Traffic light control system, traffic light control device, traffic light control method, and program

Abstract

The purpose of the present invention is to enable support of safe travel of a mobile robot on a road. This traffic light control device comprises: a hindrance state determination unit that determines whether or not there is a hindrance to the travel of a mobile robot traversing a road; and a traffic light control unit that controls a traffic light installed on a road in accordance with whether or not it is determined that a hindrance has occurred in the travel of the mobile robot.

Description

Traffic light control system, traffic light control device, traffic light control method, and program

[0001] The present disclosure relates to a traffic light control system, a traffic light control device, a traffic light control method, and a program.

[0002] As a related technique, Patent Document 1 discloses a traffic control system. In the traffic control system described in Patent Document 1, a camera is attached to a traffic light post. A traffic light control device acquires images from the camera. The control device detects pedestrians and vehicles by analyzing the images.

[0003] The control device detects the walking speed of a pedestrian moving on the sidewalk or crosswalk. If the pedestrian's walking speed is slower than a predetermined speed, the control device keeps the corresponding traffic light green until the pedestrian completely crosses the crosswalk. In this way, if the pedestrian is a small child or elderly person who walks slowly, the green light can be extended until the pedestrian completely crosses the crosswalk, thereby ensuring the safety of the pedestrian.

[0004] Japanese Patent Application Laid-Open No. 2019-036147

[0005] In recent years, technological development has progressed toward the social implementation of autonomous delivery robots. In Japan, robots that meet certain size and structural requirements are able to travel on public roads, and the social implementation of autonomous delivery robots is gaining momentum. Autonomous delivery robots use onboard cameras and sensors to detect obstacles and navigate around them automatically.

[0006] The movement speed of mobile robots such as the above-mentioned automatic delivery robots on crosswalks is thought to change depending on the surrounding environment, such as the level of congestion, the presence or absence of obstacles, etc. Patent Document 1 describes extending the green light for pedestrians walking slowly, but there may be cases in which simply determining whether the movement speed is slow is insufficient to ensure the safety of the mobile robot.

[0007] One object of the present disclosure is to provide a traffic light control system, a traffic light control device, a traffic light control method, and a program that can support the safe travel of a mobile robot on a road.

[0008] A traffic light control device according to a first aspect of the present disclosure includes an obstruction state determination unit that determines whether or not there is an obstruction to the movement of a mobile robot crossing a road, and a traffic light control unit that controls a traffic light installed on the road depending on whether or not it is determined that there is an obstruction to the movement of the mobile robot.

[0009] A traffic light control system according to a second aspect of the present disclosure includes a traffic light installed on a road that a mobile robot crosses, and the traffic light control device.

[0010] A traffic light control method according to a third aspect of the present disclosure includes determining whether or not there is an obstruction to the movement of a mobile robot crossing a road, and controlling a traffic light installed on the road depending on whether or not it is determined that there is an obstruction to the movement of the mobile robot.

[0011] A program according to a fourth aspect of the present disclosure causes a computer to execute processing including determining whether or not there is an obstruction to the movement of a mobile robot crossing a road, and controlling traffic lights installed on the road depending on whether or not it is determined that there is an obstruction to the movement of the mobile robot.

[0012] The traffic light control system, traffic light control device, traffic light control method, and program according to the present disclosure can support the safe travel of mobile robots on roads.

[0013] Fig. 1 is a block diagram showing a schematic configuration example of a traffic light control system according to the present disclosure. Fig. 2 is a block diagram showing a configuration example of a traffic light control system according to the present disclosure. Fig. 3 is a schematic diagram showing an example of an intersection where a mobile robot crosses. Fig. 4 is a flowchart showing an operation procedure of a traffic light control device. Fig. 5 is a block diagram showing an example of the hardware configuration of an electronic control device.

[0014] Prior to describing embodiments of the present disclosure, an overview of the present disclosure will be described. Fig. 1 is a block diagram showing a schematic configuration example of a traffic light control system according to the present disclosure. The traffic light control system 10 includes a traffic light control device 20 and a traffic light 30. The traffic light control device 20 includes an obstacle state determination unit 21 and a traffic light control unit 22.

[0015] The obstacle state determination unit 21 determines whether or not there is an obstacle to the travel of the mobile robot crossing a road such as an intersection. The traffic light control unit 22 controls the traffic light 30 installed at the intersection depending on whether or not it is determined that there is an obstacle to the travel of the mobile robot. For example, when it is determined that there is an obstacle to the travel of the mobile robot, the traffic light control unit 22 extends the period of time that the green light of the traffic light 30 in the direction the mobile robot is crossing the intersection compared to when it is determined that there is no obstacle to the travel of the mobile robot.

[0016] In the present disclosure, the traffic light control device 20 controls the traffic light 30 depending on whether or not there is an obstacle to the traveling of the mobile robot on a road, such as an intersection. As an example, if there is an obstacle to the traveling of the mobile robot at an intersection, the traffic light control device 20 extends the green light period of the traffic light 30 longer than usual. In this way, the traffic light control system according to the present disclosure can support the safe traveling of the mobile robot on the road.

[0017] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the following description and drawings have been omitted and simplified as appropriate for clarity of explanation. In addition, in the following drawings, the same or similar elements are designated by the same reference numerals, and duplicate explanations are omitted as necessary.

[0018] Fig. 2 is a block diagram showing an example configuration of a traffic light control system according to the present disclosure. One embodiment of the present disclosure will be described using Fig. 2. The traffic light control system 100 shown in Fig. 2 includes a traffic light control device 101, a traffic light 200, and a camera 210. In this embodiment, the traffic light control system 100 is used to support the safe travel of a mobile robot 220. The traffic light control system 100 corresponds to the traffic light control system 10 shown in Fig. 1.

[0019] In this embodiment, the mobile robot 220 is equipped with sensors such as a camera, radar, or LiDAR (Light Detection and Ranging), and an electronic control device. The sensors and electronic control device equipped on the mobile robot 220 enable the mobile robot 220 to travel autonomously.

[0020] The mobile robot 220 can travel on a sidewalk at, for example, a speed equivalent to a human walking speed. The mobile robot 220 may be configured as, for example, a delivery robot that delivers packages. The mobile robot 220 may also be configured as a security robot used for security purposes. The mobile robot 220 stores three-dimensional high-precision map information. The mobile robot 220 is assumed to be able to recognize intersections, the positions of traffic lights, and the boundaries between sidewalks and roadways using the three-dimensional high-precision map information.

[0021] The traffic light 200 is a traffic light installed on a road that the mobile robot 220 crosses. The traffic light 200 includes a traffic light for pedestrians. The mobile robot 220 acquires the light status of the traffic light 200 as traffic light information, for example, before an intersection or a crosswalk. For example, the mobile robot 220 analyzes an image from a camera mounted on the mobile robot 220 to acquire the light status of the traffic light 200. If the traffic light 200 is green, the mobile robot 220 enters the intersection or crosswalk. If the traffic light 200 is red, the mobile robot 220 waits in front of the intersection until the traffic light 200 turns green. The traffic light 200 corresponds to the traffic light 30 shown in FIG. 1 .

[0022] The camera 210 is installed on a road and captures an image of the location on the road where the mobile robot 220 is traveling. The camera 210 acquires an image of a crosswalk, for example. When the mobile robot 220 is crossing a road, the camera 210 acquires an image of the mobile robot 220 traveling on the crosswalk. The camera 210 may be installed on a traffic light pole of the traffic light 200. The number of cameras 210 at one intersection is not limited to one. Multiple cameras 210 may be installed at one intersection.

[0023] The traffic light controller 101 has an obstruction state determination unit 111 and a traffic light control unit 112. The traffic light controller 101 can be physically configured as a device having one or more memories and one or more processors. At least a portion of the functions of each unit in the traffic light controller 101 can be realized by one or more processors performing processing in accordance with instructions read from one or more memories. The traffic light controller 101 corresponds to the traffic light controller 20 shown in FIG. 1.

[0024] The obstacle state determination unit 111 acquires the state information of the mobile robot 220 and determines whether or not there is an obstacle to the traveling of the mobile robot 220 crossing a road. Here, a situation where there is an obstacle to the traveling of the mobile robot 220 means a situation where the mobile robot 220 cannot travel at a normal traveling speed due to an external or internal factor. Possible external factors include a person or an obstacle on the road. Possible internal factors include a failure of a sensor or device mounted on the mobile robot 220.

[0025] The obstacle state determination unit 111 determines, for example, whether the mobile robot 220 is in a state where it cannot move while crossing a road. The obstacle state determination unit 111 determines, for example, whether there is an extremely large number of people at a crosswalk, making it difficult for the mobile robot 220 to move. If the obstacle state determination unit 111 determines that the mobile robot 220 is in a state where it cannot move, it determines that an obstacle is occurring to the movement of the mobile robot 220.

[0026] The obstacle state determination unit 111 may determine whether an obstacle has occurred in the mobile robot 220. If an obstacle has occurred in the mobile robot 220, the mobile robot 220 cannot travel at a normal traveling speed and can only travel at a low speed in a safe mode. If the obstacle state determination unit 111 determines that an obstacle has occurred in the mobile robot 220, it determines that an obstacle has occurred in the traveling of the mobile robot 220.

[0027] The obstacle state determination unit 111 may acquire state information of the mobile robot 220 from an image captured by the camera 210. The obstacle state determination unit 111 acquires an image from the camera 210, for example, and performs image analysis on the acquired image. In the image analysis, the obstacle state determination unit 111 analyzes whether the mobile robot 220 is surrounded by people while crossing a road. The obstacle state determination unit 111 also analyzes whether the movement speed of the mobile robot 220 has extremely decreased. If the mobile robot 220 is surrounded by people while crossing a road and the movement speed of the mobile robot 220 is equal to or lower than a predetermined speed, the obstacle state determination unit 111 may determine that an obstacle is occurring to the travel of the mobile robot 220.

[0028] Alternatively or in addition to the above, the obstacle state determination unit 111 may acquire status information from the mobile robot 220 and use the acquired status information to determine whether or not an obstacle is occurring in the traveling of the mobile robot 220. The mobile robot 220, for example, performs a self-diagnosis of sensors and devices mounted thereon. If an abnormality is found in a sensor or device as a result of the self-diagnosis, the mobile robot 220 transmits a signal reporting the abnormality in the sensor or device to the traffic light control device 101. If the status information acquired from the mobile robot 220 indicates an abnormality, the obstacle state determination unit 111 may determine that an obstacle is occurring in the traveling of the mobile robot 220. The obstacle state determination unit 111 corresponds to the obstacle state determination unit 21 shown in FIG. 1 .

[0029] The traffic light control unit 112 controls the traffic lights 200 installed on the road depending on whether the obstruction state determination unit 111 determines that an obstruction is occurring to the travel of the mobile robot 220. When it determines that an obstruction is occurring to the travel of the mobile robot 220, the traffic light control unit 112 extends the green light period of the traffic light in the direction that the mobile robot 220 is crossing at the intersection compared to the normal period.

[0030] The traffic light control unit 112 may determine whether the mobile robot 220 can cross the road before the traffic light 200 next switches to red. The traffic light control unit 112 calculates, for example, a crossing time, which is the time required for the mobile robot 220 to cross an intersection. The crossing time can be calculated based on the traveling speed of the mobile robot 220 and the distance of the road to be crossed.

[0031] The traffic light control unit 112 compares the calculated crossing time with the remaining time until the traffic light 200 turns red, and determines whether the mobile robot 220 can cross the road before the traffic light 200 turns red. If the traffic light control unit 112 determines that the mobile robot 220 cannot cross the road before the traffic light 200 turns red, it may extend the green light period. The traffic light control unit 112 corresponds to the traffic light control unit 22 shown in FIG. 1.

[0032] 3 is a schematic diagram showing an example of an intersection where a mobile robot 220 crosses. The mobile robot 220 stops temporarily before a crosswalk. When the traffic light 200 is green, the mobile robot 220 starts crossing the crosswalk. The mobile robot 220 uses sensor information from the sensor 103, such as a camera or LiDAR, to autonomously cross the crosswalk while avoiding pedestrians and obstacles.

[0033] The camera 210 captures images of the mobile robot 220 traveling on the crosswalk and the surrounding area. The obstacle state determination unit 111 performs image analysis on the image from the camera 210 and determines whether or not an obstacle is occurring to the traveling of the mobile robot 220. The traffic light control unit 112 extends the green light period of the traffic light 200 when it is determined that an obstacle is occurring to the traveling of the mobile robot 220. This reduces the possibility that the mobile robot 220 will be left behind on the crosswalk after the traffic light 200 changes to red.

[0034] Next, the operation procedure will be explained. Fig. 4 is a flowchart showing the operation procedure of the traffic light control device 101. The operation procedure of the traffic light control device 101 corresponds to a traffic light control method. The obstruction state determination unit 111 determines whether or not there is an obstruction to the movement of the mobile robot 220 crossing the road (step S1). If it is determined in step S1 that there is an obstruction to the movement of the mobile robot 220, the traffic light control unit 112 extends the green light period of the traffic light 200 (step S2). If it is determined in step S1 that there is no obstruction to the movement of the mobile robot 220, the traffic light control unit 112 controls the traffic light 200 in a normal aspect cycle.

[0035] In this embodiment, the obstacle state determination unit 111 determines whether or not there is an obstacle to the movement of the mobile robot 220 traveling on a road, such as a crosswalk. The traffic light control unit 112 controls the traffic light 200 depending on whether or not there is an obstacle to the movement of the mobile robot 220. For example, if the traffic light control unit 112 determines that there is an obstacle to the movement of the mobile robot 220, it extends the period of the green light of the traffic light 200. In this way, the traffic light control device 101 can reduce the possibility that the traffic light 200 will change to red before the mobile robot 220 finishes crossing the road. Therefore, the traffic light control device 101 can support the safe movement of the mobile robot on the road.

[0036] Next, the hardware configuration of the traffic light controller 101 will be described. The traffic light controller 101 can be configured as an electronic controller or a computer device. FIG. 5 is a block diagram showing an example of the hardware configuration of an electronic controller that can be used as the traffic light controller 101. The electronic controller 500 has a processor 501 such as a CPU (Central Processing Unit), a ROM (Read Only Memory) 502, and a RAM (Random Access Memory) 503. In the electronic controller 500, the processor 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. Although not shown, the electronic controller 500 can include other circuits such as peripheral circuits, communication circuits, and interface circuits.

[0037] The ROM 502 is a non-volatile storage device. For example, a semiconductor storage device with a relatively small capacity, such as a flash memory, is used as the ROM 502. The ROM 502 stores the programs executed by the processor 501.

[0038] The program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable media or tangible storage media include RAM, ROM, flash memory, SSD or other memory technologies, Compact Disc (CD), digital versatile disc (DVD), Blu-ray (registered trademark) disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.

[0039] The RAM 503 is a volatile storage device. Various semiconductor memory devices such as a dynamic random access memory (DRAM) or a static random access memory (SRAM) are used for the RAM 503. The RAM 503 can be used as an internal buffer for temporarily storing data and the like.

[0040] The processor 501 loads a program stored in the ROM 502 into the RAM 503 and executes the program. When the CPU 501 executes the program, at least some of the functions of each unit in the signal control device 101 can be realized.

[0041] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure.

[0042] Each drawing is merely an example for describing one or more embodiments. Each drawing may not relate to only one particular embodiment, but may also relate to one or more other embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings to create, for example, an embodiment not explicitly shown or described. Not all features or steps shown in any one drawing are necessary to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0043] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0044] [Supplementary Note 1] A traffic light control device comprising: an obstacle state determination unit that determines whether or not there is an obstacle to the movement of a mobile robot crossing a road; and a traffic light control unit that controls a traffic light installed on the road depending on whether or not it is determined that there is an obstacle to the movement of the mobile robot.

[0045] [Appendix 2] The traffic light control device described in Appendix 1, wherein, when it is determined that there is an obstruction to the movement of the mobile robot, the traffic light control unit extends the period of the green light of the traffic light in the direction the mobile robot is crossing the road compared to when it is determined that there is no obstruction to the movement of the mobile robot.

[0046] [Supplementary Note 3] The traffic light control device according to Supplementary Note 1 or 2, wherein the obstruction state determination unit determines that an obstruction is occurring to the travel of the mobile robot when the mobile robot is unable to move while crossing the road.

[0047] [Appendix 4] The traffic light control device described in any one of Appendices 1 to 3, wherein the obstruction state determination unit performs image analysis on an image taken of the mobile robot on the road, and determines whether or not there is an obstruction to the travel of the mobile robot based on the results of the image analysis.

[0048] [Appendix 5] The traffic light control device according to Appendix 4, wherein the obstacle state determination unit analyzes, in the image analysis, whether the mobile robot is surrounded by people while crossing the road, and the moving speed of the mobile robot.

[0049] [Appendix 6] The traffic light control device according to Appendix 5, wherein the obstruction state determination unit determines that an obstruction is occurring to the movement of the mobile robot when the mobile robot is surrounded by people while crossing the road and the movement speed of the mobile robot is equal to or less than a predetermined speed.

[0050] [Supplementary Note 7] The traffic light control device according to any one of Supplementary Notes 4 to 6, wherein the image is captured by an imaging device installed on the road.

[0051] [Appendix 8] A traffic light control device as described in any one of Appendices 1 to 7, wherein the obstacle state determination unit determines whether or not an obstacle has occurred in the mobile robot, and if it determines that an obstacle has occurred in the mobile robot, determines that an obstacle has occurred in the mobile robot's movement.

[0052] [Appendix 9] The traffic light control device described in any one of Appendices 1 to 8, wherein the obstruction state determination unit acquires state information from the mobile robot and determines whether or not an obstruction is occurring to the traveling of the mobile robot using the acquired state information.

[0053] [Supplementary Note 10] A traffic light control system comprising: a traffic light installed on a road that a mobile robot crosses; and the traffic light control device according to any one of Supplementary Notes 1 to 9.

[0054] [Supplementary Note 11] A traffic light control method comprising: determining whether or not there is an obstacle to the movement of a mobile robot crossing a road; and controlling a traffic light installed on the road depending on whether or not it is determined that there is an obstacle to the movement of the mobile robot.

[0055] [Appendix 12] The traffic light control method described in Appendix 11, wherein, when it is determined that there is an obstruction to the travel of the mobile robot, the period of the green light of the traffic light in the direction in which the mobile robot is crossing the road is extended compared to when it is determined that there is no obstruction to the travel of the mobile robot.

[0056] [Supplementary Note 13] The traffic light control method according to Supplementary Note 11 or 12, wherein if the mobile robot is unable to move while crossing the road, it is determined that an obstacle is occurring to the travel of the mobile robot.

[0057] [Appendix 14] A traffic light control method according to any one of Appendices 11 to 13, comprising performing image analysis on an image of the mobile robot taken on the road, and determining whether or not there is an obstruction to the travel of the mobile robot based on the results of the image analysis.

[0058] [Supplementary Note 15] The traffic light control method according to Supplementary Note 14, wherein the image analysis includes analyzing whether the mobile robot is surrounded by people while crossing the road, and the moving speed of the mobile robot.

[0059] [Appendix 16] The traffic light control method described in Appendix 15, wherein if the mobile robot is surrounded by people while crossing the road and the moving speed of the mobile robot is below a predetermined speed, it is determined that an obstruction to the movement of the mobile robot is occurring.

[0060] [Supplementary Note 17] The traffic light control method according to any one of Supplementary Notes 14 to 16, wherein the image is captured by an imaging device installed on the road.

[0061] [Appendix 18] A traffic light control method as described in any one of Appendices 11 to 17, which determines whether or not an obstacle has occurred in the mobile robot, and if it is determined that an obstacle has occurred in the mobile robot, determines that there is an obstruction to the mobile robot's travel.

[0062] [Supplementary Note 19] A traffic light control method as described in any one of Supplementary Notes 11 to 18, which acquires status information from the mobile robot and uses the acquired status information to determine whether or not there is an obstruction to the traveling of the mobile robot.

[0063] [Supplementary Note 20] A program that causes a computer to execute a process including determining whether or not there is an obstacle to the movement of a mobile robot crossing a road, and controlling a traffic light installed on the road depending on whether or not it is determined that there is an obstacle to the movement of the mobile robot.

[0064] [Appendix 21] The program described in Appendix 20, wherein, when it is determined that there is an obstruction to the movement of the mobile robot, the period of time for which the green light of a traffic light in the direction in which the mobile robot is crossing the road is extended compared to when it is determined that there is no obstruction to the movement of the mobile robot.

[0065] [Supplementary Note 22] The program according to Supplementary Note 20 or 21, which determines that an obstacle is occurring to the traveling of the mobile robot when the mobile robot is unable to move while crossing the road.

[0066] [Supplementary Note 23] The program described in any one of Supplementary Notes 20 to 22, which performs image analysis on an image taken of the mobile robot on the road, and determines whether or not there is an obstruction to the movement of the mobile robot based on the results of the image analysis.

[0067] [Supplementary Note 24] The program according to Supplementary Note 23, wherein the image analysis includes analyzing whether the mobile robot is surrounded by people while crossing the road, and analyzing the moving speed of the mobile robot.

[0068] [Supplementary Note 25] The program according to Supplementary Note 24, which determines that an obstacle is occurring to the movement of the mobile robot when the mobile robot is surrounded by people while crossing the road and the movement speed of the mobile robot is below a predetermined speed.

[0069] [Supplementary Note 26] The program according to any one of Supplementary Notes 23 to 25, wherein the image is captured by an imaging device installed on the road.

[0070] [Appendix 27] A program described in any one of Appendices 20 to 26, which determines whether an obstacle has occurred in the mobile robot, and if it is determined that an obstacle has occurred in the mobile robot, determines that there is an obstacle to the mobile robot's movement.

[0071] [Supplementary Note 28] The program according to any one of Supplementary Notes 20 to 27, which acquires status information from the mobile robot and uses the acquired status information to determine whether or not there is an obstruction to the running of the mobile robot.

[0072] 10: Traffic light control system 20: Traffic light control device 21: Obstruction state determination unit 22: Traffic light control unit 30: Traffic light 100: Traffic light control system 101: Traffic light control device 111: Obstruction state determination unit 112: Traffic light control unit 200: Traffic light 210: Camera 220: Mobile robot

Claims

1. A traffic light control device comprising: an obstacle state determination unit that determines whether or not there is an obstacle to the movement of a mobile robot crossing a road; and a traffic light control unit that controls traffic lights installed on the road depending on whether or not it is determined that there is an obstacle to the movement of the mobile robot.

2. A traffic light control device as described in claim 1, wherein, when it is determined that there is an obstruction to the movement of the mobile robot, the traffic light control unit extends the period of time for which the green light is on at a traffic light in the direction in which the mobile robot is crossing the road compared to when it is determined that there is no obstruction to the movement of the mobile robot.

3. A traffic light control device as described in claim 1 or 2, wherein the obstruction state judgment unit judges that an obstruction has occurred to the movement of the mobile robot when the mobile robot is unable to move while crossing the road.

4. A traffic light control device as described in any one of claims 1 to 3, wherein the obstruction state judgment unit performs image analysis on images taken of the mobile robot on the road and judges whether or not there is an obstruction to the movement of the mobile robot based on the results of the image analysis.

5. A traffic light control device as described in claim 4, wherein the obstacle state determination unit analyzes, in the image analysis, whether the mobile robot is surrounded by people while crossing the road, and the moving speed of the mobile robot.

6. A traffic light control device as described in claim 5, wherein the obstruction state judgment unit judges that an obstruction is occurring to the movement of the mobile robot when the mobile robot is surrounded by people while crossing the road and the moving speed of the mobile robot is below a predetermined speed.

7. A traffic light control device according to any one of claims 4 to 6, wherein the image is captured by an imaging device installed on the road.

8. A traffic light control device as described in any one of claims 1 to 7, wherein the obstruction state determination unit determines whether or not an obstruction has occurred in the mobile robot, and if it determines that an obstruction has occurred in the mobile robot, determines that an obstruction has occurred in the movement of the mobile robot.

9. A traffic light control device as described in any one of claims 1 to 8, wherein the obstruction state judgment unit acquires status information from the mobile robot and uses the acquired status information to judge whether or not an obstruction is occurring to the movement of the mobile robot.

10. A traffic light control system comprising: a traffic light installed on a road crossed by a mobile robot; and a traffic light control device according to any one of claims 1 to 9.

11. A traffic light control method comprising: determining whether or not there is an obstruction to the movement of a mobile robot crossing a road; and controlling a traffic light installed on the road depending on whether or not it is determined that there is an obstruction to the movement of the mobile robot.

12. A traffic light control method as described in claim 11, wherein, when it is determined that there is an obstruction to the travel of the mobile robot, the period of time for which the green light of the traffic light in the direction in which the mobile robot is crossing the road is extended compared to when it is determined that there is no obstruction to the travel of the mobile robot.

13. A traffic light control method as described in claim 11 or 12, wherein if the mobile robot is unable to move while crossing the road, it is determined that an obstacle is occurring to the mobile robot's travel.

14. A traffic light control method as claimed in any one of claims 11 to 13, which performs image analysis on an image taken of the mobile robot on the road, and determines whether or not there is an obstruction to the movement of the mobile robot based on the results of the image analysis.

15. A traffic light control method as described in claim 14, wherein the image analysis includes analyzing whether the mobile robot is surrounded by people while crossing the road, and the moving speed of the mobile robot.

16. A traffic light control method as described in claim 15, wherein if the mobile robot is surrounded by people while crossing the road and the moving speed of the mobile robot is below a predetermined speed, it is determined that an obstruction to the movement of the mobile robot has occurred.

17. A traffic light control method according to any one of claims 14 to 16, wherein the image is captured by an imaging device installed on the road.

18. A traffic light control method as claimed in any one of claims 11 to 17, which determines whether or not an obstacle has occurred in the mobile robot, and if it is determined that an obstacle has occurred in the mobile robot, determines that there is an obstruction to the movement of the mobile robot.

19. A traffic light control method as claimed in any one of claims 11 to 18, which acquires status information from the mobile robot and uses the acquired status information to determine whether or not there is an obstruction to the movement of the mobile robot.

20. A program that causes a computer to execute a process that includes determining whether or not there is an obstacle to the movement of a mobile robot crossing a road, and controlling traffic lights installed on the road depending on whether or not it is determined that there is an obstacle to the movement of the mobile robot.

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