JP2022164163A - Traffic control apparatus and traffic control system - Google Patents

Abstract

To provide a traffic control apparatus that performs a traffic control for obstructing smooth traveling of a vehicle.SOLUTION: A traffic control apparatus comprises: a mobile object detection unit 22 that extracts position information and speed information of an intra-area mobile object from information from a roadside sensor 10 and position information from a vehicle 30; a dynamic map updating unit 23 that updates dynamic map information from the position information of the intra-area mobile object; a position estimation unit 24 that calculates a future prediction position of the intra-area mobile object from the position information and the speed information of the intra-area mobile object; a collision risk calculation unit 25 that obtains a collision tolerance time from the prediction position, calculates a time distribution of a risk level from the collision tolerance time, and calculates a notification period from the time distribution of the risk level; an adjustment route determination unit 26 that determines an adjustment route from the prediction position; and an information notification unit 27 that notifies the vehicle 30 of a warning and an adjustment route in the notification period.SELECTED DRAWING: Figure 1

Description

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

A traffic control system has been proposed that generates a route for a particular vehicle of interest to travel without colliding with other vehicles or pedestrians on a road laid within a certain area. Traffic control systems use sensors installed in vehicles or sensors installed on the roadside to detect other vehicles or pedestrians moving within an area, and it is possible for other vehicles or pedestrians to collide with the target vehicle. Generate paths to avoid collisions when possible. In such a traffic control system, when the prediction accuracy of the collision risk is low, more collision-avoiding routes than necessary are generated, which may hinder the smooth running of the vehicle of interest.

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

JP 2019-185219 A

In the route generation device disclosed in Patent Document 1, the future position of a dynamic object detected by monitoring the surroundings is estimated, and the probability of collision with other vehicles or pedestrians and the probability of collision with other vehicles or pedestrians are estimated. A collision-free route is generated from information on the time it takes to collide with a person.

However, no consideration is given to when the route information generated in this manner should be notified to the vehicle or how long the generated route information is valid. For example, if the timing of the warning of a collision or the notification of a collision avoidance route is too early, excessive collision avoidance operations will be performed, hindering the smooth running of the entire area. Conversely, if the timing is late, the avoidance response will not be in time and a collision will occur. Alternatively, if the collision could be prevented by the other vehicle involved in the collision by avoiding it, unnecessary avoidance maneuvers would be performed even though the risk of collision had already passed, and the area as a whole would still be smooth. There was a problem that it would hinder driving.

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

The traffic control device disclosed in the present application includes a sensor information receiving unit that receives information from a roadside sensor that detects objects moving within an area and position information of vehicles that are traveling within the area, and information from the roadside sensor. and a moving object detection unit that extracts position information and speed information of a moving object within an area that moves within the area including the vehicle from the position information of the vehicle; a target map updating unit, a position estimating unit that calculates a predicted future position of the moving object in the area from the position information of the moving object in the area and the speed information of the moving object in the area, a collision margin time from the predicted position, and a collision margin A collision risk calculation unit that calculates the time distribution of the risk level from time and calculates the notification period from the time distribution of the risk level, an arbitration route determination unit that determines the arbitration route from the predicted position, and a warning and arbitration route during the notification period. and an information notification unit that notifies the vehicle.

The traffic control device disclosed in the present application includes a dynamic map updating unit that updates dynamic map information from the position information of moving objects in the area, A position estimator that calculates the predicted future position of a moving object, a collision risk that calculates 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. Since the vehicle includes the calculation unit, the arbitration route determination unit that determines the arbitration route from the predicted position, and the information notification unit that notifies the vehicle of the warning and the arbitration route during the notification period, the vehicle can use the information of the arbitration route as the collision route. Depending on the time until completion and the level of risk, 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.

1 is a block diagram showing configurations of a traffic control device and a traffic control system according to Embodiment 1; FIG. 1 is a diagram showing a specific example of a traffic control system according to Embodiment 1; FIG. 4 is a flowchart for explaining the operation of the traffic control device according to Embodiment 1; 4 is a diagram showing an example of features and attributes of an in-area moving object extracted by a moving object detection unit according to Embodiment 1; FIG. 4 is a diagram showing dynamic map information created by a dynamic map updating unit and a position estimating unit according to Embodiment 1; FIG. FIG. 4 is a diagram for explaining processing of a collision risk calculation unit according to Embodiment 1; FIG. FIG. 4 is a diagram for explaining processing of a collision risk calculation unit according to Embodiment 1; FIG. FIG. 4 is a diagram for explaining processing of a collision risk calculation unit according to Embodiment 1; FIG. 1 is a schematic diagram showing an example of hardware of a traffic control device according to Embodiment 1; FIG.

Hereinafter, traffic control devices and traffic control systems according to embodiments for carrying out the present application will be described in detail with reference to the drawings. In each figure, the same reference numerals denote the same or corresponding parts.

Embodiment 1.
FIG. 1 is a block diagram showing configurations of a traffic control device 20 and a traffic control system 1 according to Embodiment 1. As shown in FIG. 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 receiver 21 , a moving object detector 22 , a dynamic map updater 23 , a position estimator 24 , a collision risk calculator 25 , an arbitration route determiner 26 and an information notifier 27 . .

The roadside sensor 10 detects an object moving within the area, and transmits information on the detected object to the sensor information receiving section 21 of the traffic control device 20 . The vehicle 30 includes an in-vehicle sensor 31 and an information receiver 32 . The in-vehicle sensor 31 estimates the position of the own vehicle and transmits the estimated position information to the sensor information receiving section 21 of the traffic control device 20 . The information receiving section 32 receives information from the information notification section 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, a central control center 120 controls the traffic of the entire area 101 under its jurisdiction. The jurisdiction area 101 has a station area 141 and an intersection area 142. The first traffic control device 121 controls traffic in the station area 141, and the second traffic control device 122 controls 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. Central control center 120 controls first traffic control device 121 and 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 serves as sensing means for avoiding interference between arrival and departure of the vehicle 130, for example. The roadside sensor 112 detects an object moving on the sidewalk, for example, a pedestrian 131 . The roadside sensor 112 serves as sensing means for avoiding contact between the vehicle 130 and the pedestrian 131, for example. 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 sensing means for avoiding collisions between vehicles or stagnation of vehicle travel due to mutual concessions 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 Embodiment 1 will be described. FIG. 3 is a flow chart explaining the operation of the traffic control device 20 according to the first embodiment. An in-vehicle 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 section 21 of the traffic control device 20 . In step S01, the sensor information receiving section 21 receives the position information of the vehicle 30 from the in-vehicle sensor 31, transmits the received information to the moving object detecting section 22, and proceeds to step S02. When there are multiple vehicles in one area as shown in FIG. 2, the sensor information receiving unit 21 receives position information from each vehicle. The in-vehicle sensor 31 of the vehicle 30 transmits the position information of the own vehicle, but also measures the positions of other vehicles or pedestrians, and transmits the position information together to the sensor information receiving unit 21. may Alternatively, the sensor information receiving section 21 may request the vehicle 30 to transmit position information, and the vehicle 30 receiving the request may transmit the position information of its own vehicle to the sensor information receiving section 21 .

The roadside sensor 10 detects an object such as a vehicle or a pedestrian that moves within the detection area, and transmits information on the detected moving object to the sensor information receiving section 21 of the traffic control device 20 . The roadside sensor 10 is, for example, a LiDAR (Light-Detection and Ranging), a millimeter wave radar, or a camera, or a combination of two or more of these. In step S02, the sensor information receiving section 21 confirms whether or not information on a moving object has been received from the roadside sensor 10, and if received, transmits the received information to the moving object detecting section 22, and proceeds to step S03. , if not received, the process returns to step S01. In the first embodiment, T is the time at which the roadside sensor 10 detects a moving object.

In step S<b>03 , the moving object detection unit 22 regards an object moving within the area including the vehicle 30 as an in-area moving object, and uses the information on the moving object received from the sensor information receiving unit 21 and the position information of the vehicle 30 to determine the area The position information and speed information of the inner 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 in-area moving objects extracted by the moving object detection unit 22. As shown in FIG. In-area moving object features include, for example, position, size, attitude, and speed information. The positional information includes, for example, latitude, longitude, and altitude information on the map. The size includes height, width, and depth information, for example. The attitude includes, for example, azimuth angle information of the attitude. For example, when the speed of a moving object is represented by the speed in the north-south direction and the speed in the east-west direction, the x-direction speed is the positive speed in the east direction, and the y-direction speed is the positive speed in the south direction. Contains speed information. Attributes include, for example, information that the detected moving object is a car, large vehicle, bus, truck, motorcycle, or pedestrian. A method for extracting features and attributes of an in-area moving object using information received from the roadside sensor 10 by the moving object detection unit 22 will be described below. For example, when the roadside sensor 10 is a LiDAR, the point cloud data obtained as the output of the LiDAR is subjected to clustering processing, the orientation information is extracted from the information of each class obtained, and the center of mass of each class is the representative of each object. The velocity can be obtained by observing the time change of the representative position. For example, if the roadside sensor 10 is a millimeter-wave radar, the position and azimuth angle of each object can be obtained by performing segmentation processing and obtaining attributes such as the center-of-gravity position, width, and 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, thereby obtaining information on the position, size, orientation, speed and attributes. Obtainable.

In step S04, the dynamic map update unit 23 uses the position information of the moving object in the area extracted by the moving object detection unit 22 in step S03 to determine the motion at time T when the moving object in the area was detected by the roadside sensor 10. The target map information is updated, and the process proceeds to step S05. In step S05, the position estimating unit 24 uses the position information of the moving object in the area and the speed information of the moving object in the area extracted by the moving object detection unit 22 in step S03, and proceeds by t from the previous time T. Then, the position of the moving object in the area at time T+t is estimated, dynamic map information at 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 estimating unit 24. As shown in FIG. 5 is a diagram showing the dynamic map information 40 at time T updated by the dynamic map updating unit 23 in step S04. 42 are mapped onto 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 showing the east-west direction with the east direction being positive, and the y-axis is an axis showing the north-south direction with the south direction being positive, for example.

The second to fourth figures from the top of FIG. 5 are diagrams showing how the future dynamic map information is created by the position estimation unit 24 in step S05. In step S05, the position estimator 24 estimates the position of each in-area moving object at time T+t, where t is the time increment when predicting the future. The second diagram from the top in FIG. 52 are predicted, and predicted positions 51 and 52 are mapped on the dynamic map information 50 at time T+t. Each position of the predicted position 51 and the predicted position 52 is obtained 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 positional information of the first moving body 41 and the second moving body 42 at a plurality of times in the past is stored, the positions of the predicted position 51 and the predicted position 52 may be obtained using this information. good. In FIG. 5, the time axis is the time axis, the downward direction in FIG.

In step S06, the collision risk calculator 25 calculates the distance between the predicted position 51 and the predicted position 52 in the dynamic map information 50 shown in the second diagram from the top in FIG. In step S07, the collision risk calculator 25 determines whether the distance between the predicted position 51 and the predicted position 52 is smaller than a predetermined threshold. It is assumed that it will not, and the process returns to step S05 to predict the position at time T+2t, which is advanced by t.

The third diagram from the top in FIG. 5 shows that, in the second step S05, the position estimation unit 24 calculates the predicted position 61, which is the predicted position of the first moving body 41 at time T+2t, and the predicted position 61 of the second moving body 42 at time T+2t. , and the predicted positions 61 and 62 are mapped on the dynamic map information 60 at time T+2t. In the second step S06, the collision risk calculator 25 calculates the distance between the predicted position 61 and the predicted position 62 in the dynamic map information 60 shown in the third diagram from the top in FIG. In the second step S07, the collision risk calculator 25 determines whether the distance between the predicted position 61 and the predicted position 62 is smaller than a predetermined threshold. It is assumed that no collision will occur, and the process returns to step S05 to predict the position at time T+3t, which is advanced by t.

The fourth diagram from the top in FIG. 5 shows that, in the third step S05, the position estimating unit 24 calculates the predicted position 71, which is the predicted position of the first moving body 41 at time T+3t, and the time T+3t of the second moving body 42. A predicted position 72, which is a predicted position at time T+3t, is predicted, and the predicted positions 71 and 72 are mapped on the dynamic map information 70 at time T+3t. In the third step S06, the collision risk calculator 25 calculates the distance between the predicted position 71 and the predicted position 72 in the dynamic map information 70 shown in the fourth diagram from the top in FIG. In the third step S07, the collision risk calculator 25 determines whether the distance between the predicted position 71 and the predicted position 72 is smaller than a predetermined threshold. . In step S08, the collision risk calculator 25 estimates that a collision will occur at time T+3t, sets a time to collision TTC (Time To Collision) from time T to 3t, and proceeds to step S09.

In the explanations of FIGS. 3 and 5, the increment of time t when predicting the future position of a moving object in the area is assumed to be constant. As long as the position can be predicted correctly, the increments of time when predicting the future need not be constant, and may be variable. FIG. 5 shows an example of determining a collision between two in-area moving objects, the first moving body 41 and the second moving body 42, but the number of in-area moving objects is not limited to two. Collisions of three or more in-area moving objects may be determined.

In step S09 of FIG. 3, the collision risk calculator 25 calculates the time distribution of the risk levels of the first moving body 41 and the second moving body 42 from the information on the collision margin time calculated in step S08. A notification period for notifying the body 41 and the second moving body 42 of a collision warning and a 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 calculator 25. FIG. 6 to 8 show examples of the risk levels obtained by the collision risk calculator 25. FIG. 6 shows an example of a short time margin for collision, FIG. 8 shows an example in which the time to collision is long. In FIGS. 6 to 8, the time to collision is shown as TTC. 6 to 8 show the relationship between the risk level and the collision margin time, and the right figures in FIGS. It is the figure which showed the relationship with the notification period to notify. 6 to 8, the horizontal axis represents the time axis when time T is zero, and the vertical axis represents the magnitude of the risk level.

The collision risk calculator 25 calculates the time distribution of risk levels based on the collision margin time obtained from the dynamic map information. The time distribution of the risk level has a peak value in the collision margin time, and when the collision margin time is short, the risk level peak value is high, and when the collision margin time is long, the risk level peak value is low. , the shorter the time to collision, the higher the calculated peak value of the risk level. In addition, the value of the risk level increases as the time increases from zero, becomes the highest when the collision margin time has passed, decreases after the collision margin time passes, and finally becomes zero. and By setting the time distribution of the risk level as described above, the shorter the time to collision, the more difficult it is to avoid a collision, and the higher the risk becomes. The time distribution of the risk level can reflect the fact that the risk becomes lower as the time increases from the time when the collision margin time has elapsed from T.

In the diagram on the left side of FIG. 6, the peak value of the risk level is high because the time to collision is short, and the risk level rises sharply toward the time to collision. In the diagram on the left side of FIG. 7, the peak value of the risk level is moderate because the time to collision is mid-term, and the risk level rises not so steeply toward the time to collision. It is In the diagram on the left side of FIG. 8, the risk level peak value is low because the time to collision is long, and the risk level rises slowly toward the time to collision.

The risk levels shown in FIGS. 6-8 are relative values. When the risk level is treated as an absolute value, the moving object detection unit 22 extracts the features and attributes of the moving objects in the area as shown in FIG. A time distribution of risk levels may be calculated using features and attributes of moving objects in the area involved in collisions. For example, the moving object detection unit 22 extracts the features and attributes of an in-area moving object as shown in FIG. 4, and estimates the mass of the in-area moving object from the extracted size information. Furthermore, in the collision risk calculation unit 25, first, as shown in FIGS. , the relative velocity, or the difference in azimuth angle, and multiplying the initial value of the time distribution of the risk level by these values to obtain the risk level value. If the other party of the collision is a vulnerable traffic person, for example, if it is a two-wheeled vehicle or a pedestrian compared to an ordinary vehicle, or if an ordinary vehicle is compared to a bus or truck, the attribute of the moving object in the area will be considered. risk level may be multiplied by a constant factor. The moving object detection unit 22 further extracts the features and attributes of the moving objects in the area, and the collision risk calculation unit 25 uses the features and attributes of the moving objects in the area in addition to the time to collision to calculate 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 calculator 25 obtains a notification period for notifying a warning and a collision avoidance route from the risk level. If the timing of notifying the collision warning and the collision avoidance route is too early, excessive collision avoidance operations will be performed, which will hinder the smooth running of the vehicle in the entire area. Conversely, if the timing of notifying the collision warning and the collision avoidance route is late, the collision avoidance response will not be in time and a collision will occur. Alternatively, if the timing of notifying the collision warning and the collision avoidance route is late, but the collision could be prevented by the avoidance behavior of the other vehicle involved in the collision, even though the risk of collision has already passed, Unnecessary evasive maneuvers will be performed, and the smooth running of the vehicle in the entire area will be hindered.

The collision risk calculation unit 25 sets, for example, a notification period to a period in which the value of the previously obtained risk level exceeds a predetermined threshold value Th. Let the end time be T2. The diagrams on the right side of FIGS. 6 to 8 show how the notification start time T1 and the notification end time T2 are obtained from the respective risk levels and threshold values Th, and the hatched period is the notification period. . By setting the period during which the risk level calculated from the collision margin exceeds the threshold as the notification period, it is possible to notify the vehicle of the warning and the arbitration route during the notification period according to the collision margin and the risk level. can. As a result, the vehicle can receive information on the arbitration route at a timing that is neither too early nor too late, so that the smooth running of the vehicle is not hindered. Furthermore, by setting the period during which the risk level value 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 will be shortened, and if the threshold Th is decreased, the notification period will be extended.

In step S10, the arbitration route determining unit 26, based on the information about the future predicted positions of the in-area moving objects estimated by the position estimating unit 24 in step S05, moves all collision-related in-area moving objects. Then, an arbitration route, which is a route of each intra-area moving object for avoiding collision, is determined, and the process proceeds to step S11. The arbitration route determination unit 26 may determine the arbitration route, for example, from an evaluation value for avoiding collisions of moving objects within the area and an evaluation value of running efficiency. In step S11, the information notifying unit 27 issues a warning during the notification period from the notification start time T1 calculated by the collision risk calculation unit 25 in step S09 to the notification end time T2. 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 or not to end the processing, returns to step S01 when continuing without ending the processing, and ends the processing as the traffic control device 20 when ending the processing. .

The warning and the arbitration route transmitted from the information notifier 27 in step S11 are received by the information receiver 32 of the vehicle 30 . At this time, if the received information is unrelated to the own vehicle, the vehicle 30 terminates the process. Execute evasive action by traveling on an arbitration route.

Note that 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 the warning and the arbitration route to the vehicle 30 during the notification period. 21 may receive the pedestrian's location information from the mobile terminal used by the pedestrian, and the information notification unit 27 may transmit the warning and the arbitration route to the mobile terminal during the notification period. The traffic control device 20 according to Embodiment 1 collects information on the position, speed, size, posture, or orientation of moving vehicles or pedestrians on roads, intersections, parking lots, stations, or other boarding/alighting points within a specific area. , detected by multiple roadside sensors 10 installed at multiple locations within the area, or by receiving location information from mobile terminals used by vehicles or pedestrians moving within the area, is called dynamic map information. It can be reflected in the database in real time. In addition, vehicles and pedestrians moving within the area will be notified at any time whether there are any vehicles or pedestrians that may impede their movement, how long it will take for the obstacles to occur, or the risks caused by the obstacles. At the same time as receiving a recommended route to avoid the obstacle at a timing that is neither too early nor too late according to the time until the obstacle occurs and the level of risk. be able to. As a result, for example, it is possible to mediate the routes or timings of entering and departing vehicles in boarding and alighting spaces such as stations, avoid contact between vehicles and people, mediate crossing timing between multiple vehicles at intersections without traffic signals, and cross roads. To realize the movement of vehicles or pedestrians without extremely lowering the smoothness of the traffic flow, such as preferential movement of pedestrians who are on the road.

As described above, the traffic control device 20 according to Embodiment 1 receives information from the roadside sensors 10 that detect objects moving within the area and sensor information reception that receives the position information of the vehicle 30 traveling within the area. a moving object detection unit 22 for extracting position information and speed information of an in-area moving object moving in an area including the vehicle 30 from the information from the roadside sensor 10 and the position information of the vehicle 30; A dynamic map updating unit 23 for updating dynamic map information from object position information, and position estimation for calculating a predicted future position of an in-area moving object from position information and speed information of an in-area moving object. A collision risk calculation unit 25 that obtains the collision margin time from the predicted position, calculates the time distribution of the risk level from the collision margin time, calculates the notification period from the risk level time distribution, and the arbitration route from the predicted position. and an information notification unit 27 for notifying the vehicle 30 of the warning and the arbitration route during the notification period. Depending on the height, it can be received at a timing that is neither too early nor too late, and does not hinder the smooth running of the vehicle.

FIG. 9 is a schematic diagram showing an example of hardware of the traffic control device 20 according to the first embodiment. The sensor information receiving unit 21 is the receiving device 201 and the information notification unit 27 is the 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 executed by a processor 203 such as a CPU or system LSI that executes programs stored in the memory 204. Realized. Also, a plurality of processing circuits may work together to perform the functions described above. Furthermore, the above functions may be realized by dedicated hardware. Where dedicated hardware implements the above functions, the dedicated hardware may be, for example, a single circuit, multiple circuits, a programmed processor, an ASIC, an FPGA, or a combination thereof. The above functions may be realized by a combination of dedicated hardware and software, or a combination of dedicated hardware and firmware. Receiver 201, transmitter 202, processor 203 and memory 204 are bus-connected to each other.

Although the present application describes exemplary embodiments, the various features, aspects, and functions described in the embodiments are not limited to application of particular embodiments, alone or Various combinations are applicable to the embodiments.
Therefore, countless modifications not illustrated are envisioned within the scope of the technology disclosed in the present application. For example, the modification, addition, or omission of at least one component shall be included.

1 traffic control system, 10 roadside sensor, 20 traffic control device, 21 sensor information receiving unit, 22 moving object detection unit, 23 dynamic map update unit, 24 position estimation unit, 25 collision risk calculation unit, 26 arbitration route determination unit, 27 information notification unit 30 vehicle 31 in-vehicle sensor 32 information reception unit 40 dynamic map information 41 first moving object 42 second moving object 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 vehicle, 131 pedestrian, 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 within an area and position information of a vehicle that is traveling within the area;
a moving object detection unit that extracts position information and speed information of an in-area moving object moving in the area including the vehicle from the information from the roadside sensor and the position information of the vehicle;
a dynamic map updating unit that updates dynamic map information from the position information of the moving object in the area;
a position estimating unit that calculates a predicted future position of the moving object within the area from position information of the moving object within the area and speed information of the moving object within 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;
an arbitration route determination unit that determines an 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 collision risk calculation unit takes a peak value in the collision margin time, calculates a time distribution of the risk level in which the shorter the collision margin time is, the higher the peak value of the risk level becomes, and calculates the risk level value in advance. 2. The traffic control device according to claim 1, wherein a period exceeding a predetermined threshold value is calculated as said notification period. The moving object detection unit further extracts features and attributes of the in-area moving object,
2. The traffic control apparatus according to claim 1, wherein the collision risk calculation unit calculates the time distribution of the risk level using the characteristics and attributes of the moving object in the area in addition to the collision margin time. A traffic control device according to any one of claims 1 to 3;
the vehicle;
A traffic control system comprising the roadside sensor.

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