WO2023042186A1 - Vehicle control system and electronic control device - Google Patents

Abstract

The present invention provides a vehicle control system and an electronic control device that make it possible to safely drive a vehicle by means of external environment recognition using vehicle-mounted sensors. This vehicle control system 100 comprises electronic control devices 120 that are each mounted to a respective vehicle 200 among a plurality of vehicles 200, and at least one server 110 that is connected to the electronic control devices 120 in a manner enabling communication therewith. The electronic control devices 120 are each provided with a recognition unit 121 that recognizes the state of a road, a determination unit 122 that determines anomalies, a transmission unit 123 that transmits, to the server 110, anomaly information including the date and time and the location of the vehicle 200 when an anomaly was determined by the determination unit 122 and the type of anomaly determined, and a vehicle control unit 124 that causes the vehicle 200 to travel along a recommended route received from the server 110. The server 110 is provided with a recording unit 111 that records anomaly occurrence information in which anomaly information received from the electronic control devices 120 is associated with nodes or links in map information, a computation unit 112 that calculates a degree of travel difficulty that is based on the anomaly determination frequency for each node or link in the anomaly occurrence information, a route selection unit 113 that selects a safe route having the smallest total degree of travel difficulty from among a plurality of route candidates in the map information, and a transmission unit 114 that transmits the safe route to the electronic control devices 120 as the recommended route.

Description

Vehicle control system and electronic controller

The present disclosure relates to vehicle control systems and electronic controllers.

Conventionally, there has been known a dangerous location information collection system that includes an on-vehicle device and a dangerous location information collection device (Patent Document 1, Claim 1, Paragraph 0005, etc.).

The in-vehicle device includes operation information acquisition means, travel information acquisition means, position information acquisition means, and control means. The operation information acquisition means acquires information on vehicle operation by the driver. The traveling information acquiring means acquires information about the traveling state of the vehicle. The position information obtaining means obtains current position information of the vehicle. The control means, when estimating that an operation has been performed to cope with an emergency based on the operation information, controls to transmit the various information to the outside.

When the danger location information collection device receives the various information from the vehicle-mounted device and determines that there is a high possibility that the operation was actually performed to deal with an emergency, the danger occurrence location information collection device collects the location information related to the danger occurrence location. Collect as information. This determination of the possibility of an emergency is made based on the operation information, the travel information, the traffic rule information of the road on which the vehicle is located, and/or the information regarding the situation around the vehicle.

Patent document 1: JP 2007-323281 A

As described above, the above-described conventional system uses the current position information of the vehicle as information regarding the location of danger when it is highly likely that the driver actually operated the vehicle in order to deal with an emergency. collect. However, in order to drive the vehicle safely by recognizing the external environment using the in-vehicle sensors, it is not enough to rely only on the information on the dangerous locations based on the driver's operation.

The present disclosure provides a vehicle control system and an electronic control device that enable the vehicle to run safely by recognizing the external environment using on-vehicle sensors.

One aspect of the present disclosure is a vehicle control system comprising: each electronic control device mounted on each of a plurality of vehicles; and at least one server communicably connected to each electronic control device. Each of the electronic control units includes a recognition unit for recognizing road conditions based on the detection results of external sensors mounted on the respective vehicles, and an abnormality including poor recognition of the road conditions by the recognition unit. and anomaly information including the position of each vehicle at the time of the anomaly judgment by the judging unit, the time, and the type of the judged anomaly to the server via a communication device mounted on each of the vehicles. a transmitting unit that transmits, the server includes a recording unit that records abnormality occurrence information in which the abnormality information received from each electronic control device is associated with each node or link of map information; a calculating unit for calculating a travel difficulty based on the abnormality determination frequency for each of the nodes or links included in the abnormality occurrence information; and a transmitter for transmitting the safe route to each of the electronic control units as a recommended route.

According to the above aspect of the present disclosure, it is possible to provide a vehicle control system and an electronic control device capable of safely driving a vehicle by recognizing the external environment using an external sensor mounted on the vehicle.

1 is a block diagram showing Embodiment 1 of a vehicle control system and an electronic control device of the present disclosure; FIG.
FIG. 2 is a flow chart showing an example of processing by the electronic control unit of FIG. 1;
FIG. 2 is a flowchart showing an example of processing by the server in FIG. 1;
FIG. 4 is a flowchart showing details of the process of selecting a safe route in FIG. 3;
FIG. 4 is a diagram showing an example of map information used in the process of selecting a safe route in FIG. 3;
5 is a graph showing an example of a result of processing for acquiring the frequency of occurrence of anomalies in FIG. 4;
5 is a graph showing an example of a result of processing for acquiring the frequency of occurrence of anomalies in FIG. 4;
FIG. 8 is a block diagram of a server in Embodiment 3 of the vehicle control system of the present disclosure;
FIG. 9 is a flowchart showing an example of processing by the server of FIG. 8;
An example of a display screen by the countermeasure support unit in FIG. 8 .
FIG. 10 is an example of a display screen for displaying the traveling difficulty level of each node/link in FIG. 9 ; FIG.
12 is a graph showing the travel difficulty for each abnormality type of the link selected in FIG. 11;
FIG. 9 is a flowchart showing an example of processing by the server of FIG. 8;

Embodiments of a vehicle control system and an electronic control device according to the present disclosure will be described below with reference to the drawings.

[Embodiment 1]
FIG. 1 is a block diagram showing Embodiment 1 of a vehicle control system and an electronic control device of the present disclosure. The vehicle control system 100 of this embodiment is, for example, an automatic driving support system that supports automatic driving of a plurality of vehicles 200 . In addition, in FIG. 1, illustration of the plurality of vehicles 200 is omitted, and only one vehicle 200 is illustrated.

The vehicle control system 100 includes, for example, at least one server 110 and a plurality of electronic control units 120 (not shown). That is, the vehicle control system 100 may include multiple servers 110 . Each electronic control unit 120 of the plurality of electronic control units 120 is mounted in each vehicle 200 of the plurality of vehicles 200 .

The server 110 is, for example, a computer configured by hardware such as a central processing unit (CPU), memories such as ROM and RAM, timers, and input/output units. Server 110 is communicably connected to electronic control unit 120 via, for example, Internet line 300, communication device 400 such as a radio base station, a radio communication line, communication device 210 mounted on vehicle 200, and an in-vehicle network. ing.

The server 110 has, for example, a recording unit 111, a calculation unit 112, a route selection unit 113, and a transmission unit 114. The server 110 may also have a storage unit 115 . Each part of these vehicle control system 100 expresses each function of vehicle control system 100 realized by executing the program recorded on memory by CPU of vehicle control system 100, for example.

The electronic control device 120 is, for example, a vehicle control device mounted on the vehicle 200 . The electronic control unit 120 is composed of, for example, one or more microcontrollers, and includes a CPU, memories such as ROM and RAM, timers, input/output units, and the like.

The electronic control unit 120 has, for example, a recognition unit 121, a determination unit 122, a transmission unit 123, and a vehicle control unit 124. Each part of these electronic control units 120 expresses each function of the electronic control unit 120 realized by executing the program recorded on memory by CPU of the electronic control unit 120, for example.

Each vehicle 200 is, for example, a gasoline vehicle, a diesel vehicle, a hybrid vehicle, an electric vehicle, or a fuel cell vehicle. Vehicle 200 includes, in addition to electronic control device 120, communication device 210, external sensor 220, vehicle sensor 230, navigation system 240, actuator 250, and notification device 260, for example. In addition, vehicle 200 includes a typical configuration of a vehicle, such as a prime mover, power transmission device, braking device, steering device, traveling device, frame, suspension, electrical device, safety device, etc., which are not shown.

The communication device 210 is an in-vehicle communication device of the vehicle 200 and is connected to the electronic control device 120 via an in-vehicle network. Communication device 210 performs wireless communication with communication device 400 such as a radio base station installed outside vehicle 200, for example.

The communication device 400 is, for example, connected to the communication device 210 of the vehicle 200 via a wireless communication line and connected to the server 110 via the Internet line 300 . Communication device 400 receives information transmitted from vehicle 200 and transmits the information to server 110 , and receives information transmitted from server 110 and transmits the information to communication device 210 of vehicle 200 .

The external sensor 220 is, for example, a sensor that detects objects around the vehicle 200, and is connected to the electronic control unit 120 via an in-vehicle network. External sensor 220 includes sensors such as a monocular camera, a stereo camera, a millimeter wave radar, a laser radar, and an ultrasonic sensor, for example. In this embodiment, the external sensor 220 includes at least a stereo camera.

The vehicle sensor 230 is, for example, a sensor that detects physical quantities related to the vehicle 200, and is connected to the electronic control unit 120 via an in-vehicle network. Vehicle sensors 230 include, for example, wheel speed sensors, acceleration sensors, angular velocity sensors, angular acceleration sensors, steering angle sensors, shift position sensors, accelerator sensors, brake sensors, advanced driving assistance systems (ADAS) and automatic driving systems (ADS). Includes various sensors required for

The navigation system 240 includes, for example, a global positioning satellite system (GNSS) receiver, a storage device storing map information, a display device displaying a map and route information to the destination, and inputting the destination and the like. and an input device for Navigation system 240 is connected to electronic control unit 120 via an in-vehicle network, for example, and outputs information on the current position of vehicle 200 and the route to the destination to electronic control unit 120 .

Actuator 250, for example, automatically operates the steering device, accelerator, brake, gear shift, etc. of vehicle 200 based on a control signal output from electronic control unit 120, thereby performing advanced driving assistance and automatic driving of vehicle 200. come true. That is, vehicle 200 is equipped with ADAS or ADS configured by communication device 210, external sensor 220, vehicle sensor 230, navigation system 240, electronic control unit 120, actuator 250, and the like.

The notification device 260 is, for example, a device that provides information, alerts, and warnings to the occupants of the vehicle 200 based on the control signal output from the electronic control device 120 . Notification device 260 includes, for example, a display device and an audio output device. The display device includes, for example, a liquid crystal display device, an organic EL display device, a head-up display, and the like. Audio output devices include, for example, speakers and buzzers.

The operations of the vehicle control system 100 and the electronic control unit 120 of this embodiment will be described below with reference to FIGS. FIG. 2 is a flow chart showing an example of processing P10 by the electronic control unit 120 of FIG. FIG. 3 is a flowchart showing an example of processing P20 of server 110 in FIG.

When starting the process P10 shown in FIG. 2, the electronic control unit 120 first executes the process P11 for acquiring the departure point and the destination. In this process P11, electronic control unit 120, for example, through vehicle control unit 124, acquires the current position of vehicle 200 from navigation system 240 as a departure point. Further, the electronic control unit 120 acquires the position information of the destination input to the input device of the navigation system 240 by the vehicle control unit 124, for example.

Next, the electronic control unit 120 executes a process P12 of requesting route information from the server 110. In this process P<b>12 , the electronic control unit 120 , for example, uses the transmission unit 123 to transmit a request for a recommended route from the departure point to the destination to the server 110 via the communication device 210 . Here, the information of the starting point and destination of the vehicle 200 included in the request for the recommended route is transmitted in a format that can be compared with the point information included in the map information stored in the storage unit 115 of the server 110, for example. .

Specifically, the information on the departure point and destination of vehicle 200 transmitted from electronic control unit 120 to server 110 includes, for example, the latitude and longitude of each of the departure point and destination. Further, the request for the recommended route transmitted from electronic control unit 120 to server 110 includes, for example, the date and time when vehicle 200 travels from the departure point to the destination.

On the other hand, when the server 110 starts the process P20 shown in FIG. In this process P21, when the route selection unit 113 of the server 110 determines that the request for the recommended route has not been received from the electronic control unit 120 of any vehicle 200, it determines that there is no request for route information (NO). , a process P24, which will be described later, is executed.

On the other hand, in this process P21, the route selection unit 113 of the server 110, for example, when it determines that it has received a request for a recommended route including a departure point and a destination from the electronic control unit 120 of at least one vehicle 200, route information is requested (YES). In this case, the server 110 executes the process P22 of selecting a safe route. This process P22 will be described later in detail with reference to FIG.

After that, the server 110 executes a process P23 of transmitting the safe route obtained in the previous process P22 as a recommended route to the electronic control unit 120 of the vehicle 200 that requested the route information. In this process P23, server 110 transmits the recommended route from the departure point of vehicle 200 to the destination to communication device 210 of vehicle 200 via Internet line 300 and communication device 400, for example, using transmission unit 114. FIG.

Next, electronic control unit 120 of vehicle 200 executes process P13 for receiving route information, for example, as shown in FIG. In this process P<b>13 , electronic control unit 120 receives the recommended route from the departure point to the destination transmitted from server 110 by vehicle control unit 124 via communication device 210 of vehicle 200 , for example. Next, electronic control unit 120 of vehicle 200 executes vehicle travel control process P14 for causing vehicle 200 to travel along the received recommended route.

In this process P14, the electronic control unit 120 of the vehicle 200 controls the actuator 250 of the vehicle 200 by means of the vehicle control unit 124, for example, so that the vehicle 200 travels along the recommended route. Further, after starting the process P14, the electronic control unit 120 executes a process P15 for recognizing the road condition and a process P16 for determining whether there is an abnormality. It should be noted that these processes P15 and P16 may be executed, for example, at each control cycle while the vehicle travel control process P14 is being executed, or may be executed as appropriate.

In process P15, the electronic control unit 120 acquires the detection results of the external sensor 220 and the vehicle sensor 230 mounted on the vehicle 200 by the recognition unit 121, and recognizes the road condition based on the detection results. Here, the recognition unit 121 recognizes, as road conditions, for example, areas where the vehicle 200 can travel, objects that the vehicle 200 should avoid, and situations in which it is difficult to recognize the road conditions.

More specifically, recognition unit 121 recognizes a road and road edges in front of vehicle 200, lane markings on the road, and the like based on the detection result of external sensor 220, so that vehicle 200 can move. Recognize possible areas. For example, recognition unit 121 recognizes an object in front of vehicle 200 based on the detection result of external sensor 220, and detects an object that may collide with vehicle 200 based on the detection result of vehicle sensor 230. do.

In addition, the recognition unit 121 recognizes the type of object, such as a car, a motorcycle, a pedestrian, a falling object, and a bump for reducing the speed of the vehicle, based on the detection result of the external sensor 220, for example. Further, the recognition unit 121 recognizes a situation in which it is difficult to recognize the road state based on the detection result of the external sensor 220 . Here, a situation in which it is difficult to recognize the road state is, for example, a situation in which it is difficult for the camera included in the external sensor 220 to recognize an object due to backlight, heavy rain, or snowfall, or a situation in which the external sensor 220 fails to detect lane markings. Including inability to recognize at least one of the left and right lanes.

Recognition unit 121 controls notification device 260 of vehicle 200, for example, when at least one of the left and right lanes cannot be recognized or when the road state becomes difficult to recognize. A warning of unrecognized lanes and unrecognized road conditions is issued to the occupants. For example, when recognition unit 121 recognizes an object that may collide with vehicle 200, recognition unit 121 controls notification device 260 to issue a collision avoidance warning to the occupants of vehicle 200, and Information on the object is output to the vehicle control unit 124 .

Here, recognition unit 121 detects, for example, when the inter-vehicle distance to the preceding vehicle becomes shorter than a threshold, or when a collision is predicted from the position and speed of vehicle 200 and the positions and speeds of other vehicles. Then, it recognizes those vehicles as potential collision objects. Also, when a collision is predicted from the position and speed of the vehicle 200 and the position and speed of a pedestrian running out onto the road, the pedestrian is recognized as an object that may collide.

For example, when the recognition unit 121 recognizes a speed reduction bump, the recognition unit 121 recognizes the bump as an object that requires deceleration when the vehicle 200 passes through. For example, when information about an object that may collide with the vehicle 200 or an object that requires deceleration is input from the recognition unit 121, the vehicle control unit 124 controls the actuator 250 of the vehicle 200 to avoid collision. The steering operation for the purpose and the collision damage mitigation brake (AEB) etc. are operated.

In addition, the recognition unit 121 recognizes, for example, poor recognition of road conditions, recognition of road conditions different from normal conditions, occurrence of warnings to the occupants of the vehicle 200, occurrence of collision avoidance control of the vehicle 200, etc. as abnormalities. Further, the recognizing unit 121 records, for example, the type of the recognized abnormality as abnormality information together with the position and the date and time when the abnormality occurred. Here, the location where the abnormality occurs includes, for example, location information of vehicle 200 acquired from navigation system 240 and identification information of a link and/or node of map information where vehicle 200 is located.

Next, the electronic control unit 120 executes, for example, a process P16 of determining whether there is an abnormality including poor recognition of the road condition by the recognition unit 121. In this process P16, the determination unit 122 determines whether or not there is an abnormality based on, for example, the presence or absence of abnormality information recorded by the recognition unit 121 in the previous process P15. Here, if the determination unit 122 determines that there is an abnormality (YES), the electronic control unit 120 executes a process P17 of transmitting abnormality information to the server 110. If the determination unit 122 determines that there is no abnormality (NO), the electronic control unit 120 Control device 120 executes a process P18 of determining whether vehicle 200 has arrived at the destination.

In processing P17 for transmitting abnormality information, electronic control unit 120 transmits abnormality information to server 110 by transmission unit 123 via communication device 210 mounted on vehicle 200, external communication device 400, and Internet line 300, for example. Send information. Here, for example, as shown in FIG. 3, server 110 repeatedly executes process P24 of determining whether or not abnormality information has been received from electronic control unit 120 of each vehicle 200 at a predetermined cycle.

The server 110 determines whether or not abnormality information has been received from the electronic control unit 120 by the recording unit 111 in this process P24, for example. In this process P24, when it is determined that the recording unit 111 has not received the abnormality information from the electronic control unit 120 (NO), the server 110 ends the process P20 shown in FIG. 3 and starts the process P20 again. . On the other hand, in this process P24, when the electronic control unit 120 determines that the recording unit 111 has received the abnormality information from the electronic control unit 120 (YES), it executes the process P25 of recording the abnormality information.

In this process P25, the server 110, for example, uses the recording unit 111 to create abnormality occurrence information in which the abnormality information received from each electronic control unit 120 is associated with each of the nodes N1 to N4 or links L1 to L7 of the map information. Record. Table 1 below shows an example of abnormality occurrence information recorded in the storage unit 115 by the recording unit 111 .

[Table 1]

As shown in Table 1, the anomaly occurrence information corresponds to, for example, an anomaly type code, date, time, latitude and longitude as anomaly information, and a position code including each link L1-L7 and/or each node N1-N4. It is information that has been attached. Here, the abnormality type code is a code representing the type of abnormality.

For example, as shown in Table 2 below, the storage unit 115 records in advance the abnormality type information in which the abnormality type and the corresponding abnormality type code are defined. Therefore, based on the abnormality type information shown in Table 2, the abnormality type corresponding to the abnormality type code of the abnormality occurrence information shown in Table 1 can be specified. Also, in the example shown in Table 2, the abnormality type information includes a weighting factor corresponding to the abnormality type. This weighting factor is, for example, an index representing the magnitude of the impact on the safety of vehicle 200 .

[Table 2]

Further, in the example shown in Table 1, the abnormality occurrence information is the weather at the position of each vehicle 200 at the time of abnormality determination by the determination unit 122 of each electronic control unit 120, each link L1-L7 and/or each node N1. - Information associated with N4. For example, when it is difficult to detect the weather by external sensor 220 of vehicle 200, recording unit 111 of server 110 records the date and time of anomaly occurrence included in the anomaly occurrence information and the location information of vehicle 200 at that time. may be obtained from a weather database (not shown).

In this way, the recording unit 111 of the server 110 receives, for example, abnormality information from the electronic control units 120 of the plurality of vehicles 200, and records abnormality occurrence information as shown in Table 1 in the storage unit 115. . This enables statistical processing based on a specific place, a specific time period, a specific type of abnormality, etc., using a large amount of abnormality information included in the abnormality occurrence information recorded in the storage unit 115 . As shown in FIG. 3, the server 110 terminates the process P20 shown in FIG. 3 after completing the process P25 of recording the abnormality information. Moreover, the server 110 repeats the process P20 shown in FIG. 3 at a predetermined cycle.

The details of the process P22 for selecting the safe route shown in FIG. 3 will be described below with reference to FIGS. 4 to 7. FIG. FIG. 4 is a flowchart showing details of the process P22 for selecting a safe route in FIG. FIG. 5 is a diagram showing an example of route candidates CR1, CR2, and CR3 of vehicle 200 based on map information MI stored in storage unit 115 of server 110. As shown in FIG. The map information MI includes, for example, a road network in which links L1-L7 such as roads are connected via nodes N1-N4 such as intersections.

When the server 110 starts the process P22 shown in FIG. 4, for example, the route selection unit 113 executes the process P221 of searching for a plurality of route candidates CR1, CR2, CR3 from the map information MI as shown in FIG. . The route selection unit 113 acquires, for example, the information of the departure point S and the destination G of the vehicle 200 included in the request for route information received from each electronic control unit 120, and obtains the map information MI stored in the storage unit 115. to select a plurality of route candidates CR1, CR2, and CR3 that can reach the destination G from the departure point S.

Next, the server 110, for example, executes a process P222 of extracting the links L1-L7 and/or the nodes N1-N4 included in the plurality of selected route candidates CR1, CR2, CR3 by the route selection unit 113. In the example shown in FIG. 5, the route selection unit 113 selects the links L1-L5 and/or N1-N4 of the route candidate CR1 and the links L1, L2, L6, L5 and/or the nodes N1, N2, N4 of the route candidate CR2. , and links L1, L7, L4, L5 and/or nodes N1, N3, N4 of route candidate CR3.

Next, the server 110, for example, uses the route selection unit 113 to execute the process P223 of acquiring the abnormality occurrence frequency. In this process P223, the route selection unit 113 receives abnormality information from the electronic control units 120 of the plurality of vehicles 200 for each of the links L1-L7 and/or the nodes N1-N4 extracted in the previous process P222. Get the received frequency.

More specifically, in process P223, route selection unit 113 extracts, for example, abnormality occurrence information that matches the traveling conditions including the month, time zone, weather, etc. in which vehicle 200 travels from departure point S to destination G. do. Here, the time period used for extracting the abnormality occurrence information may be a time period based on the time when the electronic control unit 120 of the vehicle 200 transmits the route request, or the required time from the departure point S to the destination G and the time period that takes into account the predicted passage time of each link or each node. Table 3 below shows an example of the reception frequency of abnormality information on the link L6 in FIG.

[Table 3]

Table 3 shows that the server 110, from each of the electronic control units 120 mounted on one or more vehicles 200 that traveled on the link L6 under the traveling conditions of 8:00 am and fine weather in October, This indicates that the anomaly information has been received multiple times. The route selection unit 113 calculates the abnormality determination frequency by counting the number (number of lines) of the abnormality occurrence information extracted as shown in Table 3, for example. In process P223, the route selection unit 113 acquires, for example, an abnormality occurrence frequency for each abnormality type for each of the links L1 to L7 and/or the nodes N1 to N4 that satisfy a predetermined travel condition.

FIGS. 6 and 7 are graphs showing an example of the result of the process P223 for acquiring the abnormality occurrence frequency described above. In these graphs, the horizontal axis is the abnormality type code indicating the type of the abnormality information, and the vertical axis is the number of receptions of the abnormality information, that is, the frequency of abnormality occurrence or the frequency of abnormality determination. For example, as shown in Table 2, the abnormality type codes 1 to 4 on the horizontal axis of the graph are, respectively, collision damage mitigation braking (AEB) by pedestrian recognition, lane recognition unrecognizable (lane unrecognized), backlight, and Represents obstacle avoidance.

That is, in the example shown in FIG. 6, the server 110 receives, as abnormality information from the electronic control units 120 of the plurality of vehicles 200 that have traveled on the link L6 in October, between 8:00 am and in fine weather, an abnormality indicating that the lane cannot be recognized. The type code 2 is received at a frequency of about 150 times. Further, in the example shown in FIG. 7, the server 110 recognizes a pedestrian as abnormal information from the electronic control units 120 of the plurality of vehicles 200 that traveled on the link L3 in October between 8:00 am and in fine weather. Anomaly type code 1, which indicates the operation of the AEB by the aircraft, is received at a frequency of about 79 times.

Here, it is assumed that the links L1, L2, L4, L5, L7 and the nodes N1-N4, excluding the links L3 and L6, have the same running conditions as the links L3 and L6, and the server 110 has not received any abnormality information.

Among the error types, as shown in Table 3, lane recognition failure (abnormality type code: 2) that occurs at the same point on link L6 is, for example, a case where the road division line is faded due to wear over time. occurs in Lane recognition by electronic control unit 120 is necessary for automatic driving of vehicle 200 by electronic control unit 120 . Therefore, the electronic control unit 120 of each of the plurality of vehicles 200 transmits to the server 110 as abnormality information the abnormality type code: 2 indicating that the lane cannot be recognized. Lane unrecognizable is an abnormality type for which a large amount of information is collected regardless of the month or time period.

Also, among the types of anomalies, AEB due to pedestrian recognition may be a sudden event. However, as shown in FIG. 7, when many AEBs (abnormality type code: 1) due to pedestrian recognition occur in the same time period on link L3, the following situation can be assumed. . For example, there is a workplace where many employees go to work facing the road of link L3, and there is a parking lot on the opposite side of the road across the road of the workplace, and no pedestrian crossing is installed between the workplace and the parking lot. situation.

In such a situation, many pedestrians cross roads without pedestrian crossings to take the shortest route to work. As a result, as shown in FIG. 7, many AEBs (abnormality type code: 1) occur due to pedestrian recognition during the working hours of the workplace. In this way, a point on the road where many abnormalities due to the environment around the road occur during a specific time period hinders safe passage of the vehicle 200 during that time period.

In addition to the above situation, the following situation can be assumed as a situation in which many abnormalities due to the environment around the road occur during a specific time period. For example, there is a store such as a supermarket facing the road, and the number of vehicles that can be parked in the store's parking lot is smaller than the number of parking spaces required for the number of visitors that concentrate in a particular time period. In such a case, it is assumed that obstacle avoidance (abnormality type code: 4) occurs frequently to avoid vehicles parked on the road without entering the parking lot during the specific time period.

More specifically, in the vicinity of the above-mentioned stores, for example, a large number of vehicles are parked on the road between 5:00 pm and 6:00 pm, when shoppers are concentrated. Object avoidance (abnormality type code: 4) will occur a lot. On the other hand, for example, around 8:00 am before the opening of the store, there are no parked vehicles by shoppers on the street near the store, and obstacle avoidance to avoid the parked vehicles does not occur. Similarly, even near educational facilities where there is a concentration of students picking up and dropping off during a specific time period, many vehicles park on the road during a specific time period, and obstacle avoidance (abnormality type) is used to avoid parked vehicles. Code: 4) is assumed to occur many times.

In addition, anomalies caused by natural phenomena such as backlighting (abnormality type code: 3) can occur, for example, in specific places, specific seasons, and specific time periods. When backlight occurs, for example, the image captured by the camera included in external sensor 220 of vehicle 200 may be overexposed, which may interfere with object recognition. When server 110 receives such information on anomalies caused by the natural environment from electronic control units 120 of each of vehicles 200, it is possible to specify places, seasons, and time periods in which anomalies occur frequently. .

In addition, the frequency of abnormal occurrences as described above is affected by the weather, for example. More specifically, it is conceivable that the number of parked vehicles around stores and educational facilities as described above will increase or decrease depending on whether it is raining or fine. Therefore, the number of obstacle avoidance (abnormality type code: 4) for avoiding parked vehicles can be affected by the weather. Also, abnormalities caused by natural phenomena such as backlighting occur only in specific weather conditions such as fine weather. Therefore, when the abnormality occurrence information includes the weather, it is possible to grasp the abnormality occurrence frequency according to the weather.

After completing the process P223 of acquiring the frequency of occurrence of anomalies shown in FIG. 4, the server 110 executes, for example, the process P224 of acquiring the average traffic volume. In this process P224, the server 110 obtains, for example, the average traffic volume of each link L1-L7 and/or each node N1-N4. More specifically, in this process P224, the route selection unit 113 of the server 110 stores in the storage unit 115, for example, each of the links L1 to L7 and/or each of the nodes N1 to N4 extracted in the above process P222. Get the average traffic volume

In this process P224, the route selection unit 113 selects, for example, the average traffic volume corresponding to the travel conditions such as the month, the time period, and the weather in which the vehicle 200 that requested the route information travels along the route candidates CR1, CR2, and CR3. is acquired from the storage unit 115 . As a result, for example, the average traffic volumes of link L6 and link L3 are obtained as 450 vehicles/hour and 1100 vehicles/hour, respectively. Note that the average traffic volume does not necessarily have to be stored in the storage unit 115 and may be acquired by the route selection unit 113 from outside the server 110 via the Internet line 300 .

Next, the server 110, for example, executes a process P225 of calculating the traveling difficulty of each link L1-L7 and/or each node N1-N4. In this process P225, the calculation unit 112 of the server 110 calculates the driving difficulty ADD based on the frequency of occurrence of anomalies for each of the nodes N1-N4 or the links L1-L7 of the anomaly occurrence information, for example, using the following equation (1). .

[Number 1]

In the above formula (1), N is the number of abnormality types, H(n) is the frequency of occurrence of the abnormality types, Wn is the weighting factor of the abnormality types, and Q is the previous process P224. The obtained average traffic volume of each link L1-L7 and/or each node N1-N4. That is, the calculation unit 112 calculates the traveling difficulty level ADD of each of the nodes N1 to N4 or the links L1 to L7 of the abnormality occurrence information to be higher as the abnormality determination frequency by the determination unit 122 of each electronic control unit 120 is higher.

As described above, for example, when the average traffic volume Q of the link L6 and the link L3 is 450 vehicles/hour and 1100 vehicles/hour, respectively, the driving difficulty ADD is given by the above formula (1), Table 2, and FIG. 6 and FIG. 7, they can be calculated as follows.
Link L6: Driving difficulty ADD=(150×0.7)/450=0.23
Link L3: Driving difficulty ADD=(79×0.6)/1100=0.043

As shown in Table 1, in this embodiment, the abnormality occurrence information includes the weather at the time of abnormality determination associated with each of the nodes N1-N4 or the links L1-L7. In this case, the calculation unit 112 obtains the current weather of each of the nodes N1-N4 or the links L1-L7 included in the plurality of route candidates CR1, CR2, CR3 of the map information when calculating the travel difficulty ADD. good too. In this case, the calculation unit 112 may calculate the driving difficulty level ADD based on abnormality occurrence information in which the weather at the time of abnormality determination matches the current weather.

Next, the server 110, as shown in FIG. 4, executes a process P226 of calculating the travel difficulty ADD of each route candidate CR1, CR2, CR3. In this process P226, the route selection unit 113, for example, calculates the total travel difficulty ADD of all nodes N1-N4 or links L1-L7 included in each route candidate CR1, CR2, CR3. As a result, the travel difficulty ADD of each route candidate CR1, CR2, CR3 can be calculated, for example, as follows.

Traveling difficulty ADD of route candidate CR1 = Traveling difficulty of link L1 ADD (0) + Traveling difficulty of link L2 ADD (0) + Traveling difficulty of link L3 ADD (0.043) + Traveling difficulty of link L4 ADD(0)+driving difficulty level ADD(0) of link L5=0.043

Traveling difficulty ADD of route candidate CR2 = Traveling difficulty ADD (0) of link L1 + Traveling difficulty ADD (0) of link L2 + Traveling difficulty ADD (0.23) of link L6 + Traveling difficulty of link L5 ADD(0)=0.23

Travel difficulty ADD of route candidate CR3 = Travel difficulty ADD (0) of link L1 + Travel difficulty ADD (0) of link L7 + Travel difficulty ADD (0) of link L4 + Travel difficulty ADD of link L5 ( 0) = 0

Next, the server 110 executes a process P227 of selecting a safe route, as shown in FIG. In this process P227, the route selection unit 113 of the server 110 selects the safe route that minimizes the total travel difficulty ADD from the plurality of route candidates CR1, CR2, and CR3 of the map information MI. In this embodiment, as described above, the travel difficulty ADD of the route candidate CR1 is 0.043, the travel difficulty ADD of the route candidate CR2 is 0.23, and the travel difficulty ADD of the route candidate CR3 is 0. .

Therefore, in this process P227, the route selection unit 113 selects the route candidate CR3 as a safe route. After that, the server 110 ends the process P22 shown in FIG. 4, and executes the process P23 of transmitting the recommended route shown in FIG. 3 as described above. In this process P23, the transmission unit 114 transmits the route candidate CR3 selected as the safe route as a recommended route to the electronic control unit 120 of the vehicle 200 that has performed the route information requesting process P12 shown in FIG. After that, the electronic control unit 120 of the vehicle 200 executes the processes P14 to P18 shown in FIG. 2 as described above to drive the vehicle 200 to the destination along the recommended route.

The actions of the vehicle control system 100 and the electronic control unit 120 of this embodiment will be described below.

As described above, the vehicle control system 100 of the present embodiment includes each electronic control device 120 mounted on each of the plurality of vehicles 200 and at least one server communicably connected to each electronic control device 120. 110 and. Each electronic control unit 120 has a recognition section 121 , a determination section 122 and a transmission section 123 . The recognition unit 121 recognizes road conditions based on the detection results of the external sensor 220 mounted on each vehicle 200 . The determination unit 122 determines an abnormality including poor recognition of road conditions by the recognition unit 121 . Transmitter 123 transmits abnormality information including the position and time of each vehicle 200 at the time of abnormality determination by determination unit 122 and the type of determined abnormality to server 110 via communication device 210 mounted on each vehicle 200. Send. On the other hand, the server 110 has a recording unit 111 , a calculation unit 112 , a route selection unit 113 and a transmission unit 114 . The recording unit 111 records abnormality occurrence information in which the abnormality information received from each electronic control unit 120 is associated with each of the nodes N1 to N4 or the links L1 to L7 of the map information MI. The calculation unit 112 calculates the traveling difficulty level ADD based on the abnormality determination frequency for each of the nodes N1 to N4 or the links L1 to L7 of the abnormality occurrence information. The route selection unit 113 selects a safe route that minimizes the total travel difficulty ADD from a plurality of route candidates CR1, CR2, and CR3 of the map information MI. The transmission unit 114 transmits the selected safe route to each electronic control unit 120 as a recommended route.

With such a configuration, the vehicle control system 100 of the present embodiment uses at least one server 110 to transmit the position of each vehicle 200, the time, and the determined abnormality from the electronic control unit 120 of each of the plurality of vehicles 200. Anomaly information including type can be collected. Further, server 110 records abnormality occurrence information in which abnormality information collected from each electronic control unit 120 is associated with each node N1-N4 or link L1-L7 of map information MI. As a result, the server 110 calculates the travel difficulty ADD based on the frequency of occurrence of anomalies for each of the nodes N1-N4 or the links L1-L7 of the anomaly occurrence information, and selects the route candidate CR3 with a low travel difficulty ADD as a safe route. Then, the selected safe route can be transmitted to the electronic control unit 120 of the vehicle 200 as a recommended route. Therefore, according to the vehicle control system 100 of the present embodiment, the abnormality determined by the electronic control unit 120 mounted on any vehicle 200 is also controlled by the electronic control unit 120 mounted on the other vehicle 200 in automatic driving control. can be used as an experience of As a result, it is possible to avoid a route in which abnormalities frequently occur, including poor recognition of road conditions, recognition of road conditions different from the steady state, generation of warnings to the occupants of the vehicle 200, and generation of collision avoidance control of the vehicle 200. It is possible to improve the safety of automatic driving and driving assistance of the vehicle 200 by the control device 120 . More specifically, for example, it is possible to avoid a route in which obstacle avoidance by parked vehicles and AEB due to pedestrian recognition occur frequently during a specific time period.

Further, in the vehicle control system 100 of the present embodiment, the computing unit 112 of the server 110 determines that the node N1 to N4 or the link L1 of the abnormality occurrence information increases as the abnormality determination frequency by the determination unit 122 of each electronic control unit 120 increases. - Calculate a high driving difficulty ADD for each L7.

With such a configuration, the server 110 of the vehicle control system 100 of the present embodiment selects the route candidate CR3, which has a lower abnormality determination frequency by each of the electronic control units 120, as a safe route from among the route candidates CR1, CR2, and CR3. Select as Further, server 110 transmits the selected safe route as a recommended route to electronic control unit 120 of vehicle 200 that requested the route. Therefore, according to the vehicle control system 100 of the present embodiment, it is possible to improve the safety of automatic driving and driving assistance of the vehicle 200 by the electronic control device 120 .

In the vehicle control system 100 of the present embodiment, the recording unit 111 of the server 110 stores the weather at the position of each vehicle 200 at the time of abnormality determination by the determination unit 122 of each electronic control unit 120 in each node N1- Abnormal occurrence information associated with N4 or links L1-L7 is recorded. Then, the calculation unit 112 of the server 110 acquires the current weather of each of the nodes N1 to N4 or the links L1 to L7 included in the plurality of route candidates CR1, CR2, CR3 of the map information MI when calculating the travel difficulty ADD. However, it is also possible to calculate the driving difficulty level ADD based on abnormality occurrence information in which the weather at the time of abnormality determination matches the current weather.

With such a configuration, the server 110 of the vehicle control system 100 of the present embodiment, even if the occurrence frequency of the abnormality depends on the weather, based on the determination frequency of the abnormality corresponding to the weather when the vehicle 200 is running, It is possible to calculate the travel difficulty ADD of the route candidates CR1, CR2, and CR3. Therefore, according to the vehicle control system 100 of the present embodiment, it is possible to further improve the safety of automatic driving and driving assistance of the vehicle 200 by the electronic control device 120 .

Further, in the vehicle control system 100 of the present embodiment, each electronic control unit 120, when the type of abnormality determined by the determination unit 122 cannot be specified, transmits the abnormality information together with the camera included in the external sensor 220 by the transmission unit 123. image can also be sent to the server 110 .

With such a configuration, the vehicle control system 100 of this embodiment may be able to determine the type of abnormality by analyzing the camera image transmitted from each 120 in the server 110 . Examples of cases in which the type of abnormality cannot be specified include the case where the imaging environment of the camera deteriorates and the object cannot be recognized, or the jumping out of the object in front of the vehicle 200 is detected, but the pedestrian, bicycle, animal, etc. are detected. For example, the type of the object is unknown.

In addition, in the vehicle control system 100 of this embodiment, each electronic control unit 120 includes a vehicle control unit 124 that causes each vehicle 200 to travel along the recommended route received from the server 110 .

With such a configuration, the vehicle control system 100 of the present embodiment enables each electronic control unit 120 that has received the recommended route from the server 110 to drive each vehicle 200 along the recommended route. Therefore, according to the vehicle control system 100 of the present embodiment, it is possible to further improve the safety of automatic driving and driving assistance of the vehicle 200 by the electronic control device 120 .

Also, the electronic control device 120 of the present embodiment is a control device mounted on the vehicle 200 . The electronic control unit 120 has a recognition section 121 , a determination section 122 , a transmission section 123 and a vehicle control section 124 . The recognition unit 121 recognizes road conditions based on the detection results of the external sensor 220 mounted on the vehicle 200 . The determination unit 122 determines an abnormality including poor recognition of road conditions by the recognition unit 121 . Transmission unit 123 transmits abnormality information including the position of vehicle 200 at the time of abnormality determination by determination unit 122 , the time, and the type of the determined abnormality to server 110 outside vehicle 200 via communication device 210 mounted on vehicle 200 . Send to Vehicle control unit 124 causes vehicle 200 to travel along the recommended route received from server 110 .

With such a configuration, the electronic control unit 120 of the present embodiment avoids routes in which abnormalities occur frequently, and improves the safety of automatic driving and driving assistance of the vehicle 200 in the same manner as the vehicle control system 100 described above. becomes possible.

Although the first embodiment of the vehicle control system and the electronic control device according to the present disclosure has been described above, the vehicle control system and the electronic control device according to the present disclosure are not limited to the above-described embodiments. For example, in the above-described embodiment, an example of using the traffic volume as a numerical value for normalizing the calculation formula of the driving difficulty level ADD was described, but if the abnormality determination frequency can be calculated for all passing vehicles, other can be used.

Also, the required time limit may be transmitted to the server 110 at the same time that the request for route information is transmitted from the electronic control unit 120 of the vehicle 200 to the server 110 . In this case, the route selection unit 113 of the server 110 selects, for example, from among the plurality of route candidates CR1, CR2, and CR3, a route that satisfies the required time limit and has the lowest travel difficulty ADD as a safe route. can be done.

Further, in the vehicle control system 100 of the present embodiment, the transmission unit 114 of the server 110, for example, determines whether a node or link requiring caution, which is N1-N4 or a link L1-L7, for which the frequency of abnormality determination on the recommended route is higher than a predetermined frequency. is included, the node or link that needs attention may be sent to each electronic controller 120 . In this case, the determination unit 122 of each electronic control unit 120 determines the priority of determining the type of abnormality determined at a higher frequency than a predetermined frequency in a node or link requiring caution, and the priority of determining the type of other abnormality. can be higher than

More specifically, for example, when the recognition unit 121 of each electronic control unit 120 always executes a plurality of recognition processes and the upper limit of the processing time of each recognition process is specified, the caution node Alternatively, it is conceivable to extend the upper limit of the processing time only when passing through a link. For example, in the above caution node or link where AEB due to pedestrian recognition occurs frequently, by extending the upper limit of the processing time of pedestrian recognition, pedestrian recognition processing is performed on more objects than usual, and walking is performed. Unrecognized person can be prevented.

[Embodiment 2]
Embodiment 2 of the vehicle control system according to the present disclosure will be described below with reference to FIGS. 1 to 7 of Embodiment 1 described above. The vehicle control system 100 of this embodiment differs from the vehicle control system 100 according to the first embodiment described above in the configuration of the recording unit 111 and the calculation unit 112 of the server 110 . Other configurations of the vehicle control system 100 of the present embodiment are the same as those of the vehicle control system 100 of the first embodiment described above.

In the vehicle control system 100 of this embodiment, each of the electronic control units 120 mounted on the plurality of vehicles 200 uses the recognition unit 121 in the process P15 shown in FIG. 220 and vehicle sensor 230, the road condition is recognized and abnormality information is recorded. Further, in the present embodiment, the electronic control unit 120, in the process P17 shown in FIG. .

Further, in the vehicle control system 100 of the present embodiment, the recording unit 111 of the server 110, for example, associates the type of the external sensor 220 included in the abnormality information with each of the nodes N1-N4 or the links L1-L7. Occurrence information is recorded in storage unit 115 . Table 4 below shows an example of abnormality occurrence information recorded in the storage unit 115 by the recording unit 111 in this embodiment.

[Table 4]

In addition, in Table 4, the sensor code is a code indicating the type of the external sensor 220 . The sensor code is defined for each type of external sensor 220 and recorded in storage unit 115 in advance, as shown in Table 5 below, for example.

[Table 5]

Furthermore, in the vehicle control system 100 of this embodiment, the server 110 performs the following process in the process P223 of acquiring the abnormality occurrence frequency shown in FIG. For example, the route selection unit 113 of the server 110 determines that the sensor code indicating the type of the external sensor matches in addition to the traveling conditions including the month, time zone, weather, etc., in which the vehicle 200 travels from the starting point S to the destination G. Extract the frequency of anomalies.

More specifically, as shown in Table 4, for each of the links L1 to L7, sensors that match the driving conditions of August when the vehicle 200 is running, between 17:00 and fine weather, and whose sensor codes represent stereo cameras Extract the frequency of occurrence of anomalies with a code of 1. Other processes of the vehicle control system 100 of this embodiment are the same as those of the vehicle control system 100 of the first embodiment.

As described above, in the vehicle control system 100 of the present embodiment, the recording unit 111 of the server 110 stores the type of the external sensor 220 of each vehicle 200 at the time of abnormality determination by the determination unit 122 of each electronic control unit 120, Abnormal occurrence information associated with each of the nodes N1-N4 or links L1-L7 is recorded. Further, the calculation unit 112 of the server 110 acquires the type of the external sensor 220 of each vehicle 200 when calculating the traveling difficulty level ADD, and determines the type of the external sensor 220 when determining the abnormality. Based on the abnormality occurrence information that matches the type of the sensor 220, the driving difficulty level ADD is calculated.

With such a configuration, the vehicle control system 100 of the present embodiment avoids routes in which abnormalities peculiar to the type of the external sensor 220 mounted on each vehicle 200 frequently occur, and automatically drives the vehicle 200 and assists driving. It is possible to improve the safety of More specifically, for example, when the type of abnormality is backlight, if the type of external sensor 220 is a camera, it will be affected by blown-out highlights, but if the type of external sensor 220 is a laser radar, it will not be affected. can be considered. In such a case, the vehicle control system 100 of the present embodiment allows the vehicle 200 to travel along a route suitable for the type of the external sensor 220 mounted on the vehicle 200 .

[Embodiment 3]
Finally, Embodiment 3 of the vehicle control system according to the present disclosure will be described with reference to FIGS. 1 to 7 and FIGS. 8 to 13 . FIG. 8 is a block diagram showing the configuration of the server 110 of the vehicle control system 100 of this embodiment. In the vehicle control system 100 of this embodiment, the server 110 shown in FIG. 8 has, for example, the same configuration as the server 110 of Embodiment 1 shown in FIG. I have. Other configurations of the vehicle control system 100 of the present embodiment are the same as those of the vehicle control system 100 of the first embodiment described above, so the same parts are denoted by the same reference numerals and descriptions thereof are omitted.

FIG. 9 is a flow diagram showing an example of the process P30 for supporting planning of countermeasures for reducing the occurrence of abnormalities by the server 110 of FIG. When the server 110 of the present embodiment starts the process P30 shown in FIG. 9, the countermeasure support unit 116 executes the process P31 of receiving the input of the extraction condition.

FIG. 10 is an example of a display screen by the countermeasure support unit 116 of the server 110 of FIG. Countermeasure support unit 116 includes, for example, a display device such as a liquid crystal display device or an organic EL display device, and an input device such as a touch panel, keyboard, or mouse. As shown in FIG. 10, the countermeasure support unit 116 causes the display device to display a map including each link L1-L7 and/or each node N1-N4 and extraction conditions such as month, time zone, weather, and abnormality type. .

In process P31, the countermeasure support unit 116 receives input of extraction conditions, for example, via an input device. For example, as shown in FIG. 10, the user of the server 110 scrolls the map displayed on the display device of the countermeasure support unit 116 and selects an area on the map for which countermeasures to reduce the occurrence of anomalies are desired. Select each link L1-L7 and/or each node N1-N4 in the region.

Furthermore, the user selects extraction conditions such as the month, time zone, weather, and abnormality type using a scroll bar displayed on the display device, for example, as shown in FIG. The countermeasure support unit 116 receives the input of the extraction condition selected by the user and inputs it to the calculation unit 112 . Here, it is assumed that "all data" has been input as extraction conditions for month, time period, weather, and abnormality type. Next, the server 110 executes a process P32 of acquiring an abnormality occurrence frequency.

In this process P32, the calculation unit 112 of the server 110 extracts, from the abnormality occurrence information recorded in the storage unit 115, abnormality occurrence information that matches the extraction conditions input from the countermeasure support unit 116 in the previous process P31. do. Furthermore, based on the extracted abnormality occurrence information, the calculation unit 112 calculates the abnormality occurrence frequency of each of the links L1 to L7 and/or each of the nodes N1 to N4, similarly to the process P223 shown in FIG. 4 of the first embodiment. get.

Next, the server 110 executes the process P33 of acquiring the average traffic volume shown in FIG. In this process P33, the computing unit 112 of the server 110, for example, similarly to the process P224 shown in FIG. For N4, the average traffic volume stored in the storage unit 115 is acquired. Here, since the extraction conditions for the month, time period, and weather are "all data," the average traffic volume for all months, time periods, and weather is obtained.

Next, the server 110 executes a process P34 for calculating the travel difficulty ADD of each link L1-L7 and/or each node N1-N4 shown in FIG. In this process P34, the calculation unit 112 of the server 110, similarly to the process P225 shown in FIG. A driving difficulty level ADD based on the frequency is calculated and input to the countermeasure support unit 116 . After that, the server 110 executes a process P35 of displaying the travel difficulty ADD of each link L1-L7 and/or each node N1-N4.

FIG. 11 is an example of a display screen of process P35 for displaying the travel difficulty ADD of each link L1-L7 and/or each node N1-N4 in FIG. In this process P35, the countermeasure support unit 116 displays the travel difficulty of each link L1-L7 and/or each node N1-N4 input from the calculation unit 112 in the previous process P34, as shown in FIG. display on the device. Here, as shown in FIG. 10, the travel difficulty of each link L1-L7 and/or each node N1-N4 included in the area selected on the map is displayed.

FIG. 12 is a graph showing the travel difficulty for each abnormality type of link L6 selected in FIG. On the display screen of the display device of countermeasure support unit 116 shown in FIG. 11, the user selects each link L1-L7 and/or each node N1-N4 in FIG. and then click or touch the icon labeled "Details". As a result, as shown in FIG. 12, it is possible to display the travel difficulty level for each abnormality type of the selected link L6 on the display device of the countermeasure support unit 116. FIG.

As described above, the calculation unit 112 of the server 110 calculates the travel difficulty ADD for each of the nodes N1 to N4 or the links L1 to L7 of the abnormality occurrence information extracted using the extraction condition including the time or type of abnormality, Displayed on the display device of the server 110 . Thus, according to the vehicle control system 100 of the present embodiment, it is possible to support planning of countermeasures for reducing the occurrence of abnormalities in each of the links L1-L7 and/or each of the nodes N1-N4.

More specifically, for example, as shown in FIG. 11, when a higher travel difficulty ADD is calculated for a specific link L6 than the other links L1-L5 and L7, the user selects the link L6. , click or press the "detailed display" icon. As a result, as shown in FIG. 12 , the travel difficulty ADD for each abnormality type of the selected link L6 is displayed by the countermeasure support unit 116 and the calculation unit 112 .

As a result, for example, as shown in FIG. 12, on link L6, the user can understand that the driving difficulty due to the unrecognized lane of abnormality type code: 2 is significantly higher than other abnormality types. can be done. As a result, based on the travel difficulty level ADD for each abnormality type displayed on the display device of the countermeasure support unit 116, the user can determine the road boundary line of the link L6 as a measure for reducing the travel difficulty level ADD of the link L6. can plan the re-installation of

Note that the countermeasure support unit 116 periodically analyzes the abnormality occurrence information recorded in the storage unit 115, and extracts conditions for increasing the travel difficulty ADD of each link L1-L7 and/or each node N1-N4. may be specified. In this case, for example, when it is predicted that the month, time zone, and weather conditions match the extraction conditions specified by the analysis, countermeasure support unit 116 selects each link L1 to L7 and/or The running difficulty ADD of each node N1-N4 is displayed on the display device together with the extraction conditions.

This allows the user to formulate measures to reduce the difficulty level ADD of the links L1-L7 and/or the difficulty levels ADD of the nodes N1-N4 displayed in the measure support unit 116. become. For example, as described above, in a specific time period such as the morning commuting time period, when many AEBs due to pedestrian recognition occur and the driving difficulty level ADD increases, the user may decide between the workplace and the parking lot. measures such as installing crosswalks on roads between

As described above, according to the vehicle control system 100 of the present embodiment, the travel difficulty level of each of the selected links L1-L7 and/or each of the nodes N1-N4 is displayed on the display device of the countermeasure support unit 116, and the user It is possible to support the determination of the priority of countermeasures and the narrowing down of countermeasures. Therefore, according to the vehicle control system 100 of the present embodiment, in addition to the effects of the vehicle control system 100 of the above-described first embodiment, the infrastructure for safe automatic driving by the electronic control unit 120 of the vehicle 200 is improved. Can assist with prioritization.

FIG. 13 is a flow chart showing an example of processing P40 for verifying countermeasures for reducing the occurrence of anomalies by the server 110 of FIG. 13, the server 110 of the present embodiment performs a process P41 of reproducing the traffic flow before taking measures to reduce the occurrence of abnormalities by means of the traffic flow simulator 117. FIG.

Here, the traffic flow simulator 117 simulates the running behavior of each of the plurality of vehicles 200 by inputting parameters such as traffic volume at representative points and right/left turn rates at each intersection. The traffic flow simulator 117 can be implemented using known technology such as the road traffic simulation system described in Japanese Patent Application Laid-Open No. 5-250594.

In process P41, by adjusting the parameters to be input to the traffic flow simulator 117, the known traffic flow before taking measures to reduce the occurrence of abnormalities is reproduced. More specifically, the known traffic volume of each link L1-L7 and/or each node N1-N4 and the traffic volume of each link L1-L7 and/or each node N1-N4 reproduced by the traffic flow simulator 117 and The parameters input to the traffic flow simulator 117 are adjusted so that

Next, as shown in FIG. 13, the server 110 performs a process P42 of calculating the travel difficulty ADD of each of the links L1-L7 and/or each of the nodes N1-N4 after taking measures to reduce the occurrence of abnormalities. Execute. In this process P42, the calculation unit 112 assumes, for example, that the abnormality occurrence frequency of each link and/or each node after the countermeasure is implemented is zero, and similarly to the processes P31 to P34 shown in FIG. Calculate the difficulty level ADD of L1-L7 and/or each of the nodes N1-N4.

Next, the traffic flow simulator 117 executes a process P43 of changing the right/left turn rate parameter, as shown in FIG. For example, in link L6 shown in FIG. 10, when taking measures to reduce the frequency of occurrence of anomalies, another link L3 is connected to node N2 connected to link L6. The traffic flow simulator 117 changes, for example, the right and left turn rates from the node N2 to the links L6 and L3 before and after implementing the countermeasure on the link L6, as shown in Table 6 below.

[Table 6]

As shown in Table 6, for example, as a result of taking measures such as re-installation of lane boundary lines on link L6, the driving difficulty of link L6 has decreased from 0.23 to 0 before and after taking measures. As a result, the ratios of right and left turns from node N2 to link L6 and link L3, 0.2 and 0.8, are changed to 0.472 and 0.528 before and after the implementation of countermeasures for link L6. Such an increase/decrease in the right/left turn rate can be calculated, for example, based on the mixing rate of the vehicle 200 automatically traveling under the control of the electronic control unit 120 with respect to the overall traffic volume at the node N2.

For example, assume that the rate of automatically traveling vehicles 200 in the total traffic volume is 34%, and that 100% of the vehicles 200 were turning right from node N2 to link L3 before the implementation of the countermeasure. In this case, the ratio of the total traffic volume of vehicles 200 turning right from node N2 to link L3 is 27.2% (0.8×0.34=0.272). Assuming that these vehicles 200 turn left at node N2 to link L6 after the countermeasure is implemented, the right/left turn rate from node N2 to link L6 after the countermeasure is implemented is 0.2+0.272=0.472. Become.

As shown in Table 6, before the implementation of the countermeasure, the travel difficulty ADD of link L6 was significantly higher than the travel difficulty ADD of link L3, so the right/left turn rate to link L6 was higher than the right/left turn rate to link L3. was also significantly lower. However, after the implementation of the measures, the travel difficulty level ADD of link L6 became 0, which was lower than the travel difficulty level ADD of 0.043 of link L3. The difference in right/left turn rate between L6 and link L3 has decreased and almost disappeared.

Next, the server 110 executes the process P44 of simulating the traffic flow after the implementation of the countermeasure. In this process P44, the traffic flow simulator 117 uses, for example, the parameters shown in Table 6, including right and left turn rates after implementation of the countermeasure, to The traffic flow is simulated when the difficulty level ADD is changed.

Next, the server 110 executes a process P45 of comparing the traffic flow of each link L1-L7 and/or each node N1-N4 before and after implementing the countermeasure. By this process, for example, it is possible to confirm the effect of countermeasures for reducing the occurrence of anomalies, such as traffic jam elimination by dispersing the traffic flow to the link L6 and the link L3, and to verify the countermeasures.

As described above, in the vehicle control system 100 of the present embodiment, the server 110 includes a traffic flow simulator 117 that simulates traffic flow when the travel difficulty level of each node or link of the map information MI is changed. have. With such a configuration, the vehicle control system 100 of the present embodiment makes it possible to evaluate improvements in road congestion such as congestion, in addition to the effects of the vehicle control system 100 of the first embodiment.

Although the embodiments of the vehicle control system and the electronic control device according to the present disclosure have been described in detail above with reference to the drawings, the specific configuration is not limited to this embodiment and does not depart from the gist of the present disclosure. Even if there are design changes etc. within the scope, they are included in the present disclosure.

100 Vehicle control system 110 Server 111 Recording unit 112 Calculation unit 113 Route selection unit 114 Transmission unit 117 Traffic flow simulator 120 Electronic control unit 121 Recognition unit 122 Judgment unit 123 Transmission unit 124 Vehicle control unit 200 Vehicle 210 Communication device 220 External sensor ADD Travel Difficulty level CR1-CR3 Route candidate L1-L7 Link MI Map information N1-N4 Node

Claims (10)

1. A vehicle control system comprising: each electronic control device mounted on each of a plurality of vehicles; and at least one server communicably connected to each electronic control device,
   Each of the electronic control units includes a recognition unit that recognizes road conditions based on the detection result of an external sensor mounted on each of the vehicles, and a judgment that determines an abnormality including poor recognition of the road conditions by the recognition unit. and abnormality information including the position of each vehicle at the time of abnormality determination by the determination unit, the time, and the type of the determined abnormality are transmitted to the server via a communication device mounted on each of the vehicles. a transmitter;
   The server includes a recording unit for recording abnormality occurrence information in which the abnormality information received from each electronic control unit is associated with each node or link of map information, and the node or link included in the abnormality occurrence information. a calculation unit for calculating a travel difficulty level based on the frequency of determination of the abnormality for each route; a route selection unit for selecting a safe route that minimizes the sum of the travel difficulty levels from a plurality of route candidates in the map information; and a transmitter for transmitting the route to each of the electronic control units as a recommended route.
2. The calculation unit of the server calculates the traveling difficulty level for each node or link of the abnormality occurrence information to be higher as the frequency of determination of the abnormality by the determination unit of each electronic control unit is higher. The vehicle control system according to claim 1, wherein:
3. The recording unit of the server records the abnormality occurrence information in which the weather at the position of each vehicle at the time of abnormality determination by the determination unit of each electronic control unit is associated with each node or link. ,
   The calculation unit of the server acquires the current weather of each of the nodes or links included in the plurality of route candidates of the map information when calculating the travel difficulty level, and obtains the current weather of each of the nodes or links included in the plurality of route candidates of the map information. 2. The vehicle control system according to claim 1, wherein said driving difficulty level is calculated based on said abnormality occurrence information that matches said weather.
4. The recording unit of the server stores the abnormality occurrence information in which the type of the external sensor of each vehicle at the time of abnormality determination by the determination unit of each electronic control unit is associated with each node or link. record and
   The computing unit of the server acquires the type of the external sensor of each vehicle when calculating the traveling difficulty level, and the type of the external sensor at the time of the abnormality determination is the external world at the time of calculating the traveling difficulty level. 2. The vehicle control system according to claim 1, wherein the driving difficulty level is calculated based on the abnormality occurrence information that matches the sensor type.
5. When the recommended route includes a node or link requiring caution, which is the node or link whose abnormality determination frequency is higher than a predetermined frequency, the transmitting unit of the server transmits the node or link requiring caution to each of the above sent to the electronic control unit,
   The judging unit of each electronic control unit judges the priority for judging the type of abnormality judged at a frequency higher than the predetermined frequency in the node or link requiring attention, and judges the type of the other abnormality. 2. The vehicle control system according to claim 1, wherein the priority is set higher than the priority.
6. In the electronic control device, when the type of the abnormality determined by the determination unit cannot be specified, the transmission unit transmits an image of a camera included in the external sensor together with the abnormality information to the server. The vehicle control system according to claim 1.
7. The computing unit of the server causes the display device of the server to display the traveling difficulty calculated for each of the nodes or links of the abnormality occurrence information extracted using the extraction condition including the time or the type of abnormality. The vehicle control system according to claim 1, characterized in that:
8. 8. The vehicle control system according to claim 7, wherein the server has a traffic flow simulator that simulates traffic flow when the travel difficulty level of each node or link of the map information is changed. .
9. The vehicle control system according to claim 1, wherein each of the electronic control units includes a vehicle control section that causes each of the vehicles to travel along the recommended route received from the server.
10. An electronic control device mounted on a vehicle,
    a recognition unit that recognizes road conditions based on the detection results of an external sensor mounted on the vehicle; a determination unit that determines an abnormality including poor recognition of the road conditions by the recognition unit; a transmission unit for transmitting abnormality information including the position of the vehicle, the time, and the type of the determined abnormality to a server outside the vehicle via a communication device mounted on the vehicle; and a vehicle control unit that causes the vehicle to travel along the route.

Images