Mobility support method and mobility support system for mobile objects

Abstract

To provide a technique capable of simultaneously guiding a plurality of moving bodies while ensuring traffic safety of the moving bodies.SOLUTION: A moving body included in an image of an infrastructure camera is recognized. A future trajectory of the moving body is predicted on the basis of the recognition information on the moving body. Supporting display for supporting movement of the moving body is output from a pavement lighting device on the basis of the future trajectory. When the recognition information on the moving body includes recognition information on first and second moving bodies, whether or not the future trajectories of these moving bodies intersect is determined. When it is determined the future trajectories of the first and second moving bodies intersect, an intersection avoidance trajectory to at least one of the first and second moving bodies is generated. When the intersection avoidance trajectory is generated, the supporting display corresponding to the intersection avoidance trajectory is output from the pavement lighting device.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to a method and system for assisting the movement of a mobile object such as a pedestrian. [Background technology]

[0002] Japanese Patent Application Laid-Open Publication No. 2006-233503 discloses a road lighting system attached to existing streetlights or utility poles. This conventional system includes a motion sensor. When a pedestrian is detected by the motion sensor, the conventional system emits multiple spot lights along the pedestrian's direction of travel. The multiple spot lights are emitted by multiple illumination devices that make up the conventional system. The multiple spot lights emitted from these illumination devices are reflected by the road surface. Therefore, the conventional system can guide pedestrians along the direction of the alignment of the multiple road surface reflected lights.

[0003] In addition to JP 2006-233503 A, examples of documents showing the state of the art in the technical field related to the present disclosure include WO 2019 / 146008 A and JP 2014-13524 A. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-233503 [Patent Document 2] International Publication No. 2019 / 146008 [Patent Document 3] Japanese Patent Application Laid-Open No. 2014-13524 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in conventional systems, the motion sensor only detects whether a person is present within the detection range, and does not distinguish between multiple pedestrians. Therefore, there is a limit to the number of pedestrians that can be guided simultaneously. Furthermore, in conventional systems, the direction of the spotlight emitted by each illumination device is fixed. Therefore, the light reflected from the road surface can only encourage pedestrians to move in a fixed direction.

[0006] We consider a method of placing multiple road studs on the road surface and lighting these road studs. With this method, in situations where multiple pedestrians and bicycles are passing by, it is possible to simultaneously guide these moving objects and encourage each moving object to move in a direction other than the direction of travel. However, on the other hand, in such situations, it is expected that the direction of movement of these moving objects will not be constant. Therefore, there is room for development of a method of simultaneously guiding multiple moving objects while ensuring their traffic safety.

[0007] One object of the present disclosure is to provide a technology that can simultaneously guide multiple moving bodies while ensuring the traffic safety of these moving bodies. [Means for solving the problem]

[0008] A first aspect of the present disclosure is a method for assisting movement of a moving object, which has the following features. The method includes the steps of recognizing a moving object included in an image of an infrastructure camera, predicting a future trajectory of the moving object based on the recognition information of the moving object, and outputting an assistance display from a road surface lighting device that assists the movement of the moving object based on the future trajectory. The method further includes a step of determining whether the future trajectories of the moving bodies predicted in the step of predicting the future trajectories will intersect if the recognition information of the moving bodies includes recognition information of a first and a second moving body, and a step of generating an intersection avoidance trajectory for at least one of the first and second moving bodies if it is determined that the future trajectories of the first and second moving bodies will intersect. When the intersection avoidance trajectory is generated, in the step of outputting the assistance indication, an assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device.

[0009] A second aspect of the present disclosure is a system for assisting movement of a moving object, which has the following features. The system includes a road lighting device, an infrastructure camera, and a processor. The road lighting device illuminates a road surface. The infrastructure camera captures an image of the road surface. The processor is configured to perform various processes. The processor is configured to perform the following processes: recognize a moving object included in an image of the infrastructure camera; predict a future trajectory of the moving object based on the recognition information of the moving object; and cause the road surface lighting device to output an assistance display that assists the movement of the moving object based on the future trajectory. The processor is further configured to, when the recognition information of the moving bodies includes recognition information of a first and a second moving body, perform a process of determining whether the future trajectories of these moving bodies predicted in the process of predicting the future trajectories will intersect, and, when it is determined that the future trajectories of the first and second moving bodies will intersect, a process of generating an intersection avoidance trajectory for at least one of the first and second moving bodies. When the intersection avoidance trajectory is generated, in the process of causing the road surface lighting device to output the assistance indication, the assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device. [Effects of the Invention]

[0010] According to the present disclosure, a road surface lighting device outputs an assistance display to assist the movement of a moving object based on the future trajectory of the moving object included in an image from an infrastructure camera. Furthermore, when the object of movement assistance includes a first and a second moving object, it is determined whether the future trajectories of these moving objects will intersect. Furthermore, when it is determined that the future trajectories will intersect, an intersection avoidance trajectory for at least one of the first and second moving objects is generated. Then, when an intersection avoidance trajectory is generated, an assistance display corresponding to this intersection avoidance trajectory is output from the road surface lighting device. Therefore, it is possible to simultaneously guide multiple moving objects while ensuring their traffic safety. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an outline of an embodiment. [Figure 2] 10A and 10B are diagrams illustrating a first example of light emission of an LED stud. [Figure 3] 10A and 10B are diagrams illustrating a second example of light emission of the LED stud. [Figure 4] FIG. 10 is a diagram illustrating an example of a countermeasure when two future trajectories intersect. [Figure 5] FIG. 10 is a diagram illustrating another example of a countermeasure when two future trajectories intersect. [Figure 6] 10A and 10B are diagrams illustrating examples of measures to be taken when a generated trajectory intersects with a future trajectory of another moving object. [Figure 7] 1 is a diagram illustrating an example of the configuration of a travel assistance system according to an embodiment. [Figure 8] 10 is a flowchart illustrating a flow of processing that is performed in a server and that is particularly related to the embodiment. [Figure 9] 10 is a flowchart illustrating a flow of processing that is performed in a server and that is particularly related to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals, and the description thereof will be simplified or omitted.

[0013] 1. Overview Fig. 1 is a diagram for explaining an outline of an embodiment. Fig. 1 depicts a road 1. Examples of the road 1 include a road for pedestrians, and a road for pedestrians as well as moving objects that move at a slower speed than automobiles, such as wheelchairs, self-propelled robots, and bicycles. The shape and width of the road 1 are not particularly limited.

[0014] A plurality of LED studs 2 are installed on the road surface of the road 1. In the example shown in FIG. 1, these LED studs 2 are installed at equal intervals. However, the arrangement of these LED studs 2 is not limited to this example. Furthermore, there is no particular limitation on the number of these LED studs 2 installed per unit area. Each LED stud 2 brightens the area around its installation location, and corresponds to an example of a "road surface lighting device" of the present disclosure. Other examples of road surface lighting devices include a device that irradiates light onto the road surface of the road 1 to brighten the illumination range, and a device that projects an image onto the road surface of the road 1 to brighten the projection range.

[0015] 1, the coordinates (x, y) will be used to refer to a specific LED tack 2 (x, y). For example, the lower left LED tack 2 (x, y) will be referred to as LED tack 2 (1, 1), and the upper left LED tack 2 (x, y) will be referred to as LED tack 2 (6, 1). Furthermore, the lower left LED tack 2 (x, y) will be referred to as LED tack 2 (1, 13), and the upper left LED tack 2 (x, y) will be referred to as LED tack 2 (6, 13).

[0016] A plurality of infrastructure cameras 3 are installed around the road 1. Each infrastructure camera 3 is a camera installed on a structure around the road 1 (for example, a road structure, or a facility structure such as a ceiling, pillar, or wall of a parking lot or factory). Each infrastructure camera 3 also captures an image of a predetermined range set for each infrastructure camera 3. The predetermined image capturing range includes, for example, the road surface of the road 1. Part or all of the predetermined image capturing range of one infrastructure camera 3 may overlap with that of another infrastructure camera 3.

[0017] The server 4 manages the mobility assistance system. The server 4 communicates individually with multiple LED studs 2. In communication with each LED stud 2, the server 4 transmits to each LED stud 2 assistance display information LUM(x,y) that assists the movement of the mobile object. The assistance display information LUM(x,y) includes, for example, instruction information for the LED stud 2(x,y). Examples of the instruction information include light emission color information and brightness information. The LED stud 2(x,y) emits light based on the instruction information for the LED stud 2(x,y).

[0018] The server 4 also communicates individually with the multiple infrastructure cameras 3. In communication with each infrastructure camera 3, the server 4 receives camera information CAM from each infrastructure camera 3. The camera information CAM includes, for example, ID information of the infrastructure camera 3 that sent the camera information CAM and image information acquired by this infrastructure camera 3. The image information may be a video or a still image. When the infrastructure camera 3 performs object recognition processing (described below), information on the recognition results obtained by this object recognition processing may be included in the image information.

[0019] FIG. 2 is a diagram illustrating a first example of light emission of the LED stud 2(x, y). FIG. 2 depicts moving objects 5 and 6 (pedestrians) moving on a road 1. The moving objects 5 and 6 are recognized based on images acquired by an infrastructure camera 3. A trajectory TR5 is the future trajectory of the moving object 5 predicted based on the recognition information of the moving object 5. A trajectory TR6 is the future trajectory of the moving object 6 predicted based on the recognition information of the moving object 6. The lengths of the trajectories TR5 and TR6 correspond to the distances that the moving objects 5 and 6 are predicted to travel in a few seconds (2 to 4 seconds) from the current time. These lengths are calculated, for example, based on the moving speed and direction of the moving objects 5 and 6.

[0020] In the example shown in FIG. 2, before trajectories TR5 and TR6 are predicted, the LED tacks 2(x,y) emit light of the same color and at the same level of brightness. When trajectory TR5 is predicted, the LED tacks 2(x,y) located around this trajectory TR5 (i.e., (x,y)=(2,2) to (2,4) and (3,2) to (3,4)) emit light of a specific color and at a high level of brightness. This specific color may be the same as the color of trajectory TR5 before prediction, or it may be a different color. However, the brightness level of this specific color is set to a higher level than the brightness level of trajectory TR5 before prediction. For example, consider a case where brightness levels are expressed in five levels and the brightness level of trajectory TR5 before prediction is "Level 1 to 2." In this case, the brightness level of the specific color is set to "Level 3 to 4."

[0021] When the trajectory TR6 is predicted, the LED studs 2(x,y) located around this trajectory TR6 (i.e., (x,y)=(5,10) to (5,12) and (6,10) to (6,12)) emit light in a specific color with a high level of brightness. This specific color may be the same as the color of the trajectory TR6 before prediction, or may be a different color. However, this specific color is set to a color different from that of the LED studs 2 located around the trajectory TR5. Furthermore, the brightness level of this specific color is set to a level higher than the brightness level of the trajectory TR6 before prediction.

[0022] FIG. 3 is a diagram illustrating a second example of light emission of the LED stud 2(x, y). The example shown in FIG. 3 is taken at a time slightly later than the example shown in FIG. 2, and depicts a moving object 5. FIG. 3 also depicts a moving object 7 (bicycle). As with the example shown in FIG. 2, the moving object 5 is recognized based on an image acquired by the infrastructure camera 3. As with the moving object 5, the moving object 7 is also recognized based on an image acquired by the infrastructure camera 3. Trajectory TR7 is the future trajectory of the moving object 7 predicted based on the recognition information of the moving object 7. Trajectory TR7 is longer than TR5 because the moving speed of the moving object 7 is higher than that of the moving object 5.

[0023] In the example shown in FIG. 3, the LED studs 2(x,y) located around the track TR5 (i.e., (x,y)=(2,7), (2,8), (3,6) to (3,9), (4,7) and (4,8)) emit light in a specific color with a high level of brightness. This specific color is the same as the specific color of the LED studs 2 located around the track TR5 described in FIG. 2. In addition, the brightness level of this specific color is the same as the specific color of the LED studs 2 located around the track TR5 described in FIG. 2.

[0024] In the example shown in FIG. 3, upon prediction of the trajectory TR7, the LED studs 2(x,y) located around this trajectory TR7 (i.e., (x,y)=(3,1) to (3,5) and (4,1) to (4,5)) emit light in a specific color with a high level of brightness. This specific color may be the same as the color of the trajectory TR7 before prediction, or may be a different color. However, this specific color is set to a color different from that of the LED studs 2 located around the trajectory TR5.

[0025] As shown in FIGS. 2 and 3, in this embodiment, when a moving object is recognized in an image acquired by an infrastructure camera 3, the future trajectory of the moving object is predicted. Then, LED studs 2(x, y) located around this future trajectory are caused to emit light in a specific color with a high level of brightness. When a device that irradiates light onto the road surface of the road 1 is used, it is conceivable to irradiate the road surface with a strip of light extending along the future trajectory. Furthermore, when a device that projects an image onto the road surface of the road 1 is used, it is conceivable to project an image of any shape corresponding to the future trajectory onto the road surface.

[0026] Consider a situation where multiple moving bodies are traveling on road 1. In this case, the illumination of the LED studs 2(x,y) described in FIGS. 2 and 3 is thought to be useful in preventing collisions between these moving bodies (including excessive approach; the same applies below). This is because the illumination of the LED studs 2(x,y) located around the future trajectory of each moving body makes it possible to recognize the approach of other moving bodies. However, in the example shown in FIG. 3, moving body 7 approaches moving body 5 from behind moving body 5. Therefore, from the perspective of moving body 5, it is difficult to notice the illumination of the LED studs 2(x,y) located around TR7. Therefore, for example, if moving body 5 suddenly changes direction, there is a possibility that moving body 5 will collide with moving body 7.

[0027] Therefore, in an embodiment, when multiple moving objects are recognized, it is determined whether a collision will occur between these moving objects. This collision determination is performed based on multiple future trajectories predicted for each of the multiple moving objects. For example, when the number of moving objects is two, it is determined whether the two future trajectories intersect. If these future trajectories intersect, it can be determined that a collision will occur. When the number of moving objects is three or more, it is determined whether two of the three or more future trajectories intersect. If two future trajectories intersect, it can be determined that a collision will occur between the two moving objects whose intersecting future trajectories are predicted.

[0028] When determining whether a collision has occurred, the length of the future trajectory may be changed. That is, as already mentioned, the length of the future trajectory for making the LED stud 2 emit light corresponds to the distance traveled over several seconds (2 to 4 seconds). In this case, the length of the future trajectory for determining whether a collision has occurred may be set to a distance traveled over a period of time longer than these several seconds (for example, 2 to 6 seconds).

[0029] An example of a countermeasure when two future trajectories intersect will be described with reference to FIG. 4. FIG. 4 corresponds to an example in which the length of the future trajectories for collision determination is extended in the example described in FIG. 3. That is, the trajectories TR5# and TR7# depicted in FIG. 4 are future trajectories for collision determination between moving body 5 and moving body 7. As can be seen from FIG. 4, the trajectories TR5# and TR7# intersect. Therefore, in the example shown in FIG. 4, the direction of the trajectory TR7# is changed to generate a trajectory TR7* that does not intersect with the trajectory TR5#. This trajectory TR7* corresponds to the "intersection avoidance trajectory" of the present disclosure.

[0030] When the trajectory TR7* is generated, the LED studs 2(x,y) located around the trajectory TR7* (i.e., (x,y)=(3,2) to (3,4), (4,1) to (4,6), and (5,3) to (5,5)) emit light in a specific color and at a high level of brightness. In other words, the LED studs 2(x,y) that emit light when the trajectory TR7* is generated are different from the LED studs 2(x,y) that emit light when the trajectory TR7 described in FIG. 3 is generated. Therefore, it is possible to prompt the moving body 7 to correct its direction of travel to avoid a collision with the moving body 5.

[0031] In this way, in the example shown in Fig. 4, a trajectory TR7* is generated that does not intersect with the trajectory TR5#. As already explained, the moving object 7 is approaching the moving object 5 from behind. Therefore, there is a possibility that the moving object 7 recognizes the moving object 5. Therefore, it is considered that the proposal to correct the traveling direction based on the trajectory TR7* is likely to be easily accepted by the moving object 7.

[0032] The proposal to correct the direction of travel can also be made to the moving body 5 instead of the moving body 7. Alternatively, the proposal to correct the direction of travel can be made to both the moving bodies 5 and 7. FIG. 5 is a diagram illustrating another example of a measure when two future trajectories intersect. In the example shown in FIG. 5, a trajectory TR7* that does not intersect with the trajectory TR5# is generated. Up to this point, this is the same as the example shown in FIG. 4. In the example shown in FIG. 5, the direction of the trajectory TR5# is further changed, and a trajectory TR5* that does not intersect with the trajectory TR7# is generated. This trajectory TR5* also corresponds to the "intersection avoidance trajectory" of the present disclosure.

[0033] When the trajectory TR5* is generated, the LED studs 2(x,y) located around the trajectory TR5* (i.e., (x,y)=(1,7) to (1,9), (2,7) to (2,9), (3,7) and (3,8)) emit light in a specific color with a high level of brightness. In other words, the LED studs 2(x,y) that emit light when the trajectory TR5* is generated are different from the LED studs 2(x,y) that emit light when the trajectory TR5 described in FIG. 3 is generated. Therefore, it is possible to prompt the moving body 5 to correct its direction of travel to avoid a collision with the moving body 7.

[0034] 5, a trajectory TR7* that does not intersect with the trajectory TR5# and a trajectory TR5* that does not intersect with the trajectory TR7# are generated, and therefore, a correction of the traveling direction can be proposed to both the moving bodies 5 and 7.

[0035] In the embodiment, when a trajectory TR* is generated (i.e., trajectories TR5* and TR7*) that does not intersect with the future trajectory TR# (i.e., trajectories TR5# and TR7#) for collision determination, it is determined whether or not this generated trajectory TR* intersects with the future trajectory of another moving object. The above-described determination method is applied to this intersection determination method. Then, when it is determined that the generated trajectory TR* intersects with the future trajectory of another moving object, a trajectory TR** that does not intersect with this future trajectory is generated from the generated trajectory TR*.

[0036] An example of a measure to be taken when a generated trajectory TR* intersects with a future trajectory of another moving object will be described with reference to FIG. 6. FIG. 6 corresponds to an example in which the length of the future trajectory TR# for collision determination is extended in the example described in FIG. 3. FIG. 6 also illustrates moving object 6, which was omitted in the description of FIG. 3. The trajectories TR6# and TR7*# illustrated in FIG. 6 are future trajectories for collision determination between moving object 6 and moving object 7. Note that trajectory TR7*# is also the future trajectory of moving object 7 generated based on trajectory TR7*.

[0037] As can be seen from Fig. 6, the trajectories TR6# and TR7*# intersect. Therefore, in the example shown in Fig. 6, the direction of the trajectory TR7*# is changed to generate a trajectory TR7** that does not intersect with the trajectory TR6#. This trajectory TR7** also corresponds to the "intersection avoidance trajectory" (or more accurately, the "corrected intersection avoidance trajectory") of the present disclosure.

[0038] When the trajectory TR7** is generated, the LED studs 2(x,y) located around the trajectory TR7** (i.e., (x,y)=(3,2) to (3,6), (4,1) to (4,6), (5,4) and (5,5)) emit light in a specific color with a high level of brightness. Therefore, according to the example shown in FIG. 6, it is possible to prompt the moving body 7 to correct its direction of travel to avoid a collision with the moving bodies 5 and 6.

[0039] As described above, according to the embodiment, it is possible to simultaneously guide a plurality of moving objects while ensuring the traffic safety of these moving objects. The embodiment will be described in more detail below.

[0040] 2. Mobility Support System 2-1. System configuration example Fig. 7 is a diagram showing an example of the configuration of a mobility assistance system according to an embodiment. In the example shown in Fig. 7, the mobility assistance system includes an LED stud group 2m, an infrastructure camera group 3n, and a server 4. The LED stud group 2m and the infrastructure camera group 3n communicate with the server 4 via a communication network 8. The communication network 8 is not particularly limited, and a wired or wireless network may be used.

[0041] The LED stud group 2m includes m LED studs 2 (m≧1). The installation locations of the m LED studs 2 are known. Each LED stud 2 operates according to the support display information LUM(x,y) received from the server 4, and illuminates the surroundings of its location. The support display information LUM(x,y) includes, for example, instruction information for the LED stud 2(x,y). Examples of instruction information include luminous color information and brightness information. The luminous color information is information indicating the color emitted by the light source of the LED stud 2(x,y), such as purple, blue, green, yellow, orange, or red. The brightness information is information indicating the brightness level of the light source of the LED stud 2(x,y).

[0042] The infrastructure camera group 3n includes n infrastructure cameras 3 (n≧1). The installation locations of the n infrastructure cameras 3 are known. Each infrastructure camera 3 captures an image of a predetermined range set for each infrastructure camera 3. The predetermined image capture range is also known. Each infrastructure camera 3 transmits camera information CAM to the server 4. The camera information CAM includes, for example, ID information of the infrastructure camera 3 that transmitted the camera information CAM and image information acquired by this infrastructure camera 3.

[0043] The server 4 includes an information processing device 41 and a database 42. The information processing device 41 includes at least one processor 43 and at least one memory 44. The processor 43 includes a CPU (Central Processing Unit). The memory 44 is a volatile memory such as a DDR memory, and expands various programs used in the various processes performed by the processor 43 and temporarily stores various information. The various information used by the processor 43 includes camera information CAM and map information MAP stored in the database 12.

[0044] The database 42 is formed in a predetermined storage device (for example, a hard disk or a flash memory). The database 42 stores map information MAP. The map information MAP includes data on the specifications of man-made objects such as buildings, roads, and railways (for example, type, size, central position or latitude, longitude, and height of one or more representative positions), as well as data on the specifications of natural objects such as rivers and lakes. The map information MAP also includes data on the installation positions of the LED stud group 2m and the infrastructure camera group 3n. The map information MAP further includes data on the specifications of each infrastructure camera 3 included in the infrastructure camera group 3n. The data on the specifications of each infrastructure camera 3 includes information on the angle of view of each infrastructure camera (i.e., information on a predetermined imaging range).

[0045] 2-2. Example of processing by the server 8 and 9 are flowcharts illustrating the flow of processing particularly related to the embodiment, which is performed in the server 4 (processor 43). The processing routines shown in Figs. 8 and 9 are repeatedly executed at predetermined intervals.

[0046] 8, first, the camera information CAM is acquired (step S11). As already described, the camera information CAM includes ID information of the infrastructure camera 3 that transmitted the camera information CAM and image information acquired by the infrastructure camera 3. The image information may also include information about the time when the image information was acquired.

[0047] Following the processing of step S11, object recognition processing is performed (step S12). In the object recognition processing, moving objects included in the image captured by the infrastructure camera 3 are recognized. The method for recognizing these moving objects is not particularly limited, and known methods can be applied. An example of a known method is an object recognition method using a machine learning model. When a moving object is recognized by the object recognition processing, identification information is assigned to the recognized moving object. Examples of this identification information include number information assigned to each moving object, type information of the recognized moving object (e.g., pedestrian, wheelchair, self-propelled robot, bicycle, etc.), and feature amount information of the recognized moving object.

[0048] Following the processing of step S12, it is determined whether or not a moving object has been recognized (step S13). If identification information has been generated in the processing of step S12, the determination result of step S13 is positive. If the determination result of step S13 is positive, a tracking process of the moving object is performed (step S14). This tracking process of the moving object is not particularly limited, and a known method can be applied. An example of a known method is a method (re-identification) of associating a moving object recognized in multiple frames based on feature amount information of the moving object.

[0049] By performing the tracking process, the moving speed and moving direction of the moving object recognized in the process of step S12 are calculated. Tracking information is generated for the moving object whose moving speed and moving direction have been calculated. This tracking information is stored in memory 42, for example, in combination with the identification information of the moving object.

[0050] 9, first, tracking information is acquired (step S21). Tracking information is generated for each moving object. Therefore, in the processing of step S21, tracking information for all moving objects present on the road 1 is acquired.

[0051] Following the processing of step S21, the trajectory TR and the trajectory TR# are calculated (step S22). The calculation of the trajectory TR and the trajectory TR# is performed for each moving object based on the tracking information (movement speed and movement direction) acquired in the processing of step S21. The length of the trajectory TR corresponds to the distance the moving object is predicted to move several seconds from the current time (2 to 4 seconds from now). The trajectory TR# is longer than the trajectory TR. The length of the trajectory TR# corresponds to the distance the moving object is predicted to move several seconds from the current time (for example, 2 to 6 seconds from now). Note that the calculation of the trajectory TR# does not have to be performed in the processing of step S22. In this case, the processing of step S23 is performed based on the trajectory TR calculated in the processing of step S22.

[0052] Following the processing of step S22, it is determined whether or not the two trajectories TR# intersect (step S23). For example, if only one trajectory TR# is generated in the processing of step S22, the determination result of step S23 will be negative. Also, for example, even if two or more trajectories TR# are generated in the processing of step S22, if none of these trajectories TR# intersect, the determination result of step S23 will be negative. If the determination result of step S23 is negative, the processing of step S24 is performed. On the other hand, if the determination result is positive, the processing of step S25 is performed.

[0053] In the process of step S24, support display information LUM(x, y) is generated based on at least one trajectory TR generated in the process of step S22. The support display information LUM(x, y) includes, for example, instruction information for the LED stud 2(x, y). Examples of the instruction information include luminous color information and brightness information. When two or more trajectories TR are generated in the process of step S22, luminous color information is generated so that the luminous color of the LED stud 2(x, y) located around one trajectory TR is different from that of the LED stud 2(x, y) located around another trajectory TR.

[0054] It is desirable that the color assigned as the luminous color of the LED studs 2(x, y) located around a certain track TR remains assigned without change until the moving object corresponding to this track TR is no longer recognized on the road 1. Therefore, when generating the luminous color information, it is desirable that colors such as purple, blue, green, yellow, orange, and red are assigned to each track TR in order according to the order in which the moving objects are recognized on the road 1.

[0055] Furthermore, the brightness level included in the brightness information is higher than the brightness level of the LED studs 2(x,y) that are not located around the track TR. Here, the brightness level of the LED studs 2(x,y) that are not located around the track TR is set, for example, according to the ambient illuminance of the road surface of the road 1. For example, consider a case where the brightness level is expressed in five levels and the ambient illuminance of the road surface of the road 1 is low (for example, at night). In this case, the brightness level of the LED studs 2(x,y) that are not located around the track TR is set to "Level 2-3." On the other hand, when the street lights installed on the road 1 are on even at night, the brightness level is set to "Level 1-2."

[0056] In the processing of step S25, a trajectory TR* and a trajectory TR*# are generated. The trajectory TR* is generated for at least one of the two trajectories TR# determined to intersect in the processing of step S23. Like the trajectory TR*, the trajectory TR*# is generated for at least one of the two trajectories TR# determined to intersect in the processing of step S23. Note that if the trajectory TR# has not been calculated in the processing of step S22, the trajectory TR*# does not need to be calculated in the processing of step S25. In this case, the processing of step S27 is performed based on the trajectory TR* calculated in step S25 and another trajectory TR# calculated in the processing of step S22.

[0057] Following the processing of step S25, it is determined whether the trajectory TR*# intersects with another trajectory TR# (step S26). The processing of step S26 is basically the same as the processing of step S23. The difference between the processing of these steps lies in the trajectories that are the object of the intersection determination. That is, in the processing of step S26, it is determined whether the trajectory TR*# calculated in step S25 intersects with another trajectory TR# calculated in the processing of step S22. Note that the other trajectory TR# is a trajectory TR# different from the two trajectories TR# that were the object of the intersection determination in the processing of step S23. If the determination result of step S26 is positive, the processing of step S27 is performed. On the other hand, if the determination result is negative, the processing of step S28 is performed.

[0058] In the process of step S27, the trajectory TR* is corrected to generate a trajectory TR**. The trajectory TR* to be corrected is the trajectory TR* that was generated together with the trajectory TR*# when the trajectory TR*# determined to intersect with another trajectory TR# in the process of step S26 was generated in step S25.

[0059] In the process of step S27, a trajectory TR**# may be generated together with the trajectory TR**. In this case, the process of step S26 may be performed on the trajectory TR**#. In other words, a determination may be made as to whether the trajectory TR**# generated together with the trajectory TR** intersects with another trajectory TR#. By repeating the process of step S27 and the process of step S26, it is possible to generate an appropriate trajectory TR** that does not intersect with another trajectory TR#.

[0060] In the process of step S27, instead of correcting the trajectory TR*, another trajectory TR may be corrected, or both the trajectory TR* and the another trajectory TR may be corrected.

[0061] In the process of step S28, support display information LUM(x, y) is generated based on the trajectory TR* generated in the process of step S25 or the trajectory TR* corrected in the process of step S27. The process of step S28 is basically the same as the process of step S24.

[0062] Following the processing of step S28, the support display information LUM(x, y) is transmitted to each LED stud 2 (step S29). Upon receiving the support display information LUM(x, y), the LED stud 2(x, y) emits light based on the instruction information contained in this information. [Explanation of symbols]

[0063] 1 Road 2 LED stud 2m LED stud group 3 Infrastructure camera 3n Infrastructure camera group 4 Server 5, 6, 7 Mobile body 41 Information processing device 42 Database 43 Processor 44 Memory TR5, TR6, TR7, TR5*, TR7*, TR7**, TR5#, TR6#, TR7#, TR7*# Track CAM Camera information LUM(x, y) Support display information

Claims

1. A method for supporting movement of a mobile object, performed by a server, comprising: A step of recognizing a moving object included in an image of an infrastructure camera; predicting a future trajectory of the moving object based on the recognition information of the moving object; a step of outputting an assistance display for assisting the movement of the moving object from a road surface lighting device based on the future trajectory; Including, a step of determining whether the future trajectories of the moving bodies predicted in the step of predicting the future trajectories intersect when the recognition information of the moving bodies includes recognition information of a first moving body and a second moving body; generating an intersection avoidance trajectory for at least one of the first and second moving bodies when it is determined that the future trajectories of the first and second moving bodies will intersect; Further comprising: When the intersection avoidance trajectory is generated, in the step of outputting the assistance indication, an assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device; a step of determining whether or not the future trajectory of the third moving body predicted in the step of predicting the future trajectory intersects with the intersection avoidance trajectory for at least one of the first and second moving bodies when the recognition information of the moving body includes recognition information of a third moving body; a step of correcting the crossing avoidance trajectory that intersects with the future trajectory of the third moving body when it is determined that the future trajectory of the third moving body and the crossing avoidance trajectory for at least one of the first and second moving bodies intersect; Further comprising: When the intersection avoidance trajectory that intersects with the future trajectory of the third moving body is corrected, in the step of outputting the assistance display, an assistance display corresponding to the corrected intersection avoidance trajectory is output from the road surface lighting device. A method for supporting movement of a moving body, comprising:

2. A method for supporting movement of a mobile object, performed by a server, comprising: A step of recognizing a moving object included in an image of an infrastructure camera; predicting a future trajectory of the moving object based on the recognition information of the moving object; a step of outputting an assistance display for assisting the movement of the moving object from a road surface lighting device based on the future trajectory; Including, a step of determining whether the future trajectories of the moving bodies predicted in the step of predicting the future trajectories intersect when the recognition information of the moving bodies includes recognition information of a first moving body and a second moving body; generating an intersection avoidance trajectory for at least one of the first and second moving bodies when it is determined that the future trajectories of the first and second moving bodies will intersect; Further comprising: When the intersection avoidance trajectory is generated, in the step of outputting the assistance indication, an assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device; a step of determining whether or not the future trajectory of the third moving body predicted in the step of predicting the future trajectory intersects with the intersection avoidance trajectory for at least one of the first and second moving bodies when the recognition information of the moving body includes recognition information of a third moving body; generating an intersecting avoidance trajectory for the third moving body when it is determined that the future trajectory of the third moving body and the intersecting avoidance trajectory for at least one of the first and second moving bodies will intersect; Further comprising: When the intersection avoidance trajectory for the third moving body is corrected, in the step of outputting the assistance display, an assistance display corresponding to the corrected intersection avoidance trajectory for the third moving body is output from the road surface lighting device. A method for supporting movement of a moving body, comprising:

3. 3. The method of claim 1 or 2, When the cross-avoidance trajectory is generated for at least one of the first and second moving bodies in the step of generating the cross-avoidance trajectory, the color of the support display for supporting the movement of the first and second moving bodies is different from that of the support display corresponding to the cross-avoidance trajectory for at least one of the first and second moving bodies in the step of outputting the support display. A method for supporting movement of a moving body, comprising:

4. 3. The method of claim 1 or 2, When the crossing avoidance trajectory is generated for both the first and second moving bodies in the step of generating the crossing avoidance trajectory, the color of the support display corresponding to the crossing avoidance trajectory for the first moving body is different from that of the support display corresponding to the crossing avoidance trajectory for the second moving body in the step of outputting the support display. A method for supporting movement of a moving body, comprising:

5. A system for supporting movement of a moving body, Infrastructure cameras installed around the road, a road surface lighting device that illuminates the road surface; a processor configured to perform various processes; Equipped with the processor: A process of recognizing a moving object included in an image of the infrastructure camera; A process of predicting a future trajectory of the moving object based on the recognition information of the moving object; a process of causing the road surface lighting device to output an assistance display for assisting the movement of the moving object based on the future trajectory; configured to: The processor further comprises: a process of determining whether the future trajectories of the moving bodies predicted in the process of predicting the future trajectories intersect with each other when the recognition information of the moving bodies includes recognition information of a first moving body and a second moving body; a process of generating an intersection avoidance trajectory for at least one of the first and second moving bodies when it is determined that the future trajectories of the first and second moving bodies will intersect; configured to: When the intersection avoidance trajectory is generated, in the process of causing the road surface lighting device to output the assistance indication, an assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device, The processor further comprises: a process of determining whether or not the future trajectory of the third moving body predicted in the process of predicting the future trajectory intersects with the intersection avoidance trajectory for at least one of the first and second moving bodies when the recognition information of the moving body includes recognition information of a third moving body; a process of correcting the intersection avoidance trajectory that intersects with the future trajectory of the third moving body when it is determined that the future trajectory of the third moving body and the intersection avoidance trajectory for at least one of the first and second moving bodies intersect; configured to: When the intersection avoidance trajectory that intersects with the future trajectory of the third moving body is corrected, in the process of outputting the assistance display, an assistance display corresponding to the corrected intersection avoidance trajectory is output from the road surface lighting device. A mobility support system for a mobile object.

6. A system for supporting the movement of a moving object, comprising: Infrastructure cameras installed around the road, a road surface lighting device that illuminates the road surface; a processor configured to perform various processes; Equipped with the processor: A process of recognizing a moving object included in an image of the infrastructure camera; A process of predicting a future trajectory of the moving object based on the recognition information of the moving object; a process of causing the road surface lighting device to output an assistance display for assisting the movement of the moving object based on the future trajectory; configured to: The processor further comprises: a process of determining whether the future trajectories of the moving bodies predicted in the process of predicting the future trajectories intersect with each other when the recognition information of the moving bodies includes recognition information of a first moving body and a second moving body; a process of generating an intersection avoidance trajectory for at least one of the first and second moving bodies when it is determined that the future trajectories of the first and second moving bodies will intersect; configured to: When the intersection avoidance trajectory is generated, in the process of causing the road surface lighting device to output the assistance indication, an assistance indication corresponding to the intersection avoidance trajectory is output from the road surface lighting device, The processor further comprises: a process of determining whether or not the future trajectory of the third moving body predicted in the process of predicting the future trajectory intersects with the intersection avoidance trajectory for at least one of the first and second moving bodies when the recognition information of the moving body includes recognition information of a third moving body; a process of generating an intersection avoidance trajectory for the third moving body when it is determined that the future trajectory of the third moving body and the intersection avoidance trajectory for at least one of the first and second moving bodies will intersect; configured to: When the intersection avoidance trajectory for the third moving body is corrected, in the process of outputting the assistance display, an assistance display corresponding to the corrected intersection avoidance trajectory for the third moving body is output from the road surface lighting device. A mobility support system for a mobile object.

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