JP7276653B2 - Vehicle traffic management device, in-vehicle device, vehicle traffic management system, vehicle traffic management method, and vehicle traffic management program - Google Patents

Description

The present disclosure relates to a vehicle traffic management device, an in-vehicle device, a vehicle traffic management system, a vehicle traffic management method, and a vehicle traffic management program.

Conventionally, technologies for assisting driving by a vehicle and systems using such technologies are known.

For example, Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2004-240506) discloses the following safe driving support system. That is, the safe driving support system includes a plurality of in-vehicle devices that are installed in a plurality of vehicles and are connectable to a network via an existing wireless communication network, and a plurality of in-vehicle devices that are connected to the network and are connected to the network and the wireless communication network. and a monitoring device for monitoring each vehicle by communicating with each on-vehicle device by means of a monitor, and for transmitting warning information to the on-vehicle device of a vehicle with a risk of collision to that effect. In the support system, each of the in-vehicle devices generates position-related information including the position of the vehicle on which the in-vehicle device is mounted, and transmits the generated position-related information to the vehicle via the wireless communication network and the network. is sent to a monitoring device, and the monitoring device determines whether there is a possibility that each vehicle will collide with another vehicle based on the position-related information and map data transmitted from each of the vehicle-mounted devices; The alarm information is transmitted via the network and the wireless communication network to an on-vehicle device of a vehicle that may collide with another vehicle, and each of the on-vehicle devices transmits the warning information from the monitoring device to the own vehicle. When the transmitted warning information is received, it is determined that there is a risk of the own vehicle colliding with another vehicle, and preset danger avoidance control is performed to avoid danger.

Further, Patent Document 2 (Japanese Unexamined Patent Application Publication No. 2014-41434) discloses an interrupt prediction device as follows. That is, the interruption prediction device is an interruption prediction device that predicts an interruption of the vehicle, and includes a driving environment acquisition unit that acquires the driving environment related to the own vehicle, and the current vehicle that is acquired by the driving environment acquisition unit. and the driving environment of the past vehicle cut-in scene stored in the storage device. an interruption prediction unit for detecting an interruption by the surrounding vehicle; a data updating unit for updating the driving environment of the vehicle interrupt scene stored in the device, wherein the interrupt predicting unit uses the driving environment of the vehicle interrupt scene updated by the data updating unit. Predicting interruption of the peripheral vehicle.

Japanese Patent Application Laid-Open No. 2004-240506 JP 2014-41434 A

Beyond the techniques described in Patent Literatures 1 and 2, there is a demand for techniques for improving the quality of driving assistance or travel assistance in vehicles.

The present disclosure has been made to solve the above-described problems, and aims to provide a vehicle traffic management device, an in-vehicle device, a vehicle traffic management system, and a vehicle traffic management device capable of improving the quality of driving assistance or travel assistance in a vehicle. A vehicle traffic management method and a vehicle traffic management program are provided.

A vehicle traffic management device according to the present disclosure includes a receiving unit capable of receiving measurement information from a plurality of roadside devices, and a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit. and a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle.

An in-vehicle device according to the present disclosure includes a receiving unit that receives prediction information indicating a predicted position of at least one of another vehicle and a pedestrian from a vehicle traffic management device, and based on the prediction information received by the receiving unit: , a support information generation unit for generating support information for driving support or travel support; an evaluation unit that evaluates the prediction information received by the receiving unit based on at least one of the position of the pedestrian, the actual position of the pedestrian, and an index related to running of the own vehicle; and a transmitting unit configured to transmit an evaluation result by the unit to the vehicle traffic management device.

A vehicle traffic management system of the present disclosure includes a vehicle traffic management device and an in-vehicle device. generating prediction information indicating at least one predicted position, transmitting the generated prediction information to the in-vehicle device, and the in-vehicle device performing driving assistance based on the prediction information received from the vehicle traffic management device; Alternatively, support information for driving support is generated, and the in-vehicle device determines the actual position of the other vehicle and the actual position of the pedestrian as a result of the vehicle traveling based on the generated support information. , and an index relating to running of the own vehicle, the predictive information received from the vehicle traffic management device is evaluated, and an evaluation result is transmitted to the vehicle traffic management device.

A vehicle traffic management method of the present disclosure is a vehicle traffic management method in a vehicle traffic management device, comprising: receiving measurement information from one or more roadside devices; and transmitting the generated prediction information to the target vehicle.

A vehicle traffic management method of the present disclosure is a vehicle traffic management method in an in-vehicle device, comprising the steps of: receiving prediction information indicating predicted positions of at least one of other vehicles and pedestrians from the vehicle traffic management device; a step of generating assistance information for driving assistance or travel assistance based on the predicted information obtained; and the actual position of the other vehicle as a result of the own vehicle traveling based on the generated assistance information; Evaluating the received prediction information based on at least one of the actual position of the pedestrian and an index relating to running of the own vehicle; and transmitting an evaluation result to the vehicle traffic management device. step.

A vehicle traffic management method of the present disclosure is a vehicle traffic management method in a vehicle traffic management system including a vehicle traffic management device and an in-vehicle device, wherein the vehicle traffic management device receives measurements from one or more roadside devices. generating prediction information indicating predicted positions of at least one of other vehicles and pedestrians based on the information, and transmitting the generated prediction information to the in-vehicle device; a step of generating assistance information for driving assistance or travel assistance based on the prediction information received from the management device; Evaluating the prediction information received from the vehicle traffic management device based on at least one of the actual position of the other vehicle, the actual position of the pedestrian, and an indicator regarding the travel of the own vehicle. and sending evaluation results to the vehicle traffic management device.

A vehicle traffic management program of the present disclosure is a vehicle traffic management program used in a vehicle traffic management device, comprising: a computer, a receiving unit capable of receiving measurement information from a plurality of roadside devices; A prediction information generation unit that generates prediction information indicating a prediction position of at least one of a vehicle and a pedestrian based on measurement information, and a transmission that transmits the prediction information generated by the prediction information generation unit to a target vehicle. It is a program for functioning as a department.

A vehicle traffic management program of the present disclosure is a vehicle traffic management program used in an in-vehicle device, wherein the computer receives prediction information indicating predicted positions of at least one of other vehicles and pedestrians from the vehicle traffic management device. a support information generation unit that generates support information for driving support or travel support based on the prediction information received by the reception unit; and the support information generated by the support information generation unit. Based on at least one of the actual position of the other vehicle, the actual position of the pedestrian, and an index related to the running of the vehicle, in the result of the vehicle running based on The program functions as an evaluation unit that evaluates the prediction information received by the reception unit, and a transmission unit that transmits the evaluation result of the evaluation unit to the vehicle traffic management device.

One aspect of the present disclosure can be implemented as a semiconductor integrated circuit that implements part or all of a vehicle traffic management device. Also, one aspect of the present disclosure can be implemented as a semiconductor integrated circuit that implements part or all of an in-vehicle device. Also, one aspect of the present disclosure can be implemented as a semiconductor integrated circuit that implements part or all of a vehicle traffic management system. Also, one aspect of the present disclosure can be implemented as a program for causing a computer to execute processing steps in a vehicle traffic management system.

According to the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in a vehicle.

FIG. 1 is a diagram showing the configuration of a vehicle traffic management system according to an embodiment of the present disclosure. FIG. 2 is a diagram showing the configuration of a roadside device in the vehicle traffic management system according to the embodiment of the present disclosure. FIG. 3 is a diagram showing the configuration of the vehicle traffic management device according to the embodiment of the present disclosure. FIG. 4 is a diagram showing a configuration of an in-vehicle device according to an embodiment of the present disclosure. FIG. 5 is a diagram showing an example of a travel route along which a target vehicle travels in the vehicle traffic management system according to the embodiment of the present disclosure. FIG. 6 is a diagram showing an example of a travel route along which a target vehicle travels in the vehicle traffic management system according to the embodiment of the present disclosure. FIG. 7 is a flowchart that defines the operation procedure of the vehicle traffic management device in the vehicle traffic management system according to the embodiment of the present disclosure. FIG. 8 is a flowchart that defines the operation procedure of the vehicle-mounted device in the vehicle traffic management system according to the embodiment of the present disclosure. FIG. 9 is a diagram showing an example of a sequence of traffic management processing in the vehicle traffic management system according to the embodiment of the present disclosure.

First, the contents of the embodiments of the present disclosure will be listed and described.

(1) A vehicle traffic management device according to an embodiment of the present disclosure includes a receiving unit capable of receiving measurement information from a plurality of roadside devices, and based on the measurement information received by the receiving unit, vehicles and pedestrians and a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle.

With such a configuration, it is possible to generate prediction information based on measurement information received from, for example, a plurality of roadside devices. Driving support can be performed. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(2) Preferably, the receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle, and the prediction information generating unit receives the evaluation received by the receiving unit. Based on the result, the content of the prediction information to be generated is adjusted.

With such a configuration, for example, it is possible to reflect the evaluation contents of the actual travel result using the prediction information of the target vehicle in the generation of the prediction information in the vehicle traffic management device, thereby improving the prediction accuracy, for example.

(3) Preferably, the receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle, and the vehicle traffic management device further receives the evaluation result of the prediction information received by the receiving unit. A designation unit for instructing the roadside device about the content of the measurement information to be transmitted by the roadside device based on the evaluation result.

With such a configuration, for example, it is possible to reflect the evaluation contents of the actual traveling result using the prediction information by the target vehicle in the contents of the measurement information used to generate the prediction information, such as the transmission cycle of the measurement information by the roadside device. can.

(4) An in-vehicle device according to an embodiment of the present disclosure includes: a receiving unit that receives prediction information indicating a predicted position of at least one of another vehicle and a pedestrian from a vehicle traffic management device; a support information generating unit for generating support information for driving support or driving support based on the predicted information obtained; and a result of the vehicle traveling based on the support information generated by the support information generating unit. the prediction information received by the receiving unit based on at least one of the actual position of the other vehicle, the actual position of the pedestrian, and an index related to running of the own vehicle in An evaluation unit that evaluates and a transmission unit that transmits the evaluation result of the evaluation unit to the vehicle traffic management device.

With such a configuration, the content of the evaluation of the actual driving result using the prediction information received from the vehicle traffic management device is fed back to the vehicle traffic management device, and the content of the prediction information to be transmitted by the vehicle traffic management device is improved, For example, prediction accuracy can be improved. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(5) A vehicle traffic management system according to an embodiment of the present disclosure includes a vehicle traffic management device and an in-vehicle device, the vehicle traffic management device based on measurement information received from one or more roadside devices , generating prediction information indicating a predicted position of at least one of another vehicle and a pedestrian, and transmitting the generated prediction information to the in-vehicle device, the in-vehicle device receiving from the vehicle traffic management device Assistance information for driving assistance or travel assistance is generated based on the prediction information, and the in-vehicle device calculates the actual position of the other vehicle as a result of the own vehicle traveling based on the generated assistance information. , the actual position of the pedestrian, and an index relating to running of the own vehicle, evaluating the prediction information received from the vehicle traffic management device, and providing the evaluation result to the vehicle traffic Send to the management device.

With such a configuration, the vehicle traffic management device can generate prediction information based on measurement information received from, for example, a plurality of roadside devices. It is possible to perform driving assistance or driving assistance using Further, the content of the evaluation of the actual running result of the target vehicle using the prediction information generated by the vehicle traffic management device is fed back to the vehicle traffic management device to improve the content of the prediction information generated by the vehicle traffic management device, For example, prediction accuracy can be improved. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(6) A vehicle traffic management method according to an embodiment of the present disclosure is a vehicle traffic management method in a vehicle traffic management device, comprising: receiving measurement information from one or more roadside devices; and transmitting the generated prediction information to the target vehicle.

With such a method, it is possible to generate prediction information based on measurement information received from, for example, a plurality of roadside devices. Driving support can be performed. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(7) A vehicle traffic management method according to an embodiment of the present disclosure is a vehicle traffic management method in an in-vehicle device, in which prediction information indicating the predicted position of at least one of another vehicle and a pedestrian is transmitted to the vehicle traffic management method. a step of receiving from the device; a step of generating assistance information for driving assistance or travel assistance based on the received prediction information; evaluating the received prediction information based on at least one of the actual positions of other vehicles, the actual positions of the pedestrians, and an index relating to running of the own vehicle; and transmitting to the vehicle traffic management device.

By such a method, the content of the evaluation of the actual driving result using the prediction information received from the vehicle traffic management device is fed back to the vehicle traffic management device to improve the content of the prediction information to be transmitted by the vehicle traffic management device, For example, prediction accuracy can be improved. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(8) A vehicle traffic management method according to an embodiment of the present disclosure is a vehicle traffic management method in a vehicle traffic management system including a vehicle traffic management device and an in-vehicle device, wherein the vehicle traffic management device comprises one or generating prediction information indicating predicted positions of at least one of other vehicles and pedestrians based on measurement information received from a plurality of roadside devices, and transmitting the generated prediction information to the in-vehicle device; a step in which the in-vehicle device generates assistance information for driving assistance or travel assistance based on the prediction information received from the vehicle traffic management device; based on at least one of the actual position of the other vehicle, the actual position of the pedestrian, and an index relating to the running of the own vehicle in the results of the running of the vehicle, the vehicle traffic management device and evaluating the prediction information received from and sending evaluation results to the vehicle traffic management device.

With such a method, in the vehicle traffic management device, prediction information can be generated based on measurement information received from, for example, a plurality of roadside devices. It is possible to perform driving assistance or driving assistance using Further, the content of the evaluation of the actual running result of the target vehicle using the prediction information generated by the vehicle traffic management device is fed back to the vehicle traffic management device to improve the content of the prediction information generated by the vehicle traffic management device, For example, prediction accuracy can be improved. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(9) A vehicle traffic management program according to an embodiment of the present disclosure is a vehicle traffic management program used in a vehicle traffic management device, comprising: a computer, a receiving unit capable of receiving measurement information from a plurality of roadside devices; a prediction information generation unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the reception unit; and the prediction generated by the prediction information generation unit. It is a program for functioning as a transmitting unit that transmits information to a target vehicle.

With such a configuration, it is possible to generate prediction information based on measurement information received from, for example, a plurality of roadside devices. Driving support can be performed. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

(10) A vehicle traffic management program according to an embodiment of the present disclosure is a vehicle traffic management program used in an in-vehicle device, in which a computer performs prediction indicating a predicted position of at least one of another vehicle and a pedestrian. a receiving unit that receives information from a vehicle traffic management device; a support information generating unit that generates support information for driving support or travel support based on the prediction information received by the receiving unit; and the support information generating unit. at least one of the actual position of the other vehicle, the actual position of the pedestrian, and an index regarding the travel of the own vehicle as a result of the travel of the own vehicle based on the assistance information generated by the unit; or as an evaluation unit that evaluates the prediction information received by the reception unit, and a transmission unit that transmits the evaluation result of the evaluation unit to the vehicle traffic management device. .

With such a configuration, the content of the evaluation of the actual driving result using the prediction information received from the vehicle traffic management device is fed back to the vehicle traffic management device, and the content of the prediction information to be transmitted by the vehicle traffic management device is improved, For example, prediction accuracy can be improved. Therefore, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

Embodiments of the present disclosure will be described below with reference to the drawings. The same or corresponding parts in the drawings are denoted by the same reference numerals, and the description thereof will not be repeated. Moreover, at least part of the embodiments described below may be combined arbitrarily.

[Vehicle traffic management system]
FIG. 1 is a diagram showing the configuration of a vehicle traffic management system according to an embodiment of the present disclosure.

Referring to FIG. 1 , vehicle traffic management system 300 includes vehicle traffic management device 100 and in-vehicle device 200 . The in-vehicle device 200 is mounted on a target vehicle 40 that receives services from the vehicle traffic management device 100 .

Note that the vehicle traffic management system 300 is not limited to a configuration including one in-vehicle device 200, and may be configured to include a plurality of in-vehicle devices 200 that are respectively mounted in a plurality of target vehicles.

Vehicle traffic management device 100 is, for example, a server. The vehicle traffic management device 100 can receive measurement information from the roadside devices 60A and 60B installed on the roadside. Each of the roadside devices 60A and 60B is also referred to as the roadside device 60 hereinafter.

The roadside device 60 can communicate with the vehicle traffic management device 100 via the radio base station device 20 using ITS (Intelligent Transport System) radio, for example.

The roadside device 60 acquires sensor data indicating measurement results by sensors such as a camera, LiDAR (Light Detection and Ranging), millimeter wave radar device, temperature sensor, and humidity sensor. Hereinafter, each of the sensors from which sensor data can be acquired by the roadside device 60 is also referred to as a roadside sensor.

The roadside device 60 transmits measurement information including the acquired sensor data to the vehicle traffic management device 100 via the radio base station device 20 .

The vehicle traffic management device 100 generates prediction information indicating the predicted positions of at least one of the other vehicles 41A, 41B and pedestrians 42A, 42B based on the measurement information received from one or more roadside devices 60. . The vehicle traffic management device 100 then transmits the generated prediction information to the in-vehicle device 200 . Hereinafter, each of the other vehicles 41A and 41B will also be referred to as another vehicle 41, and each of the pedestrians 42A and 42B will also be referred to as a pedestrian .

For example, the in-vehicle device 200 acquires the current position of its own target vehicle 40 based on radio waves from positioning satellites in a satellite positioning system (GNSS: Global Navigation Satellite System) such as GPS (Global Positioning System) at predetermined intervals. , to generate location information indicating the acquired current location. The in-vehicle device 200 transmits the generated location information to the vehicle traffic management device 100 via the radio base station device 20 .

The vehicle traffic management device 100 selects one or a plurality of roadside devices 60 to transmit measurement information according to the current position of the target vehicle 40 indicated by the position information received from the in-vehicle device 200 . The vehicle traffic management device 100 transmits, to the selected roadside device 60, designation information that designates the contents of the measurement information to be transmitted.

When receiving the designation information, the roadside device 60 transmits measurement information designated by the designation information to the vehicle traffic management device 100 via the radio base station device 20 as a response to the received designation information.

When the vehicle traffic management device 100 receives measurement information from one or more roadside devices 60, it generates dynamic information indicating the current positions of other vehicles 41 and pedestrians 42 using the received measurement information. The vehicle traffic management device 100 generates prediction information from dynamic information using a prediction model for calculating predicted positions after a predetermined time based on the current positions of other vehicles 41 and pedestrians 42 .

Vehicle traffic management device 100 transmits the generated dynamic information and prediction information to in-vehicle device 200 via radio base station device 20 .

The in-vehicle device 200 generates assistance information for driving assistance or travel assistance based on the prediction information received from the vehicle traffic management device 100 .

More specifically, when the in-vehicle device 200 receives the dynamic information and the prediction information from the vehicle traffic management device 100, the in-vehicle device 200 performs driving support or travel support for its own target vehicle 40 based on the received dynamic information and prediction information. Generate support information for Specifically, the in-vehicle device 200 generates support information including a travel route to the destination or various control details for automatically driving to the destination.

The in-vehicle device 200 performs route guidance or automatic driving control based on the generated support information.

The in-vehicle device 200 calculates the actual position of the other vehicle 41, the actual position of the pedestrian 42, and an index regarding the travel of the target vehicle 40 as a result of the target vehicle 40 traveling based on the generated support information. The predictive information received from the vehicle traffic management device 100 is evaluated based on at least one of: The in-vehicle device 200 then transmits the evaluation result to the vehicle traffic management device 100 .

More specifically, the in-vehicle device 200 detects other vehicles 41 and pedestrians 42 around the target vehicle 40 on the travel route traveled by the target vehicle 40 based on the generated support information.

For example, the in-vehicle device 200 acquires measurement information indicating measurement results by sensors such as LiDAR and cameras mounted on the target vehicle 40 . The in-vehicle device 200 generates position information indicating the presence or absence of other vehicles 41 and pedestrians 42 in the measurement area of the sensor and the positions of the other vehicles 41 and pedestrians 42 based on the acquired measurement information.

The in-vehicle device 200 calculates the predicted positions of the other vehicle 41 and the pedestrian 42 indicated by the prediction information received from the vehicle traffic management device 100 and the actual positions of the other vehicle 41 and the pedestrian 42 indicated by the generated position information. and evaluate the predictive information based on the results of the comparison.

In addition, the in-vehicle device 200 is mounted on the target vehicle 40, based on the measurement results of various sensors such as a brake sensor, an accelerator sensor, an acceleration sensor, a steering sensor, a fuel consumption sensor, an electricity consumption sensor, a LiDAR, a camera, and an in-vehicle camera, Each index related to the travel of the target vehicle 40 is calculated as a result of the travel of the target vehicle 40 based on the support information.

The in-vehicle device 200 calculates a plurality of indices such as an index regarding safety and security, an index regarding fuel consumption or power consumption, and an index regarding ride comfort, and evaluates the prediction information based on the calculated indices.

The in-vehicle device 200 then transmits the evaluation result of the prediction information to the vehicle traffic management device 100 via the radio base station device 20 .

When the vehicle traffic management device 100 receives one or more types of evaluation results regarding the prediction information from the in-vehicle device 200, the vehicle traffic management device 100 adjusts the contents of the prediction information to be generated based on the received evaluation results.

For example, the vehicle traffic management device 100 adjusts the content of the prediction information to be generated by changing the content of the measurement information to be transmitted from the roadside device 60 or altering the prediction model.

[Roadside device]
FIG. 2 is a diagram showing the configuration of a roadside device in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 2 , the roadside device 60 includes a designation information receiving section 61 , a sensor control section 62 , a measurement information generation section 63 and a measurement information transmission section 64 .

The vehicle traffic management device 100 transmits designation information such as sensor type designation, transmission cycle designation, and data amount designation to the roadside device 60, for example.

Upon receiving the designation information from the vehicle traffic management device 100 , the designation information reception unit 61 in the roadside device 60 outputs the received designation information to the sensor control unit 62 and the measurement information generation unit 63 .

Upon receiving the designation information from the designation information receiving section 61, the sensor control section 62 controls the roadside sensors based on the received designation information.

More specifically, for example, when the designation information includes a sensor type designation, the sensor control unit 62 causes the roadside sensor to start measurement by transmitting a control signal to the roadside sensor indicated by the sensor type designation. For example, when the designation information includes the sensor designation type and the resolution, and the roadside sensor indicated by the sensor designation type is a camera, the sensor control unit 62 generates a control signal for measuring at the designated resolution. Sending it to the camera causes the camera to start measuring at the specified resolution.

The measurement information generator 63 periodically or irregularly acquires sensor data from roadside sensors. The measurement information generation unit 63 generates measurement information including the acquired sensor data, area information indicating the measurement area of the corresponding roadside sensor, and the ID (Identifier) of the own roadside device 60, and outputs the generated measurement information. Output to the measurement information transmission unit 64 .

Further, when the measurement information generation unit 63 receives the designation information from the designation information reception unit 61, the measurement information generation unit 63 adjusts the content of the measurement information to be generated and the generation cycle of the measurement information based on the received designation information.

More specifically, for example, when the designation information includes transmission cycle designation of the measurement information, the measurement information generation unit 63 generates the measurement information in the cycle indicated by the transmission cycle designation, and transmits the generated measurement information to the measurement information transmission unit 64. Output to For example, when the designation information includes a data amount designation of the measurement information, the measurement information generation unit 63 processes the sensor data acquired from the roadside sensor as necessary to generate the measurement information of the data amount indicated by the data amount designation. It generates and outputs the generated measurement information to the measurement information transmission unit 64 .

Upon receiving the measurement information from the measurement information generation unit 63 , the measurement information transmission unit 64 transmits the received measurement information to the vehicle traffic management device 100 via the radio base station device 20 .

The vehicle traffic management device 100 transmits, for example, stop information to the roadside device 60 indicating that transmission of the measurement information should be stopped.

Upon receiving the stop information from the vehicle traffic management device 100 , the designation information reception unit 61 in the roadside device 60 outputs the received stop information to the sensor control unit 62 and the measurement information generation unit 63 .

When the sensor control unit 62 receives the stop information from the designation information receiving unit 61, the sensor control unit 62 causes the roadside sensor to stop measurement.

Upon receiving the stop information from the designation information receiving unit 61, the measurement information generating unit 63 stops generating the measurement information.

[Vehicle traffic control device]
FIG. 3 is a diagram showing the configuration of the vehicle traffic management device according to the embodiment of the present disclosure.

Referring to FIG. 3, vehicle traffic management apparatus 100 includes a receiving unit 101, a dynamic information generating unit 102, a prediction model updating unit 103, a running index improving unit 104, a specified information generating unit 105, and a storage unit. 106 , a transmission unit 107 , and a prediction information generation unit 110 . Prediction information generation section 110 includes calculation section 111 and prediction information adjustment section 112 .

Storage unit 106 is, for example, a non-volatile memory. The storage unit 106 stores, for example, map information including information on the installation location of the roadside device 60 .

The receiving unit 101 can receive measurement information from a plurality of roadside devices 60 . For example, the receiving unit 101 receives measurement information from a plurality of roadside devices 60 selected according to the current position of the target vehicle 40 as follows.

For example, the receiving unit 101 receives position information indicating the current position of the target vehicle 40 from the in-vehicle device 200 mounted on the target vehicle 40 . Receiving section 101 outputs the received position information to designation information generating section 105 .

The designation information generation unit 105 is an example of a designation unit that instructs the roadside device 60 about the contents of the measurement information that the roadside device 60 should transmit.

More specifically, upon receiving the position information from the receiving unit 101 , the designation information generating unit 105 refers to the map information in the storage unit 106 to determine the position of the target vehicle 40 based on the current position and traveling direction of the target vehicle 40 . A plurality of roadside devices 60 are selected that can generate measurement information used to generate prediction information to be transmitted to. Then, the designation information generation unit 105 transmits designation information designating the content of the measurement information to be transmitted to each of the plurality of selected roadside devices 60 via the transmission unit 107 .

Upon receiving measurement information from each of the plurality of selected roadside devices 60, the reception unit 101 outputs the received measurement information to the dynamic information generation unit 102 and notifies the designation information generation unit 105 of the reception.

For example, upon receiving the notification from the receiving unit 101 , the designation information generating unit 105 transmits stop information indicating that transmission of the measurement information should be stopped to the plurality of selected roadside devices 60 via the transmitting unit 107 .

Upon receiving the measurement information from the reception unit 101, the dynamic information generation unit 102 generates dynamic information indicating the current positions of the vehicle 41 other than the target vehicle 40 and the pedestrian 42 based on the received measurement information. .

More specifically, the dynamic information generator 102 merges multiple pieces of sensor data included in the measurement information generated by the roadside device 60 . For example, the dynamic information generation unit 102 merges each sensor data acquired by multiple types of roadside sensors in different measurement areas. Then, the dynamic information generator 102 detects the current positions of other vehicles 41 and pedestrians 42 in the measurement area by analyzing the merged sensor data.

The dynamic information generation unit 102 generates dynamic information indicating the current positions of the detected other vehicle 41 and the pedestrian 42, outputs the generated dynamic information to the prediction information generation unit 110, and transmits the information to the transmission unit 107. and transmitted to the in-vehicle device 200 via the radio base station device 20 .

The prediction information generator 110 generates prediction information indicating the predicted position of at least one of the other vehicle 41 and the pedestrian 42 based on the measurement information received by the receiver.

For example, storage unit 106 stores a prediction model for calculating the predicted positions of other vehicle 41 and pedestrian 42 after a predetermined time based on dynamic information.

When the dynamic information is received from the dynamic information generation unit 102, the calculation unit 111 in the prediction information generation unit 110 acquires the prediction model from the storage unit 106, and performs calculation using the acquired prediction model and the received dynamic information. By doing so, prediction information is generated that indicates the predicted positions of other vehicles 41 and pedestrians 42 within a predetermined time in the prediction region corresponding to the measurement region of the roadside sensor.

Operation section 111 outputs the generated prediction information to prediction information adjustment section 112 .

Upon receiving the prediction information from the calculation unit 111, the prediction information adjustment unit 112 adjusts the content of the received prediction information as necessary.

For example, the storage unit 106 stores transmission content information indicating various parameters related to prediction information to be transmitted to the target vehicle 40 . The storage unit 106 stores, for example, a prediction region, a prediction period, and a prediction information generation cycle for each target vehicle 40 , that is, the in-vehicle device 200 , as transmission content information.

Upon receiving the prediction information from calculation section 111, prediction information adjustment section 112 determines the prediction information received from calculation section 111 based on the transmission content information in storage section 106 to correspond to the prediction region and prediction period indicated by the transmission content information. extract the data that

Prediction information adjustment section 112 outputs the extracted data to transmission section 107 as prediction information.

Transmission unit 107 transmits the dynamic information received from dynamic information generation unit 102 and the prediction information received from prediction information generation unit 110 to target vehicle 40 .

For example, the receiving unit 101 receives from the target vehicle 40 the evaluation result of the prediction information transmitted to the target vehicle 40 by the transmitting unit 107 .

For example, the in-vehicle device 200 in the target vehicle 40 generates support information as described above based on the prediction information received from the vehicle traffic management device 100 . Then, the in-vehicle device 200 calculates the predicted positions of the other vehicle 41 and the pedestrian 42 indicated by the prediction information received from the vehicle traffic management device 100 and the predicted positions of the other vehicle 41 on the travel route of the target vehicle 40 based on the generated support information. And the difference from the actual position of the pedestrian 42 is calculated, and the calculated difference is transmitted to the vehicle traffic management device 100 as the predicted position evaluation result.

Further, for example, the in-vehicle device 200 in the target vehicle 40 calculates an index related to the running of the target vehicle 40 in the result of the target vehicle 40 running based on the support information, and evaluates the calculated index as a KPI (Key Performance Indicator). The result is transmitted to the vehicle traffic management device 100 .

Upon receiving the predicted position evaluation result from the in-vehicle device 200 , the reception unit 101 outputs the received predicted position evaluation result to the prediction model update unit 103 . Further, when receiving the KPI evaluation result from the in-vehicle device 200 , the receiving unit 101 outputs the received KPI evaluation result to the driving index improving unit 104 .

For example, prediction information generator 110 adjusts the content of prediction information to be generated based on the evaluation result received by receiver 101 .

More specifically, when prediction model updating section 103 receives the predicted position evaluation result from receiving section 101, prediction model update section 103 updates the prediction model in storage section 106 based on the received predicted position evaluation result.

For example, the prediction model updating unit 103 changes the coefficients of the calculation formula in the prediction model based on the predicted position evaluation result. Note that the prediction model update unit 103 may be configured to update the prediction model by giving the prediction position evaluation result to the prediction model having a machine learning function.

Upon receiving the KPI evaluation result from the receiving unit 101, the driving index improving unit 104 updates the transmission content information for each in-vehicle device 200 in the storage unit 106 based on the received KPI evaluation result.

For example, the running index improving unit 104 changes the prediction region and prediction period in the transmission content information based on the KPI evaluation result. For example, when receiving a KPI evaluation result indicating that the safety and security index is low, the driving index improvement unit 104 lengthens the prediction period in the transmission content information. For example, when receiving a KPI evaluation result indicating that the fuel consumption index is low, the driving index improving unit 104 widens the prediction area in the transmission content information. For example, when receiving a KPI evaluation result indicating that the index related to ride comfort is low, the driving index improving unit 104 shortens the generation cycle of the transmission content information.

For example, the designation information generation unit 105 instructs the roadside device 60 on the content of the measurement information to be transmitted by the roadside device 60 based on the evaluation result received by the reception unit 101 .

More specifically, the reception unit 101 outputs the predicted position evaluation result and the KPI evaluation result received from the in-vehicle device 200 to the designation information generation unit 105 .

Upon receiving the predicted position evaluation result and the KPI evaluation result from the receiving unit 101, the specified information generating unit 105 adjusts the contents of the specified information to be transmitted to the roadside device 60 based on the received predicted position evaluation result and KPI evaluation result. do.

The specified information generation unit 105 generates, for example, a predicted position evaluation result indicating that the difference between the predicted positions of the other vehicle 41 and the pedestrian 42 indicated by the prediction information and the actual positions of the other vehicle 41 and the pedestrian 42 is large. Upon receiving the request, it generates designation information for shortening the transmission cycle of the measurement information.

In addition, when the designation information generation unit 105 receives a KPI evaluation result indicating that the index related to fuel efficiency is low, for example, the designation information generation unit 105 selects more roadside devices 60 to transmit measurement information in order to request measurement information in a wider measurement area. to select.

[In-vehicle device]
FIG. 4 is a diagram showing a configuration of an in-vehicle device according to an embodiment of the present disclosure.

Referring to FIG. 4 , in-vehicle device 200 includes receiving unit 201 , support information generating unit 202 , vehicle control unit 203 , current position acquiring unit 204 , storage unit 205 , transmitting unit 206 , evaluating unit 210 and Evaluation unit 210 includes predicted position evaluation unit 211 and KPI evaluation unit 212 .

Storage unit 205 is, for example, a non-volatile memory. The storage unit 205 stores, for example, setting information related to driving preferences set by the user of the target vehicle 40, such as the driver, or travel history.

Each unit in in-vehicle device 200 is implemented by, for example, one or a plurality of ECUs (Electronic Control Units).

For example, the receiving unit 201 and the transmitting unit 206 are realized by one TCU (Telematics Communication Unit), and perform wireless communication using radio waves with the wireless base station device 20 according to communication standards such as LTE (Long Term Evolution), 3G or 5G. It is possible to

The receiving unit 201 outputs information from outside the target vehicle 40 included in the radio signal received from the radio base station device 20 to each unit in the in-vehicle device 200 . Further, the transmission unit 206 transmits to the radio base station device 20 a radio signal including information for the outside of the target vehicle 40 received from each unit in the in-vehicle device 200 .

The current position acquisition unit 204 acquires the current position of its own target vehicle 40 based on radio waves from positioning satellites, for example, at predetermined intervals, and generates position information indicating the acquired current position. The current position acquisition unit 204 outputs the generated position information to the support information generation unit 202 and also transmits the information to the vehicle traffic management device 100 via the transmission unit 206 and the radio base station device 20 .

The receiving unit 201 receives prediction information from the vehicle traffic management device 100 . For example, the receiving unit 201 also receives dynamic information from the vehicle traffic management device 100 . Receiving section 201 outputs the received prediction information and dynamic information to support information generating section 202 and predicted position evaluating section 211 .

The support information generation unit 202 generates support information for driving support or travel support based on the prediction information received from the reception unit 201 .

More specifically, the assistance information generation unit 202 uses, for example, map matching processing to determine the destination based on the location information received from the current location acquisition unit 204 and the prediction information and dynamic information received from the reception unit 201. It generates support information including control details such as the driving route to the destination or the speed in automatic driving to the destination.

The support information generator 202 outputs the generated support information to the vehicle controller 203 .

Based on the assistance information received from the assistance information generation unit 202, the vehicle control unit 203 performs control to display, for example, the driving route indicated by the assistance information on the screen of the car navigation system, or performs automatic control according to the control contents such as speed. I drive.

The evaluation unit 210 determines the actual position of the other vehicle 41, the actual position of the pedestrian 42, and the position of the target vehicle 40 as a result of the target vehicle 40 traveling based on the support information generated by the support information generation unit 202. The prediction information received by the receiving unit 201 is evaluated based on at least one of the driving indicators.

More specifically, the predicted position evaluation unit 211 in the evaluation unit 210 evaluates the predicted information based on the actual positions of the other vehicle 41 and the pedestrian 42 as a result of the target vehicle 40 traveling based on the support information. do.

For example, the predicted position evaluation unit 211 acquires measurement information indicating results of measurement by sensors such as LiDAR and a camera mounted on the target vehicle 40 . Based on the acquired measurement information, the predicted position evaluation unit 211 generates position information indicating the presence or absence of other vehicles 41 and pedestrians 42 and the positions of the other vehicles 41 and pedestrians 42 .

The predicted position evaluation unit 211 calculates the predicted positions of the other vehicle 41 and the pedestrian 42 indicated by the prediction information received from the receiving unit 201 and the actual positions of the other vehicle 41 and the pedestrian 42 indicated by the generated position information. Calculate the difference between

Predicted position evaluation section 211 outputs the calculated difference to transmission section 206 as a predicted position evaluation result.

The KPI evaluation unit 212 in the evaluation unit 210 evaluates the prediction information based on the KPI index, which is an index regarding the travel of the target vehicle 40 as a result of the travel of the target vehicle 40 based on the support information.

For example, the KPI evaluation unit 212 uses various sensors installed in the target vehicle 40, such as a brake sensor, an accelerator sensor, an acceleration sensor, a steering sensor, a fuel consumption sensor, an electricity consumption sensor, a LiDAR, a camera, and an in-vehicle camera. Get information.

The KPI evaluation unit 212 calculates an evaluation score for each index using the acquired measurement information according to each calculation formula for calculating an index for safety and security, an index for fuel or electricity consumption, and an index for ride comfort.

Here, in the course of traveling of the target vehicle 40 based on the assistance information, for example, when abrupt braking and abrupt steering are performed, the brake sensor and the steering sensor measure high brake pressure and abrupt changes in the steering angle, respectively. can get. When measurement information indicating such measurement results is used, a low evaluation score is calculated in the index related to safety and security.

In addition, when the target vehicle 40 approaches an obstacle such as another vehicle 41 while the target vehicle 40 is traveling based on the support information, the LiDAR or camera obtains a measurement result indicating that the distance to the obstacle was small. When measurement information indicating such measurement results is used, a low evaluation score is calculated in the index related to safety and security.

In addition, when the object vehicle 40 is running based on the support information and, for example, is suddenly accelerated, the acceleration sensor obtains a measurement result indicating a large change in acceleration. When measurement information indicating such measurement results is used, a low evaluation score is calculated for an index relating to ride comfort.

Also, in the process of driving the target vehicle 40 based on the support information, for example, when the driver feels stressed, the fact that the driver felt stressed can be detected by image analysis of the driver's facial expression obtained by the in-vehicle camera. The measurement results shown are obtained. When measurement information indicating such measurement results is used, a low evaluation score is calculated for an index relating to ride comfort.

Further, when the target vehicle 40 travels based on the assistance information, for example, when a traffic jam occurs, the fuel consumption sensor obtains a measurement result indicating that the traveled distance per unit fuel amount was short. When measurement information indicating such measurement results is used, a low evaluation score is calculated for the index related to fuel consumption.

The KPI evaluation unit 212 calculates a KPI index based on the evaluation score for each index. For example, the KPI evaluation unit 212 refers to the setting information in the storage unit 205, sets a standard, that is, a threshold value, for the evaluation score of each index according to the driving preference of the driver, and sets the evaluation score of each index. , the difference from the set threshold is calculated as a KPI index.

Here, since the indicators related to safety and security, electricity consumption or fuel efficiency and the indicators related to ride comfort are inconsistent, for example, if the evaluation score for the indicators related to safety and security, electricity consumption or fuel efficiency is high, the indicators related to ride comfort Evaluation scores tend to be low.

Therefore, the KPI evaluation unit 212 sets, for example, a threshold value for the evaluation score in the index related to safety and security to a predetermined value or more regardless of the setting information set by the driver. Thresholds for indicators of are set according to configuration information set by the driver.

Further, for example, if setting information indicating that fuel consumption is given priority over ride comfort is registered in storage unit 205, KPI evaluation unit 212 sets a high threshold value for an index related to fuel consumption, Set a low threshold for metrics.

The KPI evaluation unit 212 outputs the calculated KPI index to the transmission unit 206 as a KPI evaluation result. The KPI evaluation unit 212 also outputs the calculated KPI index to the support information generation unit 202 .

Upon receiving the KPI index from the KPI evaluation unit 212, the support information generation unit 202 generates support information, such as control details in automatic driving or a route to the destination, as needed to improve the KPI index based on the received KPI index. Change the driving route.

In the KPI index received from the KPI evaluation unit 212, the support information generation unit 202 reduces the traveling speed in automatic driving, for example, when the evaluation score in the index related to safety and security is equal to or less than the corresponding threshold value The timing of braking in is advanced, the driving lane in automatic driving is changed to a lane with fewer other vehicles 41, and the driving route included in the support information is changed to a route passing through a wide road.

In addition, in the KPI index received from the KPI evaluation unit 212, if the evaluation score for the index related to electricity consumption is equal to or less than the corresponding threshold value, the support information generation unit 202 may, for example, reduce the speed change as much as possible by automatically driving the vehicle. In addition, the driving speed in automatic driving is changed to an appropriate speed to reduce electricity consumption.

In the KPI index received from the KPI evaluation unit 212, the support information generation unit 202 automatically generates a Decrease the brake pressure in driving.

In addition, for example, when the evaluation score for the safety and security index is equal to or less than the threshold value, the support information generation unit 202 gives top priority to improving the safety and security index, and the evaluation score for the safety and security index exceeds the threshold value. If it is larger than the threshold, improvement is preferentially performed on the index with a large difference between the evaluation score and the threshold among the indexes with the evaluation score equal to or less than the threshold.

FIG. 5 is a diagram showing an example of a travel route along which a target vehicle travels in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 5, for example, vehicle traffic management device 100 generates prediction information based on the measurement information received from roadside device 60A and transmits it to vehicle-mounted device 200 of target vehicle 40, and vehicle-mounted device 200 receives the prediction information. Based on the prediction information, a travel route R1 to the destination D1 is generated as support information, and a situation is assumed in which the target vehicle 40 travels along the travel route R1.

As a result of the target vehicle 40 traveling along the travel route R1, the in-vehicle device 200 causes a traffic jam due to the merging of the other vehicles 41A, 41B, and 41C. A certain KPI index is calculated, and the calculated KPI index is transmitted to the vehicle traffic management device 100 as an evaluation result.

Then, for example, when the target vehicle 40 travels to the destination D1 on another day, the vehicle traffic management device 100 acquires measurement information in a wider measurement area based on the KPI index received from the in-vehicle device 200 in the past. In order to do so, the roadside device 60B is selected in addition to the roadside device 60A as the roadside device 60 to which the measurement information is to be transmitted, and the designation information is transmitted to the roadside devices 60A and 60B, respectively.

The vehicle traffic management device 100 generates prediction information based on the measurement information received from the roadside devices 60A and 60B, and transmits the generated prediction information to the in-vehicle device 200 .

The in-vehicle device 200 detects that there is a possibility of traffic congestion occurring in the middle of the travel route R1 based on the prediction information generated based on the measurement information received from the roadside devices 60A and 60B, and uses the travel route information as support information. Generate R2. As a result, the target vehicle 40 can avoid traffic congestion and travel to the destination D1.

Note that the vehicle traffic management device 100 is not limited to when the target vehicle 40 travels to the destination D1, but also when the target vehicle 40 travels to another destination. Based on this, measurement information in a wider measurement area may be acquired, and prediction information generated based on the acquired measurement information may be transmitted to the in-vehicle device 200 .

FIG. 6 is a diagram showing an example of a travel route along which a target vehicle travels in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 6, for example, vehicle traffic management device 100 generates prediction information based on measurement information received from roadside device 60 and transmits it to vehicle-mounted device 200 of target vehicle 40, and vehicle-mounted device 200 receives the prediction information. Based on the prediction information, support information including the travel speed V1 in automatic driving is generated, and a situation is assumed in which the target vehicle 40 travels along the travel route R3 at the travel speed V1.

Based on the measurement information received from the roadside device 60, the vehicle traffic management apparatus 100 generates prediction information indicating that the predicted position 42N1 of the pedestrian 42 after N seconds is on the sidewalk, and stores the generated prediction information in the vehicle. Send to device 200 .

When the target vehicle 40 turns left at the intersection while keeping the traveling speed V1 based on the received prediction information, the actual position 42N2 of the pedestrian 42 after N seconds is on the crosswalk intersecting the traveling route R3, and the vehicle suddenly brakes. needed. Therefore, the in-vehicle device 200 calculates a KPI index whose evaluation score is equal to or less than a threshold value for an index related to safety and security, an index related to fuel consumption, and an index related to ride comfort, and uses the calculated KPI index as a KPI evaluation result. 100.

The in-vehicle device 200 also calculates the difference between the predicted position 42N1 of the pedestrian 42 indicated by the prediction information and the actual position 42N2, and transmits the calculated difference to the vehicle traffic management device 100 as the predicted position evaluation result.

For example, when the target vehicle 40 travels along the travel route R3 on another day, the vehicle traffic management device 100 calculates an index relating to safety and security, an index relating to fuel efficiency, and a ride quality based on the KPI indices received from the in-vehicle device 200 in the past. Improve metrics on That is, the vehicle traffic management device 100 generates designation information for shortening the transmission period of the measurement information in order to acquire the measurement information in a shorter period and generate the prediction information, and sends the generated designation information to the roadside unit. 60.

The vehicle traffic management device 100 generates prediction information based on the measurement information received from the roadside device 60 in a shorter cycle, thereby generating prediction information indicating a more accurate predicted position of the pedestrian 42, and generating the prediction. The information is transmitted to the in-vehicle device 200 .

The in-vehicle device 200 receives prediction information indicating that the predicted position of the pedestrian 42 after N seconds will be on the pedestrian crossing, and based on the received prediction information, decelerates before the pedestrian crossing to avoid danger. By generating support information including brake control, the target vehicle 40 is decelerated before the crosswalk.

In addition, the in-vehicle device 200 generates support information including a traveling speed V2 that is slower than the traveling speed V1 based on the KPI index for which the evaluation score in the index related to safety and security is equal to or less than the threshold value, thereby generating an index related to safety and security. improve.

[Flow of operation]
Each device in the vehicle traffic management system 300 includes a computer including a memory, and an arithmetic processing unit such as a CPU in the computer reads out from the memory a program including part or all of each step of the following flowcharts and sequences. Execute. Programs for these multiple devices can each be installed from the outside. Programs for these devices are stored in recording media and distributed.

FIG. 7 is a flowchart that defines the operation procedure of the vehicle traffic management device in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 7, first, vehicle traffic management apparatus 100 receives position information of target vehicle 40 from in-vehicle apparatus 200, for example, at predetermined intervals (step S102).

Next, the vehicle traffic management device 100 selects a plurality of roadside devices 60 based on the received position information and map information, and transmits designation information for requesting measurement information to each of the selected plurality of roadside devices 60. (step S104).

Next, the vehicle traffic management device 100 receives measurement information from each of the plurality of selected roadside devices 60 (step S106).

Next, the vehicle traffic management device 100 generates dynamic information indicating the current positions of the vehicles 41 other than the target vehicle 40 and the pedestrians 42 based on the received measurement information (step S108).

Next, vehicle traffic management device 100 performs calculations using the prediction model and the generated dynamic information to generate prediction information indicating the predicted positions of other vehicles 41 and pedestrians 42 (step S110).

Next, the vehicle traffic management device 100 adjusts the content of the generated prediction information based on the transmission content information in the storage unit 106 (step S112).

Next, the vehicle traffic management device 100 transmits dynamic information and prediction information to the target vehicle 40 (step S114).

FIG. 8 is a flowchart that defines the operation procedure of the vehicle-mounted device in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 8, first, in-vehicle device 200 acquires position information of target vehicle 40, for example, at a predetermined cycle, and transmits the acquired position information to vehicle traffic management device 100 (step S202).

Next, the in-vehicle device 200 receives the dynamic information and prediction information generated based on the positional information and the like from the vehicle traffic management device 100 (step S204).

Next, based on the prediction information and the dynamic information received from the vehicle traffic management device 100, the in-vehicle device 200 provides support information including control details such as the driving route to the destination or the speed in automatic driving to the destination. is generated (step S206).

Next, the in-vehicle device 200 determines the actual position of the other vehicle 41, the actual position of the pedestrian 42, and the index related to the travel of the target vehicle 40 as a result of the target vehicle 40 traveling based on the support information. , evaluates the prediction information received from the vehicle traffic management device 100 (step S208).

Next, the in-vehicle device 200 transmits the predicted position evaluation result and the KPI evaluation result to the vehicle traffic management device 100 as the prediction information evaluation result (step S210).

FIG. 9 is a diagram showing an example of a sequence of traffic management processing in the vehicle traffic management system according to the embodiment of the present disclosure.

Referring to FIG. 9, first, a plurality of in-vehicle devices 200 transmit position information of corresponding target vehicle 40 to vehicle traffic management device 100 (step S302).

Next, the vehicle traffic management device 100 selects a plurality of roadside devices 60 based on the received position information and map information, and designates information for designating the content of measurement information to be transmitted to each roadside device 60. is generated (step S304).

Next, the vehicle traffic management device 100 transmits the generated designation information to each of the plurality of selected roadside devices 60 (step S306).

Next, each roadside device 60 receives designation information from the vehicle traffic management device 100 and generates measurement information based on the received designation information (step S308).

Next, each roadside device 60 transmits the generated measurement information to the vehicle traffic management device 100 (step S310).

Next, the vehicle traffic management device 100 generates dynamic information and prediction information to be transmitted to each in-vehicle device 200 for each in-vehicle device 200 based on the measurement information received from each roadside device 60 (step S312).

Next, the vehicle traffic management device 100 transmits the generated dynamic information and prediction information for each in-vehicle device 200 to the corresponding in-vehicle device 200 (step S314).

Next, each in-vehicle device 200 generates support information including control details such as a travel route to the destination or speed in automatic driving to the destination based on the received dynamic information and prediction information (step S316).

Next, each in-vehicle device 200 calculates the actual position of the other vehicle 41, the actual position of the pedestrian 42, and an index regarding the travel of the target vehicle 40 as a result of the travel of the corresponding target vehicle 40 based on the assistance information. (step S318).

Next, each in-vehicle device 200 transmits the predicted position evaluation result and the KPI evaluation result to the vehicle traffic management device 100 as the prediction information evaluation result (step S320).

Next, the vehicle traffic management device 100 updates the prediction model based on the predicted position evaluation result and the KPI evaluation result received from each in-vehicle device 200, and updates the transmission content information for each in-vehicle device 200 in the storage unit 106. (step S322).

Note that part or all of the functions of the vehicle traffic management device 100 according to the embodiment of the present disclosure may be provided by cloud computing. That is, the vehicle traffic management device 100 according to the embodiment of the present disclosure may be configured by a plurality of cloud servers or the like.

Further, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the prediction information adjustment unit 112 in the prediction information generation unit 110 generates a prediction based on the evaluation result received from the target vehicle 40, that is, the in-vehicle device 200. Although it is described that the content of the information is adjusted, the present invention is not limited to this. The prediction information generation unit 110 may be configured to transmit the prediction information generated based on the measurement information received from the roadside device 60 to the in-vehicle device 200 via the transmission unit 107 without including the prediction information adjustment unit 112. .

Further, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the designation information generation unit 105 generates measurement information to be transmitted by the roadside device 60 based on the evaluation result received from the target vehicle 40, that is, the in-vehicle device 200. Although the configuration is such that the content of the designation information that designates the content is adjusted, the present invention is not limited to this. The designation information generation unit 105 may be configured to transmit the designation information generated based on the map information and the position information of the target vehicle 40 to the roadside device 60 via the transmission unit 107 regardless of the evaluation result.

Further, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the storage unit 106 is configured to store transmission content information for each in-vehicle device 200, but the configuration is not limited to this. The storage unit 106 may be configured to store transmission content information common to some or all of the plurality of in-vehicle devices 200 in the vehicle traffic management system 300 .

Further, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the driving index improvement unit 104 receives the KPI evaluation result from the in-vehicle device 200 via the receiving unit 101, and the in-vehicle device 200 in the storage unit 106 Although it has been described that the transmission content information corresponding to is updated, the configuration is not limited to this. The running index improving unit 104 may be configured to update the transmission content information corresponding to the other in-vehicle device 200 in the storage unit 106 based on the KPI evaluation results received from the in-vehicle device 200 via the receiving unit 101 .

In addition, in the in-vehicle device 200 according to the embodiment of the present disclosure, the support information generation unit 202 is configured to generate support information based on position information, prediction information, and dynamic information. not a thing The support information generation unit 202 may be configured to generate support information based on position information and prediction information.

Further, in the in-vehicle device 200 according to the embodiment of the present disclosure, the evaluation unit 210 includes a predicted position evaluation unit 211 that evaluates predicted information based on the actual positions of other vehicles 41 and pedestrians 42, and a KPI indicator. Although the configuration includes the KPI evaluation unit 212 that evaluates prediction information based on the above, the present invention is not limited to this. The evaluation unit 210 may have a configuration that does not include either one of the predicted position evaluation unit 211 and the KPI evaluation unit 212 .

In addition, in the in-vehicle device 200 according to the embodiment of the present disclosure, the KPI evaluation unit 212 calculates an index regarding travel of the target vehicle 40 based on each index regarding security and safety, an index regarding fuel or electricity consumption, and an index regarding ride comfort. Although it has been described that the KPI index is calculated as follows, the present invention is not limited to this. The KPI evaluation unit 212 may be configured to calculate KPI indices based on indices other than the above indices.

By the way, a technology capable of improving the quality of driving assistance or travel assistance in a vehicle is desired.

On the other hand, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the receiving unit 101 can receive measurement information from multiple roadside devices 60 . Based on the measurement information received by the receiving unit 101, the predicted information generating unit 110 generates predicted information indicating the predicted position of at least one of the vehicle and the pedestrian. Transmission section 107 transmits the prediction information generated by prediction information generation section 110 to target vehicle 40 .

With such a configuration, the prediction information can be generated based on the measurement information received from, for example, a plurality of roadside devices 60, so that the target vehicle 40 can operate using the prediction information based on the measurement information covering a wide range. Assistance or driving assistance can be provided.

Therefore, with the vehicle traffic management device 100 according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

Moreover, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the receiving unit 101 further receives the evaluation result of the prediction information transmitted by the transmitting unit 107 from the target vehicle 40 . The prediction information generator 110 adjusts the content of prediction information to be generated based on the evaluation result received by the receiver 101 .

With such a configuration, for example, the content of the evaluation of the actual travel result using the prediction information by the target vehicle 40 can be reflected in the generation of the prediction information in the vehicle traffic management device 100, and the prediction accuracy can be improved, for example.

Moreover, in the vehicle traffic management device 100 according to the embodiment of the present disclosure, the receiving unit 101 further receives the evaluation result of the prediction information transmitted by the transmitting unit 107 from the target vehicle 40 . The designation information generation unit 105 instructs the roadside device 60 on the contents of the measurement information to be transmitted by the roadside device 60 based on the evaluation result received by the reception unit 101 .

With such a configuration, for example, the content of the evaluation of the actual travel result using the prediction information by the target vehicle 40 is reflected in the content of the measurement information used to generate the prediction information, such as the transmission cycle of the measurement information by the roadside device 60. be able to.

In addition, in the in-vehicle device 200 according to the embodiment of the present disclosure, the reception unit 201 receives prediction information indicating the predicted position of at least one of another vehicle and a pedestrian from the vehicle traffic management device 100 . The support information generation unit 202 generates support information for driving support or travel support based on the prediction information received by the reception unit 201 . The evaluation unit 210 evaluates the actual positions of other vehicles, the actual positions of pedestrians, and the travel of the own vehicle as a result of the travel of the own vehicle based on the support information generated by the support information generation unit 202. The predictive information received by the receiving unit 201 is evaluated based on at least one of the indicators. The transmission unit 206 transmits the evaluation result by the evaluation unit 210 to the vehicle traffic management device 100 .

With such a configuration, the content of the evaluation of the actual traveling result using the prediction information received from the vehicle traffic management device 100 is fed back to the vehicle traffic management device 100, and the content of the prediction information to be transmitted by the vehicle traffic management device 100 is changed. can be improved, for example to improve prediction accuracy.

Therefore, with the in-vehicle device 200 according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

Also, the vehicle traffic management system 300 according to the embodiment of the present disclosure includes a vehicle traffic management device 100 and an in-vehicle device 200 . Based on the measurement information received from one or more roadside devices 60, the vehicle traffic management device 100 generates prediction information indicating the predicted position of at least one of other vehicles and pedestrians, and uses the generated prediction information. It transmits to the in-vehicle device 200 . The in-vehicle device 200 generates assistance information for driving assistance or travel assistance based on the prediction information received from the vehicle traffic management device 100 . The in-vehicle device 200 indicates at least one of the actual positions of other vehicles, the actual positions of pedestrians, and an index related to the running of the own vehicle as a result of the running of the own vehicle based on the generated support information. Based on one, it evaluates the prediction information received from the vehicle traffic management device 100 and transmits the evaluation result to the vehicle traffic management device 100 .

With such a configuration, the vehicle traffic management device 100 can generate prediction information based on measurement information received from, for example, a plurality of roadside devices 60. Driving assistance or travel assistance using the prediction information based on the vehicle can be performed. Furthermore, the content of the evaluation of the actual running result of the target vehicle 40 using the prediction information generated by the vehicle traffic management device 100 is fed back to the vehicle traffic management device 100, and the content of the prediction information generated by the vehicle traffic management device 100 can be improved, e.g., predictive accuracy can be improved.

Therefore, in the vehicle traffic management system 300 according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in vehicles.

Also, the vehicle traffic management method according to the embodiment of the present disclosure is the vehicle traffic management method in the vehicle traffic management device 100 . In this vehicle traffic management method, first, the vehicle traffic management device 100 receives measurement information from one or more roadside devices 60 . Next, the vehicle traffic management device 100 generates prediction information indicating the predicted position of at least one of the vehicle and the pedestrian based on the received measurement information. Next, the vehicle traffic management device 100 transmits the generated prediction information to the target vehicle 40 .

With such a method, the prediction information can be generated based on the measurement information received from, for example, a plurality of roadside devices 60, so that the target vehicle 40 can operate using the prediction information based on the measurement information covering a wide range. Assistance or driving assistance can be provided.

Therefore, with the vehicle traffic management method according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

Also, the vehicle traffic management method according to the embodiment of the present disclosure is a vehicle traffic management method for the in-vehicle device 200 . In this vehicle traffic management method, the in-vehicle device 200 first receives from the vehicle traffic management device 100 prediction information indicating the predicted position of at least one of another vehicle and a pedestrian. Next, the in-vehicle device 200 generates assistance information for driving assistance or travel assistance based on the received prediction information. Next, the in-vehicle device 200 selects the actual positions of other vehicles, the actual positions of the pedestrians, and the index related to the running of the own vehicle as a result of the running of the own vehicle based on the generated support information. Evaluate the received predictive information based on at least one of them. Next, the in-vehicle device 200 transmits the evaluation result to the vehicle traffic management device.

By such a method, the content of the evaluation of the actual traveling result using the prediction information received from the vehicle traffic management device 100 is fed back to the vehicle traffic management device 100, and the content of the prediction information to be transmitted by the vehicle traffic management device 100 is changed. can be improved, for example to improve prediction accuracy.

Therefore, with the vehicle traffic management method according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

Also, the vehicle traffic management method according to the embodiment of the present disclosure is a vehicle traffic management method in vehicle traffic management system 300 including vehicle traffic management device 100 and in-vehicle device 200 . In this vehicle traffic management method, first, the vehicle traffic management device 100 generates prediction information indicating the predicted positions of at least one of other vehicles and pedestrians based on measurement information received from one or more roadside devices 60. and transmits the generated prediction information to the in-vehicle device 200 . Next, the in-vehicle device 200 generates assistance information for driving assistance or travel assistance based on the prediction information received from the vehicle traffic management device 100 . Next, the in-vehicle device 200 selects the actual position of the other vehicle, the actual position of the pedestrian, and the indicator related to the running of the own vehicle as a result of the running of the own vehicle based on the generated support information. The prediction information received from the vehicle traffic management device 100 is evaluated based on at least one of them, and the evaluation result is transmitted to the vehicle traffic management device 100 .

With this method, the vehicle traffic management device 100 can generate prediction information based on measurement information received from, for example, a plurality of roadside devices 60, so that the vehicle-mounted device 200 can generate measurement information covering a wide range. Driving assistance or travel assistance using the prediction information based on the vehicle can be performed. Furthermore, the content of the evaluation of the actual running result of the target vehicle 40 using the prediction information generated by the vehicle traffic management device 100 is fed back to the vehicle traffic management device 100, and the content of the prediction information generated by the vehicle traffic management device 100 can be improved, e.g., predictive accuracy can be improved.

Therefore, with the vehicle traffic management method according to the embodiment of the present disclosure, it is possible to improve the quality of driving assistance or travel assistance in the vehicle.

The above-described embodiments should be considered as illustrative in all respects and not restrictive. The scope of the present invention is indicated by the scope of the claims rather than the above description, and is intended to include all modifications within the scope and meaning equivalent to the scope of the claims.

The above description includes the features appended below.
[Appendix 1]
a receiving unit that receives measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on each of the measurement information received by the receiving unit;
a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle;
The receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle,
The prediction information generation unit adjusts the content of the prediction information to be generated based on the evaluation result received by the reception unit;
The vehicle traffic management apparatus further comprises a designating unit that instructs the roadside device on the content of the measurement information to be transmitted by the roadside device based on the evaluation result received by the receiving unit.

[Appendix 2]
a receiving unit that receives predicted information indicating predicted positions of at least one of other vehicles and pedestrians from the vehicle traffic management device;
an assistance information generation unit that generates assistance information for driving assistance or traveling assistance based on the prediction information received by the reception unit;
received by the receiving unit based on the actual position of the other vehicle and the actual position of the pedestrian as a result of the vehicle running based on the support information generated by the support information generating unit; a predicted position evaluation unit that evaluates the predicted information;
KPI evaluation for evaluating the prediction information received by the receiving unit based on an index related to the running of the own vehicle in the results of the running of the own vehicle based on the assistance information generated by the assistance information generating unit. Department and
An in-vehicle device, comprising: a transmission unit configured to transmit evaluation results by the predicted position evaluation unit and the KPI evaluation unit to the vehicle traffic management device.

[Appendix 3]
a vehicle traffic management device;
and an in-vehicle device,
The vehicle traffic management device generates prediction information indicating predicted positions of at least one of other vehicles and pedestrians based on measurement information received from a plurality of roadside devices, and transmits the generated prediction information to the vehicle-mounted vehicle. to the device,
The in-vehicle device generates support information for driving support or travel support based on the prediction information received from the vehicle traffic management device,
The in-vehicle device selects the actual position of the other vehicle, the actual position of the pedestrian, and an index related to the running of the own vehicle as a result of the running of the own vehicle based on the generated support information. evaluating the prediction information received from the vehicle traffic management device based on at least one of them, and transmitting an evaluation result to the vehicle traffic management device;
The vehicle traffic management device instructs the roadside device on the content of the measurement information to be transmitted by the roadside device based on the evaluation result received from the onboard device, and also instructs the roadside device on the content of the prediction information to be generated. Coordinating vehicle traffic management system.

20 Radio base station device 40 Target vehicle 41 Other vehicle 42 Pedestrian 60 Roadside device 61 Designated information receiver 62 Sensor controller 63 Measurement information generator 64 Measurement information transmitter 100 Vehicle traffic management device 101 Receiver 102 Dynamic information generator Unit 103 Prediction model update unit 104 Driving index improvement unit 105 Designated information generation unit 106 Storage unit 107 Transmission unit 110 Prediction information generation unit 111 Calculation unit 112 Prediction information adjustment unit 200 In-vehicle device 201 Reception unit 202 Support information generation unit 203 Vehicle control unit 204 current position acquisition unit 205 storage unit 206 transmission unit 210 evaluation unit 211 predicted position evaluation unit 212 KPI evaluation unit 300 vehicle traffic management system

Claims (14)

a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle;
The vehicle traffic management device , wherein the receiving unit further receives, from the target vehicle, an evaluation result of the prediction information transmitted by the transmitting unit . a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle;
The receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle,
The vehicle traffic management apparatus, wherein the prediction information generation unit adjusts the content of the prediction information to be generated based on the evaluation result received by the reception unit. A vehicle traffic management device,
a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit configured to transmit the prediction information generated by the prediction information generation unit to the target vehicle;
The receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle,
The vehicle traffic management device further comprises:
A vehicle traffic management apparatus, comprising: a designation unit that instructs the roadside device about the content of the measurement information to be transmitted by the roadside device based on the evaluation result received by the receiving unit. a receiving unit that receives predicted information indicating predicted positions of at least one of other vehicles and pedestrians from the vehicle traffic management device;
an assistance information generation unit that generates assistance information for driving assistance or traveling assistance based on the prediction information received by the reception unit;
The actual position of the other vehicle, the actual position of the pedestrian, and an index related to the travel of the own vehicle in the results of the travel of the own vehicle based on the support information generated by the support information generation unit. an evaluation unit for evaluating the prediction information received by the receiving unit based on at least one of
an in-vehicle device comprising: a transmission unit that transmits an evaluation result by the evaluation unit to the vehicle traffic management device. a vehicle traffic management device;
and an in-vehicle device,
The vehicle traffic management device generates prediction information indicating predicted positions of at least one of other vehicles and pedestrians based on measurement information received from one or more roadside devices, and uses the generated prediction information to transmitting to the in-vehicle device;
The in-vehicle device generates support information for driving support or travel support based on the prediction information received from the vehicle traffic management device,
The in-vehicle device selects the actual position of the other vehicle, the actual position of the pedestrian, and an index related to the running of the own vehicle as a result of the running of the own vehicle based on the generated support information. A vehicular traffic management system that evaluates the prediction information received from the vehicular traffic management device based on at least one of them, and transmits an evaluation result to the vehicular traffic management device. A vehicle traffic management method in a vehicle traffic management device,
receiving measurement information from one or more roadside units;
generating prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the received measurement information;
a step of transmitting the generated prediction information to a target vehicle;
and receiving, from the target vehicle, an evaluation result of the transmitted prediction information . A vehicle traffic management method for an in-vehicle device, comprising:
receiving predicted information from a vehicle traffic management device indicating predicted positions of at least one of other vehicles and pedestrians;
generating assistance information for driving assistance or travel assistance based on the received prediction information;
At least one of the actual position of the other vehicle, the actual position of the pedestrian, and an index relating to the travel of the own vehicle as a result of the own vehicle traveling based on the generated support information. evaluating the received prediction information based on
and transmitting an evaluation result to the vehicle traffic management device. A vehicle traffic management method in a vehicle traffic management system comprising a vehicle traffic management device and an in-vehicle device,
The vehicle traffic management device generates prediction information indicating predicted positions of at least one of other vehicles and pedestrians based on measurement information received from one or more roadside devices, and transmits the generated prediction information. transmitting to the in-vehicle device;
a step in which the in-vehicle device generates support information for driving support or travel support based on the prediction information received from the vehicle traffic management device;
Of the actual position of the other vehicle, the actual position of the pedestrian, and an index related to the running of the own vehicle, as a result of the running of the own vehicle based on the support information generated by the in-vehicle device Evaluating the predictive information received from the vehicle traffic management device based on at least one of them, and transmitting an evaluation result to the vehicle traffic management device. A vehicle traffic management program used in a vehicle traffic management device,
the computer,
a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit that transmits the prediction information generated by the prediction information generation unit to a target vehicle;
It is a program for functioning as
The vehicle traffic management program , wherein the receiving unit further receives, from the target vehicle, an evaluation result of the prediction information transmitted by the transmitting unit. A vehicle traffic management program used in an in-vehicle device,
the computer,
a receiving unit that receives predicted information indicating predicted positions of at least one of other vehicles and pedestrians from the vehicle traffic management device;
an assistance information generation unit that generates assistance information for driving assistance or traveling assistance based on the prediction information received by the reception unit;
The actual position of the other vehicle, the actual position of the pedestrian, and an index related to the travel of the own vehicle in the results of the travel of the own vehicle based on the support information generated by the support information generation unit. an evaluation unit for evaluating the prediction information received by the receiving unit based on at least one of
a transmission unit that transmits the evaluation result by the evaluation unit to the vehicle traffic management device;
A vehicle traffic management program to function as A vehicle traffic management method in a vehicle traffic management device,
receiving measurement information from one or more roadside units;
generating prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the received measurement information;
a step of transmitting the generated prediction information to a target vehicle;
a step of receiving an evaluation result of the transmitted prediction information from the target vehicle;
adjusting content of the prediction information to be generated based on the received evaluation result. A vehicle traffic management method in a vehicle traffic management device,
receiving measurement information from one or more roadside units;
generating prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the received measurement information;
a step of transmitting the generated prediction information to a target vehicle;
a step of receiving an evaluation result of the transmitted prediction information from the target vehicle;
and a step of instructing the roadside device about the contents of the measurement information to be transmitted by the roadside device based on the received evaluation result. A vehicle traffic management program used in a vehicle traffic management device,
the computer,
a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit that transmits the prediction information generated by the prediction information generation unit to a target vehicle;
It is a program for functioning as
The receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle,
The vehicle traffic management program, wherein the prediction information generation unit adjusts the content of the prediction information to be generated based on the evaluation result received by the reception unit. A vehicle traffic management program used in a vehicle traffic management device,
the computer,
a receiving unit capable of receiving measurement information from a plurality of roadside devices;
a prediction information generating unit that generates prediction information indicating a predicted position of at least one of a vehicle and a pedestrian based on the measurement information received by the receiving unit;
a transmission unit that transmits the prediction information generated by the prediction information generation unit to a target vehicle;
It is a program for functioning as
The receiving unit further receives an evaluation result of the prediction information transmitted by the transmitting unit from the target vehicle,
The vehicle traffic management program further comprises:
the computer,
a designating unit that instructs the roadside device on the contents of the measurement information to be transmitted by the roadside device based on the evaluation result received by the receiving unit;
A vehicle traffic management program to function as

Images