JP7094418B1 - Traffic control equipment and traffic control system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a traffic control device for performing traffic control that does not hinder the smooth running of a vehicle. SOLUTION: A moving object detection unit 22 that extracts position information and speed information of a moving object in an area from information from a roadside sensor 10 and a position information of a vehicle 30, and dynamic map information from the position information of the moving object in the area. The dynamic map update unit 23 to be updated, the position estimation unit 24 that calculates the future predicted position of the moving object in the area from the position information and the velocity information of the moving object in the area, and the collision margin time obtained from the predicted position and the collision margin. The collision risk calculation unit 25 that calculates the time distribution of the risk level from the time and calculates the notification period from the time distribution of the risk level, the mediation route determination unit 26 that determines the mediation route from the predicted position, and the warning and mediation during the notification period. It is provided with an information notification unit 27 that notifies the vehicle 30 of the route. [Selection diagram] Fig. 1

Description

The present application relates to traffic control equipment and traffic control systems.

A traffic control system has been proposed that generates a route for a specific vehicle of interest to travel on a travel path laid in a certain area without colliding with another vehicle or a pedestrian. In the traffic control system, sensors mounted on the vehicle or sensors installed on the roadside can be used to detect other vehicles or pedestrians moving in the area, and other vehicles or pedestrians can collide with the vehicle of interest. Generate a route to avoid collisions when there is a possibility. In such a traffic control system, if the accuracy of collision risk prediction is low, a route for avoiding a collision may be generated more than necessary, which may hinder the smooth running of the vehicle of interest.

Therefore, a route generation device has been proposed that generates a plurality of route candidates for avoiding a collision in consideration of the moving speed, the probability of a collision, and the time until the collision, and generates a route that does not hinder the smooth movement of the vehicle of interest. (For example, see Patent Document 1).

Japanese Unexamined Patent Publication No. 2019-185219

The route generator shown in Patent Document 1 estimates the future position of a dynamic object detected by monitoring the surroundings, and has a probability of colliding with another vehicle or pedestrian, and another vehicle or pedestrian. From the information of the time until the collision with the person, the route where the collision does not occur is generated.

However, it is not considered at what timing the information of the route generated in this way is notified to the vehicle, or how long the information of the generated route is valid. For example, if the timing of a collision warning or a collision avoidance route notification is too early, an excessive collision avoidance operation will be performed, which hinders smooth running of the entire area. On the contrary, if the timing is late, the avoidance response cannot be made in time and a collision occurs. Alternatively, if the collision can be prevented by avoiding the vehicle on the other side related to the collision, unnecessary avoidance operation will be performed even though the risk of the collision has already disappeared, and the entire area is also smooth. There was a problem that it would hinder driving.

The present application has been made to solve the above-mentioned problems, and an object of the present application is to provide a traffic control device and a traffic control system that perform traffic control that does not hinder the smooth running of a vehicle.

The traffic control device disclosed in the present application includes information from a roadside sensor that detects an object moving in an area, a sensor information receiving unit that receives position information of a vehicle traveling in the area, and information from a roadside sensor. And the moving object detector that extracts the position information and speed information of the moving object in the area moving in the area including the vehicle from the position information of the vehicle, and the movement to update the dynamic map information from the position information of the moving object in the area. The target map update unit, the position estimation unit that calculates the future predicted position of the moving object in the area from the position information of the moving object in the area and the velocity information of the moving object in the area, and the collision margin time by obtaining the collision margin time from the predicted position. The collision risk calculation unit that calculates the time distribution of the risk level from the time and the notification period from the time distribution of the risk level, the mediation route determination unit that determines the mediation route from the predicted position, and the warning and mediation route in the notification period. It is equipped with an information notification unit that notifies the vehicle.

The traffic control device disclosed in the present application includes a dynamic map update unit that updates dynamic map information from the position information of a moving object in the area, and a dynamic map updating unit that updates the dynamic map information from the position information of the moving object in the area and the speed information of the moving object in the area. Collision risk that calculates the collision margin time from the position estimation unit that calculates the future predicted position of the moving object and the predicted position, calculates the risk level time distribution from the collision margin time, and calculates the notification period from the risk level time distribution. Since it is provided with a calculation unit, an arbitration route determination unit that determines the arbitration route from the predicted position, and an information notification unit that notifies the vehicle of the warning and the arbitration route during the notification period, the vehicle collides with the information of the arbitration route. Depending on the time until and the high risk level, it can be received at a timing that is neither too early nor too late, and does not interfere with the smooth running of the vehicle.

It is a block diagram which shows the structure of the traffic control device and the traffic control system by Embodiment 1. FIG. It is a figure which shows the specific example of the traffic control system by Embodiment 1. FIG. It is a flowchart explaining the operation of the traffic control device by Embodiment 1. FIG. It is a figure which shows the example of the feature and attribute of the moving object in an area extracted by the moving object detection part in Embodiment 1. FIG. It is a figure which shows the dynamic map information created by the dynamic map update part and the position estimation part in Embodiment 1. FIG. It is a figure for demonstrating the processing of the collision risk calculation part in Embodiment 1. FIG. It is a figure for demonstrating the processing of the collision risk calculation part in Embodiment 1. FIG. It is a figure for demonstrating the processing of the collision risk calculation part in Embodiment 1. FIG. It is a schematic diagram which shows an example of the hardware of the traffic control device by Embodiment 1. FIG.

Hereinafter, the traffic control device and the traffic control system according to the embodiment for carrying out the present application will be described in detail with reference to the drawings. In each figure, the same reference numerals indicate the same or corresponding parts.

Embodiment 1.
FIG. 1 is a block diagram showing a configuration of a traffic control device 20 and a traffic control system 1 according to the first embodiment. The traffic control system 1 includes a roadside sensor 10, a vehicle 30, and a traffic control device 20. The traffic control device 20 includes a sensor information receiving unit 21, a moving object detection unit 22, a dynamic map updating unit 23, a position estimation unit 24, a collision risk calculation unit 25, an arbitration route determination unit 26, and an information notification unit 27. ..

The roadside sensor 10 detects an object moving in the area and transmits information on the detected object to the sensor information receiving unit 21 of the traffic control device 20. The vehicle 30 includes an in-vehicle sensor 31 and an information receiving unit 32. The in-vehicle sensor 31 estimates the position of the own vehicle and transmits the estimated position information to the sensor information receiving unit 21 of the traffic control device 20. The information receiving unit 32 receives information from the information notification unit 27 of the traffic control device 20.

FIG. 2 is a diagram showing a specific example of the traffic control system according to the first embodiment. In the traffic control system shown in FIG. 2, the central control center 120 controls the entire traffic in the jurisdiction area 101. The jurisdiction area 101 has a station area 141 and an intersection area 142, the first traffic control device 121 controls the traffic in the station area 141, and the second traffic control device 122 controls the traffic in the intersection area 142. .. The first traffic control device 121 and the second traffic control device 122 are the traffic control device 20 shown in FIG. The central control center 120 controls the first traffic control device 121 and the second traffic control device 122.

The roadside sensor 111 detects an object moving in the boarding / alighting space of the station facility, for example, the vehicle 130. The roadside sensor 111 is, for example, a sensing means for avoiding interference between the arrival and departure of the vehicle 130. The roadside sensor 112 detects an object moving on the sidewalk, for example, a pedestrian 131. The roadside sensor 112 is, for example, a sensing means for avoiding contact between the vehicle 130 and the pedestrian 131. The first traffic control device 121 receives the output of the roadside sensor 111 and the output of the roadside sensor 112.

The roadside sensor 113 detects a moving object at an intersection without a signal, and serves as a sensing means for avoiding a vehicle traveling stagnation due to a collision between vehicles or a concession between vehicles. The second traffic control device 122 receives the output of the roadside sensor 113.

Next, the operation of the traffic control device 20 according to the first embodiment will be described. FIG. 3 is a flowchart illustrating the operation of the traffic control device 20 according to the first embodiment. The vehicle-mounted sensor 31 of the vehicle 30 estimates the position of the own vehicle periodically or at a predetermined timing, and transmits the position information of the own vehicle to the sensor information receiving unit 21 of the traffic control device 20. In step S01, the sensor information receiving unit 21 receives the position information of the vehicle 30 from the vehicle-mounted sensor 31, transmits the received information to the moving object detection unit 22, and proceeds to step S02. As shown in FIG. 2, when there are a plurality of vehicles in one area, the sensor information receiving unit 21 receives each position information from each vehicle. The in-vehicle sensor 31 of the vehicle 30 is supposed to transmit the position information of the own vehicle, but further measures the position of another vehicle or the position of a pedestrian, and also transmits the position information to the sensor information receiving unit 21. You may. Further, the sensor information receiving unit 21 may request the vehicle 30 to transmit the position information, and the vehicle 30 that has received the request may send the position information of the own vehicle to the sensor information receiving unit 21.

The roadside sensor 10 detects an object moving in the detection area such as a vehicle or a pedestrian, and transmits information on the detected moving object to the sensor information receiving unit 21 of the traffic control device 20. The roadside sensor 10 is, for example, LiDAR (Light-Detection and Ranking), a millimeter-wave radar, or a camera, and may be a combination of two or more of these. In step S02, the sensor information receiving unit 21 confirms whether or not the information of the moving object is received from the roadside sensor 10, and if it is received, transmits the received information to the moving object detecting unit 22 and proceeds to step S03. If it has not been received, the process returns to step S01. In the first embodiment, the time when the moving object is detected by the roadside sensor 10 will be described as T.

In step S03, the moving object detection unit 22 uses an object moving in the area including the vehicle 30 as a moving object in the area, and from the information of the moving object received from the sensor information receiving unit 21 and the position information of the vehicle 30, the area The position information and the velocity information of the inward moving object are extracted and output to the dynamic map update unit 23, and the process proceeds to step S04. FIG. 4 is a diagram showing an example of features and attributes of a moving object in the area extracted by the moving object detecting unit 22. Features of moving objects in the area include, for example, position, size, attitude, and velocity information. The location information includes, for example, latitude, longitude, and altitude information on the map. The size includes, for example, height, width, and depth information. The posture includes, for example, information on the azimuth angle of the posture. For example, when the speed of a moving object is expressed by the speed in the north-south direction and the speed in the east-west direction, the speed in the x direction, which is the speed positive in the east direction, and the speed in the y direction, which is the speed positive in the south direction. Contains speed information. The attributes include, for example, information that the detected moving object is an ordinary vehicle, a large vehicle, a bus, a truck, a motorcycle or a pedestrian. The method of extracting the features and attributes of the moving object in the area by the moving object detecting unit 22 using the information received from the roadside sensor 10 will be described below. For example, when the roadside sensor 10 is LiDAR, the point cloud data obtained as the output of LiDAR is subjected to clustering processing, the attitude information is extracted from the obtained information of each class, and the center of gravity of the mass of each class is represented by each object. The speed can be obtained by observing the time change of the representative position as the position. For example, when the roadside sensor 10 is a millimeter-wave radar, the position and azimuth of each object can be obtained by performing segmentation processing and obtaining attributes such as the position of the center of gravity, the width, and the number of measurement points of each segment. For example, when the roadside sensor 10 is a camera, a specific identification target is set in advance, and the identification target is detected by image processing from the data obtained from the camera to obtain information on the position, size, posture, speed, and attributes. Obtainable.

In step S04, the dynamic map updating unit 23 moves at time T when the moving object in the area is detected by the roadside sensor 10 using the position information of the moving object in the area extracted by the moving object detecting unit 22 in step S03. The target map information is updated, and the process proceeds to step S05. In step S05, the position estimation unit 24 advances by t from T, which is the previous time, using the position information of the moving object in the area and the velocity information of the moving object in the area extracted by the moving object detecting unit 22 in step S03. The position of the moving object in the area at the time T + t is estimated, the dynamic map information at the time T + t is created, and the process proceeds to step S06.

FIG. 5 is a diagram showing dynamic map information created by the dynamic map updating unit 23 and the position estimation unit 24. The uppermost figure of FIG. 5 is a diagram showing the dynamic map information 40 at the time T updated by the dynamic map update unit 23 in step S04, and is a diagram showing the first moving body 41 and the second moving body at the time T. 42 is mapped on top of the dynamic map information 40. The first moving body 41 and the second moving body 42 are mapped on the dynamic map information 40 using the position information extracted by the moving object detection unit 22 in step S03. In FIG. 5, the x-axis is, for example, an axis indicating the east-west direction with the east direction as positive, and the y-axis is an axis indicating the north-south direction with the south direction as positive, for example.

The second to fourth figures from the top of FIG. 5 are views showing how the position estimation unit 24 created future dynamic map information in step S05. In step S05, the position estimation unit 24 estimates the position of the moving object in each area at the time T + t, where t is the time step when predicting the future. In the second figure from the top of FIG. 5, the position estimation unit 24 predicts the predicted position 51 at the time T + t of the first moving body 41 and the predicted position at the time T + t of the second moving body 42. 52 is predicted, and the predicted position 51 and the predicted position 52 are mapped on the dynamic map information 50 at time T + t. The respective positions of the predicted position 51 and the predicted position 52 are obtained by using the information of the dynamic map information 40 and the speed information extracted by the moving object detection unit 22 in step S03. Alternatively, when information on the positions of the first moving body 41 and the second moving body 42 at a plurality of past times is stored, the positions of the predicted position 51 and the predicted position 52 may be obtained using these information. good. In FIG. 5, the time axis is the time axis, the downward direction in FIG. 5 is the future direction, and the dynamic map information 50 indicates a future time point rather than the dynamic map information 40.

In step S06, the collision risk calculation unit 25 calculates the distance between the predicted position 51 and the predicted position 52 in the dynamic map information 50 in the second figure from the top of FIG. In step S07, the collision risk calculation unit 25 determines whether the distance between the predicted position 51 and the predicted position 52 is smaller than a predetermined threshold value, and since it is not smaller than the threshold value, a collision occurs at time T + t. It is presumed not to do so, the process returns to step S05, and the position at the time T + 2t, which is further advanced by t, is predicted.

In the third figure from the top of FIG. 5, in the second step S05, the position estimation unit 24 has the predicted position 61, which is the predicted position at the time T + 2t of the first moving body 41, and the time T + 2t of the second moving body 42. The predicted position 62, which is the predicted position in the above, is predicted, and the predicted position 61 and the predicted position 62 are mapped on the dynamic map information 60 at the time T + 2t. In the second step S06, the collision risk calculation unit 25 calculates the distance between the predicted position 61 and the predicted position 62 in the dynamic map information 60 of the third figure from the top of FIG. In the second step S07, the collision risk calculation unit 25 determines whether the distance between the predicted position 61 and the predicted position 62 is smaller than the predetermined threshold value, and is not smaller than the threshold value. Therefore, at time T + 2t. It is estimated that no collision will occur, the process returns to step S05, and the position at the time T + 3t, which is further advanced by t, is predicted.

In the fourth figure from the top of FIG. 5, in the third step S05, the position estimation unit 24 has the predicted position 71, which is the predicted position at the time T + 3t of the first moving body 41, and the time T + 3t of the second moving body 42. The predicted position 72, which is the predicted position in the above, is predicted, and the predicted position 71 and the predicted position 72 are mapped on the dynamic map information 70 at the time T + 3t. In the third step S06, the collision risk calculation unit 25 calculates the distance between the predicted position 71 and the predicted position 72 in the dynamic map information 70 in the fourth figure from the top of FIG. In the third step S07, the collision risk calculation unit 25 determines whether the distance between the predicted position 71 and the predicted position 72 is smaller than a predetermined threshold value, and since it is smaller than the threshold value, proceeds to step S08. .. In step S08, the collision risk calculation unit 25 estimates that a collision will occur at time T + 3t, and proceeds to step S09 with the collision margin time TTC (Time To Collection), which is the time from time T to collision, set to 3t.

In the explanations of FIGS. 3 and 5, the time step t when predicting the position of a moving object in the area in the future is fixed, but the length of time until the prediction can be correctly known, and the future If the position can be predicted correctly, the time step when predicting the future may not be constant or may be variable. In FIG. 5, an example of determining the collision of two moving objects in the area of the first moving body 41 and the second moving body 42 is shown, but the number of moving objects in the area is not limited to two. Collision of three or more moving objects in the area may be determined.

In step S09 of FIG. 3, the collision risk calculation unit 25 calculates the time distribution of the risk levels of the first moving body 41 and the second moving body 42 from the information of the collision margin time calculated in step S08, and first moves. The notification period for notifying the body 41 and the second moving body 42 of the collision warning and the collision avoidance route is calculated, and the process proceeds to step S10.

6 to 8 are diagrams for explaining the processing of the collision risk calculation unit 25. 6 to 8 show an example of the risk level obtained by the collision risk calculation unit 25, FIG. 6 shows an example in which the collision margin time is short, and FIG. 7 shows an example in which the collision margin time is medium. 8 shows an example in which the collision margin time is long. In FIGS. 6 to 8, the collision margin time is shown as TTC. The figures on the left side of FIGS. 6 to 8 show the relationship between the risk level and the collision margin time, and the figures on the right side of FIGS. 6 to 8 show the risk level and the warning and collision avoidance routes. It is a figure which showed the relationship with the notification period to notify. In FIGS. 6 to 8, the horizontal axis represents the time axis when the time T is set to zero, and the vertical axis represents the magnitude of the risk level.

The collision risk calculation unit 25 calculates the time distribution of the risk level based on the collision margin time obtained from the dynamic map information. For the time distribution of the risk level, the peak value is taken in the collision margin time, the peak value of the risk level is high when the collision margin time is short, and the peak value of the risk level is low when the collision margin time is long. The shorter the collision margin time, the higher the peak value of the calculated risk level. In addition, the risk level value increases as the time increases from zero, becomes the highest when the collision margin time elapses, decreases after the collision margin time, and finally becomes zero. And. By setting the time distribution of the risk level as described above, the shorter the collision margin time, the more difficult it is to avoid the collision and the higher the risk. It can be reflected in the time distribution of the risk level that the risk decreases as the time increases from the time when the collision margin time elapses from T.

In the figure on the left of FIG. 6, the peak value of the risk level is high because the collision margin time is short, and it is shown that the risk level rises sharply toward the collision margin time. In the figure on the left of FIG. 7, the peak value of the risk level is medium because the collision margin time is in the middle period, and it is shown that the risk level rises not so steeply toward the collision margin time. Has been done. In the figure on the left of FIG. 8, the peak value of the risk level is low due to the long collision margin time, and it is shown that the risk level is slowly increasing toward the collision margin time.

The risk levels shown in FIGS. 6 to 8 are relative values. When the risk level is treated as an absolute value, the moving object detection unit 22 extracts the characteristics and attributes of the moving object in the area as shown in FIG. 4, and the collision risk calculation unit 25 not only the collision margin time but also the collision margin time. The time distribution of the risk level may be calculated using the characteristics and attributes of the moving object in the area related to the collision. For example, the moving object detection unit 22 extracts the features and attributes of the moving object in the area as shown in FIG. 4, and estimates the mass of the moving object in the area from the information of the extracted size. Further, in the collision risk calculation unit 25, first, as shown in FIGS. 6 to 8, the initial value of the time distribution of the risk level is obtained from the collision margin time, and then the mass of the moving object in the area related to the collision is obtained. Calculate the value of the product, relative velocity, or difference in azimuth angle, and multiply these values by the initial value of the time distribution of the risk level to obtain the value of the risk level. Also, if the opponent of the collision is a vulnerable person, for example, a motorcycle or a pedestrian against an ordinary vehicle, or an ordinary vehicle against a bus or a truck, depending on the attributes of moving objects in the area. The risk level may be multiplied by a certain coefficient. The moving object detection unit 22 further extracts the characteristics and attributes of the moving object in the area, and the collision risk calculation unit 25 uses the characteristics and attributes of the moving object in the area in addition to the collision margin time to determine the time distribution of the risk level. By calculating, the value of the risk level can be calculated more accurately, and the notification period for notifying the warning and the collision avoidance route can be obtained more accurately.

Next, the collision risk calculation unit 25 obtains a notification period for notifying the warning and the collision avoidance route from the risk level. If the timing of notifying the collision warning and the collision avoidance route is early, an excessive collision avoidance operation will be performed, which hinders the smooth running of the vehicle in the entire area. On the contrary, if the timing of notifying the collision warning and the collision avoidance route is late, the collision avoidance cannot be dealt with in time and a collision occurs. Alternatively, if the timing of the collision warning and the collision avoidance route is delayed, but the collision can be prevented by the avoidance behavior of the other vehicle related to the collision, even though the risk of the collision has already disappeared. Unnecessary avoidance operations will be performed, which hinders the smooth running of the vehicle in the entire area.

In the collision risk calculation unit 25, for example, the period in which the previously obtained risk level value exceeds a predetermined threshold value Th is set as the notification period, the beginning of the notification period is the notification start time T1, and the end of the notification period is notified. The end time is T2. The figures on the right side of FIGS. 6 to 8 show that the notification start time T1 and the notification end time T2 are obtained from the respective risk levels and the threshold value Th, and the period shown by the diagonal line is the notification period. .. By setting the period during which the risk level value obtained from the collision margin time exceeds the threshold value as the notification period, it is possible to notify the vehicle of the warning and arbitration route during the notification period according to the collision margin time and the risk level value. can. As a result, the vehicle can receive the information on the arbitration route at a timing that is neither too early nor too late, and does not interfere with the smooth running of the vehicle. Further, by setting the period in which the value of the risk level exceeds a predetermined threshold value Th as the notification period, the length of the notification period can be adjusted according to the magnitude of the threshold value Th. For example, if the threshold Th is increased, the notification period is shortened, and if the threshold Th is decreased, the notification period is lengthened.

In step S10, the arbitration path determination unit 26 refers to all the moving objects in the area related to the collision based on the information of the future predicted position of the moving object in the area estimated by the position estimation unit 24 in step S05. Then, the arbitration path, which is the path of the moving object in each area for avoiding the collision, is determined, and the process proceeds to step S11. The arbitration route determination unit 26 may determine the arbitration route from, for example, an evaluation value for avoiding a collision of moving objects in the area and an evaluation value of running efficiency. In step S11, the information notification unit 27 gives a warning during the notification period between the notification start time T1 and the notification end time T2 obtained by the collision risk calculation unit 25 in step S09, and the arbitration route determination unit 26 in step S10. The determined arbitration route is transmitted to all vehicles, and the process proceeds to step S12. In step S12, the traffic control device 20 confirms whether to end the process, returns to step S01 if the process is continued without ending, and ends the process as the traffic control device 20 if the process ends. ..

The warning and arbitration route transmitted from the information notification unit 27 in step S11 are received by the information reception unit 32 of the vehicle 30. At this time, the vehicle 30 ends the process if the received information is not related to the own vehicle, and if the received information is related to the own vehicle, the vehicle 30 is manually or automatically operated as necessary. Drive along the arbitration route and perform avoidance actions.

The sensor information receiving unit 21 receives the position information of the vehicle 30 from the in-vehicle sensor 31, and the information notification unit 27 transmits a warning and an arbitration route to the vehicle 30 during the notification period. 21 may receive pedestrian position information from a mobile terminal used by the pedestrian, and the information notification unit 27 may transmit a warning and an arbitration route to the mobile terminal during the notification period. The traffic control device 20 according to the first embodiment provides information on the position, speed, size, posture, or direction of a moving vehicle or pedestrian at a boarding / alighting place such as a road, an intersection, a parking lot, or a station in a specific area. , It is called dynamic map information by detecting with a plurality of roadside sensors 10 installed at a plurality of places in the area, or by receiving position information from a mobile terminal used by a vehicle or a pedestrian moving in the area. It can be reflected in the database in real time. In addition, vehicles or pedestrians moving within the area are always informed of the presence or absence of vehicles or pedestrians that hinder their movement, the time until the obstacle occurs, or the risks posed by the obstacle. It can be obtained in real time from the map information, and at the same time, it receives recommended routes to avoid the failure at a timing that is neither too early nor too late, depending on the time until the failure occurs and the high risk. be able to. As a result, for example, arbitration of the route or timing of the approaching vehicle and the departing vehicle in the boarding / alighting space such as a station, avoidance of contact between the vehicle and a person, arbitration of the intersection timing between multiple vehicles at an intersection without a traffic signal, and crossing a road. It realizes the movement of vehicles or pedestrians that does not significantly reduce the smoothness of traffic flow, such as the priority movement of pedestrians.

As described above, the traffic control device 20 according to the first embodiment receives information from the roadside sensor 10 that detects an object moving in the area and sensor information that receives the position information of the vehicle 30 traveling in the area. The moving object detection unit 22 that extracts the position information and the speed information of the moving object in the area moving in the area including the vehicle 30 from the information from the roadside sensor 10 and the position information of the vehicle 30, and the moving object detecting unit 22 in the area. The dynamic map update unit 23 that updates the dynamic map information from the position information of the object, and the position estimation that calculates the future predicted position of the moving object in the area from the position information of the moving object in the area and the velocity information of the moving object in the area. The collision risk calculation unit 25, which obtains the collision margin time from the predicted position, calculates the risk level time distribution from the collision margin time, and calculates the notification period from the risk level time distribution, and the arbitration route from the predicted position. Since the arbitration route determination unit 26 for determining the arbitration route and the information notification unit 27 for notifying the vehicle 30 of the warning and the arbitration route during the notification period are provided, the vehicle 30 can transmit the information of the arbitration route to the time to collision and the risk level. Depending on the height, it can be received at a timing that is neither too early nor too late, and does not interfere with the smooth running of the vehicle.

FIG. 9 is a schematic diagram showing an example of the hardware of the traffic control device 20 according to the first embodiment. The sensor information receiving unit 21 is a receiving device 201, and the information notification unit 27 is a transmitting device 202. The moving object detection unit 22, the dynamic map update unit 23, the position estimation unit 24, the collision risk calculation unit 25, and the arbitration route determination unit 26 are performed by a processor 203 such as a CPU and a system LSI that executes a program stored in the memory 204. It will be realized. Further, a plurality of processing circuits may cooperate to execute the above function. Further, the above functions may be realized by dedicated hardware. When the above functions are realized by dedicated hardware, the dedicated hardware is, for example, a single circuit, a composite circuit, a programmed processor, an ASIC, an FPGA, or a combination thereof. The above function may be realized by a combination of dedicated hardware and software, or a combination of dedicated hardware and firmware. The receiving device 201, the transmitting device 202, the processor 203, and the memory 204 are bus-connected to each other.

Although the present application describes exemplary embodiments, the various features, embodiments, and functions described in the embodiments are not limited to the application of a particular embodiment, either alone or. Various combinations are applicable to the embodiments.
Therefore, innumerable variations not exemplified are envisioned within the scope of the techniques disclosed in the present application. For example, it is assumed that at least one component is modified, added or omitted.

1 Traffic control system, 10 Roadside sensor, 20 Traffic control device, 21 Sensor information receiver, 22 Moving object detection unit, 23 Dynamic map update unit, 24 Position estimation unit, 25 Collision risk calculation unit, 26 Mediation route determination unit, 27 Information notification unit, 30 Vehicles, 31 In-vehicle sensor, 32 Information receiver, 40 Dynamic map information, 41 First moving body, 42 Second moving body, 50 Dynamic map information, 51 Predicted position, 52 Predicted position, 60 Dynamic map information, 61 predicted position, 62 predicted position, 70 dynamic map information, 71 predicted position, 72 predicted position, 101 jurisdiction area, 111, 112, 113 roadside sensor, 120 central control center, 121 first traffic control device , 122 Second traffic control device, 130 vehicles, 131 pedestrians, 141 station area, 142 intersection area, 201 receiver, 202 transmitter, 203 processor, 204 memory.

Claims (4)

A sensor information receiving unit that receives information from a roadside sensor that detects an object moving in the area and position information of a vehicle traveling in the area.
A moving object detection unit that extracts position information and speed information of a moving object in an area moving in the area including the vehicle from the information from the roadside sensor and the position information of the vehicle.
A dynamic map update unit that updates dynamic map information from the position information of moving objects in the area,
A position estimation unit that calculates the future predicted position of the moving object in the area from the position information of the moving object in the area and the velocity information of the moving object in the area.
A collision risk calculation unit that obtains a collision margin time from the predicted position, calculates a risk level time distribution from the collision margin time, and calculates a notification period from the risk level time distribution.
The arbitration route determination unit that determines the arbitration route from the predicted position,
A traffic control device including a warning and an information notification unit for notifying the vehicle of the arbitration route during the notification period. The collision risk calculation unit takes a peak value in the collision margin time, calculates a time distribution of the risk level in which the peak value of the risk level becomes higher as the collision margin time is shorter, and the value of the risk level is set in advance. The traffic control device according to claim 1, wherein a period exceeding a predetermined threshold value is calculated as the notification period. The moving object detection unit further extracts the features and attributes of the moving object in the area.
The traffic control device according to claim 1, wherein the collision risk calculation unit calculates a time distribution of the risk level by using the characteristics and attributes of the moving object in the area in addition to the collision margin time. The traffic control device according to any one of claims 1 to 3 and
With the vehicle
A traffic control system characterized by having the roadside sensor.

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