Driving risk analysis device, driving assistance device, driving risk analysis method, and driving assistance system

Abstract

The purpose of the present invention is to provide a technology capable of performing appropriate driving support for each automatic driving mode. This driving risk analysis device comprises: a probe information acquisition unit that acquires, from a probe vehicle, probe information including position information indicating the position of a probe vehicle when a driving risk has occurred in the probe vehicle and automatic driving mode information indicating an automatic driving mode of the probe vehicle when the driving risk has occurred; and an analysis unit that, on the basis of the probe information, generates risk map information that is associated with road map information and indicates, for each automatic driving mode, an area in which the occurrence frequency of the driving risk is equal to or greater than a threshold value.

Description

Driving risk analysis device, driving assistance device, driving risk analysis method, and driving assistance system

[0001] The present disclosure relates to a driving risk analysis device, a driving assistance device, a driving risk analysis method, and a driving assistance system.

[0002] A technology has been proposed that collects information from one or more vehicles on points where a contact risk between the vehicle and another object has occurred, and points where the driver of the vehicle has looked aside, to generate a caution-required point map that is a map indicating points that the driver should pay attention to (for example, Patent Document 1). According to such a technology, when a driver approaches a point on the caution-required point map, it is possible to notify or display the point to prompt the driver to be alerted.

[0003] Japanese Unexamined Patent Application Publication No. 2018-167647

[0004] Points that a driver should pay attention to differ depending on the automated driving mode such as the automated driving level, but the conventional technology does not consider the automated driving mode, so there is a problem that appropriate driving assistance cannot be performed.

[0005] The present disclosure has been made in view of the above problems, and aims to provide a technology capable of performing appropriate driving assistance for each automated driving mode.

[0006] A driving risk analysis device according to the present disclosure includes a probe information acquisition unit that acquires, from a probe vehicle, probe information including position information indicating the position of the probe vehicle when a driving risk occurs, and automated driving mode information indicating the automated driving mode of the probe vehicle when the driving risk occurs, and an analysis unit that generates, based on the probe information, risk map information associated with road map information and indicating, for each automated driving mode, areas where the occurrence frequency of driving risks is equal to or higher than a threshold, and a distribution control unit that distributes the risk map information to the outside.

[0007] According to this disclosure, based on probe information, risk map information is generated and distributed externally, which is associated with road map information and indicates areas where the frequency of driving risks exceeds a threshold for each autonomous driving mode. With such a configuration, appropriate driving assistance can be provided for each autonomous driving mode.

[0008] The purpose, features, aspects, and advantages of this disclosure will become clearer from the following detailed description and accompanying drawings.

[0009] Figure 1 is a block diagram showing the configuration of the driver assistance system according to Embodiment 1. Figure 2 is a diagram showing an example of probe information. Figure 3 is a diagram showing an example of risk map information. Figure 4 is a flowchart showing the operation of the probe vehicle-side device according to Embodiment 1. Figures 5(a) to 5(c) are flowcharts showing the operation of the driver risk analysis device according to Embodiment 1. Figure 6 is a block diagram showing the configuration of the driver assistance system according to Modification 2 of Embodiment 1. Figure 7 is a block diagram showing the configuration of the driver assistance system according to Embodiment 2. Figure 8 is a diagram illustrating a first example of driver assistance execution conditions and driver notification control. Figure 9 is a diagram illustrating a second example of driver assistance execution conditions and driver notification control. Figure 10 is a flowchart showing the operation of the driver assistance device according to Embodiment 2. Figure 11 is a block diagram showing the configuration of the driver assistance system according to Modification 1 of Embodiment 2. Figure 12 is a diagram illustrating driver assistance according to Modification 2 of Embodiment 2. Figure 13 is a block diagram showing the hardware configuration of the driver risk analysis device according to another modification. Figure 14 is a block diagram showing the hardware configuration of the driver risk analysis device according to another modification.

[0010] <Embodiment 1> Figure 1 is a block diagram showing the configuration of the driving support system according to this embodiment 1. The driving support system in Figure 1 comprises a probe vehicle-side device 1 installed on the probe vehicle and a driving risk analysis device 3, which is a server installed outside the probe vehicle, and the probe vehicle-side device 1 and the driving risk analysis device 3 are able to communicate with each other via a wide-area communication network 9.

[0011] <Probe Vehicle-Side Device 1> The probe vehicle-side device 1 shown in Figure 1 comprises a surrounding detection device 1a, a risk detection unit 1b, an automatic driving control device 1c, a vehicle control information acquisition unit 1d, a positioning device 1e, a location information acquisition unit 1f, a probe information generation unit 1g, and a communication device 1h.

[0012] The surrounding detection device 1a detects surrounding information indicating the conditions around the probe vehicle. The surrounding detection device 1a is, for example, a camera, an image processing device, a Lidar (Light Detection and Ranging), a millimeter-wave sensor, etc., and the surrounding information includes, for example, the position and speed of objects other than the probe vehicle around the probe vehicle, and the shape of the lane in which the probe vehicle is traveling. The objects include at least one of moving objects such as other vehicles and geographical features. In this specification, for example, at least one of A, B, C, ..., and Z means any one of all combinations that can be obtained by selecting one or more types from multiple types of A, B, C, ..., and Z.

[0013] The risk detection unit 1b determines (detects) whether or not a driving risk has occurred for the probe vehicle based on the surrounding information detected by the surrounding detection device 1a. For example, the risk detection unit 1b calculates a driving risk value indicating the degree of driving risk for the probe vehicle based on the surrounding information. The driving risk value includes, for example, at least one of the risk value of contact between the probe vehicle and objects around the probe vehicle, and the risk value of the probe vehicle deviating from its lane.

[0014] The risk detection unit 1b determines that an operating risk has occurred if it determines that an operating risk value, such as the contact risk value, is above a threshold, and determines that no operating risk has occurred if it determines that the operating risk value is below the threshold. The first and second examples of this determination will be explained below.

[0015] <Example 1> The risk detection unit 1b calculates the relative distance L(t) from the time-series information of the relative position P(t) of other vehicles relative to the probe vehicle. When the relative distance L(t) falls below a predetermined distance Lth, the risk detection unit 1b determines that the contact risk value, which has the inverse relationship to the relative distance L(t), has exceeded a threshold, and determines that a driving risk has occurred. The predetermined distance Lth is, for example, 1m, or the stopping distance based on the speed of the probe vehicle.

[0016] <Second Example> The risk detection unit 1b calculates the time CT at which the probe vehicle and the other vehicle will come into contact if evasive action is not taken, based on the time-series information of the relative position P(t) of the other vehicle with respect to the probe vehicle. When time CT falls below a predetermined time Tth, the risk detection unit 1b determines that the contact risk value, which has the inverse relationship with time CT, has exceeded a threshold, and determines that a driving risk has occurred. The predetermined time Tth is, for example, 1 second.

[0017] The automatic driving control device 1c in Figure 1 is capable of executing an automatic driving mode. When the automatic driving mode is executed, the automatic driving control device 1c controls the probe vehicle to perform at least a portion of the driving operations performed by the driver of the probe vehicle. In this embodiment 1, the automatic driving mode is an automatic driving level, and the case in which the automatic driving control device 1c executes an automatic driving level LV-k (k = 0 to 5) as the execution of the automatic driving mode is described, but as will be described later, it is not limited to this. Generally speaking, the higher the automatic driving level, the more complex the driving operations performed by the probe vehicle tend to be.

[0018] The vehicle control information acquisition unit 1d acquires from the automatic driving control device 1c automatic driving mode information that indicates the automatic driving mode of the probe vehicle, that is, the automatic driving mode being executed by the automatic driving control device 1c.

[0019] The positioning device 1e acquires the positioning results of the probe vehicle, for example, using GNSS (Global Navigation Satellite System).

[0020] The position information acquisition unit 1f generates and acquires position information indicating the position of the probe vehicle based on the positioning results of the positioning device 1e. The position information acquisition unit 1f may generate position information based solely on the positioning results of the positioning device 1e, or it may generate position information based on the positioning results of the positioning device 1e and the detection results of a vehicle speed sensor and an acceleration sensor (not shown). Alternatively, position information may be generated by performing map matching processing using the positioning results of the positioning device 1e and road map information.

[0021] The probe information generation unit 1g generates probe information including the automatic driving mode information from the vehicle control information acquisition unit 1d and the location information from the location information acquisition unit 1f when the risk detection unit 1b detects the occurrence of a driving risk for the probe vehicle.

[0022] Figure 2 shows an example of probe information generated by the probe information generation unit 1g. The probe information in Figure 2 includes not only automatic driving mode information (M(n)) and location information (P(n)), but also the ID of the driving risk detected by the risk detection unit 1b (IDn), the time information (T(n)) when the occurrence of the driving risk was detected, and the ID of the probe vehicle in which the occurrence of the driving risk was detected (V(n)). The ID of the probe vehicle (V(n)) is obtained, for example, from the LAN (Local Area Network) inside the probe vehicle.

[0023] The communication device 1h in Figure 1 transmits the probe information generated by the probe information generation unit 1g to an external device such as the driving risk analysis device 3 via the wide-area communication network 9.

[0024] <Driving Risk Analysis Device 3> The driving risk analysis device 3 shown in Figure 1 comprises a server communication unit 3a, a probe information acquisition unit 3b, a storage unit 3c, an analysis unit 3d, a risk map information storage unit 3e, and a distribution control unit 3f.

[0025] The server communication unit 3a receives probe information from the probe vehicle-side device 1 by communicating with the communication device 1h via the wide-area communication network 9.

[0026] The probe information acquisition unit 3b acquires probe information received by the server communication unit 3a from the server communication unit 3a. In other words, the probe information acquisition unit 3b indirectly acquires probe information from the probe vehicle, including location information when a driving risk occurs in the probe vehicle and automatic driving mode information when such a driving risk occurs. The probe information acquisition unit 3b may include the server communication unit 3a, or the probe information acquisition unit 3b may directly acquire probe information from the probe vehicle-side device 1 without going through the server communication unit 3a and the wide-area communication network 9.

[0027] The memory unit 3c temporarily stores the probe information acquired by the probe information acquisition unit 3b.

[0028] The analysis unit 3d generates risk map information that, based on the probe information acquired by the probe information acquisition unit 3b and stored in the storage unit 3c, associates with road map information and shows areas where the frequency of driving risks is above a threshold for each autonomous driving level (autonomous driving mode). In this embodiment 1, since the probe information is stored in the storage unit 3c, the analysis unit 3d can use the latest probe information and past probe information to generate the risk map information, or it can use probe information from multiple probe vehicles to generate the risk map information.

[0029] For example, the analysis unit 3d generates risk map information as shown in Figure 3 by appropriately performing statistical analysis on the occurrence of driving risks based on probe information. An example of generating risk map information will be described below.

[0030] For example, the analysis unit 3d determines the number of times, for each autonomous driving level LV-k, that the location information included in the probe information within a certain past period (e.g., one month) substantially indicates each link LK-m associated with the road map information. The number of occurrences of the driving risk RSK(m,k) for each pair of link LK-m and autonomous driving level LV-k corresponds to NO(m,k).

[0031] The analysis unit 3d sets the driving risk RSK(m,k) to "driving risk present (=1)" if the number of occurrences NO(m,k) of the driving risk RSK(m,k) is equal to or greater than the threshold number NOth. On the other hand, the analysis unit 3d sets the driving risk RSK(m,k) to "no driving risk (=0)" if the number of occurrences NO(m,k) of the driving risk RSK(m,k) is less than the threshold number NOth. In other words, if NO(m,k) ≥ NOth, RSK(m,k) = 1 (driving risk present) is set, and if NO(m,k) < NOth, RSK(m,k) = 0 (no driving risk) is set. The threshold number NOth is, for example, 20 times. Note that the threshold number NOth may be changed based on traffic volume, for example, by increasing the threshold number NOth as traffic volume increases.

[0032] The analysis unit 3d generates risk map information as shown in Figure 3 by performing the above processing. For example, for link LK-0 in Figure 3, there is no driving risk at all autonomous driving levels, so RSK(0,k) = 0 | k = 0 to 5. For link LK-2, there is driving risk at autonomous driving levels 0 and 1, and no driving risk at other autonomous driving levels, so RSK(2,k) = 1 | k = 0 to 1, and RSK(2,k) = 0 | k = 2 to 5. For link LK-3, there is driving risk at autonomous driving levels 2 and 3, and no driving risk at other autonomous driving levels, so RSK(3,k) = 1 | k = 2 and 3, and RSK(3,k) = 0 | k = 0, 1, 4, and 5.

[0033] For convenience, in the following explanation, areas (links) associated with road map information where the frequency of driving risk occurrences exceeds a threshold may be referred to as "risk areas." In the above example, the analysis unit 3d used the number of driving risk occurrences over a certain period in the past as the frequency of driving risk occurrences, but this is not the only method. For example, the analysis unit 3d may use the reciprocal of the interval between driving risk occurrences as the frequency of driving risk occurrences.

[0034] Furthermore, the analysis unit 3d may determine whether there is a driving risk for a pair of link LK-m and autonomous driving level LV-k based on whether the average value of the occurrence frequency is above a threshold, or whether the weighted average of occurrence frequencies, with greater weighting for more recent occurrences, is above a threshold. Alternatively, the analysis unit 3d may generate risk map information by extracting links LK-m, which are substantially indicated by the position information included in the latest probe information, as risk areas for each autonomous driving level LV-k.

[0035] The risk map information storage unit 3e in Figure 1 stores the risk map information generated by the analysis unit 3d. The distribution control unit 3f distributes the risk map information generated by the analysis unit 3d and stored in the risk map information storage unit 3e to an external source such as a vehicle via the server communication unit 3a. The vehicle referred to here may or may not be a probe vehicle. In this embodiment 1, the risk map information storage unit 3e distributes the risk map information to the source of the distribution request in accordance with the distribution request from an external source, but it is not limited to this.

[0036] <Operation> Figure 4 is a flowchart showing the operation of the probe vehicle-side device 1 according to this embodiment 1.

[0037] In step S1, the vehicle control information acquisition unit 1d acquires automatic driving mode information from the automatic driving control device 1c. In step S2, the location information acquisition unit 1f acquires location information based on the positioning result of the positioning device 1e. In step S3, the risk detection unit 1b acquires surrounding information from the surrounding detection device 1a. Note that the order of steps S1 to S3 may be changed as appropriate.

[0038] In step S4, the risk detection unit 1b determines whether or not a driving risk has occurred for the probe vehicle based on the surrounding information. If it is determined that a driving risk has occurred, the process proceeds to step S5; if it is determined that no driving risk has occurred, the process proceeds to step S7.

[0039] In step S5, the probe information generation unit 1g generates probe information including the automatic driving mode information from step S1 and the location information from step S2. In other words, the probe information generation unit 1g generates probe information including the automatic driving mode information and location information when the occurrence of a driving risk for the probe vehicle is detected. In step S6, the communication device 1h transmits the probe information to the driving risk analysis device 3.

[0040] In step S7, the probe vehicle-side device 1 determines whether the probe vehicle has finished its run. If it is determined that the probe vehicle has finished its run, the operation shown in Figure 4 ends. If it is not determined that the probe vehicle has finished its run, the process proceeds to step S1. Note that the timing of transmitting probe information is not limited to when the occurrence of a driving risk is detected. For example, the probe vehicle-side device 1 may store probe information until the probe vehicle finishes its run, and then transmit all the stored probe information to the driving risk analysis device 3 at once when the probe vehicle finishes its run.

[0041] Figures 5(a) to 5(c) are flowcharts illustrating the operation of the driving risk analysis device 3 according to this embodiment 1. The driving risk analysis device 3 performs the information collection process shown in Figure 5(a), the analysis process shown in Figure 5(b), and the information distribution process shown in Figure 5(c). These three processes may be performed in parallel by three programs, or selectively by a single program.

[0042] <Information Gathering Process> In step S11 of Figure 5(a), the probe information acquisition unit 3b determines whether or not it has acquired the probe information received by the server communication unit 3a from the server communication unit 3a. If it is determined that the probe information has been acquired, the process proceeds to step S12; if it is not determined that the probe information has been acquired, the process in step S11 is repeated.

[0043] In step S12, the probe information acquisition unit 3b stores the probe information acquired from the server communication unit 3a in the storage unit 3c. After that, the process proceeds to step S11.

[0044] <Analysis Processing> In step S21 of FIG. 5(b), the analysis unit 3d determines whether or not the current timing is the analysis timing. If it is determined that the timing is the analysis timing, the process proceeds to step S22, and if it is not determined that the timing is the analysis timing, the process of step S21 is performed again.

[0045] In step S22, the analysis unit 3d generates risk map information based on the probe information stored in the storage unit 3c. In step S23, the analysis unit 3d stores the risk map information in the risk map information storage unit 3e. Thereafter, the process proceeds to step S21.

[0046] <Information Distribution Processing> In step S31 of FIG. 5(c), the distribution control unit 3f determines whether or not the server communication unit 3a has received a distribution request. If it is determined that a distribution request has been received, the process proceeds to step S32, and if it is not determined that a distribution request has been received, the process of step S31 is performed again.

[0047] In step S32, the distribution control unit 3f distributes the risk map information stored in the risk map information storage unit 3e to the distribution request source via the server communication unit 3a. Thereafter, the process proceeds to step S31.

[0048] Note that the distributed risk map information may be the risk map information of links corresponding to the travel route of the distribution request source, may be the risk map information of a predetermined partial area, may be the risk map information of all areas, or may be the risk map information of only updated areas. That is, the scope of the distributed risk map information is not limited.

[0049] <Summary of Embodiment 1> According to the driving risk analysis device 3 according to the first embodiment as described above, based on the probe information including the position information and the automated driving mode information when a driving risk occurs in a probe vehicle, risk map information associated with road map information and indicating, for each automated driving mode, areas where the occurrence frequency of driving risks is equal to or higher than a threshold value is generated and distributed to the outside such as vehicles.

[0050] Generally, when operating at autonomous driving level LV-1 (e.g., ACC (Adaptive Cruise Control) on), the driver's driving tasks are reduced compared to when operating at autonomous driving level LV-0 (e.g., fully manual driving). However, drivers may become overly confident in their driving, resulting in delayed reactions to situations such as other vehicles cutting in front of them. In response to this, vehicles operating at autonomous driving level LV-1 that have received risk map information can use the risk map information to notify the driver of areas where other vehicles frequently cut in recklessly, designating these as risk areas for autonomous driving level LV-1, through notifications and displays. Thus, by distributing risk map information externally, the driving risk analysis device 3 according to this embodiment 1 can provide appropriate driving assistance, such as notifying the driver of points to pay attention to for each autonomous driving mode, in vehicles that have received the risk map information.

[0051] <Modification 1> In Embodiment 1, the probe vehicle-side device 1 determined whether or not a driving risk occurred for the probe vehicle based on surrounding information, and generated probe information based on the determination result, location information, and automatic driving mode information. However, it is not limited to this. For example, the probe vehicle-side device 1 may transmit surrounding information, location information, and automatic driving mode information. The driving risk analysis device 3 may then determine whether or not a driving risk occurred for the probe vehicle based on surrounding information, and generate probe information based on the determination result, location information, and automatic driving mode information.

[0052] With this configuration, the communication resources transmitted from the probe vehicle-side device 1 to the driving risk analysis device 3 increase somewhat. However, since the driving risk analysis device 3 is generally a server with high processing power, it is possible to improve the accuracy of determining the driving risk of the probe vehicle. Furthermore, a reduction in the processing power of the probe vehicle-side device 1 can also be expected.

[0053] <Modification 2> The position of the probe vehicle in the location information included in the probe information may be expressed on a lane-by-lane basis, and the area in the risk map information generated by the analysis unit 3d may also be expressed on a lane-by-lane basis. With this configuration, appropriate driving assistance can be provided for each lane.

[0054] Furthermore, in order for the position information included in the probe information to be expressed on a lane-by-lane basis, the probe vehicle-side device 1 only needs to detect the lane the probe vehicle is traveling in. For lane detection, a high-precision locator device (HDL) capable of recognizing the lane the probe vehicle is traveling in may be used, which has a high-precision map database containing road shape information on a lane-by-lane basis and a sub-meter-level high-precision positioning device. In other words, as shown in Figure 6, an HDL 1e3 having a high-precision map database 1e1 and a high-precision positioning device 1e2 may be used as the positioning device 1e in Figure 1.

[0055] Alternatively, an image recognition device that recognizes the lane the probe vehicle is traveling in may be used to detect the driving lane. Alternatively, a device capable of recognizing the lane the probe vehicle is traveling in may be used to detect the driving lane, comprising an image recognition device, a road-level normal-accuracy map database storing the number of lanes, and a positioning device with positioning performance of several meters.

[0056] Furthermore, while the risk map information in Figure 3 uses a link-specific format, other data formats may be used for the risk map information. For example, when HDL is used as in this modified example 2, a lane-specific format may be used in the risk map information instead of a link-specific format. Alternatively, for example, by providing one or more rows corresponding to one or more lanes for each row of link IDs in Figure 3, both link-specific and lane-specific formats may be used in the risk map information.

[0057] <Modification 3> In Embodiment 1, the risk detection unit 1b may generate a risk type indicating the type of driving risk based on at least one of the surrounding information and information obtained from the automatic driving control device 1c indicating that the driver has intervened in the driving.

[0058] The probe vehicle-side device 1 may then transmit probe information, which further includes the risk type generated by the risk detection unit 1b, to the driving risk analysis device 3. The risk type may include physical risks that are physically related to the probe vehicle, and the physical risks may include at least one of the following PRisk(1), PRisk(2), PRisk(3), and PRisk(4).

[0059] <PRisk(1)> PRisk(1) is the risk of contact between the probe vehicle and a moving object other than the probe vehicle. If the risk detection unit 1b is able to generate sub-information indicating one of the following based on surrounding information including the relative positional relationship between the probe vehicle and the moving object: a collision with a moving object in front, a collision with a moving object behind, contact with a moving object to the right, or contact with a moving object to the left, then PRisk(1) may include such sub-information.

[0060] <PRisk(2)> PRisk(2) is the risk of contact between the probe vehicle and the terrain. If the risk detection unit 1b is capable of generating sub-information indicating the type of terrain (e.g., road structure, fallen object, etc.) based on surrounding information, PRisk(2) may include such sub-information.

[0061] <PRisk(3)> PRisk(3) is the risk of the probe vehicle deviating from its lane. If the risk detection unit 1b is capable of generating sub-information indicating the type of deviation of the probe vehicle (e.g., deviation from the driving lane, deviation from the lane, deviation from the road, falling off the road, etc.) based on surrounding information, PRisk(3) may include such sub-information.

[0062] <PRisk(4)> PRisk(4) is the risk of the probe vehicle violating road traffic laws. If the risk detection unit 1b is able to generate sub-information indicating the type of road traffic law violation by the probe vehicle (e.g., speeding, violation of rules indicated by signs, etc.) based on surrounding information, PRisk(4) may include such sub-information.

[0063] The analysis unit 3d of the driving risk analysis device 3 may generate risk map information that shows risk areas for each automated driving mode and for each physical risk, based on probe information that further includes physical risks. For example, the analysis unit 3d may generate risk map information by statistically analyzing physical risks for a specific automated driving mode and a specific area. For example, the analysis unit 3d may create a database of areas for each automated driving mode with the most frequently occurring physical risk as the representative risk, or it may add the occurrence rate of each physical risk to the risk map information for each physical risk. With such a configuration, appropriate driving assistance can be provided for each automated driving mode and for each physical risk.

[0064] <Modification 4> In Modification 3, the risk detection unit 1b generated physical risks related to the probe vehicle as risk types based on surrounding information, but it is not limited to this. For example, the risk detection unit 1b may generate driver state risks related to the driver state of the probe vehicle as risk types based on the driver state of the probe vehicle detected by the DMS (Driver Monitoring System). The driver state risk may include at least one of DRisk(1), which is the risk of the probe vehicle driver being distracted, and DRisk(2), which is the risk of the probe vehicle driver falling asleep at the wheel. The probe vehicle-side device 1 may transmit probe information further including the driver state risks generated by the risk detection unit 1b to the driving risk analysis device 3.

[0065] The analysis unit 3d may generate risk map information that shows risk areas for each autonomous driving mode and for each driver state risk, based on probe information that further includes driver state risk. With such a configuration, appropriate driving assistance can be provided for each autonomous driving mode and for each driver state risk.

[0066] Furthermore, modified examples 3 and 4 may be combined. That is, as shown in Figure 6, the risk detection unit 1b may generate physical risk as a risk type based on surrounding information from the surrounding detection device 1a, and generate driver state risk as a risk type based on the driver state from the DMS 1j. In other words, the risk type may include both physical risk and driver state risk.

[0067] <Modification 5> In a configuration where the risk type includes physical risk and driver condition risk, the analysis unit 3d may define a risk area where physical risk and driver condition risk occur simultaneously as a special attention area in the risk map information. For example, in the risk map information of Figure 3, RSK(m,k) is set to "0" or "1", but RSK(m,k) for the special attention area may be set to "2".

[0068] <Modification 6> The probe information may further include attribute information that indicates at least one of the following as attributes: the time, day of the week, weather, and whether or not the day the driving risk occurred was a public holiday. The analysis unit 3d may then generate risk map information that shows the risk area for each automated driving mode and attribute based on the probe information that further includes the attribute information. With such a configuration, appropriate driving assistance can be provided for each automated driving mode and attribute.

[0069] The probe information may include the model number of the probe vehicle's automatic driving control device 1c, or product information of the probe vehicle (model number, vehicle type, vehicle class, manufacturer information), and the analysis unit 3d may include this information in the risk map information. In addition, the attribute information may indicate the model number of the probe vehicle's automatic driving control device 1c, or the vehicle's product information as an attribute, and the analysis unit 3d may generate risk map information that shows risk areas for each automatic driving mode and for each model number or product information.

[0070] <Modification 7> In Embodiment 1, the analysis unit 3d set the driving risk RSK(m,k) for the link and automatic driving level combination to "1" or "0" based on whether the number of occurrences of driving risks was equal to or greater than a threshold number. As a result, the driving risk RSK(m,k) in the risk map information was represented as a binary value (0,1), but it is not limited to this.

[0071] For example, if the number of occurrences is greater than or equal to a threshold number, the analysis unit 3d may move the driving risk RSK(m,k) in the risk map information closer to "0" the closer the number of occurrences is to the threshold number, and move the RSK(m,k) closer to "1" the further the number of occurrences is from the threshold number. In this way, the driving risk RSK(m,k) in the risk map information may be represented by three or more values. For example, the driving risk RSK(m,k) may be represented by a continuous value between "0" and "1", or by a discrete value between "0" and "1".

[0072] With this configuration, driving assistance can be finely adjusted in response to the frequency of occurrence. In a configuration where the risk type includes physical risk and driver condition risk, the analysis unit 3d may calculate the sum of the driving risk RSK(m,k) determined from physical risk and the driving risk RSK(m,k) determined from driver condition risk as the driving risk RSK(m,k) in the risk map information.

[0073] Furthermore, in Embodiment 1, the probe vehicle-side device 1 determined that a driving risk had occurred when the contact risk value increased based on the time-series information of the relative position P(t) of other vehicles, and set RSK=1. However, it is not limited to this. For example, the probe vehicle-side device 1 may use an evaluation function such that when the inter-vehicle distance VL is shorter than the stopping distance Lstop, the shorter the inter-vehicle distance VL, the closer RSK is to 1, and the longer the inter-vehicle distance VL, the closer RSK is to 0, to determine the degree of driving risk RSK as a multi-value or continuous value. Alternatively, for example, the probe vehicle-side device 1 may be configured so that the degree of driving risk RSK as a multi-value or continuous value increases as the inter-vehicle distance VL decreases rapidly.

[0074] The probe vehicle-side device 1 may transmit probe information including a multi-value or continuous-value driving risk RSK when such a risk occurs. The server-side analysis unit 3d may then perform statistical processing based on the probe information to obtain a multi-value or continuous-value driving risk RSK(m,k).

[0075] <Modification 8> In Embodiment 1, the automatic driving mode was the automatic driving level, but since there are various forms of automatic driving levels, consistency may not be achieved between devices. Therefore, the automatic driving mode may be an automatic assistance type such as ACC (Adaptive cruise control), LKAS (Lane Keeping Assist System), and AEB (Autonomous Emergency Braking).

[0076] Furthermore, the autonomous driving mode may include at least one of the autonomous driving level and the type of automatic assistance, and may also include at least one of the on / off settings for ACC, LKAS, AEB, and their respective control parameters. For example, the ACC control parameters may include constant speed and on / off settings for lane change following. With such a configuration, appropriate driving assistance can be provided not only for each autonomous driving level but also for each type of automatic assistance.

[0077] <Modification 9> In Embodiment 1, the driving risk analysis device 3 was a server and separate from the probe vehicle-side device 1, but it is not limited to this. For example, the driving risk analysis device 3 may be provided on the probe vehicle as part of the probe vehicle-side device 1.

[0078] <Embodiment 2> Figure 7 is a block diagram showing the configuration of the driver assistance system according to this second embodiment. The driver assistance system in Figure 7 comprises a driver risk distribution device 5, which is a server located outside the vehicle, and a vehicle system 7 located inside the vehicle. The driver risk distribution device 5 and the vehicle system 7 are able to communicate with each other via a wide-area communication network 9.

[0079] <Driving Risk Distribution Device 5> The driving risk distribution device 5 in Figure 7 comprises a risk map information storage unit 5a, a distribution control unit 5b, and a server communication unit 5c. The risk map information storage unit 5a, the distribution control unit 5b, and the server communication unit 5c are the same as the risk map information storage unit 3e, the distribution control unit 3f, and the server communication unit 3a in Figure 1, respectively. As a result, the driving risk distribution device 5, like the driving risk analysis device 3 in Figure 1, distributes risk map information, which is associated with road map information and indicates areas where the frequency of driving risk occurrence is above a threshold for each predetermined first automatic driving mode, to an external party such as the vehicle system 7. Note that the driving risk distribution device 5 in Figure 7 may also comprise all the components of the driving risk analysis device 3 in Figure 1.

[0080] <Vehicle System 7> The vehicle system 7 in Figure 7 comprises a communication device 7a, a positioning device 7b, an automatic driving control device 7c, a driving support device 7d, and a notification device 7e. The vehicle may be a probe vehicle, and the vehicle system 7 in Figure 7 may comprise all the components of the probe vehicle side device 1 in Figure 1.

[0081] The communication device 7a receives risk map information distributed from the driving risk distribution device 5 via the wide-area communication network 9.

[0082] The positioning device 7b is the same as the positioning device 1e in Figure 1, and acquires vehicle positioning results using, for example, GNSS. The automatic driving control device 7c is the same as the automatic driving control device 1c in Figure 1, and when the automatic driving mode is executed, it performs control to have the vehicle perform at least a part of the driving operations performed by the vehicle driver.

[0083] The notification device 7e includes an audio output device and at least one of a display device such as a monitor or a HUD (Head Up Display), and notifies the vehicle driver by at least one of auditory notification and visual display.

[0084] The driver assistance device 7d performs notification control as driver assistance, which is a control that notifies the vehicle driver from the notification device 7e based on the risk map information from the communication device 7a, the positioning results from the positioning device 7b, and the automatic driving mode information indicating the automatic driving mode from the automatic driving control device 7c. In other words, the driver assistance device 7d provides driver assistance for the vehicle based on the risk map information. The configuration of the driver assistance device 7d will be described below.

[0085] The driver assistance device 7d comprises a risk map information acquisition unit 7d1, a location information acquisition unit 7d2, a vehicle control information acquisition unit 7d3, and a support control unit 7d4. The driver assistance device 7d may further include a communication device 7a, a positioning device 7b, an automatic driving control device 7c, and a notification device 7e.

[0086] The risk map information acquisition unit 7d1 acquires the risk map information received by the communication device 7a. In other words, the risk map information acquisition unit 7d1 acquires risk map information that shows the risk area for each of the first automatic driving modes, as described above.

[0087] The location information acquisition unit 7d2 generates and acquires location information indicating the vehicle's position based on the positioning results of the positioning device 7b, similar to the location information acquisition unit 1f in Figure 1.

[0088] The vehicle control information acquisition unit 7d3 acquires automatic driving mode information from the automatic driving control device 7c, which indicates the second automatic driving mode of the vehicle, in the same manner as the vehicle control information acquisition unit 1d in Figure 1.

[0089] The support control unit 7d4 determines, based on risk map information, location information, and autonomous driving mode information, that the conditions for executing driver assistance have been met, and then performs notification control to the driver as driver assistance for the vehicle. The following describes the conditions for executing driver assistance and examples of notification control to the driver.

[0090] <First Example> Figure 8 is a diagram illustrating the first example of the conditions for executing driver assistance and the control of notifications to the driver. The triangles in the figure indicate the position of the vehicle being assisted by the driver assistance device 7d. This vehicle is traveling on link LK-2 toward link LK-3, on a road that includes links LK-1, LK-2, LK-3, and LK-4 connected in series by nodes ND12, ND23, and ND34. Note that links LK-1 to LK-4 in Figure 8 correspond to links LK-1 to LK-4 in Figure 3.

[0091] The driving assistance execution conditions in the example shown in Figure 8 are that the vehicle's second autonomous driving mode is the same as the first autonomous driving mode in the risk map information, and that the distance between the vehicle and the risk area of ​​the first autonomous driving mode is less than or equal to a threshold. The threshold may be, for example, 100m, or it may be the distance the vehicle would travel if it were traveling at its current speed for 5 minutes.

[0092] In the example in Figure 8, the vehicle's current autonomous driving level (second autonomous driving mode) is autonomous driving level LV-2. In autonomous driving level LV-2 of the autonomous driving levels (first autonomous driving mode) in Figure 3, the link where RSK(m,k) is "1", i.e., the link with driving risk, is link LK-3.

[0093] In the example shown in Figure 8, the support control unit 7d4 determines that the above driving assistance execution conditions are met because the distance between the vehicle and link LK-3 is below the threshold. Therefore, the support control unit 7d4 notifies the driver that continuing to drive at the current autonomous driving level will cause the vehicle to enter a risk area, such as "You will enter a risk area in 5 minutes." Note that, as in the example shown in Figure 8, the vehicle's current autonomous driving level may be displayed, or link LK-3 may be displayed in a way that distinguishes it from other links. Alternatively, the autonomous driving level at which the link the vehicle is currently driving on enters a risk area may be displayed.

[0094] <Second Example> Figure 9 is a diagram illustrating the second example of the conditions for executing driver assistance and the control of notifications to the driver, and shows the same triangular symbols and links as in Figure 8.

[0095] In the example shown in Figure 9, the conditions for executing driver assistance are that the vehicle's second autonomous driving mode is the same as the first autonomous driving mode in the risk map information, and the vehicle is located within the risk area of ​​the first autonomous driving mode.

[0096] In the example in Figure 9, the vehicle's current autonomous driving level (second autonomous driving mode) is autonomous driving level LV-1. In autonomous driving level LV-1 of the autonomous driving levels (first autonomous driving mode) in Figure 3, the links where RSK(m,k) is "1", i.e., links with driving risk, are links LK-2 and LK-4.

[0097] In the example shown in Figure 9, since the vehicle is within link LK-2, the support control unit 7d4 determines that the above-mentioned driving assistance execution conditions are met. Therefore, the support control unit 7d4 notifies the driver that the vehicle is currently traveling in a risk area at the vehicle's current autonomous driving level, such as "The vehicle is currently traveling in a risk area." Note that, as in the example shown in Figure 9, the vehicle's current autonomous driving level may be displayed, or links LK-2 and LK-4 may be displayed in a way that distinguishes them from other links. Furthermore, the autonomous driving level at which the link the vehicle is currently traveling in becomes a risk area may be displayed.

[0098] <Operation> Figure 10 is a flowchart showing the operation of the driver assistance device 7d according to this second embodiment. In step S41, the vehicle control information acquisition unit 7d3 acquires automatic driving mode information from the automatic driving control device 7c. In step S42, the position information acquisition unit 7d2 acquires position information based on the positioning result of the positioning device 7b. In step S43, the risk map information acquisition unit 7d1 acquires risk map information. Note that the order of steps S41 to S43 may be changed as appropriate.

[0099] In step S44, the support control unit 7d4 determines whether the driving support execution conditions have been met based on the risk map information, location information, and automatic driving mode information. If it is determined that the driving support execution conditions have been met, the process proceeds to step S45; otherwise, the process proceeds to step S46.

[0100] In step S45, the support control unit 7d4 performs driving assistance. In step S46, the driving assistance device 7d determines whether the vehicle has finished traveling. If it is determined that the vehicle has finished traveling, the operation shown in Figure 10 ends; otherwise, the process proceeds to step S41.

[0101] <Summary of Embodiment 2> According to the driving assistance device 7d of Embodiment 2 described above, based on risk map information indicating risk areas for each first automatic driving mode, location information, and automatic driving mode information indicating the vehicle's second automatic driving mode, driving assistance is provided when the second automatic driving mode is the same as the first automatic driving mode, the distance between the vehicle and the risk area of ​​the first automatic driving mode is below a threshold, or the vehicle is located within the risk area of ​​the first automatic driving mode. With this configuration, appropriate driving assistance can be provided for each automatic driving mode of the vehicle, such as providing notifications only that are appropriate for the vehicle's automatic driving mode.

[0102] <Modification 1> As shown in Figure 11, an HDL7b3 may be provided that includes a high-precision map database 7b1 and a high-precision positioning device 7b2, similar to the HDL1e3 which includes the high-precision map database 1e1 and high-precision positioning device 1e2 in Figure 6.

[0103] Furthermore, similar to the modification 2 of Embodiment 1, the risk area in the risk map information and the vehicle's position in the position information based on the positioning results of the HDL 7b3 may be represented on a lane-by-lane basis. The support control unit 7d4 may then provide driving assistance based on the risk map information in which the risk area is represented on a lane-by-lane basis, the position information in which the vehicle's position is represented on a lane-by-lane basis, and the automatic driving mode information. With such a configuration, appropriate driving assistance can be provided for each lane.

[0104] <Modification 2> In a configuration where risk areas and location information are represented on a lane-by-lane basis, as in Modification 1 of Embodiment 2, when a vehicle is traveling on a road with multiple lanes on one side, the support control unit 7d4 may determine a recommended lane based on risk map information, location information, and autonomous driving mode information. The recommended lane is the lane with the lowest driving risk for the first autonomous driving mode, which is the same as the vehicle's second autonomous driving mode, among the multiple lanes on one side that the vehicle is traveling on.

[0105] For example, the support control unit 7d4 extracts the driving risk for each of the multiple lanes on one side from the risk map information, corresponding to the vehicle's second autonomous driving mode and the first autonomous driving mode. The support control unit 7d4 determines the lane with the lowest extracted driving risk as the recommended lane. Then, the support control unit 7d4 provides driving assistance by notifying the driver to ensure the vehicle travels in the recommended lane.

[0106] Figure 12 is a diagram illustrating the driver assistance system according to this modified example 2. In Figure 12, a vehicle is traveling along link LK-m in lane LA toward link LK-m+1 on a two-lane road in each direction, including lane LA and lane LB, with links LK-m, LK-m+1, LK-m+2, and LK-m+3 connected in series. Figure 12 also shows the driving risks for lane LA and lane LB in the first lane and second lane LB for the same first autonomous driving mode as the vehicle's second autonomous driving mode, as shown in the risk map information.

[0107] In the case of Figure 12, the support control unit 7d4 determines that for link LK-m, the first lane LA is the recommended lane because it has a lower driving risk than the second lane LB, and for link LK-m+1, the second lane LB is the recommended lane because it has a lower driving risk than the first lane LA. For link LK-m+2, the support control unit 7d4 determines that the second lane LB is the recommended lane because the driving risks of the first lane LA and the second lane LB are the same, so unnecessary lane changes are avoided. For link LK-m+3, the support control unit 7d4 determines that the first lane LA is the recommended lane because it has a lower driving risk than the second lane LB. As a result, the support control unit 7d4 provides driver assistance by notifying the driver in the order of links LK-m, LK-m+1, LK-m+2, and LK-m+3, so that the vehicle travels in the first lane LA, second lane LB, second lane LB, and first lane LA.

[0108] In the above explanation, the support control unit 7d4 performed driver assistance by notifying the driver to ensure the vehicle traveled in the recommended lane, but this is not the only way it can perform this. The support control unit 7d4 may also perform driver assistance by controlling the automatic driving control device 7c to ensure the vehicle travels in the recommended lane along the arrows in Figure 12. Automatic driving control may be enabled and disabled manually by the driver, or it may be enabled only after an announcement is made to the driver and permission is obtained from the driver.

[0109] According to the modified example 2 described above, the vehicle can travel in a lane where the driving risk for the vehicle's autonomous driving mode is as low as possible.

[0110] <Modification 3> In Modification 2 of Embodiment 2, the support control unit 7d4 changed the vehicle's driving lane to reduce driving risk, but the level of automated driving may be changed to reduce driving risk.

[0111] For example, the support control unit 7d4 extracts candidate driving risks and current driving risks from the risk map information based on the risk map information, location information, and autonomous driving mode information. The candidate driving risk is the driving risk in relation to the vehicle's position and the candidate autonomous driving mode, which is a first autonomous driving mode different from the vehicle's second autonomous driving mode. The current driving risk is the driving risk in relation to the vehicle's position and the first autonomous driving mode, which is the same as the vehicle's second autonomous driving mode.

[0112] The support control unit 7d4 then determines whether the driving risk of the extracted candidate is lower than the current driving risk for the first autonomous driving mode, which is the same as the vehicle's second autonomous driving mode. If the support control unit 7d4 determines that the driving risk of the candidate is lower than the current driving risk, it performs at least one of the following as driver assistance: notifying the driver of the vehicle and controlling the vehicle's autonomous driving mode, so that the vehicle operates in the candidate autonomous driving mode. With this configuration, the vehicle can use the autonomous driving mode with the lowest possible driving risk.

[0113] <Modification 4> Similar to Modification 3 of Embodiment 1, the risk map information may indicate risk areas for each autonomous driving mode and for each physical risk (risk type). The support control unit 7d4 may then notify and control the physical risk corresponding to the autonomous driving level and position of the vehicle based on the risk map information, location information, autonomous driving mode information, and the physical risk of the vehicle, or it may perform autonomous driving control appropriate to the physical risk. With such a configuration, appropriate driving assistance can be provided for each autonomous driving mode and for each physical risk.

[0114] <Modification 5> Similar to Modification 4 of Embodiment 1, the risk map information may show the risk area for each autonomous driving mode and for each predetermined second driver state risk (risk type).

[0115] Furthermore, as shown in Figure 11, the driver assistance device 7d may be further equipped with a driver status acquisition unit 7d5 that acquires a first driver status risk from the vehicle's driver. The driver status acquisition unit 7d5 may acquire the first driver status risk from a DMS outside the driver assistance device 7d, or it may include a DMS that detects the first driver status risk.

[0116] Furthermore, the support control unit 7d4 may determine whether or not to perform notification control to the vehicle driver based on the first driver state acquired by the driver state acquisition unit 7d5, if the distance between the vehicle and the risk area of ​​the second driver state risk in the risk map information is below a threshold. The support control unit 7d4 may also set the criteria for determining whether to perform notification control lower when the first driver state risk is the same as the second driver state risk than when the first driver state risk is different from the second driver state risk. With this configuration, if the first driver state acquired by the driver state acquisition unit 7d5 is the same as the second driver state risk in the risk map information, it is easier to provide notification to the driver, such as early notification to the driver.

[0117] <Modification 6> Similar to Modification 5 of Embodiment 1, a risk area where both physical risk and driver condition risk occur simultaneously may be defined as a special attention area in the risk map information. Furthermore, the support control unit 7d4 may set a lower criterion for determining whether to perform notification control when the distance between the vehicle and the special attention area is below a threshold than the criterion when the distance between the vehicle and a risk area other than the special attention area is below a threshold. With such a configuration, if a risk area is a special attention area, it becomes easier to notify the driver, for example, by early notification to the driver.

[0118] <Modification 7> Similar to Modification 6 of Embodiment 1, the risk map information may indicate risk areas for each autonomous driving mode and attribute. The support control unit 7d4 may then provide driving assistance based on the risk map information, location information, autonomous driving mode information, and vehicle attributes. With this configuration, appropriate driving assistance can be provided for each autonomous driving mode and attribute.

[0119] <Modification 8> Similar to Modification 7 of Embodiment 1, the driving risk RSK(m,k) in the risk map information may be represented by three or more values. For example, the support control unit 7d4 may provide driving assistance when the driving risk RSK(m,k) is equal to or greater than the threshold RSKth. The threshold RSKth is, for example, 0.5. The threshold RSKth may be adjusted based on at least one of the driver's physical condition on the day and the driver's skill level. For example, if the driver's condition is unsuitable for driving, the support control unit 7d4 may reduce the threshold RSKth.

[0120] <Modification 9> Similar to Modification 8 of Embodiment 1, the automatic driving mode may include automatic assist types. With this configuration, appropriate driving assistance can be provided for each automatic assist type.

[0121] <Modification 10> The driving risk analysis device 3 in Figure 1 may be installed in the vehicle as part of the vehicle system 7 in Figure 7. With this configuration, the vehicle can independently analyze driving risks, generate risk map information, and provide driving support based on the risk map information, thus enabling a more compact system.

[0122] <Other Modifications> The probe information acquisition unit 3b, analysis unit 3d, and distribution control unit 3f of the driving risk analysis device 3 shown in Figure 1 above will be referred to below as "probe information acquisition unit 3b, etc." The probe information acquisition unit 3b, etc. is realized by the processing circuit 81 shown in Figure 13. That is, the processing circuit 81 includes a probe information acquisition unit 3b that acquires probe information from a probe vehicle, an analysis unit 3d that generates risk map information based on the probe information, and a distribution control unit 3f that distributes the risk map information to the outside. Dedicated hardware may be applied to the processing circuit 81, or a processor that executes a program stored in memory may be applied. Examples of processors include central processing units, processing units, arithmetic units, microprocessors, microcomputers, and DSPs (Digital Signal Processors).

[0123] If the processing circuit 81 is dedicated hardware, it may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Each function of the probe information acquisition unit 3b, etc., may be implemented by a circuit with distributed processing circuits, or the functions of each part may be implemented together by a single processing circuit.

[0124] When the processing circuit 81 is a processor, functions such as the probe information acquisition unit 3b are realized in combination with software, etc. The software, etc., may include, for example, software, firmware, or both. The software, etc., is written as a program and stored in memory. As shown in Figure 14, the processor 82 applied to the processing circuit 81 realizes the functions of each part by reading and executing the program stored in memory 83. In other words, the driving risk analysis device 3 includes memory 83 for storing a program that, when executed by the processing circuit 81, will ultimately execute the steps of acquiring probe information from the probe vehicle, generating risk map information based on the probe information, and distributing the risk map information externally. In other words, this program can be said to cause the computer to execute the procedures and methods of the probe information acquisition unit 3b, etc. Here, memory 83 may be, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), HDD (Hard Disk Drive), magnetic disk, flexible disk, optical disk, compact disk, minidisc, DVD (Digital Versatile Disc), their drive devices, or any storage medium used in the future.

[0125] The above describes a configuration in which each function of the probe information acquisition unit 3b, etc., is realized by either hardware or software. However, this is not the only configuration, and some parts of the probe information acquisition unit 3b, etc., may be realized by dedicated hardware, and other parts by software, etc. For example, the probe information acquisition unit 3b can be realized by a processing circuit 81 as dedicated hardware, and the other functions can be realized by a processing circuit 81 as a processor 82 reading and executing a program stored in memory 83.

[0126] As described above, the processing circuit 81 can realize each of the above functions by hardware, software, or a combination thereof. The driving risk analysis device 3 described above can also be applied to a driving risk analysis system constructed as a system by appropriately combining a vehicle device, a communication terminal, the functions of an application installed on at least one of the vehicle device and the communication terminal, and a server. The communication terminal includes, for example, mobile phones, smartphones, and tablets. Each function or component of the driving risk analysis device described above may be distributed among the devices that make up the system, or may be concentrated in one of the devices. In addition, although the components of the driving risk analysis device 3 have been described above, the same applies to the components of the driving support device 7d.

[0127] In this disclosure in English, the articles 'a' and 'an' mean one or more. Therefore, 'a', 'an', 'one or more', and 'at least one' can be used interchangeably.

[0128] Furthermore, it is possible to freely combine each embodiment and each variation, and to modify or omit each embodiment and each variation as appropriate.

[0129] The above explanation is illustrative and not limiting in all respects. It should be understood that countless variations not illustrated are conceivable.

[0130] 3 Driving risk analysis device, 3b Probe information acquisition unit, 3d Analysis unit, 3f Distribution control unit, 7d Driving support device, 7d1 Risk map information acquisition unit, 7d2 Position information acquisition unit, 7d3 Vehicle control information acquisition unit, 7d4 Support control unit, 7d5 Driver status acquisition unit.

Claims

1. A driving risk analysis device comprising: a probe information acquisition unit that acquires probe information from a probe vehicle, including location information indicating the location of the probe vehicle when a driving risk occurs in the probe vehicle, and automatic driving mode information indicating the automatic driving mode of the probe vehicle when the driving risk occurs; an analysis unit that generates risk map information based on the probe information, associated with road map information, and indicating areas where the frequency of occurrence of the driving risk is above a threshold for each automatic driving mode; and a distribution control unit that distributes the risk map information to an external party.

2. A driving risk analysis device according to claim 1, wherein the position of the probe vehicle in the position information and the area in the risk map information generated by the analysis unit are represented on a lane-by-lane basis.

3. An operating risk analysis device according to claim 1, wherein the probe information further includes a risk type indicating the type of operating risk, and the risk map information generated by the analysis unit indicates the area for each automatic driving mode and each risk type.

4. A driving risk analysis device according to claim 3, wherein the risk type includes physical risks relating to the probe vehicle, and the physical risk includes at least one of the risks of contact between the probe vehicle and an object other than the probe vehicle, and the risk of the probe vehicle deviating from its lane.

5. A driving risk analysis device according to claim 3, wherein the risk type includes driver state risk relating to the driver state of the probe vehicle, and the driver state risk includes at least one of the driver distraction risk and drowsiness risk of the driver of the probe vehicle.

6. A driving risk analysis device according to claim 3, wherein the risk type includes a physical risk relating to the probe vehicle and a driver state risk relating to the driver state of the probe vehicle, and the area in which the physical risk and the driver state risk occur simultaneously is defined as a special attention area in the risk map information generated by the analysis unit.

7. Driving risk analysis device according to claim 1, wherein the probe information further includes attribute information indicating as an attribute at least one of the following: the time, day of the week, weather, and whether or not the day on which the driving risk occurred is a public holiday, and the risk map information generated by the analysis unit indicates the area for each automatic driving mode and each attribute.

8. A driving risk analysis device according to claim 1, wherein the automatic driving mode includes at least one of an automatic driving level and an automatic assist type.

9. A driving assistance device for providing driving assistance to a vehicle, comprising: a risk map information acquisition unit that acquires risk map information associated with road map information and indicating areas where the frequency of occurrence of driving risks is above a threshold for each predetermined first automatic driving mode; a location information acquisition unit that acquires location information indicating the location of the vehicle; a vehicle control information acquisition unit that acquires automatic driving mode information indicating a second automatic driving mode of the vehicle; and a support control unit that provides driving assistance based on the risk map information, the location information, and the automatic driving mode information, when the second automatic driving mode is the same as the first automatic driving mode, the distance between the vehicle and the area of ​​the first automatic driving mode is below a threshold, or the vehicle is located within the area of ​​the first automatic driving mode.

10. A driving assistance device according to claim 9, wherein the area in the risk map information and the position of the vehicle in the position information are represented on a lane-by-lane basis.

11. A driving assistance device according to claim 10, wherein the support control unit, based on the risk map information, the location information, and the automatic driving mode information, performs at least one of the following as driving assistance: notifying the driver of the vehicle and controlling the automatic driving of the vehicle, so that when the vehicle is traveling on a road with multiple lanes on one side, the vehicle travels in the lane with the lowest driving risk for the first automatic driving mode which is the same as the second automatic driving mode.

12. A driving assistance device according to claim 9, wherein the support control unit performs, as the driving assistance, at least one of the following: notifying the driver of the vehicle and controlling the vehicle's automatic driving, when the driving risk for a candidate automatic driving mode which is a first automatic driving mode different from the second automatic driving mode and the position of the vehicle is lower than the driving risk for a first automatic driving mode which is the same as the second automatic driving mode and the position of the vehicle, the vehicle performs the candidate automatic driving mode.

13. A driving assistance device according to claim 9, further comprising a driver state acquisition unit that acquires a first driver state risk from the driver of the vehicle, wherein the risk map information indicates the area for each first automatic driving mode and for each risk type indicating the type of driving risk, the risk type includes a predetermined second driver state risk, and the support control unit determines whether or not to perform notification control of the vehicle to the driver based on the first driver state risk when the distance between the vehicle and the area of ​​the second driver state risk is less than or equal to a threshold, and the criteria for the determination of whether or not to perform notification control is set lower when the first driver state risk is the same as the second driver state risk than when the first driver state risk is different from the second driver state risk.

14. A driving assistance device according to claim 13, wherein the risk type further includes predetermined physical risks, the area in which the physical risk and the second driver state risk occur simultaneously is defined as a special attention area in the risk map information, and the support control unit makes the criterion for the determination of performing the notification control lower when the distance between the vehicle and the special attention area is less than or equal to a threshold, than when the distance between the vehicle and the area other than the special attention area is less than or equal to a threshold.

15. A driving risk analysis method comprising: a probe information acquisition unit acquires probe information from the probe vehicle, including location information indicating the location of the probe vehicle when a driving risk occurs in the probe vehicle, and automatic driving mode information indicating the automatic driving mode of the probe vehicle when the driving risk occurs; an analysis unit generates risk map information based on the probe information, associated with road map information, and indicating areas where the frequency of occurrence of the driving risk is above a threshold for each automatic driving mode; and a distribution control unit distributes the risk map information externally.

16. A driving support system comprising a driving risk analysis device and a driving support device that communicates with the driving risk analysis device, wherein the driving risk analysis device includes a probe information acquisition unit that acquires probe information from the probe vehicle, which includes location information indicating the position of the probe vehicle when a driving risk occurs in the probe vehicle and automatic driving mode information indicating the automatic driving mode of the probe vehicle when the driving risk occurs; an analysis unit that generates risk map information based on the probe information, which is associated with road map information and indicates areas where the frequency of occurrence of the driving risk is above a threshold for each automatic driving mode; and a distribution control unit that distributes the risk map information to an external party, wherein the driving support device provides driving support for the vehicle based on the risk map information.

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