Traffic facility control system, traffic facility control method, and program

Abstract

To provide a traffic facility control system that can both ensure a physical safety of a moving person and reduce a psychological burden on the moving person.SOLUTION: A traffic facility control system 1 according to an embodiment comprises: a detection unit 1a that detects a movement capability of a person; a determination unit 1b that determines a psychological state of the person; and a control unit 1c that controls a traffic facility installed on at least one of a location near a current location of the person, a location on a route where the person moves, and a location along the route, based on the movement capability of the person and the psychological state of the person.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a traffic facility control system, a traffic facility control method, and a program. [Background technology]

[0002] Patent Document 1 describes a technology that statistically calculates the time required to cross a crosswalk for each attribute from pedestrian information received from a transmitter attached to each pedestrian, and determines the extension time for the green period of a traffic light based on the results. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 3530090 Summary of the Invention [Problem to be solved by the invention]

[0004] However, while the technology described in Patent Document 1 increases the safety of pedestrians when crossing the crosswalk by setting the green period of the traffic light to the time required for pedestrians to cross the crosswalk, it can cause psychological burden (stress) because pedestrians' psychological state varies from time to time.

[0005] The present disclosure has been made in consideration of the problems described above, and provides a traffic facility control system, a traffic facility control method, and a program that are capable of ensuring the physical safety of travelers while reducing the psychological burden on the travelers. [Means for solving the problem]

[0006] The traffic equipment control system according to the present disclosure includes a detection unit that detects a person's mobility, a determination unit that determines the person's psychological state, and a control unit that controls traffic equipment installed in at least one of the vicinity of the person's current location, a position on the route the person is traveling, and a position along the route based on the person's mobility and the person's psychological state.

[0007] As a result, the traffic equipment control system can control traffic equipment installed near a person's current location, at a location on the route the person is traveling, and at a location along the route, based on the person's mobility and psychological state, thereby ensuring both the physical safety of the person and reducing the psychological burden on the person.

[0008] The detection unit may detect at least the walking ability of the person as the mobility of the person. In this way, the traffic facility control system can detect the walking ability used for controlling the traffic facility on the spot, thereby enabling control of the traffic facility based on the current walking ability.

[0009] The detection unit may detect the mobility of the person by detecting the presence or absence of carried items or accompanying persons that impede the movement of the person and calculating the mobility of the person based on the detection result. In this way, the traffic facility control system can detect not only the person's own walking ability but also the walking ability that takes into account the presence of carried items or accompanying persons as the walking ability used for controlling traffic facilities, making it possible to control traffic facilities based on the walking ability that is more suited to the person's condition.

[0010] The traffic facility control system may include a first acquisition unit that acquires vital information of the person measured by a measuring device worn by the person, and the determination unit may determine the psychological state of the person based on the vital information. In this way, the traffic facility control system can determine the psychological state of a person based on the vital information measured by a measuring device worn by the person, thereby enabling control of traffic facilities based on an accurate psychological state of the person.

[0011] The traffic equipment control system may include an identification unit that identifies the person, and the determination unit may determine the psychological state of the person from the vital information using a learning model that has been machine-learned about the person identified by the identification unit. In this way, the traffic equipment control system can accurately determine the psychological state of the person by using a learning model that has been machine-learned about the person from vital information measured by a measuring device worn by the person.

[0012] The traffic facility control system may further include a second acquisition unit that acquires imaging data of a facial image of the person, and the determination unit may determine the psychological state of the person based on the imaging data. In this way, the traffic facility control system can accurately determine the psychological state of the person by determining the psychological state of the person based on the imaging data of a facial image that is likely to reveal the person's psychological state.

[0013] The traffic facility control system may include an identification unit that identifies the person, and the determination unit may determine the psychological state of the person from the imaging data using a learning model that has been machine-learned for the person identified by the identification unit. In this way, the traffic facility control system can more accurately determine the psychological state of a person by determining the psychological state of the person using a learning model that has been machine-learned for the person based on imaging data of a face image that is likely to reveal the person's psychological state.

[0014] The control unit may be configured to control at least one of the timing of a change and the duration of a changed state for at least one of a change in display and a change in shape of the traffic facility. In this way, the traffic facility control system performs control to change at least one of the display and shape of the traffic facility based on a person's mobility and psychological state, thereby enabling control of the traffic facility taking into account a person's mobility and psychological state.

[0015] The traffic facility control system may include an identification unit that identifies the person, and a third acquisition unit that acquires disease information indicating a disease related to the walking ability of the person identified by the identification unit, and the control unit may control the traffic facility based on the mobility ability of the person, the psychological state of the person, and the disease information. In this way, the traffic facility control system can control the traffic facility while also taking into account the disease information of the person.

[0016] The traffic facility control system may include a prediction unit that predicts the direction in which the person will move, and the control unit may control the traffic facility based on the predicted direction in which the person will move, the mobility of the person, and the psychological state of the person. In this way, the traffic facility control system can control the traffic facility by taking into account the result of the prediction of the direction in which the person will move.

[0017] The traffic facility control system may include a visibility determination unit that determines whether the person is viewing the mobile terminal device, and the control unit may control the traffic facility based on the mobility of the person, the person's psychological state, and the determination result of the visibility determination unit. In this way, the traffic facility control system can control the traffic facility taking into consideration whether the person is viewing the mobile terminal device, thereby improving safety.

[0018] The control unit may be configured to notify a notification device provided as part of the traffic facility according to the content of control of the traffic facility other than the notification device. In this way, the traffic facility control system can notify people of the control content of the traffic facility other than the notification device by the notification device, thereby further improving safety.

[0019] The traffic facility control system may include an identification unit that identifies the person, and a notification unit that issues a notification according to the content of control over the traffic facility to a terminal device used by the person identified by the identification unit. In this way, the traffic facility control system can notify the person of the content of control over the traffic facility to the terminal device used by the person, thereby further improving safety.

[0020] The traffic facility control system may include an identification unit that identifies the person, and an inquiry unit that inquires of a terminal device used by the person identified by the identification unit about whether or not to control the traffic facility based on the person's mobility and psychological state. This enables the traffic facility control system to decide whether or not to control the traffic facility while respecting the person's will.

[0021] The detection unit may detect the mobility of a user of a mobile body as a person to be detected, and the control unit may control traffic facilities installed near the current location of the mobile body, on the route along which the mobile body travels, and at least one of positions along the route, based on the mobility of the person and the psychological state of the person. In this way, the traffic facility control system can ensure the physical safety of the person and reduce the psychological burden on the person, even when the person is traveling using a mobile body.

[0022] The transportation facility control method disclosed herein inputs the results of detecting a person's mobility ability, inputs the results of judging the person's psychological state, and controls transportation facilities installed in at least one of the vicinity of the person's current location, a location on the route the person is traveling, and a location along the route based on the person's mobility ability and the person's psychological state.

[0023] As a result, the transportation facility control method can control transportation facilities installed near a person's current location, at a location on the route the person is traveling, and at a location along the route, based on the person's mobility and psychological state, thereby making it possible to ensure both the physical safety of the person and the reduction of the person's psychological burden.

[0024] The program disclosed herein is a program for causing a computer to execute a process of inputting the results of detecting a person's mobility ability, inputting the results of judging the person's psychological state, and controlling transportation facilities installed in at least one of the vicinity of the person's current location, a location on the route the person is traveling, and a location along the route based on the person's mobility ability and the person's psychological state.

[0025] As a result, the program can control transportation facilities installed near a person's current location, at locations on the route the person is traveling, and at locations along the route based on the person's mobility and psychological state, thereby making it possible to ensure both the person's physical safety and reduce the person's psychological burden. Effect of the Invention

[0026] According to the present disclosure, it is possible to provide a traffic facility control system, a traffic facility control method, and a program that can ensure the physical safety of travelers while reducing the psychological burden on the travelers. [Brief description of the drawings]

[0027] [Figure 1] 1 is a block diagram showing an example of a configuration of a traffic facility control system according to an embodiment. [Diagram 2] 2 is a flow diagram illustrating an example of control in the traffic facility control system of FIG. 1. [Diagram 3] 2 is a block diagram showing an example of the configuration of a transportation system including the traffic facility control system of FIG. 1. [Figure 4] FIG. 4 is a schematic top view showing an example of the arrangement of transportation facilities in the transportation system of FIG. 3. [Diagram 5] FIG. 4 is a schematic top view showing an example of the arrangement of transportation facilities in the transportation system of FIG. 3. [Figure 6] FIG. 5 is a schematic top view of an enlarged portion of the exemplary transportation facility layout of FIG. 4, illustrating a scene in which another person has been detected in the area. [Figure 7] FIG. 4 is a diagram showing an example of a table used to control transportation facilities in the transportation system of FIG. 3. [Figure 8] 2 is a block diagram showing another example of the configuration of a transportation system including the transportation facility control system of FIG. 1. [Figure 9] 9 is a diagram showing an example of a table used to collect information for controlling transportation facilities in the transportation system of FIG. 8. FIG. [Figure 10] 10 is a schematic top view showing another example of the arrangement of transportation facilities in the transportation system of FIG. 3 or FIG. 8. [Figure 11] 10 is a block diagram showing an example configuration of a learning system that generates a learning model used in the transportation system of FIG. 3 or FIG. 8. [Figure 12] FIG. 12 is a diagram showing an example of teacher data used in the learning system of FIG. [Figure 13] FIG. 12 is a diagram showing another example of teacher data used in the learning system of FIG. [Figure 14] FIG. 2 illustrates an example of a hardware configuration included in the apparatus. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] The present invention will be described below through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. Also, not all of the configurations described in the embodiments are necessarily essential as means for solving the problems. The embodiments will be described below with reference to the drawings.

[0029] <Embodiment> FIG. 1 is a block diagram showing an example of the configuration of a traffic facility control system according to the present embodiment. As shown in FIG. 1, the transportation facility control system 1 according to this embodiment is a system for controlling one or more transportation facilities (transportation infrastructure), and may include a detection unit 1a, a determination unit 1b, and a control unit 1c.

[0030] The detector 1a detects the mobility of a person. The detector 1a can detect the mobility of a person as one of a plurality of levels set based on a predetermined criterion, for example.

[0031] The detection unit 1a may include a sensor for the purpose of detecting the person's mobility itself, measuring a value that is used to calculate the person's mobility, or acquiring imaging data that is used to calculate the person's mobility. The type and number of sensors are not important, and the detection method is also not important. Here, the sensor that detects the person's mobility itself may be a sensor that measures one or more predetermined types of information that can express the person's mobility. In addition, a sensor that acquires imaging data that is moving image data or a series of still image data captured at a predetermined interval corresponds to an imaging device (hereinafter, a camera).

[0032] For example, the detection unit 1a includes a camera that captures image data and can detect the movement of a person (the state of movement) from the captured image data. The detection unit 1a can then determine the mobility of the person by comparing it with a predetermined standard based on at least one piece of information such as the speed and magnitude of the movement (for example, the range of movement of the hands and feet), and output the determination result as the detection result.

[0033] Furthermore, the detection unit 1a may be configured to detect at least the walking ability of a person as the mobility of a person. Of course, the walking ability of a person may also be detected by using the above-mentioned type of sensor used for detecting the mobility of a person. The detection unit 1a may be configured to detect the running ability of a person as the mobility of a person.

[0034] The following method is also an example of a detection method specialized for a person's walking ability. For example, the detection unit 1a can capture an image of a person with a camera and input the captured image data into a learning model for skeletal recognition to recognize the skeleton from the person's posture and physique, and can also calculate the stride length and walking speed from the deformation of the skeleton. The detection unit 1a can then calculate and obtain the person's walking ability based on the skeleton, stride length, and walking speed.

[0035] The detection unit 1a can also be configured to capture an image of a person with a camera and determine, from the captured image data, at least one of whether or not the person is using a wheelchair, whether or not the person is using a white cane, and whether or not the person is using a cane of a different color. Since people who use wheelchairs or canes are expected to have low walking ability, in that case, the detection unit 1a can output a detection result indicating that the walking ability of a person using a white cane is at a low level, and can output a detection result indicating that the walking ability of a person using a white cane is at an even lower level.

[0036] The detection unit 1a may also include, for example, a sensor that detects personal items or accompanying persons that impede the movement of the person. This sensor may be a camera, but is not limited thereto, and may also be, for example, a sensor that detects radio waves from personal items configured to emit predetermined radio waves.

[0037] The detection unit 1a may detect the mobility of a person by detecting the presence or absence of carried items or accompanying persons that hinder the movement of the person using a sensor, and calculating the mobility of the person based on the detection result. The movement of a person here may refer to the movement of a person alone, that is, walking or running. The detection unit 1a may also detect the mobility of a person by calculating the mobility of the person based on the detection result of the presence or absence of carried items or accompanying persons and the walking ability detected separately.

[0038] Examples of carry-on items that impede the movement of a person include carry-on items larger than a predetermined size, such as a large backpack or suitcase, and carry-on items of a predetermined shape, such as a backpack that is sagging and heavy. Examples of accompanying persons include accompanying persons smaller than a predetermined size, such as a baby. Note that, for example, when two people are moving together, which person is to be the person to be detected can be determined according to a predetermined criterion, and the other person can be excluded from the detection target. However, both of them can also be the people to be detected. Of course, the same applies to cases where three or more people are moving together.

[0039] The determination unit 1b determines the psychological state of a person detected by the detection unit 1a. However, the order of the processes in the detection unit 1a and the determination unit 1b does not matter as long as the psychological state and the mobility of the target person can be associated with each other. For example, the determination unit 1b may determine the psychological state of a person, and the detection unit 1a may detect the mobility of the person determined by the determination unit 1b.

[0040] The determination unit 1b can determine the person's psychological state as one of a plurality of levels set based on a predetermined criterion, for example. The person's psychological state can be determined, for example, as the person's stress level, but is not limited thereto. For example, the determination unit 1b can extract data of a face area (face image data) from the imaging data obtained by a camera, and detect or determine the person's facial expression from the face image data. Then, the determination unit 1b can determine the person's psychological state based on the detected or determined facial expression. Here, when the detection unit 1a includes a camera, the camera used to acquire the facial image data can be the camera included in the detection unit 1a, but can also be a separate camera.

[0041] Furthermore, the determination unit 1b may include a sensor other than a camera that measures the psychological state of a person, for example.

[0042] The judgment unit 1b can also be configured to identify the person to be judged and obtain information indicating the person's psychological state from an external system. In this case, the person and information indicating the person's psychological state are stored in association with each other in the external system, and by updating this information to the latest state, judgment based on the latest information is possible, and the information indicating the latest psychological state can be reflected in the control described below. Of course, the judgment unit 1b is not limited to these examples, and any judgment method is possible.

[0043] Next, examples of installation locations for the cameras and other sensors included in the detection unit 1a and the determination unit 1b will be given. The sensors in the detection unit 1a and the determination unit 1b can be installed in a state supported by a support such as a pole or a gate arranged at the installation location.

[0044] The sensors provided in the detection unit 1a can be installed at approximately equal intervals in the area to be managed among the areas where people are expected to move, or can be installed at approximately equal intervals on roads such as sidewalks that can be expected as routes along which people move, but the arrangement is not limited to being at equal intervals. For example, the intervals at which the sensors are installed can be narrowed at points where there are changes in the road, such as intersections and curves. The sensors provided in the detection unit 1a can be installed at least in places where people are likely to pass through, such as the entrances to the area to be managed, and can also be installed continuously from the entrances, for example at regular intervals. In addition, if there is a bus (which may be an autonomous moving object) that travels around a certain route in the area to be managed, the sensors can be installed at bus stops.

[0045] Here, the area to be managed can be the area in which transportation facilities subject to control by the control unit 1c described below are located, and can also be an area specified, for example, by city, district, prefecture, etc.

[0046] When the determination unit 1b includes sensors, the sensors can be installed at approximately equal intervals in the area to be managed among the areas where people are expected to move, or at approximately equal intervals on roads such as sidewalks, like the sensors of the detection unit 1a, but the placement is not limited to equal intervals. For example, the intervals at which the sensors are installed can be narrowed at points where there are changes in the road, such as intersections and curves. Also, like the sensors of the detection unit 1a, the sensors of the determination unit 1b can be installed at least at places where people are likely to pass through among the areas to be managed, and can be installed continuously from those places, for example at regular intervals, or can be installed at bus stops.

[0047] The intervals at which the sensors are installed in the detection unit 1a and the determination unit 1b are installed may be narrower, and for example, the interval at which the detection result and the determination result tend to change may be narrower.

[0048] When the determination unit 1b is provided with a sensor, the sensor can use the sensor in the detection unit 1a, or can be installed in the same installation location as all or part of the sensors in the detection unit 1a. In this case, sensing by the sensor is performed.

[0049] In addition, since the sensors in the detection unit 1a and the determination unit 1b perform sensing at each installation location, the sensing area at each installation location can also be called a sensing zone. For example, the detection result of a person's mobility and the determination result of a person's psychological state can also be used for managing a health condition, so this sensing zone can also be called a health care zone. This health care zone is a zone where data indicating a health condition is obtained simply by a person passing through the zone by walking or the like. The health care zone can be equipped with various sensors such as cameras required for obtaining information, and supports such as poles or gates that support the various sensors. As described as the installation location of the sensor, the health care zone can be installed at least in a place where a person is likely to pass through in the area to be managed, and can also be installed continuously from that place, for example, at a certain interval, or can be installed at a bus stop.

[0050] Also, as can be seen from people moving on roads such as sidewalks, people do not move in only one direction in the area in which they move, but include movement from two opposing directions, unless the road is a one-way street, etc. Therefore, for the sensors provided in both the detection unit 1a and the determination unit 1b, at least two sets can be arranged so as to be able to handle people coming and going from at least the above two directions, or sensors capable of detecting multiple directions (or all directions) including at least the above two directions can be adopted.

[0051] The control unit 1c inputs the person's mobility and psychological state obtained by the detection unit 1a and the determination unit 1b, respectively. Then, based on the input mobility and psychological state of the person, the control unit 1c controls transportation facilities installed in at least one of the vicinity of the person's current location, positions on the route along which the person is moving, and positions along the route.

[0052] Here, the vicinity of the person's current location can be, for example, the position of the sensor in the detection unit 1a or the detection range of that sensor, but if the determination unit 1b is equipped with a sensor, it can also be defined as the position of that sensor or its detection range.

[0053] Alternatively, if a sensor can roughly detect the distance and direction from the sensor to a person, the vicinity of the person's current location can be an area within a predetermined range of distance and direction based on the position of the person detected by the sensor. For example, a traffic facility installed near the person's current location can be a traffic facility whose azimuth angle is within a predetermined range of angles based on the direction of the person's face and is installed within a predetermined distance from the person, or a traffic facility installed within a predetermined radius around the person.

[0054] Furthermore, the position on the route along which the person moves can be within a range of a predetermined distance in the direction of travel of the person from the person's current position, which is represented by the position of a sensor or the actual position of the person detected, and the direction of travel can be along the road, for example, if the road is a sidewalk or other road. As will be described later, the route can also be a route indicated by a navigation system in a mobile terminal device (not shown) used by the person, and in this case, the direction of travel can be the direction of travel indicated by this route. Furthermore, a position along the route can be a position included in a range that is a predetermined distance wide in a direction perpendicular to the direction of travel (left and right of the person) at a position on the route.

[0055] An example of control in the control unit 1c will be described later, but only a simple example will be shown. For example, the control unit 1c customizes the length of the green period of the traffic light according to the result indicating whether the person is in a wheelchair or not and the result indicating whether the person is in an overstressed state or calm. The overstressed state can refer to a state of impatience or irritation. For example, the length of the green period of the traffic light is made longer for a person who uses a wheelchair compared to a person who does not use a wheelchair, and the length of the green period of the traffic light is made longer for a person in an overstressed state compared to a person who is calm. This is because in an overstressed state, it is necessary to control traffic facilities with greater consideration given to the safety of people's movement. In this example, the control is determined based on two types of judgment results, that is, based on two-stage judgment results, but it is of course possible to determine the control based on three or more judgment results.

[0056] In addition, when multiple people are the targets of detection and judgment, the priority of information used for control in the control unit 1c can be set to the information about the person with the lowest mobility and the information about the person with the worst psychological state. For example, the control unit 1c can control traffic facilities, such as determining the length of the green period of a traffic light, according to the person with the lowest mobility or the person with the worst psychological state.

[0057] The control unit 1c can be realized by, for example, a processor such as a CPU (Central Processing Unit), a working memory, and a non-volatile storage device. A control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby fulfilling the functions of the control unit 1c. In addition, the control unit 1c can be realized by a configuration including an integrated circuit, without being limited to this example.

[0058] The control program may include at least one of a program for realizing functions other than the sensor in the detection unit 1a and a program for making a judgment in the judgment unit 1b. In this case, the processor reads the program into a working memory and executes it to perform the functions of the control unit 1c as well as at least one of the functions other than the sensor in the detection unit 1a and the judgment unit 1b (if a sensor is provided, the functions other than the sensor in the judgment unit 1b). Functions not included in the control program may be realized by a hardware configuration.

[0059] Next, an example of a traffic facility control method executed in the traffic facility control system 1 will be described with reference to Fig. 2. Fig. 2 is a flow diagram for explaining an example of control in the traffic facility control system 1 of Fig. 1.

[0060] In this traffic facility control method, first, the control unit 1a inputs the result of detecting a person's mobility (step S1), and inputs the result of judging the person's psychological state (step S2). The order of steps S1 and S2 does not matter. In steps S1 and S2, the detection result of the detection unit 1a and the judgment result of the judgment unit 1b can be input, respectively.

[0061] Next, the control unit 1a controls transportation facilities installed near the person's current location, at locations on the route the person is traveling, and at locations along the route based on the person's mobility and psychological state (step S3), and then ends the processing.

[0062] The above-mentioned control program may include a program for causing a computer to execute the processing shown in the traffic facility control method. As can be seen from this example, the traffic facility control system 1 may also be constructed as a system that does not include at least one of the detection unit 1a and the determination unit 1b. However, even in this case, the detection results and the determination results must be input to the system.

[0063] With the above configuration, the traffic equipment control system 1 can control traffic equipment installed near the person's current location, at a location on the route the person is traveling, and at a location along the route, based on the travel ability and psychological state of the person. Therefore, the traffic equipment control system 1 can ensure both the physical safety of the person and the reduction of the psychological burden on the person. In other words, this embodiment can take into consideration both the physical safety of the person and the comfortable travel of the person, thereby improving the safety and comfort of the person traveling.

[0064] Moreover, by configuring the traffic facility control system 1 to detect at least a person's walking ability as a person's mobility, the walking ability used for controlling the traffic facility can be detected on the spot. Therefore, in such a configuration example, it becomes possible to control the traffic facility based on the current walking ability.

[0065] Furthermore, by configuring the traffic facility control system 1 to calculate a person's mobility based on the results of detecting the presence or absence of personal items or accompanying persons that impede the person's mobility, it is possible to detect not only the person's own walking ability but also the walking ability that takes into account the presence of personal items or accompanying persons as the walking ability to be used for controlling traffic facilities. Therefore, in this configuration example, it becomes possible to control traffic facilities based on the walking ability that is more suited to the person's condition.

[0066] Next, a detailed description will be given of an example configuration of the traffic facility control system 1. Fig. 3 is a block diagram showing an example configuration of a traffic system including the traffic facility control system 1.

[0067] 3, the transportation system 2 can include a traffic facility control device 10 and multiple traffic facilities 20a, 20b, ... as part of the traffic facility control system 1. Note that the traffic facility control system 1 will be described on the assumption that it does not include the traffic facilities 20a, 20b, ... that are the targets of control, but it can also be defined as a system that includes these.

[0068] The traffic facility control device 10 is a device that controls multiple traffic facilities 20a, 20b, etc., and can be configured to include a computer, for example. The traffic facility control device 10 can be configured as a standalone device, but it can also be configured as a distributed system in which its functions are distributed. Of course, the traffic facility to be controlled may be one.

[0069] Furthermore, the traffic system 2 may include, as part of the traffic facility control system 1, a group of sensors for obtaining information used for control in the traffic facility control device 10. As shown in Fig. 3, the group of sensors may include, for example, a plurality of cameras 30a, 30b, ... and may also include wearable devices 40a, 40b, ... worn by each person.

[0070] In the following, when the transportation facilities 20a, 20b,... are not distinguished from one another, they will be referred to as transportation facility 20. Similarly, when the cameras 30a, 30b,... and the wearable devices 40a, 40b,... are not distinguished from one another, they will be referred to as camera 30 and wearable device 40, respectively.

[0071] The traffic facility control device 10 may include a control unit 11 that controls the entire traffic facility control device 10, a memory unit 12 that is composed of a memory device, and a communication unit 13 that is composed of a communication interface or the like that communicates with external devices.

[0072] The control unit 11 is assumed to have functions other than the sensor in the detection unit 1a and functions other than the sensor in the determination unit 1b in addition to the functions of the control unit 1c. The control unit 11 can be realized by, for example, a processor, a working memory, and a non-volatile storage device, as with the control unit 1c. The control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby achieving the functions of the control unit 11. The control program can include a program for achieving functions other than the sensor in the detection unit 1a and a program for achieving functions other than the sensor in the determination unit 1b. In that case, the processor reads the program into the working memory and executes it, thereby achieving these functions. Note that functions not included in the control program can be achieved by a hardware configuration.

[0073] The storage unit 12 can store a facility information DB 12a, which is a DB storing information on the traffic facilities 20, a learning model 12b, a learning model 12c, and a person information DB 12d, which is a DB storing person information. The information on the traffic facilities 20, the person information, and the coefficients of the learning models 12b and 12c stored in the storage unit 12 can be updated to the latest information as appropriate. In addition, although not shown, the storage unit 12 also stores position information indicating the installation positions of sensors such as the installed camera 30. Details of the facility information DB 12a, the learning model 12b, the learning model 12c, and the person information DB 12d will be described later.

[0074] The communication unit 13 communicates with the camera 30 via the same or different wired network in order to obtain information necessary for the control of the traffic facility 20 in the control unit 11, and communicates with the wearable device 40 via a wireless network, passing the obtained information to the control unit 11. The communication unit 13 also communicates with the traffic facility 20 via the wired network in order to obtain the current state of the traffic facility 20 as necessary (for example, the current control state, such as the current display color of a traffic light) and to transmit a control signal for controlling the traffic facility 20 that is the target of control. However, the communication unit 13 may be configured to communicate with other devices wirelessly, regardless of the method of communication with other devices, as long as wireless communication is established with at least the wearable device 40.

[0075] The camera 30 is used as a sensor for the detection unit 1a and the determination unit 1b, and captures images of people including their faces and entire bodies, acquires the image data, and transmits it to the traffic facility control device 10. The camera 30 may have a built-in or connected communication interface for this transmission. The image data is received by the communication unit 13 of the traffic facility control device 10 and passed to the control unit 11.

[0076] The wearable device 40 is an example of a measuring device that measures a person's vital information in order to determine the person's psychological state. The wearable device 40 can be, but is not limited to, a smart watch, a smart ring, an IC chip embedded in the body, etc.

[0077] Furthermore, the vital information measured by the wearable device 40 may be information indicating one or more of, for example, pulse or heart rate, respiration (rate), blood pressure, body temperature, etc. The value of the vital information is information that changes even for the same person, for example, while holding the urge to go to the bathroom, while running, while walking normally, etc.

[0078] The wearable device 40 directly or indirectly transmits the acquired vital information to the traffic facility control device 10. The wearable device 40 may have a built-in communication interface or may be connected to a communication interface for the transmission.

[0079] In a simple example, the wearable device 40 can be configured to spontaneously transmit vital information to the traffic facility control device 10, for example at a predetermined interval. This transmission may be direct or indirect. In this case, the traffic facility control device 10 may have a function of collecting and managing vital information as a server device (not shown) or the like. In this case, it is preferable to allow the wearable device 40 or a mobile terminal device (not shown) connectable thereto to transmit vital information to the traffic facility control device 10 in advance. In this example of spontaneous transmission, it is not necessary for the traffic facility control device 10 to send a vital information transmission request with the wearable device 40 specified, and a specifying unit, which will be described later, is not required.

[0080] Whether the vital information is transmitted directly or indirectly, it is received by the communication unit 13 of the traffic facility control device 10 and passed to the control unit 11. As in this example, the traffic facility control device 10 can include an acquisition unit (for convenience, referred to as a first acquisition unit) that acquires vital information of a person measured by a measuring device worn by the person. In the example of Fig. 3, the communication unit 13 and the control unit 11 that controls the acquisition are examples of this first acquisition unit.

[0081] Here is an example in which the wearable device 40 indirectly transmits vital information. The wearable device 40 transmits the vital information to the above-mentioned mobile terminal device used by the person wearing the wearable device 40 by short-range wireless communication or the like, and the mobile terminal device transmits the vital information to the traffic facility control device 10. This mobile terminal device can be, for example, a mobile phone such as a smartphone, a tablet terminal, or a mobile PC (Personal Computer). Note that the above and later-described short-range wireless communication method is not important, and various methods such as Wi-Fi (registered trademark), Bluetooth (registered trademark), Bluetooth Low Energy (registered trademark), and ZigBee (registered trademark) can be used.

[0082] In addition, the transmission of vital information can also be performed via a communication interface capable of short-range wireless communication with the wearable device 40 or a mobile terminal device, which is built into or connected to a sensor such as the camera 30 that functions as part of the detection unit 1a or the determination unit 1b.

[0083] The wearable device 40 or the mobile terminal device can be configured to automatically transmit vital information when it enters an area where wireless communication with this communication interface is possible. In such a configuration, there is no need for the traffic facility control device 10 to send a vital information transmission request specifying the wearable device 40 or the mobile terminal device, and the specifying unit described below is not required. Also in this case, it is preferable to allow the wearable device 40 or the mobile terminal device to transmit vital information to the traffic facility control device 10 in advance.

[0084] Alternatively, the wearable device 40 can be configured to return vital information when a vital information transmission request is received from the traffic facility control device 10 via this communication interface. In this case, however, the traffic facility control device 10 needs to include an identification unit that identifies a person, and to issue a vital information transmission request by specifying the wearable device 40 or mobile terminal device associated with the person (individual) identified by the identification unit. In this way, the traffic facility control device 10 transmits a vital information transmission request to the wearable device 40 or mobile terminal device used by the person identified by the identification unit, and obtains vital information in response to the request. Details of the identification unit will be described later together with an explanation of the person information DB 12d.

[0085] Next, the information stored in the storage unit 12 will be described in detail. The facility information DB 12a can be a DB that stores, for each traffic facility 20, facility identification information such as an ID for identifying the traffic facility 20 and an equipment number, facility type information indicating the type of the traffic facility 20, and location information indicating the installation location of the traffic facility 20 in association with each other. The traffic facility 20 to be controlled can be one or more of various types of traffic facilities 20 described below with reference to Figs. 4 to 6, regardless of their type or number. The facility type information can be included in the facility identification information or can be implicitly included therein.

[0086] The location information may be any information that identifies a location, such as information indicating latitude and longitude, or information indicating coordinates on map data. The location information can be referenced for use in comparison with the location of a person, or in comparison with the location of a sensor such as a camera 30 when the location of a person is used. Furthermore, the location information can include information indicating a direction that can be seen by a person when the traffic facility 20 is a facility equipped with a function of displaying information that can be seen by a person. Furthermore, the location information can include information indicating a direction that is suitable for a person to listen to when the traffic facility 20 is a facility equipped with a function of outputting sound.

[0087] The learning model 12b is a learning model that inputs imaging data (image data) of a person captured by the camera 30 and outputs a detection result that detects (determines) the person's mobility, and the algorithm, etc., is not limited to the above. The input parameters are not limited to the above. The learning model 12b can output, as the detection result, information indicating one of a plurality of levels that are predetermined based on a predetermined criterion, for example.

[0088] The learning model 12b can be obtained, for example, as follows. That is, a data set including imaging data obtained by imaging a person with a camera (which may or may not have the same performance as the camera 30) and correct answer data obtained by having the person answer the question about the person's mobility or by having a doctor or the like judge the person's mobility is input to an unlearned learning model, and machine learning is performed to obtain the learning model 12b. The learning model 12b can be a model that can accurately determine a person's mobility from the imaging data by having the learning model learn a data set about a large number of people without overlearning. A system that performs such learning will be described later.

[0089] In this way, the control unit 11 can be configured to detect the mobility of a person based on the imaging data using the learning model 12b as a function of the detection unit 1a. However, the control unit 11 can also be configured to detect the mobility of a person based on the imaging data without using the learning model 12b.

[0090] Furthermore, the control unit 11 can detect the mobility of a person based on the imaging data captured by the camera 30 as part of the function of the detection unit 1a, without being limited to using the learning model 12b. The imaging data used for detection can be imaging data capturing an image of the entire person, and it is not necessary to capture the facial expression of the person just for detection. However, in the case of a configuration in which the psychological state of the person is judged based on at least the facial expression of the person, or in the case of a configuration in which the person is identified from a facial image, the imaging data includes data capturing an image of the person's face. By configuring the traffic facility control device 10 to detect the mobility of a person based on the imaging data captured by the camera 30, it becomes possible to control traffic facilities based on the accurate mobility of the person.

[0091] The learning model 12c is a learning model that inputs at least one of vital information of a person obtained from the wearable device 40 and image data of a person including a face captured by the camera 30, and outputs a judgment result of judging the psychological state of the person, and the algorithm thereof is not limited. The input parameters are not limited to these. The learning model 12c can output, as a judgment result, information indicating one of a plurality of levels predetermined based on a predetermined criterion, for example.

[0092] The learning model 12c can be obtained, for example, as follows. That is, a data set including at least one of vital information and imaging data of a person including a face captured by the camera 30, and correct answer data obtained by having the person answer questions about their psychological state at that time, is input to an unlearned learning model, and machine learning is performed to obtain the learning model 12c. The learning model 12c can be a model that can accurately determine a person's psychological state from at least one of vital information and imaging data by having the learning model learn a data set about a large number of people without overlearning. A system that performs such learning will be described later.

[0093] In this way, the control unit 11 can be configured to use the learning model 12c as a function of the determination unit 1b to determine the psychological state of a person based on the vital information measured by the wearable device 40. However, the control unit 11 can also be configured to determine the psychological state of a person based on the vital information measured by the wearable device 40 without using the learning model 12c.

[0094] Furthermore, without being limited to using the learning model 12c, the control unit 11 can determine the psychological state of a person based on the vital information acquired by the first acquisition unit as a function of the determination unit 1b. The traffic facility control device 10 is configured to determine the psychological state of a person based on vital information measured by a measuring device worn by the person, thereby enabling control of traffic facilities based on an accurate psychological state of the person.

[0095] Furthermore, as described above, the control unit 11 can be configured, as a function of the judgment unit 1b, to use the learning model 12c to judge a person's psychological state based on imaging data capturing an image of a person including their face (i.e., imaging data including facial image data).

[0096] Here, as described above, imaging data of a person's facial image captured by the camera 30 is received by the communication unit 13 of the traffic facility control device 10 and passed to the control unit 11. As in this example, the traffic facility control device 10 can include an acquisition unit (for convenience, referred to as a second acquisition unit) that acquires imaging data of a person's facial image. In the example of Fig. 3, the communication unit 13 and the control unit 11 that controls the acquisition are examples of this second acquisition unit.

[0097] In this way, the traffic equipment control device 10 is configured to determine a person's psychological state using a learning model that has been machine-learned about that person based on facial image data.Since a person's psychological state is likely to be reflected in a facial image, and since a determination is made using a learning model, it can be said that a person's psychological state can be determined more accurately.

[0098] However, as described above, the control unit 11 may be configured to determine a person's psychological state based on imaging data including face image data without using the learning model 12c. For example, the control unit 11 may be configured to detect a facial expression of a person shown in a face image based on imaging data including face image data, and to determine a person's psychological state based on the detected facial expression.

[0099] In this way, the traffic facility control device 10 can be configured to determine a person's psychological state based on facial image data, and can therefore accurately determine the person's psychological state, since the person's psychological state is easily reflected in a facial image. Although a person's psychological state can be determined based on either the imaging data showing the person's facial expression or the vital information measured by the wearable device 40, a combination of both can more accurately determine (estimate) the person's psychological state, such as stress level.

[0100] Furthermore, the learning models 12b and 12c can be constructed as a single learning model that inputs, for example, vital information of a person and imaging data of a person, and outputs a detection result of the person's mobility and a judgment result of the person's psychological state. Alternatively, the learning models 12b and 12c can be constructed as a single learning model that inputs, for example, vital information of a person and imaging data of a person, and outputs the traffic facility 20 to be controlled and the control content. In these cases, the algorithm of the learning model is not important.

[0101] The traffic facility control device 10 can include an identification unit as described above, and the person information DB 12d can be included as a part of this identification unit. The traffic facility control device 10 can include, as the identification unit, the person information DB 12d and a function of identifying a person while referring to the person information DB 12d, and this function can be provided in the control unit 11. The identification unit can identify a person, for example, by at least one of face recognition processing and gait recognition processing. Note that the person information DB 12d is a DB that is referenced to identify a person, and does not need to be stored in a configuration that does not require identification of a person, that is, a configuration that does not include the identification unit.

[0102] The person information DB12d can be, for example, a DB that stores at least one of face image data and gait data, and personal identification information such as name or ID, for each person to be managed. The face image data can be employed in a configuration in which the identification unit identifies a person by face recognition processing, and the gait data can be employed in a configuration in which the identification unit identifies a person by gait recognition processing. Of course, the identification unit executes both face recognition processing and gait recognition processing, and can determine that the person has been identified when authentication is successful in both, for example.

[0103] In addition, the personal identification information may include information such as an ID that identifies the wearable device 40, or information such as an ID that identifies a mobile terminal device that can be connected to the wearable device 40, instead of or in addition to the name or ID.

[0104] The identification unit can identify a person by, for example, comparing the imaging data obtained by the camera 30 with at least one of the face image data and gait data stored in the person information DB 12d, and output the corresponding personal identification information, etc. When face recognition processing is used to identify a person, it is preferable that the camera 30 is installed so as to match conditions such as position, imaging direction, imaging magnification, etc., so that the face of the person can be imaged, and imaging is performed. When gait recognition processing is used to identify a person, it is not necessary for the camera 30 to be installed so as to match such conditions, and it is sufficient that the camera 30 is installed so as to match conditions such as position, imaging direction, imaging magnification, etc., so that the figure of the person walking can be imaged (i.e., the whole person can be imaged).

[0105] The identification unit may, for example, detect a person from the imaging data obtained by the camera 30, and execute the above-mentioned comparison process when the person is detected. In other words, the identification unit may execute the above-mentioned comparison process when a person enters the imaging range of the camera 30.

[0106] The identification unit can also be configured to identify a person using a learning model. That is, instead of the person information DB 12d, a learning model that inputs at least one of face image data and imaging data of an entire person and outputs information indicating the person, the wearable device 40, or the mobile terminal device can be stored in the storage unit 12. During operation, the control unit 11 inputs imaging data captured by the camera 30 to this learning model to obtain information indicating the person, the wearable device 40, or the mobile terminal device. In addition, in the learning stage, machine learning can be performed on the mobile terminal device used by each individual, and the resulting learning model or learned coefficients, etc. can be transmitted to the traffic facility control device 10, so that the traffic facility control device 10 can identify a person using the individual's learning model.

[0107] Here, a modified example of the learning model 12c will be described. The learning model 12c can be stored as a model trained by machine learning for each person. The control unit 11 may use the learning model trained by machine learning for the person identified by the identification unit to determine the psychological state of the person from the vital information measured by the wearable device 40. In this way, the traffic facility control device 10 determines the psychological state of the person using the learning model trained by machine learning for the person from the vital information measured by the wearable device 40 worn by the person, and therefore can more accurately determine the psychological state of the person.

[0108] Moreover, the learning model 12c can be constructed as a model dedicated to each attribute information, instead of being a model dedicated to each person. Here, the attribute information can include, for example, at least one of generation or age, sex, and race. The control unit 11 may use a learning model machine-learned on the attribute information to determine the psychological state of a person from vital information measured by the wearable device 40 for a person corresponding to the attribute information. In this way, the traffic facility control device 10 can be configured to determine the psychological state of a person using a learning model machine-learned on the attribute information of the person from vital information measured by the wearable device 40 worn by the person. Since it is expected that the vital information depends on the attribute information in large part, it can be said that the traffic facility control device 10 configured in this way can accurately determine the psychological state of the person.

[0109] Next, the function of the control section 1c in the control section 11 will be described. Based on the mobility and psychological state of the person obtained by any of the various examples described above, the control unit 11 controls the transportation facilities 20 installed in at least one of the vicinity of the person's current location, the location on the route along which the person is moving, and the location along the route. The definitions of the current location, the route, etc. are as described above.

[0110] For example, the control unit 11 may control at least one of the timing of a change and the duration of a changed state for at least one of a change in display and a change in shape in the traffic facility 20. Here, a change in the shape of the traffic facility 20 may include, for example, raising and lowering a liftable median strip, guard rail, a group of poles, etc., thereby making it possible to expand / contract the road width.

[0111] A traffic equipment control device 10 configured in this manner performs control to change at least one of the display and shape of the traffic equipment 20 based on a person's mobility and psychological state, making it possible to control the traffic equipment 20 taking into account a person's mobility and psychological state.

[0112] Before describing an example of such control in the transportation system 2 in FIG. 3, an example of the arrangement of the transportation facilities 20 to which the control can be applied will be described with reference to FIG. 4 to FIG. 6. FIG. 4 and FIG. 5 are schematic top views showing an example of the arrangement of the transportation facilities 20 in the transportation system 2 in FIG. 3, and FIG. 5 is a diagram showing a state in which some of the transportation facilities have transitioned to a different state from that in FIG. 4 due to control. FIG. 6 is a schematic top view enlarging a part of the example of the arrangement of the transportation facilities in FIG. 4, showing a scene in which another person is detected in the area. Note that FIG. 6 also illustrates the transportation facilities that were omitted in FIG. 4.

[0113] 4 to 6, for the sake of convenience, only a part of the area in which the traffic facilities 20 to be controlled by the traffic facility control device 10 are located is illustrated as an example. However, the area in which the traffic facilities 20 to be controlled are located is not limited to this example, and may include an area outside the illustrated area. Furthermore, the area in which the traffic facilities 20 to be controlled are located may be an area specified, for example, by city, district, or prefecture, as described above.

[0114] The area in which some or all of the traffic facilities 20 controlled by the traffic facility control device 10 exist can be, for example, an area including one main road and two minor roads as shown in Figures 4 to 6. In Figures 4 to 6, the main road is a road equipped with lanes (roadways) 51 to 53 and sidewalks 54, 55, the first minor road is a road equipped with roadways 56, 57 and sidewalks 58, 59 that crosses the main road, and the second minor road is a road equipped with roadways 60, 61 and sidewalks 62, 63 that forms a T-junction with the main road at the end of the main road.

[0115] In addition, in this area shown in Figures 4 to 6, two crosswalks 50 are provided that cross the first minor road's roadways 56, 57, and pedestrian bridges 64, 65 are provided along the first minor road to allow pedestrians to cross over the main road's roadways 51-53.

[0116] All of the transportation facilities 20 to be controlled shown in FIGS. 4 to 6 are connected to the transportation facility control device 10 via a network, and are controlled in accordance with control signals transmitted from a control unit 11.

[0117] As shown in Figs. 4 to 6, the traffic facilities 20 to be controlled include traffic lights 20a, 20b, 20d, 20e, 20f, and 20g, a pedestrian crossing signal 20c, a liftable median strip 20j and 20k, a digital signage 20p, elevators 20q, 20r, 20s, and 20t, a liftable braille block 20v, a display variable sign 20w, and a liftable guardrail 20x. For convenience, traffic lights for the roadway 53 are not shown, but are assumed to be placed in appropriate locations. Of course, the number and arrangement of each traffic facility 20 shown in the examples are not limited to these. In addition, the traffic facilities 20 to be controlled may be only a part of the traffic facilities shown in the examples, or may include other types of traffic facilities not shown in the examples.

[0118] The liftable separation strips 20j, 20k are provided with a physical separation strip and a mechanism for lifting and lowering it, and the liftable separation strip can be switched between being formed and not being formed by lifting and lowering the separation strip. Note that instead of the liftable separation strips 20j, 20k, a configuration can be adopted in which the formation and non-formation of the separation strip can be switched by changing the display color.

[0119] The elevation median strips 20j, 20k can be controlled to opposite elevation states to make the main road a two-way road, and can be lowered to make it a one-way road. For the sake of simplicity, an example will be given below in which the main road is only controlled to be a two-way road.

[0120] As shown in Fig. 4, the liftable separator 20j can be lowered to a height substantially equal to the surface of the roadways 51 and 52, thereby eliminating the partition between the roadways 51 and 52 and making them roadways in the same direction. In this case, the upper surface of the liftable separator 20j may be colored so that it can be visually recognized as a white line, a broken white line, a yellow line, or the like on the road. In addition, the liftable separator 20k in this state can be raised higher than the surface of the roadways 52 and 53 to a height that can separate the roadways 52 and 53, which are the oncoming lanes, from each other, thereby forming a physical partition between the roadways 52 and 53 and making them roadways in opposite directions.

[0121] On the other hand, as shown in Fig. 5, the liftable separator 20j is raised above the surfaces of the roadways 51 and 52 to a height that allows the oncoming lanes 51 and 52 to be separated from each other, thereby forming a physical partition between the roadways 51 and 52 and making them roadways in opposite directions. In this state, the liftable separator 20k is lowered to a height that is almost the same as the surfaces of the roadways 52 and 53, thereby eliminating the partition between the roadways 52 and 53 and making them roadways in the same direction. In this case, the upper surface of the liftable separator 20k may be colored so that it can be visually recognized as a white line, a dashed white line, a yellow line, or the like on the road.

[0122] As another example of use, the rise-up separator 20j can be raised higher than the surfaces of the roadways 51, 52 to change the roadway 51 into a sidewalk, in which case the rise-up separator 20k can also be raised higher than the surfaces of the roadways 52, 53 to form a physical separation between the roadways 52, 53 and turn them into roadways in opposite directions.

[0123] There are scenes where the traffic lights 20a and 20b are controlled to be synchronized and have the same light color, and scenes where they are controlled to be displayed separately. In the former scene, as shown in FIG. 4, the rising / lowering separator 20j is lowered to a height substantially equal to the surface of the roadways 51 and 52, and the rising / lowering separator 20k is raised to a height higher than the surface of the roadways 52 and 53. In the latter scene, as shown in FIG. 5, the rising / lowering separator 20j is raised to a height substantially equal to the surface of the roadways 51 and 52, and the rising / lowering separator 20k is lowered to a height substantially equal to the surface of the roadways 52 and 53. The traffic light 20d is controlled to have a light color opposite to that of the traffic light 20a for red and green. In addition, there are also scenes where either the traffic light 20a or 20d is controlled to be yellow, and in that case the other is controlled to be red.

[0124] The traffic lights 20e and 20f are controlled in the same way as the traffic lights 20a and 20b, respectively, but because of differences in their installation locations, it is possible to create a time difference in control between the traffic lights 20a and 20e and between the traffic lights 20b and 20f. In other words, there are situations in which the traffic lights 20e and 20f are controlled to display the same light color in synchronization with each other, and situations in which they are controlled to display different lights. In the former situation, the liftable divider 20j is lowered and the liftable divider 20k is raised, and in the latter situation, the liftable divider 20j is raised and lowered, respectively. The traffic light 20g is controlled to display the opposite light color to the traffic light 20e for red and green. There are also situations in which either the traffic light 20e or 20g is controlled to be yellow, in which case the other is controlled to be red.

[0125] Furthermore, when the rising / lowering median strip 20k shown in FIG. 5 is in the lowered state and the rising / lowering median strip 20j is in the raised state, the traffic lights 20b and 20f can display characters or a mark notifying that passage is prohibited.

[0126] All four pedestrian crossing signals 20c are visible when pedestrians cross the pedestrian crossing, and can be controlled synchronously. The pedestrian crossing signals 20c are controlled to be green when the traffic light 20a is red, and are controlled to be red when the traffic light 20a is green or yellow. Of course, the pedestrian crossing signals 20c can also be controlled to flash green a predetermined time before the traffic light 20a changes from red to green. Note that the control between the traffic lights 20a and the pedestrian crossing signals 20c is not limited to these controls, and it is sufficient that the timing for changing the light color is set in consideration of safety.

[0127] The digital signage 20p is a display device that displays various notification contents, such as notifications encouraging safe driving and notifications described below, to vehicles traveling on the roadway 51 or on the roadways 51, 52 when the rise-up median strip 20j is lowered, and is installed on a pole or the like provided near the sidewalk 54 or the boundary between the sidewalk 54 and the roadway 51.

[0128] The liftable braille block 20v is a movable braille block that includes a main body embedded in a location on the sidewalk 54 suitable for use by people using a white cane, multiple rod-shaped members that form the braille, and a mechanism for raising and lowering the multiple rod-shaped members relative to the main body. The liftable braille block 20v is configured to form braille by simultaneously raising the multiple rod-shaped members that form the braille, and to form a state in which no braille is present (to make braille non-formed) by lowering them to a surface that is approximately aligned with the upper surface of the sidewalk 54. In this way, the liftable braille block 20v can switch between forming and not forming braille by raising and lowering the multiple rod-shaped members.

[0129] The variable display sign 20w is a display device that displays to a person a road sign selected from a plurality of road signs, and is installed on, for example, a pole or the like provided on a sidewalk 55 as shown in FIG.

[0130] The liftable guardrail 20x includes a physical protective fence and a mechanism for lifting and lowering it, and can switch between forming and not forming the protective fence by lifting and lowering the protective fence. As shown in Fig. 6, the liftable guardrail 20x can be installed, for example, near the center in the width direction of the sidewalk 55, in a range that does not interfere with movement to the stairs of the footbridge 64 even when it is lifted in the direction along the sidewalk 55. A plurality of liftable guard poles can also be used instead of the liftable guardrail 20x.

[0131] The elevators 20q and 20r are both installed on the footbridge 64, and are devices for transporting people up and down between the upper walkway of the footbridge 64 and the walkways 54 and 55, respectively. The elevators 20s and 20t are both installed on the footbridge 65, and are devices for transporting people up and down between the upper walkway of the footbridge 65 and the walkways 54 and 55, respectively.

[0132] 4 to 6, cameras 30b, 30c, 30d, and 30e corresponding to camera 30 are installed on sidewalks 54 and 55, and a sensing zone 30a equipped with sensors including camera 30 is also installed at a location on sidewalk 54 corresponding to the entrance to this area. Cameras 30b and 30c and cameras 30d and 30e can be installed, for example, on poles provided on sidewalks 54 and 55, respectively. Sensing zone 30a can be one in which sensors are installed on an arch spanning both ends of sidewalk 54, but it can also be one in which sensors are installed on a pole like camera 30b.

[0133] 4 to 6 show a state in which people U1, U1a, U2, U3, U4, and U5, a white cane ST being used by person U3, a wheelchair WC being used by person U4, a bicycle B1 being used by person U5, a car M1, and an autonomous moving vehicle M2 such as an autonomous moving bus are present within the illustrated area. However, since people and cars are constantly moving, this shows only a momentary state. Here, person U1a is an accompanying person of person U1.

[0134] In the transportation system 2 having the above-described configuration example, an example of control of the transportation facility 20 in response to detection of a person or the like will be described with reference to FIG. 7. Only one example of detection of mobility, judgment of psychological state, and control of the transportation facility 20 based on the results will be described here, but various examples can be applied. For convenience, an example of control by the control unit 11 will be described in which control is performed to achieve a certain state when conditions stipulated by mobility, psychological state, etc. are met. However, if the certain state is the same as the current state, this means that no control is actually performed, and if it is different from the current state, this means that control is performed to achieve the certain state.

[0135] Fig. 7 is a diagram showing an example of a table used to control the transportation facility 20 in the transportation system 2 in Fig. 3. For convenience, Fig. 7 uses the symbols given in Figs. 4 to 6 for the facility IDs for identifying the transportation facility 20, but is not limited thereto.

[0136] 7 can be stored in the storage unit 12, for example, and can be referred to by the control unit 11 during control. This table 12t can also be stored as a part of the facility information DB 12a.

[0137] First, the scenes shown in FIG. 4 and FIG. 5 will be described. In Fig. 4, the control unit 11 detects the presence of a person based on the image data captured by the camera 30b, and when it detects that the person U1a is an accompanying person of the person U1, it calculates the skeleton, stride length, and walking speed by inputting the image data into a learning model for skeleton recognition, and calculates the walking ability of the person U1 based on these values. Here, the detection of the presence of a person itself can be performed by another sensor. In addition, the calculated walking ability of the person U1 is at a lower level than the walking ability detected when the person U1 is not accompanied by anyone.

[0138] Furthermore, the control unit 11 detects the facial expression of the person U1 based on the facial image data included in the imaging data captured by the camera 30b, and determines the stress level of the person U based on the facial expression. In a configuration example in which a person needs to be identified in a process such as determining a stress level, the control unit 11 may then execute a facial recognition process based on the facial image data captured by the camera 30b to identify the person U1.

[0139] When the walking ability of person U1 is lower than a predetermined ability level and the stress level of person U1 is higher than a predetermined stress level (hereinafter, condition A), the control unit 11 controls the traffic facility 20 as exemplified below. In other cases, for example, the control unit 11 may not control the traffic facility 20 according to the walking ability and stress level, but may only control the traffic facility 20 based on other factors unrelated to person U1 (e.g., the degree of congestion, etc.). Note that condition A refers to condition A illustrated in table 12t in FIG. 7, and hereinafter, conditions B to E also refer to conditions B to E illustrated in table 12t, respectively.

[0140] In the case of condition A, the control unit 11 can control, for example, the pedestrian crossing signal 20c to turn green after a predetermined time considering the time it takes for the person U1 to reach the pedestrian crossing 50, or to extend the time the signal remains green. Accordingly, the traffic light 20a is similarly controlled for its illumination color, and the traffic light 20d is controlled in a manner opposite to that of the traffic light 20a. The pedestrian crossing signal 20c is a pedestrian crossing signal within a predetermined distance from the camera 30b, and although a description thereof will be omitted, the traffic facility 20 to be controlled can be determined in a similar manner according to the position of the camera 30b and the position of each traffic facility 20.

[0141] In the case of condition A, the control unit 11 can also perform the following additional control. That is, the control unit 11 can also perform control to lower the elevation separation strip 20j and raise the elevation separation strip 20k. This allows more space for vehicles to pass by making the roadway adjacent to the sidewalk 54 on which the person U1 with low walking ability and high stress level is walking into a two-lane roadway consisting of roadways 51 and 52, thereby improving the safety of the pedestrians U1 and U1a walking on the sidewalk 54 adjacent to the roadway.

[0142] In addition, such control can be switched between not being executed and being executed depending on whether the traffic volume of vehicles such as automobiles M1 and autonomous moving bodies M2 is greater than a predetermined volume. In this case, the traffic volume can be calculated by analyzing the image data captured by cameras 30 installed at various locations.

[0143] As an alternative example of additional control, in the case of condition A, the control unit 11 can also perform control to raise the elevation separation strip 20j and raise the elevation separation strip 20k. In that case, the control unit 11 can also perform control to display an indication that the roadway 51 has been changed to a sidewalk at the traffic light 20a. This allows the roadway 51 adjacent to the sidewalk 54 on which the person U1 with low walking ability and high stress level is walking to be changed to a sidewalk, thereby improving the safety of the people U1 and U1a.

[0144] Also, when this alternative example is adopted, or when the elevation-type median strips 20j, 20k are not provided, it is preferable to provide an elevation-type median strip or an elevation-type guardrail between the original sidewalk 54 and the roadway 51, not shown, and lower it to add the roadway 51 as a sidewalk when condition A is met, and raise it when condition A is not met and the roadway 51 is not added. In this way, when it is desired to improve the safety of pedestrians, the elevation-type median strip or the like provided therebetween can be lowered to control the width of the sidewalk 54 to be expanded by the width of the road indicated by the roadway 51, and in other cases, the sidewalk can be controlled to be reduced to only the sidewalk 54. Also, for the expansion / reduction of the sidewalk 54, instead of the elevation-type median strip, a configuration can be adopted in which the boundary between the sidewalk and the roadway can be switched between being formed / not formed by changing the display color.

[0145] In addition, even when this alternative example is adopted, it is possible to switch between non-execution and execution depending on whether the traffic volume of vehicles such as the automobile M1 and the autonomous moving body M2 is greater than a predetermined volume. In addition, when this alternative example is adopted, it is also possible to control so that the control is not performed during a time period when the autonomous moving body M2 passes through the roadway 51 as shown in Fig. 4, and that the roadway is in a two-lane state consisting of the roadways 51 and 52 as shown in Fig. 4 during that time period, and is in a one-lane state as shown in Fig. 5 during a time period when the autonomous moving body M2 does not pass through.

[0146] In the case of condition A, as a further additional alternative example, the control unit 11 can also control the digital signage 20p to notify the control contents of the traffic facility 20 other than the notification device such as the digital signage 20p, preferably the control contents of the traffic facility 20 within a predetermined area. This makes it possible to inform people and vehicle drivers that the control contents of the traffic facility 20 have changed.

[0147] In this way, the control unit 11 may send a notification to a notification device provided as part of the traffic facility 20 according to the content of control of the traffic facility other than the notification device. In this way, the traffic facility control device 10 can notify people of the control content of the traffic facility 20 other than the notification device by the notification device, thereby improving safety. Also, this notification can be executed only under specific conditions such as condition A, but can also be executed under any conditions under which the traffic facility 20 is controlled.

[0148] The notification device is not limited to a display device such as the digital signage 20p, but may be an audio output device or a display device with an audio output function. The notification device may be installed in a location where the control content affects people, or between that location and a location where people are detected. When notifying the control content in the case of condition A, it is advisable to simultaneously notify a user of the control content with a notice to call attention to the control content, such as "please take your time" or "please proceed quickly." On the other hand, when notifying the control content in the case of conditions other than A, it is advisable for the control device to notify normal notification content such as the speed limit or "please observe the speed limit while passing through."

[0149] Furthermore, the contents to be notified by the notification device when controlling the traffic facility 20 can also be notified to the terminal device used by the person U1 or the persons U1, I1a by instant message, e-mail, or the like. This terminal device can be a mobile terminal device or the like used by the person. Furthermore, since this notification requires identification of the person or the terminal device used by the person, the traffic facility control device 10 is provided with the above-mentioned identification unit.

[0150] The traffic facility control device 10 may further include a notification unit that notifies the terminal device used by the person identified by the identification unit (e.g., person U1 in this example) according to the contents of the control of the traffic facility 20. The notification contents in this case may be, for example, only a general description of the control, such as "such control will be performed," or may include personal information of the person identified by the identification unit, thereby reassuring the person by informing him or her that the traffic facility 20 is being controlled. After controlling the traffic facility 20 according to the person's movement, the traffic facility control device 10 may also delete information other than information indicating that the person is at that location or information necessary for notification, and in this case, the notification contents may include a notice that the information has been deleted, thereby reassuring the person.

[0151] In this way, the traffic facility control device 10 can be configured to notify a person of the control contents of the traffic facility 20 on the terminal device used by that person, thereby giving the person a sense of security and thereby further improving safety.

[0152] The traffic facility control device 10 may also include an inquiry unit that inquires of a terminal device used by a person identified by the identification unit as to whether or not to control the traffic facility 20 based on the person's mobility and psychological state. The terminal device can respond to this inquiry by incorporating an application program for responding to this inquiry. This allows the traffic facility control device 10 to decide whether or not to control the traffic facility 20, respecting the person's will, such as whether or not to enjoy the service of controlling the traffic facility 20 based on their own movement.

[0153] The timing of this inquiry may be before entering the area to be controlled, but it can also be, for example, the following timing. That is, when a person passes the position of the sensor of the detection unit 1a such as the camera 30b, the person's mobility and psychological state are obtained, and at that timing, the terminal device of the person may be inquired as to whether or not they wish to change the control of the traffic facility according to their mobility and psychological state. Regardless of the timing, the control unit 11 receives the answer and decides whether or not to change the control depending on the answer. This makes it possible to respect the person's will, and to give the person a sense of security by knowing that they are a target person.

[0154] In addition, when condition A is not satisfied, if the walking ability of person U1 is lower than a predetermined ability level and the stress level of person U1 is equal to or lower than a predetermined stress level (hereinafter, condition B), the control unit 11 can control the transportation equipment 20 as shown in the following example.

[0155] In the case of condition B, since the person U1 is not irritated, it is assumed that making the person U1 wait for the traffic light will not cause a big problem. Therefore, the control unit 11 can control, for example, the pedestrian crossing traffic light 20c so that the light turns red after a predetermined time considering the time it takes for the person U1 to reach the pedestrian crossing 50. Accordingly, the traffic light 20a is similarly controlled in terms of the lighting color, and the traffic light 20d is controlled in a manner opposite to that of the traffic light 20a.

[0156] In the case of condition B, the control unit 11 can perform additional control for the lift-up dividers such as the lift-up divider 20j, which is the opposite of that in the case of condition A. Specifically, the control unit 11 can also perform control to raise the lift-up divider 20j and lower the lift-up divider 20k. However, in the case of condition B, unlike the case of condition A, for example, it is not necessary to switch between non-execution and execution according to the traffic volume, and it is also sufficient not to apply the example of expanding / reducing the sidewalk and the example of notifying the control content described as an alternative example of the additional control. On the other hand, in the case of condition B, as in the further alternative example of the additional control in the case of condition A, the control unit 11 can also control the digital signage 20p to notify the control content of the traffic facility 20 other than the notification device such as the digital signage 20p.

[0157] Also, if an elderly person U2 is detected instead of person U1, U1a, it is determined that the walking ability is lower than a predetermined ability level, and control can be performed as in the cases of conditions A and B, but in this case, a different control can also be performed.

[0158] Next, the scene shown in Fig. 6 will be described. In this scene, a person U3 is walking using a white cane ST, a person U4 is moving in a wheelchair WC, and a person U5 is riding a bicycle B1. The person U3 is detected by the camera 30b, and the people U4 and U5 are detected by the camera 30d.

[0159] The white cane ST and the wheelchair WC can be detected as a type of carry-on that impedes the movement of the person U3 and the person U4, respectively, and for example, the walking ability of the person U3 and the person U4 can be detected as being lower than a predetermined ability level (a second predetermined ability level and a third predetermined ability level, respectively) that is lower than the above-mentioned predetermined ability level. The second predetermined ability level can be set to a level higher than the third predetermined ability level, but is not limited to this. For example, information can be added that the white cane ST or the wheelchair WC is used at the same predetermined strength level. Conversely, the bicycle B1 can be detected as something that improves the mobility of the person U5, and for example, it can be detected as a level that is significantly higher than the walking ability of a normal person.

[0160] When the walking ability of the person U3 detected by the camera 30b is lower than the second predetermined ability level and the stress level of the person U3 is higher than the predetermined stress level (hereinafter, condition C), the control unit 11 controls the rod-shaped members of the ascending braille block 20v closest to the camera 30b to be raised, thereby making the braille block appear. At this time, the control unit 11 may also simultaneously perform the control described in condition A.

[0161] In this way, the lift-up braille block 20v may be controlled to make the braille blocks appear when a person U3 using a white cane ST is detected. In addition, although this is based on a different condition from condition C, the lift-up braille block 20v may be controlled to make the braille blocks appear in the normal state, and when a person carrying a suitcase is detected, for example, the rod members may be lowered to retract the braille blocks.

[0162] When the walking ability of person U4 detected by camera 30d is lower than the third predetermined ability level and the stress level of person U4 is higher than a predetermined stress level (hereinafter, condition D), the control unit 11 controls the display variable sign 20w closest to camera 30d to display a mark or letters indicating that the zone is a wheelchair zone (a no bicycle zone). At this time, the control unit 11 may simultaneously perform the control as described in condition A. However, because person U4 is moving in the same direction as person U1 and is moving on sidewalk 55 instead of sidewalk 54, the control of the liftable medians 20j, 20k is generally the opposite to that in condition A.

[0163] In addition, if an elderly person is detected instead of or in addition to a wheelchair, a mark or letter indicating that the zone is a no-bicycle zone can be displayed on the display variable sign 20w, and at the same time, control can be performed to widen the width of the sidewalk as described under condition A.

[0164] In addition, as one of the traffic facilities 20, a display device may be provided that shows, for example, a crosswalk parallel to the pedestrian bridge 64 on the road surface, and when a wheelchair and / or an elderly person is detected, the display device may display the crosswalk.

[0165] When the walking ability of the person U5 detected by the camera 30d is considerably higher than that of a normal person and the stress level of the person U5 is higher than a predetermined stress level (hereinafter, condition E), the control unit 11 controls the liftable guardrail 20x close to the camera 30d to be raised. This allows a bicycle zone to be formed on the sidewalk 55, improving the safety of other pedestrians. Furthermore, when a bicycle zone is formed, a display device similar to the display variable sign 20w may be used to display that the area is a bicycle zone.

[0166] Conversely, the control unit 11 can also perform control to make the liftable guardrail 20x appear when a person using a white cane or a person with a staggered gait is detected. In other words, the condition corresponding to the case where a person using a white cane or a person with a staggered gait is detected can also be included in the condition E.

[0167] Furthermore, even when condition D is satisfied, the control unit 11 can also perform control to raise the liftable guardrail 20x in order to protect people in wheelchairs or the elderly, or to serve as a handrail for the elderly.

[0168] Although the above describes control examples using simple conditions A to E, the present invention is not limited to these, and various application examples can be applied, such as controlling the traffic facility 20 by prioritizing detection by a camera 30 according to the human detection status of each camera 30. Furthermore, although a person's mobility basically does not change much while moving on a road, a person's psychological state may change even while moving. Therefore, for example, the control unit 11 can control the traffic facility 20 by changing the timing of changing the pedestrian crossing signal 20c to green and / or the length of the green period based on a change in a person's psychological state, such as a change in psychological state before and at the time of reaching a pedestrian crossing.

[0169] In addition, in the above explanation, the transportation facility 20 is basically controlled based on people's mobility and psychological state, and in some examples, control based on traffic volume is also given, but control based on other information can also be performed.

[0170] For example, the control of the traffic facility 20 can be changed based on the person's attention to the surroundings. This attention changes depending on, for example, the viewing situation of the mobile terminal device. Therefore, the traffic facility control device 10 can be provided with a viewing determination unit (not shown) that determines whether or not the person is viewing the mobile terminal device. Here, the mobile terminal device to be determined may be any device, and it can be determined whether or not the mobile terminal device is being held by, for example, determining whether or not it corresponds to one or more objects of a predetermined shape in the imaging data. Furthermore, if there is a possibility that the person is turning their face, or is looking at the mobile terminal device, it can be determined that the person is viewing the mobile terminal device. As can be seen from this example, the viewing determination unit can be composed of, for example, the control unit 11 and information for determination stored in the storage unit 12.

[0171] The control unit 11 may control the traffic facility based on the person's mobility and psychological state, and the judgment result of the visibility judgment unit. With this configuration, the traffic facility control device 10 can control the traffic facility 20 while taking into consideration whether or not the person is gazing at the mobile terminal device, thereby improving safety.

[0172] The traffic facility control device 10 may also include a prediction unit (not shown) that predicts the direction in which a person will move. The person to be predicted may be a person who is the subject of detection by the detection unit 1a or a person who is the subject of judgment by the judgment unit 1b, but may also be a person who is identified by the identification unit.

[0173] The prediction unit can be composed of, for example, the control unit 11 and information required for prediction stored in the storage unit 12. In this case, the control unit 11 can determine, for example, the direction of a person's face (direction of gaze) and predict that the person will head in a direction that matches the direction of the face on the map data stored in the storage unit 12. This is because a person may look in the direction they will head next.

[0174] Alternatively, the prediction unit can be composed of the control unit 11 and the communication unit 13. In the latter case, the control unit 11 can perform control so as to receive the prediction result from the person's mobile terminal device via the communication unit 13. In this case, when the person is using a navigation system built into the mobile terminal device, the control unit 11 can obtain the route information or destination information via the communication unit 13 and use the information as the prediction result.

[0175] Then, the control unit 11 controls the traffic facilities 20 based on the predicted direction in which the person will move, the person's mobility, and the person's psychological state. In particular, the control unit 11 can determine the traffic facilities 20 to be controlled based on the predicted direction in which the person will move. For example, the control unit 11 controls the traffic facilities 20 near the person's current location and in the direction in which the person will move, based on the person's mobility and psychological state. This allows the traffic facility control device 10 to control the traffic facilities 20 taking into account the results of predicting the direction in which the person will move. Note that the control unit 11 can eliminate the impact on others caused by controlling even distant traffic facilities 20 by controlling nearby traffic facilities 20 based on the mobility of a person with the lowest mobility, for example.

[0176] An example of control considering the prediction result will be given. When the control unit 11 refers to such a prediction result and finds that, for example, the user U1, U1a is planning to move from the sidewalk 54 to the sidewalk 55, and also satisfies, for example, condition A, the control unit 11 can perform the following control. That is, the control unit 11 may control the elevator 20q of the footbridge 64 to wait in a state in which it is lowered after a predetermined time considering the time it takes to reach the elevator 20r by walking on the footbridge 64, etc. In addition to such control, the control unit 11 may also control the elevator 20r to wait in a state in which it is raised after a predetermined time considering the time it takes to reach the elevator 20r by walking on the footbridge 64, etc. In addition, during these controls, the doors of the elevators 20q, 20r may be opened for a longer period of time.

[0177] The control of the elevators 20q, 20r can also be applied to cases where the prediction unit is not provided. That is, when the control conditions are met, the control unit 11 can control the elevator on the side closer to the pedestrian on the footbridge 64, 65 to be lowered, and can also control the elevator on the side farther from the pedestrian to be raised at the same time or with a slight delay. When the control conditions are met, the control unit 11 can also control the elevator doors to be opened longer. This type of control can prevent a situation in which such a person is caught in the elevator doors, particularly if the control conditions include a condition of a person with low mobility, such as a person using a cane (white cane or normal cane) or a person using a wheelchair.

[0178] As described above in various examples, according to the present embodiment, consideration can be given to the physical safety of people and to their comfortable travel, and the safety and comfort of people who are traveling can be improved. For example, by controlling traffic facilities to suit the person with the lowest mobility (most of whom are people who are stressed by travel), control can be provided that is beneficial in terms of safety and comfort for people with low mobility. Of course, people with high mobility can also benefit in terms of safety from such control of traffic facilities. For example, the traffic facility control device 10 can be configured to notify people with high mobility that the traffic facilities are being controlled comfortably to suit people with low mobility, for example, in a notification or the like. With such a configuration, people with high mobility can also recognize that they are behaving better through this notification, and thus can obtain satisfaction in that respect.

[0179] As shown in the example of bicycle B1, the detection unit 1a in Fig. 1 can also detect the mobility of a user of a moving object as a person to be detected. In other words, the mobility of a person detected in this case refers to the mobility of a person moving using a moving object. Here, various types of moving objects, such as a bicycle, an autonomous moving object M2, an automobile M1, a motorcycle, etc., can be applied as the moving object, and it does not matter whether the moving object is capable of autonomous movement or not.

[0180] In this example, the control unit 11 can control the traffic facilities 20 installed near the current location of the mobile object, on the route along which the mobile object moves, and at least one of the locations along the route, based on the mobility of the person and the psychological state of the person. In this way, even when a person moves using a mobile object, the traffic facility control device 10 can ensure the physical safety of the person and reduce the psychological burden of the person. In this example, the identification unit can transmit necessary notifications to the mobile object by identifying the mobile object used by the person instead of or in addition to identifying the person.

[0181] For example, the control unit 11 can control the communication unit 13 to send a notification on the road or on a signboard to urge a moving body in which a person with low mobility is riding to move to the center lane or to slow down earlier than usual. The control unit 11 can also control the communication unit 13 to display a preferred route on the road or on a signboard to a moving body in which a person with a high stress level is riding.

[0182] Furthermore, the control unit 11 can be configured to control the transportation facility 20 as well as an autonomous mobile object that autonomously travels along a route on which the transportation facility 20 is installed, based on the mobility and psychological state of the person. For example, the control unit 11 not only controls the transportation facility 20 based on the mobility and psychological state of the person, but also optimally controls the autonomous mobile object that autonomously travels along a route on which the traffic facility 20 to be controlled is installed as a set.

[0183] More specifically, the control unit 11 can control the autonomous moving body to lower the upper speed limit when there is a person who is determined to have low mobility, such as a person with a small baby or a person carrying a heavy backpack, or when there is another person with low mobility. Here, the upper speed limit can be lowered by tuning the way the autonomous moving body runs in automatic driving, for example. In addition, the control unit 11 can also control the autonomous moving body in which a person with low mobility is riding to move toward the center lane on the road or on a signboard, or to decelerate earlier than usual. In addition to or instead of lowering the upper speed limit, the control unit 11 can also control the autonomous moving body to change the driving route to a route with fewer curves. For example, the control unit 11 can control the autonomous moving body in which a person with a high stress level is riding to set a preferable route, such as one with fewer curves.

[0184] The control unit 11 can control any type of autonomous moving body. However, the control unit 11 can control differently depending on whether a person is riding on a certain type of autonomous moving body or another type of autonomous moving body.

[0185] In this way, the traffic facility control device 10 can expand the facilities to be controlled to include autonomous mobile bodies used by people, and can move the autonomous mobile body so as to provide the user of the autonomous mobile body with physical safety and satisfaction (comfort) that takes into account the user's mobility. Therefore, with such a traffic facility control device 10, even a user who is using an autonomous mobile body for the first time can receive a mobility service using the autonomous mobile body safely and comfortably, and of course, can receive the mobility service in the same way the next time or later they use the autonomous mobile body.

[0186] Next, examples of other information referred to when controlling the traffic facility 20 will be described with reference to Fig. 8 and Fig. 9. Fig. 8 is a block diagram showing another example of the configuration of a traffic system including the traffic facility control system 1 of Fig. 1, and Fig. 9 is a diagram showing an example of a table used to collect information for controlling the traffic facility in the traffic system of Fig. 8.

[0187] The transportation system 2a shown in FIG. 8 is the transportation system 2 in FIG. 3, which is provided with a disease information DB 12e, which is a DB storing disease information. The disease information DB 12e can be stored in an external server device connected to the traffic facility control device 10, and such an example will be described. However, the disease information DB 12e can also be stored in the storage unit 12, and for example, the disease information can be stored in association with individual identification information in the person information DB 12d. The information stored as the disease information DB 12e can be updated to the latest information as appropriate. The external server device can be operated, for example, by a hospital or the like, but is not limited thereto.

[0188] The traffic facility control device 10 shown in Fig. 8 may further include an acquisition unit (for convenience, referred to as a third acquisition unit) that acquires disease information indicating a disease related to the walking ability of the person identified by the identification unit. In the example of Fig. 8, the communication unit 13 and the control unit 11 that controls the acquisition are examples of this third acquisition unit.

[0189] Then, the control unit 11 controls the transportation facility 20 based on the mobility of the person, the person's psychological state, and the disease information. For example, when the disease information of the detected person indicates paralysis of one leg, the control unit 11 controls the transportation facility 20 with the mobility level of the detected person lowered by one level.

[0190] As a result, the traffic facility control device 10 shown in FIG. 8 can control the traffic facility 20 taking into account disease information, including diseases related to a person's actual walking, enabling control that is more in line with the person's condition.

[0191] Here, an example of information acquisition by the control unit 11 will be described with reference to the table in Fig. 9. First, the control unit 11 identifies a person from the imaging data obtained by the camera 30. Then, the control unit 11 searches for the learning model 12b, which is a model for the mobility ability dedicated to the person, and the learning model 12c, which is a model for the mental state dedicated to the person, with reference to the table shown in Fig. 9, inputs information such as the imaging data required for each, and obtains the detection result and the judgment result, respectively. The control unit 11 also acquires the disease information of the person with reference to the table shown in Fig. 9.

[0192] Based on the detection results, judgment results, and disease information collected in this manner, the control unit 11 refers to the table 12t illustrated in FIG. 7, reads out the transportation facility 20 to be controlled and its control details, and controls the transportation facility 20.

[0193] The example of acquiring information described with reference to Fig. 9 can be similarly used in the transportation system 3 shown in Fig. 3, except for acquiring disease information. The example of acquiring disease information described with reference to Fig. 9 can also be used in a method of acquiring information for identifying a person, a mobile terminal device used by the person, or a mobile object.

[0194] Next, an example of an arrangement of the transportation facility 20 different from those in Figures 4 to 6 will be described with reference to Figure 10. Figure 10 is a schematic top view showing another example of an arrangement of the transportation facility 20 in the transportation system 2 in Figure 3 or the transportation system 2a in Figure 8.

[0195] As illustrated in FIG. 10, a part of the transportation network can be developed as a group of roads for specific users, such as a road 71 for cars and motorcycles, a road 72 for bicycles, and a road 73 for pedestrians. Here, the bicycle road 72 can be defined as a road for low-speed personal mobility, or a road for bicycles and the personal mobility. Although the roads 71 ​​to 73 are illustrated as straight lines for convenience, they can also include curves. In addition, the road 71 is illustrated as a two-lane road including an oncoming lane, but it can also be a one-way road with one or more lanes, and in that case, a road heading in the opposite direction similar to the road 71 can be provided.

[0196] In the traffic network shown in FIG. 10, the dedicated road 71 is provided with a sensing zone 30a and a camera 30e, and as an example of the traffic facility 20, a digital signage 20p and a liftable median strip 74 equivalent to the liftable median strip 20j are provided. The bicycle road 72 is provided with a sensing zone 30a and a camera 30e, and as an example of the traffic facility 20, a digital signage 20p is provided. The pedestrian road 73 is provided with a sensing zone 30a and a camera 30e, and as an example of the traffic facility 20, a digital signage 20p, a liftable braille block 20v, and a display variable sign 20w are provided. Of course, the installation interval of the camera 30e and the position of the sensing zone 30a do not matter in each road 71 to 73, and other types of traffic facilities 20 can also be installed. In FIG. 10, trees 75 are planted beside each road 71 to 73.

[0197] In such a configuration, the control unit 11 obtains detection results, determination results, etc., and based on them, controls the traffic facility 20. Compared to the areas illustrated in Figures 4 to 6, the frequency of control is lower because there are no intersections, but the control unit 11 will control the traffic facility 20 at an appropriate time based on the detection results, determination results, etc.

[0198] For example, on a dedicated road 71, when the control unit 11 detects that an autonomous moving body M2 carrying a person with poor walking ability and a high stress level is traveling, the control unit 11 controls the autonomous moving body M2 to lower its upper limit speed and also controls the digital signage 20p to display this information, thereby notifying other vehicles M1 and M2.

[0199] Also, for example, on a bicycle-only road 72, when the control unit 11 detects a bicycle B1 ridden by a person U5 with poor walking ability and a high stress level, it controls the digital signage 20p to display a warning notice.

[0200] Also, for example, in the pedestrian-only road 73, when the control unit 11 detects a person with low walking ability and a high stress level, such as a person U4 using a wheelchair WC or a person U3 using a white cane ST, the control unit 11 controls the display variable sign 20w or the digital signage 20p to display a notice informing other people that there is a person using a wheelchair or a white cane. When the control unit 11 detects a person with low walking ability and a high stress level, such as a person U3 using a white cane ST, or when the control unit 11 detects a person with walking ability corresponding to the person U3 using a white cane ST regardless of stress level, the control unit 11 controls the liftable braille block 20v to lift the rod-shaped member to make the braille block appear.

[0201] In addition, other moving objects may also intrude into roads for automobiles only, roads for motorcycles only, roads for automobiles and motorcycles only, roads for bicycles only, roads for pedestrians only, etc. For example, pedestrians may intrude into roads for automobiles only, and vehicles may intrude into roads for pedestrians only. Therefore, even if a person or vehicle that is not suitable for use of such a road intrudes, the control unit 11 may display a warning on the notification device based on the detection result, the determination result, etc., or may control the other type of traffic facility 20 so that a pedestrian is not injured.

[0202] Finally, a configuration example of a learning system that generates the above-mentioned various learning models will be described with reference to Fig. 11 to Fig. 13. Fig. 11 is a block diagram showing a configuration example of a learning system that generates a learning model used in the transportation system 2 in Fig. 3 or the transportation system 2a in Fig. 8. Fig. 12 is a diagram showing an example of teacher data used in the learning system in Fig. 11, and Fig. 13 is a diagram showing another example of teacher data used in the learning system in Fig. 11.

[0203] 11 may include a control unit 81, an input unit 82, and a storage unit 83. The learning system 80 may be constructed using a computer such as a PC for AI (Artificial Intelligence) learning. However, the learning system 80 may be configured as a single device or may have functions distributed across multiple devices.

[0204] The control unit 81 controls the entire learning system 80. The control unit 81 can be realized, for example, by an integrated circuit, and can be realized, for example, by a processor, a working memory, and a non-volatile storage device. A control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby fulfilling the function of the control unit 81. The control program can include a learning program that executes learning. Note that the storage device can also utilize the memory unit 83.

[0205] The input unit 82 can be configured with at least one of an interface for performing data input operations and a communication interface for inputting data from an external device via communication. The input unit 82 inputs a data set of teacher data 84 required for learning, and stores it in the memory unit 83 so that it can be referenced during learning. The memory unit 83 can store this teacher data 84, and can store a learning model 85 as an unlearned model.

[0206] In the processing by the learning system 80, the control unit 81 performs machine learning on a learning model 85 as an unlearned model based on teacher data 84, and sets the learning model 85 as a trained model. Furthermore, when re-learning is required, the learning model 85 as a trained model can be re-trained based on a newly prepared data set.

[0207] The teacher data 84 for generating the learning model 12b can be a data set consisting of the imaging data and the correct answer data as described above, but can also be a data set as exemplified in FIG. 12. The data set exemplified in FIG. 12 includes, as explanatory variables, range of motion information, which is information obtained by detecting a person's range of motion, and walking speed information, which is information obtained by calculating a person's walking speed. In addition, the data set exemplified in FIG. 12 includes, as a target variable, a value obtained by having the person answer a question indicating a level of mobility or by having a doctor or the like determine the level. Here, an example is shown in which mobility is expressed at three levels, high, normal, and low, but the present invention is not limited to this.

[0208] The teacher data 84 for generating the learning model 12c can be a data set consisting of at least one of vital information and imaging data and correct answer data as described above, for example, a data set as illustrated in FIG. 13. The data set illustrated in FIG. 13 includes pulse information and body temperature information, which are part of vital information, as explanatory variables, and includes a level indicating a psychological state as a target variable. This level includes a value obtained by having the person answer a question. Here, an example is shown in which the psychological state is expressed at three levels, good, normal, and poor, but the present invention is not limited to this.

[0209] In addition, when generating a learning model that integrates learning model 12c and learning models 12b and 12c, a similar learning system can be used, although only the algorithm, teacher data, etc. are different. In this case, the teacher data 84 can be, for example, data that combines the data sets illustrated in Figures 12 and 13. In addition, when generating other learning models, a similar learning system can be used, although only the algorithm, teacher data, etc. are different.

[0210] <Other embodiments> The traffic facility control system according to the above-described embodiment is not limited to the above-described configuration example, and is not limited to a configuration for executing the above-described control example, as long as it can perform its functions.

[0211] Each of the devices constituting the traffic facility control system described in the above embodiment may have the following hardware configuration. Figure 14 is a diagram showing an example of the hardware configuration included in the device.

[0212] 14 is a device in the traffic facility control system according to the above embodiment, and includes a processor 101, a memory 102, and a communication interface (I / F) 103. The processor 101 may be, for example, a CPU, a GPU (Graphics Processing Unit), or an MPU (Micro Processor Unit) also called a microprocessor. The processor 101 may include multiple processors.

[0213] The functions of each part in each device can be realized by processor 101 reading a program stored in memory 102 and executing it in cooperation with communication I / F 103. Note that communication I / F 103 is provided with at least one of a wireless communication I / F and a wired communication I / F depending on the device. In addition, each device can include an I / F with, for example, a sensor, an input / output device, etc., that is necessary depending on the device.

[0214] The above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiments when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disk (DVD), Blu-ray® disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals.

[0215] The present disclosure is not limited to the above-described embodiment, and can be appropriately modified without departing from the spirit and scope of the present disclosure. In addition, the present disclosure includes implementation in which the examples in the above-described embodiment are appropriately combined. [Explanation of symbols]

[0216] 1 Traffic facility control system 2.2a Transportation System 1a Detection unit 1b Judgment part 1c Control section 10 Traffic facility control device 11 Control section 12 Storage section 12a Equipment information DB 12b, 12c Learning Model 12d Person information DB 12e Disease Information DB 13. Communications Department 20a, 20b Traffic equipment (traffic lights) 20c Pedestrian crossing signal 20d, 20e, 20f, 20g traffic lights 20j, 20k, 74 Elevating median strip 20p Digital Signage 20q, 20r, 20s, 20t elevator 20v Elevating Braille Blocks 20w variable display sign 20x Elevating Guardrails 30a Camera (sensing zone) 30b, 30c, 30d, 30e Camera 40, 40a, 40b Wearable devices 50 Crosswalk 51, 52, 53, 56, 57, 60, 61 Lanes (Roadways) 54, 55, 58, 59, 62, 63 Sidewalk 64, 65 Pedestrian Bridge 71, 72, 73 Dedicated roads 75 Trees 80 Learning System 81 Control Unit 82 Input section 83 Memory section 84 Teacher Data 85 Learning Model 100 devices 101 Processor 102 Memory 103 Communication Interface B1 Bicycle M1 Automobile M2 Autonomous Mobile Vehicle (Autonomous Mobile Bus) ST White Cane U1, U1a, U2, U3, U4, U5 people WC Wheelchair

Claims

1. A detection unit that detects the mobility of a person; A determination unit for determining the person's psychological state; and a control unit that controls transportation facilities installed in at least one of the vicinity of the person's current location, a location on the route the person is traveling, and a location along the route, based on the person's mobility and psychological state; the person's state of mind is the person's stress level; The control unit controls the transportation facility to improve safety for the movement of the person when the stress level of the person is higher than a predetermined level. Traffic facility control system.

2. The detection unit detects at least the walking ability of the person as the mobility of the person. The traffic facility control system according to claim 1 .

3. The detection unit detects the presence or absence of carrying items or accompanying persons that hinder the movement of the person, and calculates the mobility of the person based on the detection result, thereby detecting the mobility of the person.

3. A traffic facility control system according to claim 1 or 2.

4. a first acquisition unit that acquires vital information of the person measured by a measuring device worn by the person, The determination unit determines a psychological state of the person based on the vital sign information.

3. A traffic facility control system according to claim 1 or 2.

5. An identification unit for identifying the person, The determination unit determines a psychological state of the person from the vital information by using a learning model machine-learned on the person identified by the identification unit.

5. A traffic facility control system according to claim 4.

6. a second acquisition unit that acquires imaging data of a facial image of the person; The determination unit determines the psychological state of the person based on the imaging data.

3. A traffic facility control system according to claim 1 or 2.

7. An identification unit for identifying the person, The determination unit determines a psychological state of the person from the imaging data by using a learning model machine-learned on the person identified by the identification unit. The traffic facility control system according to claim 6.

8. The control unit controls at least one of a timing of a change and a duration of a changed state for at least one of a change in display and a change in shape of the traffic facility.

3. A traffic facility control system according to claim 1 or 2.

9. An identification unit for identifying the person; a third acquisition unit that acquires disease information indicating a disease related to the walking ability of the person identified by the identification unit; Equipped with The control unit controls the transportation facility based on the mobility of the person, the psychological state of the person, and the disease information.

3. A traffic facility control system according to claim 1 or 2.

10. A prediction unit is provided for predicting a direction in which the person is moving, The control unit controls the traffic facility based on the predicted direction of travel of the person, the mobility of the person, and the psychological state of the person.

3. A traffic facility control system according to claim 1 or 2.

11. a viewing determination unit that determines whether the person is viewing the mobile terminal device, The control unit controls the traffic facility based on the mobility of the person, the psychological state of the person, and the judgment result by the visibility judgment unit.

3. A traffic facility control system according to claim 1 or 2.

12. The control unit notifies a notification device provided as part of the transportation facility according to the content of control for facilities other than the notification device among the transportation facilities.

3. A traffic facility control system according to claim 1 or 2.

13. An identification unit for identifying the person; a notification unit that notifies a terminal device used by the person identified by the identification unit according to the content of control over the transportation facility; The traffic facility control system according to claim 1 or 2, comprising:

14. An identification unit for identifying the person; an inquiry unit that inquires of a terminal device used by the person identified by the identification unit about whether or not to control the transportation facility based on the mobility and psychological state of the person; The traffic facility control system according to claim 1 or 2, comprising:

15. The detection unit detects the mobility of a user of a moving body as a person to be detected, The control unit controls transportation facilities installed in at least one of a vicinity of a current location of the moving object, a route along which the moving object moves, and a location along the route, based on the mobility ability of the person and the psychological state of the person. The traffic facility control system according to claim 1 .

16. Input the results of detecting a person's mobility, inputting the result of the judgment of the person's psychological state; Executing equipment control to control transportation equipment installed in at least one of a vicinity of a current location of the person, a location on a route traveled by the person, and a location along the route based on the mobility capability of the person and the psychological state of the person; the person's state of mind is the person's stress level; The facility control is a control of the transportation facility to improve safety for the movement of the person when the stress level of the person is higher than a predetermined level. Traffic facility control method.

17. On the computer, Input the results of detecting a person's mobility, inputting the result of the judgment of the person's psychological state; executing equipment control to control transportation equipment installed in at least one of a vicinity of a current location of the person, a location on a route traveled by the person, and a location along the route, based on the mobility capability of the person and the psychological state of the person; A process comprising: the person's state of mind is the person's stress level; The facility control is a control of the transportation facility to improve safety for the movement of the person when the stress level of the person is higher than a predetermined level. A program for executing a process.

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