[0033] Here, the autonomous mobile robot (110) can operate in a driving area corresponding to the shoulder of the road. The autonomous mobile robot (110) may include basic components necessary for driving on a road, such as a battery, motor, and tires. In addition, the autonomous mobile robot (110) may further include a camera or lidar, enabling it to autonomously navigate to its next destination on the road. For example, referring to FIG. 3, an embodiment of an autonomous mobile robot (110) according to one embodiment of the present invention is illustrated.

[0034] In addition, the autonomous mobile robot (110) can determine whether a traffic jam has started based on road sensing information and preset conditions, and transmit location information about the location where the traffic jam has started to the server (120) using a wireless mobile communication means such as 3G, 4G / LTE, 5G, LoRa, etc.

[0035] In another embodiment, an autonomous mobile robot (110) operates in a driving area corresponding to the shoulder of a road, determines a location based on GPS on an HD map, and then uses lidar to generate road sensing information, which is information on the speed of a plurality of vehicles located in a road area on which vehicles travel, on the HD map, and can determine whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0036] An autonomous mobile robot (110) can determine its own location on an HD map using GPS or high-performance DGPS. More specifically, the autonomous mobile robot (110) can secure its current location in the form of longitude and latitude coordinates using GPS or DGPS, and by mapping these coordinates on an HD map, the location of the autonomous mobile robot (110) on the HD map can be determined.

[0037] Meanwhile, the autonomous mobile robot (110) drives in a driving area corresponding to the shoulder of a road on an HD map, and uses lidar to generate road sensing information, which is information on the speed of multiple vehicles located in the road area where vehicles travel on the HD map, and can determine whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0038] 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.

[0039] For example, referring to FIG. 4, an autonomous mobile robot (110) can generate road sensing information by measuring the speed of a vehicle located in a road area using a lidar while staying in a driving area on an HD map.

[0040] 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.

[0041] In another embodiment, the autonomous mobile robot (110) can determine whether a traffic jam has started by using a plurality of road sensing information generated while moving in the opposite direction of the vehicle's driving direction in a road area from a starting point where the autonomous mobile robot (110) starts to operate.

[0042] Here, the starting point from which the autonomous mobile robot (110) 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.

[0043] For example, referring to FIG. 5, an autonomous mobile robot (110) 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, and generates road sensing information at each location and calculates the speed of multiple vehicles. That is, the autonomous mobile robot (110) can generate road sensing information a total of four times and calculate the speed of multiple vehicles.

[0044] Additionally, the autonomous mobile robot (110) can determine whether a traffic jam has occurred in a road area using the four road sensing information and preset conditions. The preset conditions are described in detail in the following examples.

[0045] 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.

[0046] For example, referring to FIG. 5, the autonomous mobile robot (110) can determine that a traffic jam has started in the road area of ​​point 4 (4) when the speed of multiple vehicles included in the road sensing information generated at each of 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.

[0047] At this time, the autonomous mobile robot (110) can 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 autonomous mobile robot (110) can transmit a message to the server (120) to convey the content, 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.

[0048] On the other hand, if the speed of multiple vehicles included in the road sensing information exceeds the critical speed, the autonomous mobile robot (110) can transmit a message to the server (120) to convey the information, and then move in the direction of vehicle travel in the road area to determine again whether a traffic jam has started in the road area.

[0049] In another embodiment, the autonomous mobile robot (110) 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 vehicles and the measured time interval based on the point cluster.

[0050] For example, an autonomous mobile robot (110) can scan a road area with lidar to create a point cluster, and recognize multiple vehicles in the point cluster by utilizing deep learning technology, etc. In addition, the autonomous mobile robot (110) can scan the road area with 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 recognized multiple vehicles and the scanned time interval.

[0051] In another embodiment, the HD map may include a driving area corresponding to the shoulder of a road and an area where an autonomous mobile robot (110) operates, and a road area, which is an area where vehicles travel from the shoulder of the road to the centerline of the road.

[0052] 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.

[0053] 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.

[0054] In another embodiment, the autonomous mobile robot (110) may generate road sensing information that further includes information about the density of multiple vehicles, and may further base its judgment on the information about the density of the multiple vehicles when determining whether a traffic jam has started in a road area.

[0055] An autonomous mobile robot (110) 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 autonomous mobile robot (110) 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 autonomous mobile robot (110) can generate road sensing information that further includes information regarding the density of multiple vehicles.

[0056] In addition, the autonomous mobile robot (110) 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 is lower than the critical density at point 4 (4), the autonomous mobile robot (110) can determine that a traffic jam has started in the road area at point 4 (4).

[0057] At this time, the autonomous mobile robot (110) can appropriately combine information about the density and speed of multiple vehicles to determine the onset of a traffic jam. For example, the autonomous mobile robot (110) can determine that a traffic jam has started when the density of multiple vehicles exceeds a 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 autonomous mobile robot (110) can combine information about the density and speed of multiple vehicles in various forms to determine the onset of a traffic jam.

[0058] The server (120) receives location information and transmits a guidance request requesting guidance on the location where the designated state included in the location information started.

[0059] At this time, the server (120) can receive location information about the location where the designated state started from the autonomous mobile robot (110).

[0060] 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 autonomous mobile robot (110) transmits location information (e.g., longitude / latitude) regarding the location of point 4 (4) to the server (120), and the server (120) can receive the location information.

[0061] In response to the guidance request, the guide robot (130) guides the autonomous mobile robot (110) to start a designated state in front at a preset distance away.

[0062] At this time, the guide robot (130) can autonomously move to a location a preset distance away in the opposite direction of the vehicle's travel direction from the location of the autonomous mobile robot (110), and then use a variable guide sign, warning light, or speaker to indicate that there is a point ahead where a traffic jam begins. Furthermore, if there are multiple preset distances, the guide robot (130) can exist in multiple numbers.

[0063] For example, referring to FIG. 6, the autonomous mobile robot (110) can transmit location information to the server (120) while remaining at the location where the traffic jam starts in the road area. Then, the guide robot (130) can move to a location a preset distance away from the autonomous mobile robot (110) after receiving a guidance request signal requesting guidance for that location from the server (120). Then, the guide robot (130) can guide vehicles driving at that location that a traffic jam starts ahead.

[0064] In another embodiment, the guide robot (130) may use variable guide signs, warning lights, or speakers to indicate that there is a point ahead where a designated state begins.

[0065] That is, the guide robot (130) can use a variable message sign (VMS) to inform that a traffic jam has started at a certain distance ahead in the form of text. In addition, the guide robot (130) can inform that a traffic jam has started ahead by emitting or flashing warning lights. In addition, the guide robot (130) can inform that a traffic jam has started ahead by outputting a voice, warning sound, etc. through a speaker.

[0066] FIG. 2 is a flowchart illustrating a method for generating traffic information using an autonomous mobile robot according to one embodiment of the present invention.

[0067] In step S210, the autonomous mobile robot (110) determines whether a traffic jam has started in the road area based on road sensing information, which is information about the speed of multiple vehicles located in the road area on which the vehicle is traveling, and preset conditions.

[0068] In step S220, the autonomous mobile robot (110) transmits location information about the location where the designated state started.

[0069] In step S230, the server (120) receives the location information and transmits a guidance request requesting guidance on the location where the designated state included in the location information started.

[0070] Finally, in step S240, the guide robot (130) responds to the guidance request and guides the autonomous mobile robot (110) to start a designated state in front at a preset distance away.

[0071] In another embodiment, an autonomous mobile robot (110) operates in a driving area corresponding to a shoulder of a road, determines a location based on GPS on an HD map, and then uses lidar to generate road sensing information, which is information on the speed of a plurality of vehicles located in a road area on which vehicles travel, on the HD map, and can determine whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

[0072] 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. An autonomous mobile robot that determines whether a traffic jam has started in a road area based on road sensing information, which is information on the speed of multiple vehicles located in a road area where vehicles travel, and preset conditions, and transmits location information on the location where the traffic jam has started; A server that receives the above location information and transmits a guidance request requesting guidance on the location where the designated state included in the above location information started; and In response to the above guidance request, a guidance robot that guides the start of a designated state in front at a location a preset distance away from the autonomous mobile robot; A traffic information generation system using an autonomous mobile robot, characterized by including:

2. In paragraph 1, The above autonomous mobile robot Drive in the driving area corresponding to the shoulder of the road, After determining the location based on GPS on the HD map, road sensing information, which is information on the speed of multiple vehicles located in the road area where the vehicles travel on the HD map, is generated using lidar. A traffic information generation system using an autonomous mobile robot, characterized in that it determines whether a traffic jam has started in the road area based on the above road sensing information and preset conditions.

3. In paragraph 1, The above autonomous mobile robot A traffic information generation system using an autonomous mobile robot, 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.

4. In paragraph 3, The above preset conditions are A traffic information generation system using an autonomous mobile robot, 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.

5. In paragraph 2, The above autonomous mobile robot A traffic information generation system using an autonomous mobile robot, characterized in that the system 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.

6. In paragraph 2, 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 A traffic information generation system using an autonomous mobile robot, characterized in that it includes a road area, which is an area where vehicles travel from the shoulder of the road to the centerline of the road.

7. In paragraph 2, The above autonomous mobile robot 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, A traffic information generation system using an autonomous mobile robot, characterized in that it is further based on information regarding the density of the plurality of vehicles.

8. In paragraph 1, The above guide robot An autonomous mobile robot that generates traffic information, characterized by indicating that there is a point ahead where a traffic jam begins using variable guidance signs, warning lights, or speakers.

9. A step in which an autonomous mobile robot determines whether a traffic jam has started in a road area based on road sensing information, which is information on the speed of multiple vehicles located in the road area on which the vehicle is traveling, and preset conditions; A step in which the autonomous mobile robot transmits location information regarding the location where the designated state begins; A step in which the server receives the location information and transmits a guidance request requesting guidance for the location where the designated state included in the location information started; and A step in which the guide robot guides the autonomous mobile robot to start a designated state in front at a preset distance in response to the above-mentioned guidance request. A method for generating traffic information using an autonomous mobile robot, characterized by including:

10. In paragraph 8, The above autonomous mobile robot Drive in the driving area corresponding to the shoulder of the road, After determining the location based on GPS on the HD map, road sensing information, which is information on the speed of multiple vehicles located in the road area where the vehicles travel on the HD map, is generated using lidar. A method for generating traffic information using an autonomous mobile robot, characterized in that it determines whether a traffic jam has started in the road area based on the road sensing information and preset conditions.

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