Mobile robot, travel control device, travel control method, and program

Abstract

The present invention makes it possible to more correctly determine whether or not a mobile robot can cross a road. This travel control device includes: a traffic light information acquisition unit that acquires traffic light information of a traffic light; a situation acquisition unit that acquires situation information of a place where the mobile robot travels when crossing the road; a crossing time calculation unit that calculates, by using the situation information, a crossing time required for the mobile robot to cross the road; a crossing possibility determination unit that compares a remaining time until the traffic light changes to a red signal with the calculated crossing time, and determines, on the basis of a result of the comparison, whether or not the mobile robot can cross the road by a time when the traffic light changes to the red signal; and a travel control unit that causes the mobile robot to start crossing the road when the crossing possibility determination unit determines that the crossing is possible.

Description

Mobile robot, travel control device, travel control method, and program

[0001] The present disclosure relates to a mobile robot, a driving control device, a driving control method, and a program.

[0002] As a related technique, Patent Document 1 discloses an automated driving device such as a delivery robot. The automated driving device described in Patent Document 1 is a vehicle that travels on sidewalks at a maximum speed of about a brisk walk, specifically about 6 km / h. The automated driving device is equipped with a camera and a sensor. The automated driving device detects obstacles and pedestrians using the camera and the sensor, and travels on the sidewalk while avoiding the obstacles and pedestrians.

[0003] When an automated driving device travels across a pedestrian crossing, it stops at the crosswalk and transmits a crossing determination request to the pedestrian traffic light. The pedestrian traffic light calculates the time required for the automated driving device to cross the crosswalk based on the traveling speed of the automated driving device, and determines whether or not it is possible to cross based on the calculated time and the remaining time until the green light is on. If the pedestrian traffic light determines that it is possible to cross, the automated driving device travels across the crosswalk. If the pedestrian traffic light determines that it is not possible to cross, the automated driving device continues to stop even if the pedestrian traffic light is green.

[0004] Japanese Patent Application Laid-Open No. 2023-039657

[0005] The traveling speed of an automated driving device may change depending on the situation at the crosswalk. For example, if there are many pedestrians on the crosswalk, the traveling speed of the automated driving device may be slower than when there are few pedestrians. Furthermore, if there are obstacles such as vehicles extending onto the crosswalk or fallen objects, the traveling speed of the automated driving device may be slower than when there are no obstacles. In Patent Document 1, the pedestrian traffic light does not take into account changes in traveling speed depending on the situation. As a result, the pedestrian traffic light described in Patent Document 1 may not correctly determine whether the automated driving device can cross the crosswalk.

[0006] One of the objectives of the present disclosure is to provide a mobile robot, a driving assistance device, a driving assistance method, and a program that can more accurately determine whether the mobile robot can cross a road before the traffic light switches to red.

[0007] A driving control device according to a first aspect of the present disclosure includes a traffic light information acquisition unit that acquires traffic light information for traffic lights installed on a road that a mobile robot is to cross; a situation acquisition unit that acquires situation information for a location where the mobile robot will travel when crossing the road; a crossing time calculation unit that uses the situation information to calculate the crossing time required for the mobile robot to cross the road; a crossing feasibility determination unit that compares the remaining time until the traffic light changes to red with the calculated crossing time and determines, based on the result of the comparison, whether the mobile robot will be able to cross the road by the time the traffic light changes to red; and a driving control unit that causes the mobile robot to start crossing the road if the crossing feasibility determination unit determines that the mobile robot is able to cross.

[0008] A mobile robot according to a second aspect of the present disclosure includes a drive unit that drives the mobile robot, a sensor that monitors the surroundings of the mobile robot, and the above-mentioned travel control device.

[0009] A driving control method according to a third aspect of the present disclosure includes acquiring traffic light information for traffic lights installed on a road that a mobile robot is to cross, acquiring situation information for a location where the mobile robot will travel when crossing the road, calculating a crossing time required for the mobile robot to cross the road using the situation information, comparing the time remaining until the traffic light turns red with the calculated crossing time, determining based on the result of the comparison whether the mobile robot can cross the road by the time the traffic light turns red, and if it is determined that the mobile robot can cross the road, causing the mobile robot to start crossing the road.

[0010] A program according to a fourth aspect of the present disclosure causes a computer to perform processing including acquiring traffic light information for traffic lights installed on a road that a mobile robot will cross, acquiring situation information for a location where the mobile robot will travel when crossing the road, calculating the crossing time required for the mobile robot to cross the road using the situation information, comparing the time remaining until the traffic light turns red with the calculated crossing time, determining based on the result of the comparison whether the mobile robot will be able to cross the road by the time the traffic light turns red, and if it is determined that the mobile robot can cross the road, having the mobile robot start crossing the road.

[0011] The mobile robot, driving assistance device, driving assistance method, and program according to the present disclosure can more accurately determine whether the mobile robot can cross the road before the traffic light changes to red.

[0012] Fig. 1 is a block diagram showing an example of the configuration of a mobile robot according to the present disclosure; Fig. 2 is a block diagram showing an example of the configuration of a driving control device; Fig. 3 is a schematic diagram showing an example of an intersection that a mobile robot crosses; Fig. 4 is a flowchart showing the operation procedure of the driving control device; Fig. 5 is a block diagram showing an example of the hardware configuration of an electronic control device;

[0013] 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.

[0014] Fig. 1 is a block diagram showing an example configuration of a mobile robot according to the present disclosure. One embodiment of the present disclosure will be described using Fig. 1. The mobile robot 100 shown in Fig. 1 includes a drive unit 101, a travel control device 102, and a sensor 103.

[0015] In this embodiment, the mobile robot 100 is configured to be capable of autonomous travel. The mobile robot 100 can travel on a sidewalk, for example, at a speed equivalent to a human walking speed. The mobile robot 100 may be configured, for example, as a delivery robot that delivers packages. The mobile robot 100 may also be configured as a security robot used for security purposes. The mobile robot 100 stores high-precision three-dimensional map information, and is capable of recognizing intersections, the locations of traffic lights, and the boundaries between sidewalks and roadways.

[0016] The driving unit 101 drives the mobile robot 100. The driving unit 101 includes, for example, wheels and a motor. The driving control device 102 controls the driving of the mobile robot. The sensor 103 is a surrounding monitoring sensor that monitors the surrounding conditions of the mobile robot 100. The sensor 103 includes, for example, a camera, radar, or LiDAR (Light Detection and Ranging). The sensor 103 may include, for example, multiple cameras that capture images of the front, rear, right, and left sides of the vehicle. In addition to the components shown in FIG. 1 , the mobile robot 100 may also have an energy source such as a battery.

[0017] 2 is a block diagram showing an example configuration of the driving control device 102. The driving control device 102 has a traffic light information acquisition unit 121, a situation acquisition unit 122, a crossing time calculation unit 123, a crossing possibility determination unit 124, and a driving control unit 125. The driving control device 102 can be physically configured as a device having one or more memories and one or more processors. At least a part of the function of each unit in the driving control device 102 can be realized by one or more processors performing processing in accordance with instructions read from one or more memories.

[0018] The traffic light information acquisition unit 121 acquires traffic light information for traffic lights installed on roads such as intersections that the mobile robot 100 crosses. In this embodiment, the traffic light information acquisition unit 121 acquires the light status of traffic lights present in the traveling direction of the mobile robot 100 as traffic light information. The traffic light information acquisition unit 105 particularly acquires the light status of pedestrian traffic lights. The traffic light information acquisition unit 105 may acquire the light status of traffic lights from roadside facilities such as traffic lights using, for example, road-to-vehicle communication. Alternatively, the traffic light information acquisition unit 105 may acquire the light status of traffic lights by analyzing video from a camera that captures the area ahead of the vehicle.

[0019] The situation acquisition unit 122 acquires situation information of a location where the mobile robot 100 travels when crossing an intersection. The situation acquisition unit 122 acquires situation information of a location where the mobile robot 100 travels, such as a crosswalk, using, for example, sensor information from the sensor 103. For example, the situation acquisition unit 122 performs image analysis on an image acquired using the sensor 103 to acquire situation information.

[0020] The situation acquisition unit 122 acquires, for example, the congestion status of an intersection as situation information. For example, the situation acquisition unit 122 detects the number of people crossing the intersection. For example, the situation acquisition unit 122 detects the number of people crossing the intersection by analyzing an image acquired using the sensor 103. The situation acquisition unit 122 determines the congestion status of the intersection or crosswalk according to the number of people crossing the intersection. The congestion status can be indicated using congestion levels such as "very congested," "congested," and "not congested."

[0021] The situation acquisition unit 122 may acquire, as situation information, the presence or absence of an obstacle at a location where the mobile robot 100 travels when crossing an intersection. The situation acquisition unit 122 analyzes, for example, an image acquired using the sensor 103. If there is a vehicle parked on the crosswalk, the situation acquisition unit 122 detects the vehicle on the crosswalk as an obstacle. If there is an object fallen on the crosswalk, the situation acquisition unit 122 detects the object as an obstacle.

[0022] The crossing time calculation unit 123 calculates the time required for the mobile robot 100 to cross an intersection using the situation information acquired by the situation acquisition unit 122. The crossing time calculation unit 123 estimates the traveling speed of the mobile robot 100 according to the acquired situation information, for example. For example, when there are many people on the crosswalk and the crosswalk is crowded, the crossing time calculation unit 123 estimates a speed lower than the normal traveling speed as the traveling speed of the mobile robot 100. When there is an obstacle on the crosswalk, the crossing time calculation unit 123 estimates a speed lower than the normal traveling speed as the traveling speed of the mobile robot 100.

[0023] The crossing time calculation unit 123 calculates the time required for the mobile robot 100 to pass through the intersection, i.e., the crossing time, based on the estimated traveling speed and the length of the crosswalk. The crossing time calculation unit 123 may obtain the length of the crosswalk from, for example, high-precision map information stored in the mobile robot 100. Alternatively, the crossing time calculation unit 123 may obtain the length of the crosswalk from an image taken by a camera mounted on the mobile robot 100.

[0024] When the traffic light is green, the crossing possibility determination unit 124 compares the time remaining until the traffic light changes to red with the crossing time calculated by the crossing time calculation unit 123. Based on the result of the comparison, the crossing possibility determination unit 124 determines whether the mobile robot can cross the intersection by the time the traffic light changes to red. The traffic light installed at the intersection may notify the mobile robot 100 of the next time the traffic light will change to red. In that case, the crossing possibility determination unit 124 may calculate the time remaining until the traffic light changes to red using information acquired from the traffic light. The crossing possibility determination unit 124 determines that crossing is not possible if the time obtained by adding a predetermined margin to the crossing time is shorter than the remaining time.

[0025] The travel control unit 125 controls the travel of the mobile robot 100. If the crossing possibility determination unit 124 determines that crossing is possible, the travel control unit 125 causes the mobile robot 100 to start crossing the road. If the crossing possibility determination unit 124 determines that crossing is not possible, the travel control unit 125 causes the mobile robot 100 to stop in front of the road.

[0026] 3 is a schematic diagram showing an example of an intersection where the mobile robot 100 crosses. Here, it is assumed that the pedestrian traffic light 200 is green when the mobile robot 100 reaches the crosswalk. The driving control unit 125 causes the mobile robot 100 to temporarily stop just before the crosswalk. If the crossing possibility determination unit 124 determines that crossing is possible, the driving control unit 125 resumes the movement of the mobile robot 100 and causes the mobile robot to cross the crosswalk. In this case, the mobile robot 100 uses sensor information from the sensor 103, such as a camera or LiDAR, to autonomously cross the crosswalk while avoiding pedestrians and obstacles.

[0027] If the crossing possibility determination unit 124 determines that the mobile robot 100 is not allowed to cross the crosswalk, the driving control unit 125 keeps the mobile robot 100 stopped in front of the crosswalk. In this case, the mobile robot 100 does not cross the crosswalk even if the traffic light 200 is green. If the traffic light 200 switches to red and then switches to green, the driving control unit 125 may resume the movement of the mobile robot 100 and have the mobile robot cross the crosswalk. If the pedestrian traffic light 200 is red when the mobile robot 100 reaches the crosswalk, the driving control unit 125 may resume the movement of the mobile robot 100 and have the mobile robot cross the crosswalk after the traffic light 200 switches to green.

[0028] Next, the operation procedure will be described. Fig. 4 is a flowchart showing the operation procedure of the driving control device 102. The operation procedure of the driving control device 102 corresponds to a driving control method. The driving control unit 125 stops the mobile robot 100 before an intersection (step S1). When the traffic light is green, it is not necessarily necessary to stop the mobile robot 100 before the intersection.

[0029] The traffic light information acquisition unit 121 acquires traffic light information for traffic lights installed at the intersection (step S2). The driving control unit 125 determines whether the traffic light information acquired in step S2 indicates a green light (step S3). If it is determined in step S3 that the traffic light information indicates a green light, the situation acquisition unit 122 acquires situation information for the intersection (step S4).

[0030] The crossing time calculation unit 123 calculates the crossing time of the mobile robot 100 using the situation information acquired in step S4 (step S5). The crossing possibility determination unit 124 uses the crossing time calculated in step S5 to determine whether the mobile robot 100 can cross the intersection before the traffic light turns red (step S6). If it is determined in step S6 that the mobile robot 100 can cross the intersection, the driving control unit 125 causes the mobile robot 100 to start crossing the intersection (step S7).

[0031] If the driving control unit 125 determines in step S3 that the traffic light information does not indicate a green light, it waits until the next traffic light turns green (step S8). Even if the driving control unit 125 determines in step S6 that crossing is not possible, it proceeds to step S8 and waits until the next traffic light turns green. If the next traffic light turns green, the driving control unit 125 proceeds to step S7 and causes the mobile robot 100 to start crossing the intersection. After waiting until the next traffic light turns green in step S8, the driving control device 102 may perform steps S4 to S6 to determine whether the mobile robot 100 can cross the intersection.

[0032] In this embodiment, the situation acquisition unit 122 acquires situation information about the road that the mobile robot 100 is to cross. The traveling speed of the mobile robot 100 changes depending on the road conditions, and the crossing time of the mobile robot 100 changes depending on the change in traveling speed. In this embodiment, the crossing time calculation unit 123 calculates the crossing time depending on the conditions of the road that the mobile robot 100 is to cross. The crossing feasibility determination unit 124 determines whether the mobile robot 100 can cross the road using the crossing time calculated depending on the road conditions. In this manner, the cruise control device 102 can more accurately determine whether the mobile robot can cross the road before the traffic light phase changes to red.

[0033] If it is determined that the mobile robot 100 cannot cross the road while the light is green, the driving control device 102 does not allow the mobile robot 100 to cross the road. This prevents the mobile robot 100 from being left behind at an intersection, allowing the mobile robot 100 to travel safely.

[0034] Next, the hardware configuration of the driving control device 102 will be described. The driving control device 102 can be configured as an electronic control device or a computer device. FIG. 5 is a block diagram showing an example of the hardware configuration of an electronic control device that can be used as the driving control device 102. The electronic control device 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 control device 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 control device 500 can include other circuits such as peripheral circuits, communication circuits, and interface circuits.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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 driving control device 102 can be realized.

[0039] 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.

[0040] 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.

[0041] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0042] [Supplementary Note 1] A driving control device comprising: a traffic light information acquisition unit that acquires traffic light information for traffic lights installed on a road that a mobile robot will cross; a situation acquisition unit that acquires situation information for a location where the mobile robot will travel when crossing the road; a crossing time calculation unit that uses the situation information to calculate the crossing time required for the mobile robot to cross the road; a crossing feasibility determination unit that compares the time remaining until the traffic light changes to red with the calculated crossing time and determines whether the mobile robot will be able to cross the road by the time the traffic light changes to red based on the result of the comparison; and a driving control unit that causes the mobile robot to start crossing the road if the crossing feasibility determination unit determines that the mobile robot can cross.

[0043] [Supplementary Note 2] The driving control device according to Supplementary Note 1, wherein the situation acquisition unit acquires the situation information using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

[0044] [Supplementary Note 3] The driving control device according to Supplementary Note 2, wherein the situation acquisition unit analyzes an image acquired by using the periphery monitoring sensor to acquire the situation information.

[0045] [Supplementary Note 4] The driving control device according to any one of Supplementary Notes 1 to 3, wherein the situation acquisition unit acquires a congestion state of the road as situation information.

[0046] [Supplementary Note 5] The driving control device according to Supplementary Note 4, wherein the situation acquisition unit detects people crossing the road, and acquires the congestion situation based on the number of people detected.

[0047] [Supplementary Note 6] The driving control device according to any one of Supplementary Notes 1 to 5, wherein the situation acquisition unit acquires, as situation information, the presence or absence of an obstacle in a location where the mobile robot travels when crossing the road.

[0048] [Appendix 7] The driving control device described in any one of Appendices 1 to 6, wherein the driving control unit stops the mobile robot in front of the road, and if it is determined that the mobile robot can cross the road, resumes the driving of the mobile robot and causes the mobile robot to cross the road.

[0049] [Supplementary Note 8] A mobile robot comprising: a drive unit for driving the mobile robot; a sensor for monitoring the surroundings of the mobile robot; and the driving control device according to any one of Supplementary Notes 1 to 7.

[0050] [Supplementary Note 9] A driving control method comprising: acquiring traffic light information for traffic lights installed on a road that a mobile robot will cross; acquiring situation information for a location where the mobile robot will travel when crossing the road; calculating a crossing time required for the mobile robot to cross the road using the situation information; comparing the time remaining until the traffic light changes to red with the calculated crossing time; determining based on the result of the comparison whether the mobile robot can cross the road by the time the traffic light changes to red; and if it is determined that the mobile robot can cross the road, having the mobile robot start crossing the road.

[0051] [Supplementary Note 10] The travel control method according to Supplementary Note 9, wherein the situation information is acquired using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

[0052] [Supplementary Note 11] The cruise control method according to Supplementary Note 10, further comprising analyzing an image acquired using the periphery monitoring sensor to acquire the situation information.

[0053] [Supplementary Note 12] The cruise control method according to any one of Supplementary Notes 9 to 11, wherein a congestion state of the road is acquired as situation information.

[0054] [Supplementary Note 13] The driving control method according to Supplementary Note 12, further comprising detecting people crossing the road, and acquiring the congestion state based on the number of people detected.

[0055] [Supplementary Note 14] The travel control method according to any one of Supplementary Note 9 to 13, wherein the presence or absence of an obstacle in a location where the mobile robot travels when crossing the road is acquired as situation information.

[0056] [Supplementary Note 15] The travel control method described in any one of Supplementary Notes 9 to 14, wherein the mobile robot is stopped in front of the road, and if it is determined that the mobile robot can cross the road, the mobile robot is allowed to resume traveling and cross the road.

[0057] [Supplementary Note 16] A program that causes a computer to execute processing including: acquiring traffic light information for traffic lights installed on a road that a mobile robot will cross; acquiring situation information for a location where the mobile robot will travel when crossing the road; calculating a crossing time required for the mobile robot to cross the road using the situation information; comparing the time remaining until the traffic light turns red with the calculated crossing time; and determining based on the result of the comparison whether the mobile robot will be able to cross the road by the time the traffic light turns red; and if it is determined that the mobile robot can cross the road, having the mobile robot start crossing the road.

[0058] [Supplementary Note 17] The program according to Supplementary Note 16, wherein the situation information is acquired using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

[0059] [Supplementary Note 18] The program according to Supplementary Note 17, further comprising: analyzing an image acquired using the perimeter monitoring sensor to acquire the situation information.

[0060] [Supplementary Note 19] The program according to any one of Supplementary Notes 16 to 18, wherein the program acquires a congestion status of the road as status information.

[0061] [Supplementary Note 20] The program according to Supplementary Note 19, further comprising: detecting people crossing the road; and acquiring the congestion status based on the number of people detected.

[0062] [Supplementary Note 21] The program according to any one of Supplementary Notes 16 to 20, wherein the program acquires, as situation information, the presence or absence of an obstacle in a location where the mobile robot travels when crossing the road.

[0063] [Supplementary Note 22] The program described in any one of Supplementary Notes 16 to 21, wherein the mobile robot is stopped in front of the road, and if it is determined that the mobile robot can cross the road, the mobile robot is allowed to resume moving and cross the road.

[0064] 100: Mobile robot 101: Driving unit 102: Travel control device 103: Sensor 121: Traffic light information acquisition unit 122: Situation acquisition unit 123: Crossing time calculation unit 124: Crossing possibility determination unit 125: Travel control unit 200: Traffic light

Claims

1. A driving control device comprising: a traffic light information acquisition unit that acquires traffic light information for traffic lights installed on a road that a mobile robot will cross; a situation acquisition unit that acquires situation information for a location where the mobile robot will travel when crossing the road; a crossing time calculation unit that uses the situation information to calculate the crossing time required for the mobile robot to cross the road; a crossing feasibility determination unit that compares the time remaining until the traffic light changes to red with the calculated crossing time and determines whether the mobile robot will be able to cross the road by the time the traffic light changes to red based on the result of the comparison; and a driving control unit that causes the mobile robot to start crossing the road if the crossing feasibility determination unit determines that crossing is possible.

2. A driving control device according to claim 1, wherein the situation acquisition unit acquires the situation information using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

3. The driving control device according to claim 2, wherein the situation acquisition unit analyzes an image acquired using the surroundings monitoring sensor to acquire the situation information.

4. A driving control device according to any one of claims 1 to 3, wherein the situation acquisition unit acquires the congestion status of the road as the situation information.

5. The driving control device according to claim 4, wherein the situation acquisition unit detects people crossing the road and acquires the congestion situation based on the number of people detected.

6. A driving control device as described in any one of claims 1 to 5, wherein the situation acquisition unit acquires as the situation information the presence or absence of obstacles in the location where the mobile robot travels when crossing the road.

7. A driving control device as described in any one of claims 1 to 6, wherein the driving control unit stops the mobile robot in front of the road, and if it is determined that the mobile robot can cross the road, resumes the driving of the mobile robot and causes the mobile robot to cross the road.

8. A mobile robot comprising: a drive unit for moving the mobile robot; a sensor for monitoring the surroundings of the mobile robot; and a travel control device according to any one of claims 1 to 7.

9. A driving control method comprising: acquiring traffic light information for traffic lights installed on a road that a mobile robot will cross; acquiring situation information for a location where the mobile robot will travel when crossing the road; calculating the crossing time required for the mobile robot to cross the road using the situation information; comparing the time remaining until the traffic light turns red with the calculated crossing time; determining based on the result of the comparison whether the mobile robot can cross the road by the time the traffic light turns red; and if it is determined that the mobile robot can cross the road, causing the mobile robot to start crossing the road.

10. A driving control method according to claim 9, wherein the situation information is acquired using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

11. The cruise control method according to claim 10, wherein the situation information is acquired by analyzing an image acquired using the surroundings monitoring sensor.

12. A cruise control method according to any one of claims 9 to 11, wherein the congestion status of the road is acquired as the situation information.

13. The cruise control method according to claim 12, further comprising detecting people crossing the road, and acquiring the congestion status based on the number of people detected.

14. A travel control method according to any one of claims 9 to 13, wherein the situation information obtained is the presence or absence of an obstacle in a location where the mobile robot travels when crossing the road.

15. A travel control method according to any one of claims 9 to 14, wherein the mobile robot is stopped in front of the road, and if it is determined that the mobile robot can cross the road, the mobile robot resumes traveling and crosses the road.

16. A program that causes a computer to execute a process including: acquiring traffic light information for traffic lights installed on a road that a mobile robot will cross; acquiring situation information for the location where the mobile robot will travel when crossing the road; calculating the crossing time required for the mobile robot to cross the road using the situation information; comparing the time remaining until the traffic light turns red with the calculated crossing time; determining based on the result of the comparison whether the mobile robot will be able to cross the road by the time the traffic light turns red; and, if it is determined that the mobile robot can cross the road, having the mobile robot begin crossing the road.

17. The program according to claim 16, wherein the situation information is acquired using sensor information from a periphery monitoring sensor that monitors the periphery of the mobile robot.

18. The program according to claim 17, wherein the situation information is acquired by analyzing an image acquired using the perimeter monitoring sensor.

19. The program according to any one of claims 16 to 18, wherein the congestion status of the road is acquired as the status information.

20. The program according to claim 19, further comprising: detecting people crossing the road; and acquiring the congestion status based on the number of people detected.

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