Road condition monitoring system

Abstract

To secure a sufficient time in which a congestion can be avoided.SOLUTION: A road situation monitoring system comprises a plurality of vehicles and a server which is communicable to the vehicles. When an abnormality of a road is detected, the vehicle executes transmitting to the server notification data including a type of the abnormality, a detection position where the abnormality is detected and a detection time when the abnormality is detected. When the notification data are received, the server executes transmitting to the plurality of vehicles advance report data indicating that the abnormality occurs at the detection position. When the notification data are received, the server executes calculating an analytic value indicating an influence degree upon a congestion at the detection position on the basis of the detection time. In a case where the analytic value satisfies a condition indicating that the influence degree on the congestion is high, the server executes transmitting to the plurality of vehicles prediction data indicating that a possibility for the congestion to occur at the detection position is high. When calculating the analytic value, a learnt model which is machine-learnt may be adoptable.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a road condition monitoring system.

Background Art

[0002] The information processing system of Patent Document 1 includes a plurality of vehicles and an information center. The information center acquires detection data detected by the vehicles. Further, the information center grasps whether or not a traffic jam is occurring on the road based on the detection data acquired from the plurality of vehicles, specifically, the position information of the vehicles and the speed of the vehicles, etc.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the information processing system of Patent Document 1, it is only possible to grasp that there is a traffic jam on the road at the present time, that is, that a traffic jam has already occurred. Merely providing the already-occurred traffic jam to vehicle drivers or the like may not ensure sufficient time for vehicle drivers or the like to avoid the traffic jam.

Means for Solving the Problems

[0005] A road condition monitoring system for solving the above problems comprises multiple vehicles and a server capable of communicating with the vehicles, wherein when a road anomaly is detected, the vehicles transmit notification data to the server including the type of anomaly, the location where the anomaly was detected, and the time at which the anomaly was detected, and when the server receives the notification data, it transmits breaking news data to the multiple vehicles indicating that the anomaly has occurred at the detection location, and when the notification data is received... ,before The process involves calculating an analytical value indicating the degree of impact on traffic congestion at the detected location, and, if the analytical value satisfies the conditions indicating a high degree of impact on traffic congestion, transmitting predictive data indicating a high probability of traffic congestion occurring at the detected location to multiple vehicles. Furthermore, the server will, with respect to the same detected location, set the analysis value corresponding to that detected location to a value indicating a lower impact on the traffic congestion as the period from the detection time included in the latest notification data to the current time becomes longer. .

[0006] With the above configuration, when a vehicle detects an anomaly in the road, the server can become aware that an anomaly has occurred. The server then sends this information to each vehicle as breaking news, allowing the driver of each vehicle to predict that traffic congestion may occur at the detected location.

[0007] In addition to sending real-time data, the server calculates analytical values ​​indicating the degree of impact on traffic congestion at the detected location. If the analytical values ​​meet the conditions indicating a high degree of impact on traffic congestion, the server sends predictive data to each vehicle indicating a high probability of congestion occurring. Therefore, drivers of each vehicle can understand not only that an anomaly has occurred on the road, but also that there is a high probability that this anomaly will cause traffic congestion. [Brief explanation of the drawing]

[0008] [Figure 1] This is a schematic diagram of the road condition monitoring system. [Figure 2] This is a sequence diagram showing the first detection control and the first distribution control. [Figure 3] This is a sequence diagram showing the second detection control and the second distribution control. [Modes for carrying out the invention]

[0009] <Outline configuration of the road condition monitoring system> An embodiment of the present invention will be described below with reference to Figures 1 to 3. First, the general configuration of the road condition monitoring system 100 will be described.

[0010] As shown in Figure 1, the road condition monitoring system 100 is equipped with multiple vehicles 10. These vehicles 10 are, for example, cars owned by the user. Note that Figure 1 shows only one vehicle 10 as a representative example.

[0011] Vehicle 10 is equipped with a vehicle speed sensor 31, an acceleration sensor 32, a GNSS receiver 33, an accelerator pedal operation amount sensor 34, and a brake operation amount sensor 35. Vehicle 10 is also equipped with a brake system 36 and an airbag system 37.

[0012] The vehicle speed sensor 31 detects the vehicle speed SP, which is the speed of the vehicle 10. The acceleration sensor 32 is a so-called three-axis sensor. That is, the acceleration sensor 32 can detect longitudinal acceleration GX, lateral acceleration GY, and vertical acceleration GZ. The longitudinal acceleration GX is the acceleration along the longitudinal axis of the vehicle 10. The lateral acceleration GY is the acceleration along the lateral axis of the vehicle 10. The vertical acceleration GZ is the acceleration along the vertical axis of the vehicle 10.

[0013] The GNSS receiver 33 detects the position coordinates PC, which are the coordinates of the location where the vehicle 10 is located, by communicating with a GNSS satellite (not shown). GNSS is an abbreviation for Global Navigation Satellite System.

[0014] The accelerator pedal operation amount sensor 34 detects the accelerator pedal operation amount ACC, which is the amount of accelerator pedal operation performed by the driver. The brake pedal operation amount sensor 35 detects the brake pedal operation amount BRA, which is the amount of brake pedal operation performed by the driver.

[0015] The brake system 36 includes a brake device and a brake control device. The brake device is a so-called mechanical brake device that mechanically brakes the wheels of the vehicle 10. The brake control device controls the braking to prevent the wheels of the vehicle 10 from locking up when the brake device applies sudden braking. In other words, the brake system 36 has an ABS function. ABS is an abbreviation for Anti-lock Braking System. The airbag device 37 is a device that absorbs the impact on the occupants of the vehicle 10 by inflating the bag contained in the airbag device 37.

[0016] Vehicle 10 is equipped with a control device 20. The control device 20 acquires various signals from a vehicle speed sensor 31, an acceleration sensor 32, a GNSS receiver 33, an accelerator pedal operation amount sensor 34, and a brake operation amount sensor 35. The control device 20 can also control the brake system 36 and the airbag system 37 by outputting control signals to them. The control device 20 acquires signals from the brake system 36 and the airbag system 37 indicating the operating status of the brake system 36 and the airbag system 37.

[0017] The control device 20 comprises an execution unit 21, a storage unit 22, and a communication unit 23. The communication unit 23 can communicate with external devices of the vehicle 10 via a communication network 200. The storage unit 22 stores information acquired by the control device 20. The storage unit 22 also pre-stores various programs. The storage unit 22 includes ROM, RAM, and storage. The execution unit 21 executes various processes by reading programs from the storage unit 22. In this embodiment, one of the programs stored in the storage unit 22 is a part of a program related to road condition monitoring executed by the road condition monitoring system 100. An example of the execution unit 21 is a CPU.

[0018] In this embodiment, the execution unit 21 executes the following processes at each predetermined control cycle. The execution unit 21 calculates a vehicle required driving force, which is a required value of the driving force necessary to run the vehicle 10, based on the accelerator operation amount ACC and the vehicle speed SP. Further, the execution unit 21 calculates a road surface gradient AR, which is the gradient of the road surface where the vehicle 10 is located, based on the longitudinal acceleration GX, the lateral acceleration GY, and the vertical acceleration GZ. The execution unit 21 calculates a predicted longitudinal acceleration GXA, which is a predicted value of the acceleration along the front and rear axes of the vehicle 10, based on the vehicle required driving force, the road surface gradient AR, and the like.

[0019] As shown in FIG. 1, the road condition monitoring system 100 includes a server 50. The server 50 includes an execution unit 51, a storage unit 52, and a communication unit 53. The communication unit 53 can communicate with devices outside the server 50 via the communication network 200. Therefore, the server 50 can communicate with a plurality of vehicles 10. The storage unit 52 stores information and the like acquired by the server 50. Further, the storage unit 52 stores various programs in advance. Note that the storage unit 52 includes a ROM, a RAM, and a storage. The execution unit 51 executes various processes by reading the programs in the storage unit 52. In this embodiment, one of the programs stored in the storage unit 52 is a part of the program related to the monitoring of the road condition executed by the road condition monitoring system 100. Note that an example of the execution unit 51 is a CPU.

[0020] <First Detection Control> Next, referring to FIG. 2, the first detection control executed by the control device 20 of the vehicle 10 will be described. In this embodiment, the control device 20 repeatedly executes the first detection control at each predetermined control cycle.

[0021] As shown in Figure 2, when the control device 20 starts the first detection control, it executes the process in step S11. In step S11, the control device 20 determines whether or not a predetermined first precondition is met. An example of the first precondition is that the amount of change in vehicle speed SP per unit time is less than or equal to a predetermined specified amount of change. If the control device 20 determines in step S11 that the first precondition is not met, the control device 20 terminates the current first detection control. The control device 20 then proceeds to step S11 again. On the other hand, if the control device 20 determines in step S11 that the first precondition is met, the control device 20 proceeds to step S12.

[0022] In step S12, the control device 20 determines whether a predetermined detection condition is satisfied. Here, the detection condition is a condition determined for detecting a change in the road. In the present embodiment, the detection condition includes an accident requirement, an abnormal road surface requirement, a flooding requirement, a low friction requirement, and an obstacle requirement. The accident requirement is a requirement for detecting that an accident has occurred on the road as a change in the road. An example of the accident requirement is the requirement that the airbag device 37 has operated. The abnormal road surface requirement is a requirement for detecting that there is an abnormality in which excessive unevenness has occurred on the road as a change in the road. An example of the abnormal road surface requirement is the requirement that the absolute value of the vertical acceleration GZ is equal to or greater than a predetermined specified acceleration. The flooding requirement is a requirement for detecting that there is a flooded point on the road as a change in the road. An example of the flooding requirement is the requirement that the absolute value of the difference between the predicted longitudinal acceleration GXA and the longitudinal acceleration GX is equal to or greater than a predetermined specified difference. The low friction requirement is a requirement for detecting that there is a low friction point on the road as a change in the road. An example of the low friction requirement is the requirement that the braking system 36 is performing the ABS function and the braking operation amount BRA is equal to or less than a first operation amount determined in advance. The obstacle requirement is a requirement for detecting that there is an obstacle on the road as a change in the road. An example of the obstacle requirement is the requirement that the braking system 36 is performing the ABS function and the braking operation amount BRA is equal to or greater than a second operation amount determined in advance. Then, when any one of the accident requirement, the abnormal road surface requirement, the flooding requirement, the low friction requirement, and the obstacle requirement is satisfied, the control device 20 determines that the detection condition is satisfied. In step S12, when the control device 20 determines that the detection condition is not satisfied, the control device 20 ends the current first detection control. Then, the control device 20 proceeds to step S11 again for processing. On the other hand, in step S12, when the control device 20 determines that the detection condition is satisfied, the control device 20 proceeds to step S13 for processing.

[0023] In step S13, the control device 20 generates a type code CK, a detected location PD, and a detected time TD. Here, the type code CK indicates the type of anomaly detected in the processing of step S12. For example, if the control device 20 determines in step S12 that the accident requirement is met, the type code CK is an accident code CK1, indicating that an accident has occurred on the road as an anomaly in the road. Similarly, if the control device 20 determines in step S12 that the abnormal road surface requirement is met, the type code CK is an abnormal road surface code CK2, indicating that there is an anomaly in the road where excessive unevenness has occurred. If the control device 20 determines in step S12 that the submersion requirement is met, the type code CK is a submersion code CK3, indicating that there is a point on the road that is submerged as an anomaly in the road. If the control device 20 determines in step S12 that the low friction requirement is met, the type code CK is a low friction code CK4, indicating that there is a point on the road with low friction as an anomaly in the road. If the control device 20 determines in step S12 that the obstacle requirements are met, the type code CK is the obstacle code CK5, which indicates that there is an obstacle on the road as a road anomaly. The detected position PD is the position coordinates PC at the time the process in step S12 was executed. The detected time TD is the time the process in step S12 was executed. After step S13, the control device 20 proceeds to step S14.

[0024] In step S14, the control device 20 sends first notification data DN1, which includes type code CK, detection position PD, and detection time TD, to the server 50. As a result, the server 50 receives the first notification data DN1. After step S14, the control device 20 terminates the current first detection control. The control device 20 then proceeds to step S11 again.

[0025] <First Distribution Control> Next, with reference to Figure 2, the first distribution control performed by the server 50 will be described. In this embodiment, each time the server 50 receives the first notification data DN1 through the first detection control, the server 50 performs the first distribution control.

[0026] As shown in Figure 2, when the server 50 starts the first distribution control, it executes the process in step S31. In step S31, the server 50 sends rapid report data DP to multiple vehicles 10 indicating that an anomaly has occurred in the road at the detected location PD. Here, the rapid report data DP includes a type code CK, the detected location PD, and the detected time TD. In this embodiment, an example of a vehicle 10 to which the rapid report data DP is sent is a vehicle 10 located within a predetermined distance from the detected location PD. The predetermined distance is, for example, several kilometers to several tens of kilometers. As a result, the control devices 20 of multiple vehicles 10 receive the rapid report data DP. At this time, the control device 20 of the vehicle 10 notifies the driver of the vehicle 10, etc., via a display or the like provided in the vehicle 10, that an anomaly has occurred in the road at the detected location PD. After step S31, the server 50 proceeds to step S32.

[0027] In step S32, the server 50 sets an initial value for the analysis value VA based on the type code CK included in the first notification data DN1. For example, if the type code CK is either accident code CK1 or abnormal road surface code CK2, the server 50 sets the initial value of the analysis value VA to "200". Also, for example, if the type code CK is either submersion code CK3, low friction code CK4, or obstacle code CK5, the server 50 sets the initial value of the analysis value VA to "100". Here, the analysis value VA indicates the degree of impact on traffic congestion at the detected location PD. Furthermore, the larger the value of the analysis value VA, the greater the impact on traffic congestion due to the road anomaly. After step S32, the server 50 terminates this first distribution control.

[0028] <Second detection control> Next, with reference to Figure 3, the second detection control performed by the control device 20 of the vehicle 10 will be described. In this embodiment, the control device 20, upon receiving the rapid report data DP, repeatedly performs the second detection control at predetermined control cycles until a predetermined period has elapsed since receiving the rapid report data DP. Here, an example of a predetermined period is several hours to more than ten hours.

[0029] As shown in Figure 3, when the control device 20 starts the second detection control, it executes the process in step S61. In step S61, the control device 20 determines whether or not a predetermined second precondition is met. An example of the second precondition is that the vehicle has traveled to the detection position PD included in the rapid report data DP, and the amount of change in the vehicle speed SP per unit time is less than or equal to a predetermined specified amount of change. Note that "traveling to the detection position PD included in the rapid report data DP" does not mean that the position coordinates PC of the vehicle 10 must perfectly match the detection position PD; for example, an error of several meters to several tens of meters is acceptable. If the control device 20 determines in step S61 that the second precondition is not met, the control device 20 terminates the current second detection control. The control device 20 then proceeds to step S61 again. On the other hand, if the control device 20 determines in step S61 that the second precondition is met, the control device 20 proceeds to step S62.

[0030] In step S62, the control device 20 determines whether or not predetermined detection conditions are met. Here, the detection conditions in step S62 are the same as the detection conditions in step S12 described above. In other words, the process in step S62 is to determine whether or not any abnormality has been detected at the location where it was determined in step S12 that the detection conditions were met. Whether or not the control device 20 determines that the detection conditions are not met, or whether or not the control device 20 determines that the detection conditions are met, after step S62, the control device 20 proceeds to step S63.

[0031] In step S63, the control device 20 sends one of the first notification data DN1 and the second notification data DN2 to the server 50. Specifically, if the control device 20 determines in step S62 that the detection conditions are met, the control device 20 generates the first notification data DN1. The control device 20 then sends the first notification data DN1 to the server 50. Here, the first notification data DN1 in step S63 includes the type code CK, the detected location PD, and the detection time TD, similar to step S14. The type code CK in step S63 indicates the type of anomaly detected in the processing of step S62. The detected location PD in step S63 is the position coordinates PC at the time the processing of step S62 was executed. The detection time TD in step S63 is the time the processing of step S62 was executed. After step S63, the control device 20 terminates this second detection control. The control device 20 then proceeds to step S61 again.

[0032] On the other hand, if the control device 20 determines in step S62 that the detection conditions are not met, the control device 20 generates second notification data DN2. The control device 20 then sends the second notification data DN2 to the server 50. Here, the second notification data DN2 does not include the type code CK indicating the type of anomaly, but includes the undetected code CN, the detected location PD, and the detected time TD. The undetected code CN indicates that no road anomaly has occurred. After step S63, the control device 20 terminates this second detection control. The control device 20 then proceeds to step S61 again.

[0033] <Second Distribution Control> Next, with reference to Figure 3, the second distribution control performed by the server 50 will be described. In this embodiment, provided that the server 50 has received the first notification data DN1 and has performed the first distribution control, the server 50 repeatedly performs the second distribution control until a specified period has elapsed since the first distribution control was performed. Here, the server 50 performs the second distribution control for each target detection location PD. An example of the specified period is several hours to more than ten hours. Note that Figure 3 shows the server 50 receiving the first notification data DN1 and the second notification data DN2 from the second detection control. However, depending on the vehicle 10's travel route, etc., the server 50 may not have received the first notification data DN1 and the second notification data DN2 from the second detection control at the time the second distribution control is performed.

[0034] As shown in Figure 3, when the server 50 starts the second distribution control, it executes the process in step S81. In step S81, the server 50 calculates the analysis value VA based on the period from the detection time TD to the current time, the number of times the first notification data DN1 has been received, and the number of times the second notification data DN2 has been received. At this time, the server 50 calculates the analysis value VA by correcting the initial value of the analysis value VA set in step S32 described above.

[0035] First, let's explain how the analysis value VA is calculated based on the period from the detection time TD to the current time. Specifically, the server 50 obtains the detection time TD included in the first notification data DN1 for the same detection location PD. The server 50 then decreases the analysis value VA as the period from the detection time TD included in the latest first notification data DN1 to the current time increases. In other words, for the same detection location PD, the server 50 sets the analysis value VA corresponding to the detection location PD to a value that indicates a low degree of impact on congestion as the period from the detection time TD included in the latest first notification data DN1 to the current time increases. In this embodiment, the server 50 adds "-25" to the correction amount for the initial value of the analysis value VA for every hour the period from the latest detection time TD to the current time increases. For example, if the period from the latest detection time TD to the current time is 3 hours, the correction amount for the initial value of the analysis value VA is "-75".

[0036] Next, the calculation of the analysis value VA based on the number of times the first notification data DN1 has been received will be explained. For the same detection location PD, the server 50 increases the analysis value VA the more times the first notification data DN1 has been received by the second detection control. In other words, when a newly received detection location PD included in the first notification data DN1 is the same as a detection location PD included in the first notification data DN1 received in the past, the server 50 sets the analysis value VA corresponding to that detection location PD to a value indicating a high degree of impact on congestion. In this embodiment, for each increase in the number of times the first notification data DN1 has been received by the second detection control, the server 50 adds "+25" to the correction amount of the initial value of the analysis value VA. For example, if the number of times the first notification data DN1 has been received by the second detection control is 3, the correction amount of the initial value of the analysis value VA is "+75". However, if the analysis value VA exceeds a predetermined upper limit, the server 50 sets the analysis value VA to the upper limit. An example of an upper limit is "200".

[0037] Furthermore, the calculation of the analysis value VA based on the number of times the second notification data DN2 is received will be explained. For the same detection location PD, the server 50 reduces the analysis value VA as the number of times the second notification data DN2 is received by the second detection control increases. In other words, when the server 50 receives the second notification data DN2, it sets the analysis value VA corresponding to the detection location PD in which no anomalies are indicated in the second notification data DN2 to a value indicating a low impact on congestion. In this embodiment, for each increase in the number of times the second notification data DN2 is received by the second detection control, the server 50 adds "-25" to the correction amount for the initial value of the analysis value VA. For example, if the number of times the second notification data DN2 is received by the second detection control is 3, the correction amount for the initial value of the analysis value VA is "-75". After step S81, the server 50 proceeds to step S82.

[0038] In step S82, the server 50 determines whether the analyzed value VA meets a predetermined distribution condition indicating a high degree of impact on congestion. Here, the distribution condition is that the analyzed value VA is greater than a predetermined baseline value. An example of a baseline value is "100".

[0039] In step S82, if server 50 determines that the delivery conditions are not met, server 50 terminates this second delivery control. Then, server 50 proceeds to step S81 again. On the other hand, if server 50 determines in step S82 that the delivery conditions are met, server 50 proceeds to step S83.

[0040] In step S83, the server 50 transmits prediction data DE to multiple vehicles 10, indicating that there is a high probability of congestion occurring at the detected location PD. In this embodiment, an example of a vehicle 10 to which the prediction data DE is transmitted is a vehicle 10 that has received the breaking news data DP. As a result, the control devices 20 of multiple vehicles 10 receive the prediction data DE. At this time, the control devices 20 of the vehicles 10 notify the drivers of the vehicles 10, etc., via displays or other devices installed in the vehicles 10, that there is a high probability of congestion occurring at the detected location PD. After step S83, the server 50 terminates this second distribution control. Then, the server 50 proceeds to step S81 again.

[0041] <Operation of this embodiment> For example, suppose an obstacle is lying at a specific point on the road. Also, suppose a vehicle 10 passes through the aforementioned specific point. In this case, the control device 20 of vehicle 10 performs a first detection control, in which the control device 20 of vehicle 10 transmits first notification data DN1 to the server 50. Then, the server 50 performs a first distribution control, in which the server 50 transmits breaking news data DP to multiple vehicles 10. Subsequently, suppose that a vehicle 10 that has received the breaking news data DP passes through the aforementioned specific point, i.e., the detection location PD included in the breaking news data DP. In this case, the control device 20 of the vehicle 10 that has passed the detection location PD performs a second detection control, in which the control device 20 of vehicle 10 transmits either the first notification data DN1 or the second notification data DN2 to the server 50. Then, in step S82 of the second distribution control performed by the server 50, if the distribution condition is met, i.e., if the analysis value VA is determined to be greater than a predetermined reference value, the server 50 transmits prediction data DE to multiple vehicles 10.

[0042] <Effects of this embodiment> (1) In this embodiment, when the server 50 receives the first notification data DN1 through the first detection control, the server 50 can understand that a road anomaly has occurred. The driver of the vehicle 10 that receives the breaking news data DP through the first distribution control can then predict for themselves that congestion may occur at the detected location PD included in the breaking news data DP. In addition, the first and second distribution controls performed by the server 50 calculate an analysis value VA that indicates the degree of impact on congestion at the detected location PD. The second distribution control performed by the server 50 then sends prediction data DE, which indicates a high probability of congestion occurring at the detected location PD, to multiple vehicles 10 if the distribution conditions are met, i.e., if the analysis value VA indicates a high degree of impact on congestion. Therefore, the driver of the vehicle 10 that receives the breaking news data DP and prediction data DE can understand not only that a road anomaly has occurred, but also in advance that there is a high probability that congestion will occur as a result of that anomaly.

[0043] (2) Generally, even if a road anomaly is detected by the vehicle 10, it is highly likely that the road anomaly will be resolved as time passes. Therefore, traffic congestion caused by the above-mentioned road anomaly also tends to be resolved as time passes. In this regard, in step S82 of the second distribution control, the server 50 calculates the analysis value VA based on the period from the detection time TD included in the latest first notification data DN1 to the current time. This makes it possible to calculate the analysis value VA more accurately than if the passage of time from the detection time TD included in the latest first notification data DN1 were not taken into account.

[0044] (3) Generally, when road anomalies are detected by the vehicle 10 multiple times, the impact on traffic congestion caused by those road anomalies tends to be higher. In this regard, in step S82 of the second distribution control, the server 50 increases the analysis value VA as the number of times the first notification data DN1 is received by the second detection control increases. This makes it possible to calculate the analysis value VA more accurately than when the number of times road anomalies are detected is not taken into account.

[0045] (4) For example, even if a road anomaly is detected by a vehicle 10, if another vehicle 10 that has passed the detection location PD where the detection was made does not detect the road anomaly, the road anomaly may have already been resolved. In this case, it is highly likely that the traffic congestion caused by the road anomaly has also been resolved. In this regard, in step S82 of the second distribution control, the server 50 reduces the analysis value VA as the number of times the second notification data DN2 is received by the second detection control increases. This makes it possible to calculate the analysis value VA more accurately by taking into account the number of times the road anomaly was not detected in the second detection control.

[0046] <Example of changes> This embodiment can be implemented with the following modifications. This embodiment and the following modifications can be combined with each other to the extent that they do not contradict each other technically.

[0047] In the above embodiment, the first detection control may be modified. For example, the first precondition of step S11 may be changed. Specifically, if the amount of variation in the steering angle per unit time by the driver of vehicle 10 is large, it may be incorrectly determined in step S12 that the detection condition is met. Therefore, the first precondition of step S11 may include that the amount of variation in the steering angle per unit time by the driver of vehicle 10 is less than or equal to a predetermined constant value. In other words, the first precondition of step S11 may adopt other requirements in order to remove noise from the processing in step S12.

[0048] For example, the detection conditions in step S12 may be changed. Specifically, the detection conditions may include only some of the accident requirements, abnormal road surface requirements, submersion requirements, low friction requirements, and obstacle requirements.

[0049] For example, the accident requirement in step S12 may be that the absolute value of the longitudinal acceleration GX is equal to or greater than a predetermined specified acceleration. For example, the low-friction requirement in step S12 may be the requirement that so-called VDIM is operating. VDIM is an abbreviation for Vehicle Dynamics Integrated Management. This VDIM is a system for stably controlling the attitude of the vehicle 10.

[0050] For example, the obstacle requirement in step S12 may be that a function that automatically applies the brakes to mitigate the damage of a collision with vehicle 10 is in operation. Alternatively, for example, the obstacle requirement in step S12 may be that a lane change operation, a so-called double lane change operation, has been detected, immediately after vehicle 10 has changed lanes from the first lane to the second lane. If the detection conditions in step S12 are to be changed, the detection conditions in step S62 should be changed in the same manner.

[0051] In the above embodiment, the second detection control may be modified. For example, similar to the first detection control described above, the second precondition in step S61 may be changed, or the detection conditions in step S62 may be changed.

[0052] • In the above embodiment, the first distribution control may be modified. For example, in step S32, the initial value setting configuration for the analysis value VA may be changed. Specifically, in step S32, the server 50 may set the same value as the initial value for the analysis value VA regardless of the type code CK included in the first notification data DN1.

[0053] • In the above embodiment, the second distribution control may be modified. For example, in step S81, the calculation configuration for the analysis value VA based on the period from the detection time TD to the current time may be changed. Specifically, the correction amount for the initial value of the analysis value VA for each hour increase in the period from the latest detection time TD to the current time is not limited to "-25", but may be a negative value greater than "-25" or less than "-25". Also, specifically, the server 50 may calculate the analysis value VA regardless of the period from the detection time TD to the current time.

[0054] For example, in step S81, the calculation configuration for the analysis value VA based on the number of times the first notification data DN1 is received may be changed. Specifically, the correction amount for the initial value of the analysis value VA for each increase in the number of times the first notification data DN1 is received by the second detection control is not limited to "+25", but may be greater than "+25" or less than "+25", as long as it is a positive value. Furthermore, the correction amount for the initial value of the analysis value VA for each increase in the number of times the first notification data DN1 is received by the second detection control may be changed according to the type code CK included in the first notification data DN1. In addition, the correction amount for the initial value of the analysis value VA for each increase in the number of times the first notification data DN1 is received by the second detection control may be changed according to the prevalence of vehicles 10 capable of performing the second detection control. Also, specifically, the server 50 may calculate the analysis value VA regardless of the number of times the first notification data DN1 is received.

[0055] For example, in step S81, the calculation configuration for the analysis value VA based on the number of times the second notification data DN2 is received may be changed. Specifically, the correction amount for the initial value of the analysis value VA for each increase in the number of times the second notification data DN2 is received by the second detection control is not limited to "-25", but may be a negative value greater than "-25" or less than "-25". Furthermore, the correction amount for the initial value of the analysis value VA for each increase in the number of times the second notification data DN2 is received by the second detection control may be changed according to the prevalence of vehicles 10 capable of performing the second detection control. Also, specifically, the server 50 may calculate the analysis value VA regardless of the number of times the second notification data DN2 is received.

[0056] For example, in step S81, the server 50 may calculate the analysis value VA based on the vehicle speed SP at which the vehicle 10 that received the rapid data DP passes the detection position PD. Specifically, the server 50 may increase the analysis value VA as the vehicle speed SP at which the vehicle passes the detection position PD decreases.

[0057] • The degree to which road anomalies affect traffic congestion can vary depending on various factors. Therefore, a pre-trained model that has been trained in advance may be used as the configuration for calculating the analytical value VA. For example, in the above configuration, a configuration can be adopted in which multiple input variables, including a variable indicating the period from the detection time TD to the current time, are input into a pre-trained model that has been trained in advance, and an output variable indicating the analytical value VA is output.

[0058] In the above embodiment, the targets for transmission of the rapid report data DP and predictive data DE in the first and second distribution control are not limited to multiple vehicles 10. For example, the server 50 may transmit one or more of the rapid report data DP and predictive data DE to an administrative agency or other entity responsible for road management. This can improve the likelihood that road anomalies will be resolved quickly. [Explanation of symbols]

[0059] 10...Vehicle, 20...Control device, 21...Execution unit, 22...Storage unit, 23...Communication unit, 31...Vehicle speed sensor, 32...Accelerometer, 33...GNSS receiver, 34...Accelerator operation amount sensor, 35...Brake operation amount sensor, 36...Brake system, 37...Airbag device, 50...Server, 51...Execution unit, 52...Storage unit, 53...Communication unit, 100...Road condition monitoring system, 200...Communication network.

Claims

1. The system comprises multiple vehicles and a server capable of communicating with the said vehicles. The aforementioned vehicle is When a road anomaly is detected, notification data including the type of anomaly, the location where the anomaly was detected, and the time of detection of the anomaly is sent to the server. Execute, The aforementioned server, Upon receiving the notification data, the system transmits breaking news data to multiple vehicles indicating that the anomaly has occurred at the detection location. When the aforementioned notification data is received, an analytical value indicating the degree of impact on traffic congestion at the detected location is calculated, When the aforementioned analysis values ​​satisfy the conditions indicating a high degree of influence on the traffic congestion, predictive data indicating a high probability of traffic congestion occurring at the detected location is transmitted to multiple vehicles. Execute, The aforementioned server, For the same detection location, the longer the period from the detection time included in the latest notification data to the current time, the lower the analytical value corresponding to that detection location will be, indicating a lower impact on the traffic congestion. Road condition monitoring system.

2. The aforementioned server, When the detection location included in the newly received notification data is the same as the detection location included in the previously received notification data, the analysis value corresponding to that detection location is set to a value indicating a high degree of impact on the traffic congestion. The road condition monitoring system according to claim 1.

3. When the aforementioned notification data is designated as the first notification data, The aforementioned vehicle is After receiving the aforementioned breaking news data, if no anomaly is detected when driving to the detection location included in the breaking news data, a second notification data indicating that no anomaly occurred at the detection location is transmitted to the server. The aforementioned server, When the second notification data is received, the analysis value corresponding to the detection location, which is indicated in the second notification data as not having occurred, is set to a value that indicates a low degree of impact on the traffic congestion. The road condition monitoring system according to claim 1.

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