Information collection and analysis device and information collection and analysis system

Abstract

The purpose of the present disclosure is to provide a technology for analyzing the causes of anomalous events at a vehicle in detail. An information collection and analysis device (201) comprises: an information collection unit (21) that, when an anomalous event has occurred at a vehicle (100), collects probe information that associates information about the anomalous event and information about a driving mode from the vehicle (100); and an analysis unit (23) that identifies a cause of the anomalous event as a cause classification on the basis of the driving mode and creates caution information that associates the anomalous event and the cause classification. The driving mode includes a first driving mode in which a driver performs steering wheel operation of the vehicle and an automatic driving control device (53) does not perform steering wheel operation, a second driving mode in which the driver normally performs steering wheel operation but the automatic driving control device (53) intervenes in steering wheel operation to execute LKAS when a risk of lane departure has been detected, and a third driving mode in which the automatic driving control device (53) always controls steering wheel operation of the vehicle (100).

Description

[Technical Field]

[0001] The present disclosure relates to a technique for collecting and analyzing information on a specific event that occurs in a vehicle, including lane departure or operation of an LKAS. [Background technology]

[0002] Patent document 1 describes a system that collects information on uncontrollable locations where the LKAS (Lane Keeping Assist System) does not function, and based on the information on the uncontrollable locations, determines locations where the LKAS frequently does not function as anomalous locations and presents them to the driver. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-126888 Summary of the Invention [Problem to be solved by the invention]

[0004] The system of Patent Document 1 determines whether or not there is a singular point simply based on the operating state of the LKAS, and therefore is unable to perform detailed analysis of the causes of lane departures and other such issues at singular points.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a technology for performing a detailed analysis of the cause of a peculiar event occurring in a vehicle. [Means for solving the problem]

[0006] The information collection and analysis device disclosed herein includes an information collection unit that collects probe information from a vehicle that is capable of automatic driving control by an automatic driving control device, when a unique event including lane departure or LKAS operation occurs, linked to information on the unique event and information on the driving mode that indicates the degree of automatic driving control at the time the unique event occurs, and an analysis unit that identifies the cause of the unique event as a cause classification based on the driving mode and creates attention-requiring information that links the unique event to the cause classification.The driving modes include a first driving mode in which the driver operates the steering wheel of the vehicle and the automatic driving control device does not perform steering operations, a second driving mode in which the driver normally operates the steering wheel and the automatic driving control device intervenes in steering operations and executes LKAS if it detects a risk of lane departure, and a third driving mode in which the automatic driving control device always controls the steering operation of the vehicle. [Effects of the Invention]

[0007] The information collection and analysis device of the present disclosure can identify the cause of an unusual event in detail based on the operation mode. Objects, features, aspects, and advantages of the present disclosure will become more apparent from the following detailed description and the accompanying drawings. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of an information collection and analysis system according to a first embodiment. [Figure 2] 4 is a flowchart showing an operation of the probe information generating device. [Figure 3] 10 is a flowchart showing an information collection process performed by the information collection and analysis device. [Figure 4] FIG. 3 is a diagram showing probe information according to the first embodiment. [Figure 5] 10 is a flowchart showing an environment analysis process performed by the information collection and analysis device. [Figure 6] FIG. 10 is a diagram illustrating the relationship between a singular point and a general singular point. [Figure 7] FIG. 10 is a diagram showing the relationship between environmental cause events and environmental cause classifications. [Figure 8]It is a diagram showing attention-required information stored in the cause memory unit. [Figure 9] It is a block diagram showing the configuration of the information collection and analysis system according to Embodiment 2. [Figure 10] It is a flowchart showing individual analysis processing by the information collection and analysis device. [Figure 11] It is a diagram showing the relationship between individual cause events and individual cause classifications. [Figure 12] It is a block diagram showing the configuration of the information collection and analysis system according to Embodiment 3. [Figure 13] It is a block diagram showing the configuration of the information collection and analysis system according to Embodiment 4. [Figure 14] It is a diagram showing an example of display of cause information in a vehicle. [Figure 15] It is a diagram showing the hardware configuration of the information collection and analysis device or the probe information generation device. [Figure 16] It is a diagram showing the hardware configuration of the information collection and analysis device or the probe information generation device.

Modes for Carrying Out the Invention

[0009] <A. Embodiment 1> <A-1. Configuration> FIG. 1 is a block diagram showing the configuration of an information collection and analysis system 1001 according to Embodiment 1. The information collection and analysis system 1001 includes a plurality of vehicles 100, an information collection and analysis device 201, and a wide-area communication network 301 that connects each vehicle 100 and the information collection and analysis device 201. Although only one vehicle 100 is shown in FIG. 1, the information collection and analysis system 1001 includes a plurality of vehicles 100.

[0010] The vehicle 100 includes a probe information generation device 101, a positioning device 51, a peripheral detection device 52, and an automatic driving control device 53. When a specific event such as lane departure or LKAS operation occurs in the vehicle 100, the probe information generation device 101 creates probe information and transmits it to the information collection and analysis device 201.

[0011] The positioning device 51 measures the position of the vehicle 100. The positioning device 51 may be configured with a GNSS receiver, or may have a mechanism for correcting the position measured by the GNSS receiver using a vehicle sensor or map matching.

[0012] The periphery detection device 52 detects lane departure by image processing, but the method for detecting lane departure is not limited to image processing, as long as the periphery detection device 52 can detect lane departure.

[0013] The automatic driving control device 53 controls the automatic driving of the vehicle. The automatic driving control device 53 has at least an LKAS function.

[0014] The probe information generating device 101 includes a position information acquiring unit 11, a lane departure detecting unit 12, a control information acquiring unit 13, a probe information generating unit 14, and a probe information transmitting unit 15.

[0015] The position information acquisition unit 11 acquires the vehicle's position information from the positioning device 51 and outputs it to the probe information generation unit 14.

[0016] The lane departure detection unit 12 acquires information on whether lane departure has occurred from the surroundings detection device 52 and outputs the information to the probe information generation unit 14.

[0017] The control information acquisition unit 13 acquires, from the automatic driving control device 53, control information indicating the content of the automatic driving control by the automatic driving control device 53 and driving mode information indicating the driving mode of the vehicle 100. The control information includes information on whether the LKAS has functioned. In other words, the control information acquisition unit 13 functions as an information acquisition unit that acquires the driving mode and the operating status of the LKAS. The driving mode indicates the degree of automatic driving control by the automatic driving control device 53, and there are the following three driving modes.

[0018] The first driving mode is a mode in which the driver operates the steering wheel, and the automatic driving control device 53 does not intervene in the steering operation. The second driving mode is a mode in which the driver operates the steering wheel, and if the automatic driving control device 53 determines that the vehicle 100 is at risk of deviating from its lane, it intervenes in the steering operation and executes the LKAS. The third driving mode is a mode in which the driver does not operate the steering wheel, and the automatic driving control device 53 performs steering control to keep the vehicle within the lane. Note that at least automated driving level 3 or higher as defined by the Society of Automotive Engineers (SAE) belongs to the third driving mode.

[0019] The probe information generation unit 14 recognizes that the vehicle 100 has deviated from its lane based on the information from the lane departure detection unit 12. The probe information generation unit 14 also recognizes that the LKAS has been activated in the vehicle 100 based on the control information acquired from the control information acquisition unit 13. In this specification, the lane departure of the vehicle 100 or the activation of the LKAS in the vehicle 100 is referred to as an unusual event. When the probe information generation unit 14 detects that an unusual event has occurred in the vehicle 100, it generates probe information including location information of the unusual point where the unusual event occurred and transmits the generated probe information to the information collection and analysis device 201.

[0020] Next, we will explain the configuration of the information collection and analysis device 201. The information collection and analysis device 201 is configured with a server or the like external to the vehicle 100. The information collection and analysis device 201 is configured with an information collection unit 21, a collected information storage unit 22, an analysis unit 23, and a cause storage unit 24.

[0021] The information collection unit 21 collects probe information from a plurality of vehicles 100 and stores the information in the collected information storage unit 22 .

[0022] The analysis unit 23 analyzes the probe information stored in the collected information storage unit 22 at any timing and classifies the cause of the peculiar event based on the peculiar event and the operating mode at the time the peculiar event occurred. The causes of the peculiar events classified by the analysis unit 23 are called cause classifications. The analysis unit 23 links the peculiar events with their cause classifications to create caution information.

[0023] In the present embodiment, the analysis unit 23 classifies the cause of a driving environment-caused event, which is a specific event caused by the driving environment, as an environmental cause classification. The driving environment-caused event is not caused by a cause specific to the vehicle 100 or its driver, etc., but is caused by the driving environment such as the road shape, and can occur in the same manner in other vehicles 100 under the same driving environment. The analysis unit 23 associates the driving environment-caused event with the environmental cause classification, and creates environmental attention information, which is attention information regarding the driving environment-caused event.

[0024] The cause storage unit 24 includes an environmental cause storage unit 25. The environmental cause storage unit 25 stores the environmental attention information created by the analysis unit 23.

[0025] <A-2. Operation> FIG. 2 is a flowchart showing the operation of the probe information generation device 101. Hereinafter, the operation of the probe information generation device 101 will be described along the flowchart of FIG. 2.

[0026] First, in step S101, the probe information generation unit 14 acquires a vehicle ID from an in-vehicle LAN (not shown in FIG. 1). Here, the vehicle ID is an example of an individual ID for uniquely identifying the vehicle 100 or the driver of the vehicle 100. Instead of the vehicle ID, a personal ID unique to the driver may be used.

[0027] After step S101, in step S102, the position information acquisition unit 11 acquires the position information of the vehicle 100 from the positioning device 51. After step S102, in step S103, the control information acquisition unit 13 acquires driving mode information indicating the driving mode being executed from the automatic driving control device 53.

[0028] After step S103, in step S104, the probe information generation unit 14 determines whether or not a unique event including lane departure or LKAS activation of the vehicle 100 has occurred. The occurrence of lane departure is determined by the lane departure detection unit 12 based on information from the periphery detection device 52 that performs white line recognition, for example. The LKAS activation state is determined by the control information acquisition unit 13 based on control information acquired from the automatic driving control device 53.

[0029] The singular events that can occur in the vehicle 100 are divided into three singular events A, B, and C. Singular event A is an event in which the LKAS does not operate and lane departure occurs. The singular point where singular event A occurs is the lane departure location. Singular event A can occur in the first driving mode, the second driving mode, and the third driving mode. Singular event B is an event in which the LKAS operates but lane departure occurs. The singular point where singular event B occurs may be the lane departure location or the LKAS operation location. Singular event A can occur in the second driving mode and the third driving mode. Singular event C is an event in which the LKAS operates but lane departure does not occur. The singular point where singular event C occurs is the LKAS operation location. Singular event C can occur in the second driving mode. In the third driving mode, the vehicle 100 is steered and controlled by the automatic driving control device 53 to travel near the center of the lane, and therefore the LKAS does not operate.

[0030] If a singular event has occurred in step S104, the processing of the probe information generation device 101 proceeds to step S105. In step S105, the probe information generation unit 14 generates probe information Prove(P, EV, V, M) by associating the position P of the singular point where the singular event occurred, the singular event EV, the vehicle ID V, and the driving mode M. Then, the probe information transmission unit 15 transmits the probe information to the information collection and analysis device 201. Note that the probe information may include the time T at which the singular event occurred and additional information INFO. The additional information INFO includes information such as driving environment information, weather information, vehicle speed / steering, and brake / accelerator operation.

[0031] After step S105, or if no unusual event has occurred in step S104, the processing of the probe information generation unit 14 proceeds to step S106. In step S106, the probe information generation unit 14 determines whether or not the vehicle 100 has finished traveling. If the vehicle 100 has not finished traveling in step S106, the processing of the probe information generation device 101 returns to step S102. If the vehicle 100 has finished traveling in step S106, the processing of the probe information generation device 101 ends.

[0032] Although the probe information generation unit 14 transmits the probe information in step S105 in the above description, the transmission timing is not limited to this. For example, the probe information generation unit 14 may transmit all of the probe information that has been created up to that point at the end of the travel of the vehicle 100.

[0033] Next, the operation of the information collection and analysis device 201 will be described. The information collection and analysis device 201 performs multiple tasks, including information collection processing and cause analysis processing. However, the processing program for executing each function of the information collection and analysis device 201 may be configured as a single task, or may be configured as three or more tasks. Furthermore, the processing program may have any configuration, such as multi-process or multi-thread.

[0034] 3 is a flowchart of the information collection process by the information collection and analysis device 201. The information collection process by the information collection and analysis device 201 will be described below with reference to FIG. 3. First, in step S201, the information collection unit 21 determines whether or not probe information has been received from the vehicle 100, and repeats the process of step S201 until probe information is received. When the information collection unit 21 receives probe information from the vehicle 100 in step S201, it stores the probe information in the collection information storage unit 22 in step S202. Thereafter, the process of the information collection unit 21 returns to step S201.

[0035] FIG. 4 illustrates an example of N pieces of probe information stored in the collected information storage unit 22. An information ID for identifying the probe information is assigned to each piece of probe information. For example, a number in chronological order in which the probe information is collected is assigned to this information ID. The probe information Probe(n) with information ID=n includes at least the position P(n) of the singular point, the vehicle ID V(n), the singular event EV(n), and the driving mode M(n). In the example of FIG. 4, the probe information Probe(n) includes the time T(n) and additional information INFO(n), which will be described later in a modified example.

[0036] Fig. 5 is a flowchart of the environmental cause analysis process by the information collection and analysis device 201. The environmental cause analysis process by the information collection and analysis device 201 will be described below with reference to Fig. 5. First, in step S301, the analysis unit 23 determines whether or not it is now the timing to analyze, and if it determines that it is now the timing to analyze, it proceeds to the process of step S302, and if it determines that it is not the timing to analyze, it repeats the process of step S301.

[0037] Here, the analysis timing may be a fixed cycle such as once a day or once a week. Alternatively, the analysis timing may be when the information collecting unit 21 acquires special probe information, such as information that the LKAS has not been activated and lane departure has occurred. Alternatively, the analysis timing may be when an analysis instruction is acquired from a server administrator (not shown).

[0038] In step S302, the analysis unit 23 loads probe information such as that shown in FIG. 4 from the collected information storage unit 22 and extracts general peculiar points Q(m) from the probe information acquired from multiple vehicles 100. Specifically, the analysis unit 23 defines a point where peculiar points frequently occur in multiple vehicles as a general peculiar point Q(m), and counts the number of general peculiar points Q(m), MD. Here, a "point where peculiar points frequently occur" is, for example, a point where a peculiar event occurs M min times (e.g., four times) or more within a certain period (e.g., one day) and the occurrence rate is 100 ppm or more. For example, the occurrence rate of a peculiar event at point A is calculated by dividing the number of vehicles 100 where a peculiar event occurred at point A during a certain period TA by the number of vehicles 100 that traveled through point A during period TA. Here, the analysis unit 23 can acquire the number of vehicles 100 that have traveled through the point A during the period TA from the Vehicle Information and Communication System (VICS, registered trademark) or the like.

[0039] When defining the general singular point Q(m), the analysis unit 23 considers multiple singular points located in close proximity to each other as the same point. For example, the analysis unit 23 considers singular points P(m1), P(m2), ... P(mKm) that satisfy the conditions |P(m1) - P(mkm)| ≦ THdis and km = 2 or more and km or less to be the same point. Here, THdis is, for example, 10 m. Note that if the positioning accuracy of the positioning device 51 is high, THdis may be shorter, for example, 5 m. Alternatively, the road including the singular points P(m1), P(m2), ... P(mKm) may be divided into sublinks of 10 m each, and if P(m1), P(m2), ... P(mKm) exist within the same sublink, P(m1), P(m2), ... P(mKm) may be determined to be the same point.

[0040] Next, in step S303, the analysis unit 23 determines whether or not there is a general singular point Q(m). If there is no general singular point Q(m) in step S303, the processing of the analysis unit 23 returns to step S301, and if there is a general singular point Q(m), the processing of the analysis unit 23 proceeds to step S304.

[0041] FIG. 6 is a diagram showing the singular point P(n) and the general singular point Q(m) on a map. There are eleven singular points P(1), P(2), P(3), P(4), P(5), P(6), P(7), P(8), P(9), P(10), and P(11) on the travel route 61 of the vehicle 100. According to the conditions described above, the singular points P(3), P(5), P(7), P(10), and P(11) are determined to be the same point and correspond to the general singular point Q(1). Furthermore, the singular points P(4), P(6), P(8), and P(9) are determined to be the same point and correspond to the general singular point Q(2).

[0042] The position of the general singular point Q is determined using the positions of multiple singular points P corresponding to the general singular point Q. For example, the position of the general singular point Q may be the average value of the positions of the corresponding multiple singular points P. In the example of FIG. 6, the position of the singular point P with the smallest ID among the corresponding multiple singular points P is the position of the general singular point. In other words, the position of the singular point P(3) is the position of the general singular point Q(1), and the position of the singular point P(4) is the position of the general singular point Q(2).

[0043] In step S304, the analysis unit 23 sets 1 to the counter m of the general singular point Q(m) for which environmental cause classification is performed.

[0044] Next, in step S305, the analysis unit 23 performs environmental cause classification of the general singular point Q(m) based on the singular event and operation mode of the singular point P(mk) corresponding to the general singular point Q(m).

[0045] FIG. 7 is a diagram showing an example of the criteria for classifying environmental causes. A pattern in which peculiar event A (lane departure occurs and LKAS does not operate) occurs in the first driving mode (fully manual driving) is designated as pattern A1. Similarly, a pattern in which peculiar event A occurs in the second driving mode is designated as pattern A2, and a pattern in which peculiar event A occurs in the third driving mode is designated as pattern A3. Furthermore, a pattern in which peculiar event B (LKAS is activated (semi-activated) but lane departure occurs) occurs in the second driving mode is designated as pattern B2. A pattern in which peculiar event B occurs in the third driving mode is designated as pattern B3. Furthermore, a pattern in which peculiar event C (LKAS is activated and lane departure is avoided) occurs in the second driving mode is designated as pattern C2.

[0046] For example, if lane departure occurs at a certain general singular point Q(m) in the first driving mode (fully manual driving) and the LKAS operates normally in the second driving mode, i.e., if pattern A1 and pattern C2 occur, the general singular point Q(m) is classified as environmental cause classification R1: "a point where driving attention decreases."

[0047] Furthermore, at a certain general singular point Q(m), if lane departure occurs in the first driving mode (fully manual driving) and the LKAS is semi-activated in the second driving mode, i.e., if pattern A1 or pattern B2 occurs, the analysis unit 23 determines that the LKAS was unable to keep up with the driver's steering operation and caused the lane departure, and classifies the general singular point Q(m) as a "road shape caution point" in environmental cause classification R2, which is prone to lane departure. Note that semi-activated LKAS refers to a case where the LKAS was activated but did not function, i.e., was unable to keep the vehicle within the lane.

[0048] Furthermore, if lane departure occurs at a certain general singular point Q(m) in the first driving mode (fully manual driving) and the LKAS is semi-activated in the third driving mode, i.e., if pattern A1 or pattern B3 occurs, the analysis unit 23 classifies the general singular point Q(m) as environmental cause classification R3: "LKAS non-operating point, possible road surface deterioration." A general singular point Q(m) classified as environmental cause classification R3 is a point where lane departure occurred despite the third driving mode, in which lane departure is less likely to occur than in the second driving mode because the steering is performed by the vehicle, and therefore a decrease in road surface μ due to poor white markings or road surface deterioration is expected.

[0049] Furthermore, if the LKAS does not operate and a lane departure occurs at a general singular point Q(m) in the second or third driving mode, i.e., if pattern A2 or A3 occurs, the general singular point Q(m) is classified as an "LKAS non-operating point" under environmental cause category R4. A general singular point Q(m) classified as environmental cause category R4 is likely to have a defective white line.

[0050] For example, suppose that pattern A1 occurred twice and pattern C2 occurred twice at general singular point Q(2), which includes singular points P(4), P(6), P(8), and P(9). In this case, the analysis unit 23 determines the cause CAUSE of the singular event occurring at general singular point Q(2) to be environmentally caused event R according to the table in Figure 7, and further analyzes the classification CLASS of environmentally caused event R to be environmentally caused classification R1 (point of reduced driving attention).

[0051] For example, suppose that pattern A1 occurred twice, pattern A2 occurred twice, and pattern B3 occurred once at general singular point Q(1), which includes singular points P(3), P(5), P(7), P(10), and P(11). In this case, the analysis unit 23 determines the CAUSE of the singular event at general singular point Q(1) as environmental cause event R according to the table in FIG. 7, and further determines the classification CLASS of environmental cause event R as environmental cause classification R3 (LKAS non-operating point, possible road surface deterioration) or environmental cause classification R4 (LKAS non-operating point). Here, the analysis unit 23 may adopt the environmental cause classification R3 or R4 that has the most occurrences of the corresponding pattern, or may adopt both. Furthermore, if the number of occurrences of the corresponding patterns is the same, the analysis unit 23 may prioritize the environmental cause classification that requires more attention. The order of environmental cause classifications that require attention is R4, R3, R2, and R1.

[0052] Next, in step S306, the analysis unit 23 creates environmental caution information by linking the environmental cause event, the environmental cause classification, and the location information of the general singular point Q(m), and stores the environmental caution information in the environmental cause storage unit 25.

[0053] Thereafter, in step S307, the analysis unit 23 increments by one the counter m of the general singular point Q(m) for which environmental cause classification is performed.

[0054] Furthermore, in step S308, the analysis unit 23 determines whether the counter m of the general singular points Q(m) for which environmental cause classification is to be performed is equal to or less than the number MD of general singular points Q. If m≦MD, there are general singular points Q(m) for which environmental cause classification has not yet been performed, so the processing by the analysis unit 23 returns to step S305. If m>MD, environmental cause classification has been completed for all general singular points Q(m), so the processing by the analysis unit 23 returns to step S301.

[0055] FIG. 8 shows the environmental caution information stored in the environmental cause memory unit 25. In the environmental caution information, a QID(m) which is the ID of a general specific location, a location Q(m) of the general specific location, an environmental cause event CAUSE(m), and an environmental cause classification CLASS(m) are associated with each other.

[0056] <A-3. Effect> As described above, the information collection and analysis system 1001 according to Embodiment 1 includes a probe information generation device 101 and an information collection and analysis device 201. When a specific event including a lane departure or an LKAS operation occurs in the vehicle 100 that can be automatically driven by the automatic driving control device 53, the information collection unit 21 of the information collection and analysis device 201 collects from the vehicle the probe information in which the information of the specific event and the information of the driving mode representing the degree of automatic driving control at the time of the occurrence of the specific event are associated with each other, and an analysis unit 23 that specifies the cause of the specific event as a cause classification based on the driving mode and creates caution information in which the specific event and the cause classification are associated with each other. The driving mode includes a first driving mode in which the driver operates the steering wheel of the vehicle 100 and the automatic driving control device 53 does not execute the steering wheel operation, a second driving mode in which the driver operates the steering wheel during normal times and the automatic driving control device 53 intervenes in the steering wheel operation to execute LKAS when detecting a risk of lane departure, and a third driving mode in which the automatic driving control device 53 always controls the steering wheel operation of the vehicle 100.

[0057] With the above configuration, the information collection and analysis device 201 can specify the cause of the occurrence of the specific event in detail as a cause classification according to the driving mode.

[0058] Also, in the present embodiment, the probe information includes the position information of the specific location where the specific event occurred and the individual ID unique to the vehicle 100 or the driver of the vehicle 100. Then, based on the position information of the specific location and the individual ID, the analysis unit 23 determines whether the specific event is an environmental cause event caused by the driving environment of the vehicle 100, classifies the driving environment that caused the environmental cause event as an environmental cause classification based on the driving mode, and creates caution information linking the environmental cause event, the environmental cause classification, and the position information of the specific location where the environmental cause event occurred.

[0059] <A-4. Variation> The probe information may include information on the vehicle type or vehicle class of the vehicle 100 as additional information shown in FIG. 4. In this case, in the information collection and analysis device 201 that collects the probe information, the analysis unit 23 can perform environmental cause classification by vehicle type or vehicle class. That is, the analysis unit 23 uses the probe information collected from vehicles 100 of the same model, vehicle type, or vehicle class to perform an environmental cause classification determination according to the table in FIG. 7. The vehicle type is, for example, a classification of the vehicle 100 based on the body type such as a sedan or a minivan. The vehicle class is, for example, a grading of the vehicle 100 based on the body size or the engine displacement.

[0060] <​​​ The probe information generation device 101 may create probe information for all peculiar events that occur in the vehicle 100 and transmit all of the probe information to the information collection and analysis device 201. The probe information generation device 101 may not transmit to the information collection and analysis device 201 probe information that matches predetermined exclusion conditions. Here, the predetermined exclusion conditions are assumed to be, for example, when the vehicle 100 changes lanes, or when the vehicle 100 deviates from its lane or approaches a lane boundary line to avoid approaching another vehicle. Whether or not these exclusion conditions are met is determined based on information about surrounding vehicles or surrounding photograph information detected by the periphery detection device 52, or driving information about the vehicle 100, such as steering, turn signals, and braking, acquired from an in-vehicle LAN or the like.

[0062] Furthermore, information necessary to determine whether or not these exclusion conditions are met may be included in the probe information as additional information. In this case, the information collection and analysis device 201 that collected the probe information can determine whether or not the probe information meets the exclusion conditions, and discard the probe information that meets the exclusion conditions.

[0063] The analysis unit 23 may repeatedly classify the environmental causes of the general peculiar point information at regular intervals, such as monthly or yearly, and store the environmental caution information of the general peculiar point information as time-series information in the environmental cause storage unit 25. The analysis unit 23 may then further subdivide the environmental cause classification of the general peculiar point information based on changes over time in the environmental cause classification of the general peculiar point information. The analysis unit 23 may also delete old environmental caution information from the environmental cause storage unit 25.

[0064] For example, the analysis unit 23 creates environmental caution information for general peculiar point information on a monthly basis, and if a location that was previously a general peculiar point is no longer detected as a peculiar point multiple times, for example, three times in a row, it may determine that the environmental cause has been improved and delete the environmental caution information for that general peculiar point from the environmental cause storage unit 25.

[0065] Furthermore, if the rate at which a general anomalous point is probed as an anomalous point is increasing, the analysis unit 23 may determine that the environment is gradually deteriorating and add a sub-environmental cause classification such as "environmental deterioration in progress" to the environmental cause classification of the general anomalous point.

[0066] Furthermore, when the rate of increase in the rate at which a general peculiar point is probed as a peculiar point exceeds a predetermined threshold, the analysis unit 23 may add a sub-environmental cause classification such as "Caution required for environmental deterioration" or "Sudden environmental deterioration" to the environmental cause classification of the general peculiar point. Then, for a general peculiar point where the rate at which it is probed as a peculiar point exceeds a predetermined threshold, the information collection and analysis device 201 may report the general peculiar point to the road administrator as having a poor driving environment.

[0067] If lane departure occurs in the second or third driving mode at the same singular point where an environmentally-caused event occurred, and the rate at which the LKAS operates decreases over time, the analysis unit 23 may classify the same singular point as a point where road conditions are deteriorating and LKAS operation is unstable.

[0068] The vehicle 100 may be equipped with a DMS (Driver Monitoring System) that detects the driver's state, such as whether the driver is looking away, dozing, or absent-minded. The probe information generation unit 14 may then include the driver's state as additional information in the probe information. That is, the probe information may include the driver's state indicating the driver's driving aptitude state related to the driver's looking away or reduced alertness. In this case, the analysis unit 23 of the information collection and analysis device 201 that has collected the probe information can add sub-environmental cause classifications that take the driver's state into consideration to the environmental cause classification of the general peculiar point. For example, the analysis unit 23 may add sub-environmental cause classifications such as "point where dozing occurs frequently," "point where looking away frequently," and "point where absent-mindedness occurs frequently" to the environmental cause classification R1 "point where driving attention is reduced" according to the driver's state.

[0069] In addition, when the analysis unit 23 determines that the general specific location is the environmental cause classification R2 "Attention point of road shape", and the driver state is in a state suitable for driving rather than a side glance state, a drowsy state, or a distracted state, the sub-environmental cause classification of "Particularly attention should be paid to driving" may be added to the environmental cause classification of the general specific location. That is, the general specific location is treated as a location where lane departure may occur even when driving carefully.

[0070] <B. Embodiment 2> <B-1. Configuration> FIG. 9 is a block diagram showing the configuration of the information collection and analysis system 1002 according to Embodiment 2. The information collection and analysis system 1002 is different from the information collection and analysis system 1001 according to Embodiment 1 in that it includes an information collection and analysis device 202 instead of the information collection and analysis device 201. The information collection and analysis device 202 is different from the information collection and analysis device 201 in that it includes an individual cause storage unit 26 instead of the environmental cause storage unit 25.

[0071] The information collection and analysis device 201 according to Embodiment 1 analyzed the environmental causes of specific events occurring at general specific locations. In contrast, the information collection and analysis device 202 according to this embodiment analyzes individual causes that are specific to the vehicle 100 or the driver for specific events occurring at specific locations that are not general specific locations.

[0072] <B-2. Operation> FIG. 10 is a flowchart showing the individual cause analysis process by the information collection and analysis device 202. Hereinafter, the individual cause analysis process will be described along the flowchart of FIG. 10.

[0073] First, since steps S401 and S402 are the same as steps S301 and S302 in FIG. 5, the description thereof will be omitted.

[0074] After step S402, in step S403, the analysis unit 23 sets the counter v of the vehicle ID for which the individual cause is to be analyzed to 1. The vehicle ID is included in the probe information as shown in Fig. 4, and the analysis unit 23 classifies the individual causes of the individually causal event by vehicle ID.

[0075] 10, the analysis unit 23 classifies the individual causes of the individual-cause events for all vehicle IDs V=1, 2, ..., VD. However, the analysis unit 23 may classify the individual causes only for specific vehicle IDs selected by a predetermined selection logic. Furthermore, the analysis unit 23 may determine the order of vehicles for which the individual causes are to be analyzed, and classify the individual causes for a predetermined number of vehicles each time this process is started.

[0076] The timing of the individual cause analysis process may be the same as or different from the timing of the environmental cause analysis process described in the first embodiment.

[0077] After step S403, in step S404, the analysis unit 23 determines whether an individual singular point among the singular points corresponding to vehicle ID=v conforms to a predetermined rule. An individual singular point is a singular point whose distance from the general singular point Q(m) is equal to or greater than a predetermined threshold. Specifically, the analysis unit 23 extracts VN(v) pieces of probe information Prove(P,EV,V=v,M) corresponding to vehicle ID=v from the collected plurality of pieces of probe information Prove(P,EV,V=v,M). Furthermore, the analysis unit 23 extracts DN(v) pieces of probe information Prove of individual singular points whose distance from the general singular point Q(m)|m=1, 2, ..., M is equal to or greater than a threshold from the probe information Prove(P,EV,V=v,M). If the individual singular point conforms to the predetermined rule, the processing of the analysis unit 23 proceeds to step S405. If not, the processing of the analysis unit 23 proceeds to step S407.

[0078] The predetermined rule for individual peculiar points is, for example, that the number of individual peculiar points DN(v) is equal to or greater than a predetermined threshold, for example, 3 or greater. Alternatively, the predetermined rule for individual peculiar points is, for example, that the proportion DN(v) / VN(v) of individual peculiar points among the peculiar points corresponding to vehicle ID=v is equal to or greater than a predetermined threshold, for example, 0.1 or greater.

[0079] A specific event that occurs at an individual specific point is called an individual cause event. An individual cause event occurs at a point where it does not generally occur in other vehicles 100, and is therefore considered to be due to a cause specific to the vehicle 100 or driver in which the individual cause event occurred.

[0080] In step S405, the analysis unit 23 classifies the cause of the individual causal event based on the individual causal event and the operating mode at the time of the individual causal event. The causes of the individual causal event classified here are referred to as individual cause classifications. That is, the analysis unit 23 determines the individual cause classification of the individual causal event.

[0081] 11 is a diagram showing an example of the criteria for individual cause classification. In FIG. 11, the notation of pattern A1 and the like is the same as in FIG.

[0082] For example, suppose that pattern A1 and pattern C2 occurred at an individual peculiar point for vehicle 100 with vehicle ID = 1. This means that lane departure or LKAS activation occurred for vehicle 100 with vehicle ID = 1 at a point where lane departure or LKAS activation would not occur for a typical vehicle. Therefore, analysis unit 23 determines the individual cause classification for vehicle 100 with vehicle ID = 1 as U1: "poor driving skill (of the driver)."

[0083] For example, suppose that pattern A1 and pattern B2 occurred at an individual singular point for vehicle 100 with vehicle ID = 1. This means that vehicle 100 with vehicle ID = 1 deviated from its lane at a point different from that of a typical vehicle because the LKAS was unable to keep up with the driver's steering operation. Therefore, analysis unit 23 determines that vehicle 100 with vehicle ID = 1 is a vehicle that has been driven in a way that makes it impossible for the LKAS to control it, and classifies the individual cause as U2: "vehicle driven recklessly."

[0084] For example, suppose that pattern B3 occurred at an individual singular point for vehicle 100 with vehicle ID = 1. This means that vehicle 100 with vehicle ID = 1 deviated from its lane in the third driving mode without the LKAS activated at a point different from that of a typical vehicle. Therefore, analysis unit 23 determines that there is a problem with vehicle 100 with vehicle ID = 1, and classifies the individual cause as U3: "tire deterioration."

[0085] For example, suppose that pattern A1 and pattern A2 occurred at an individual singular point for vehicle 100 with vehicle ID = 1. This means that vehicle 100 with vehicle ID = 1 deviated from its lane in the second driving mode without its LKAS being activated at a point different from that of a typical vehicle. Therefore, analysis unit 23 determines that there is a problem with the LKAS function of vehicle 100 with vehicle ID = 1, and classifies the individual cause as U4: "LKAS function degradation."

[0086] For example, suppose that pattern A3 occurred at an individual singular point for vehicle 100 with vehicle ID = 1. This means that vehicle 100 with vehicle ID = 1 deviated from its lane in a point different from that of a typical vehicle because the LKAS did not activate in the third driving mode. Therefore, analysis unit 23 determines that there is a problem with the LKAS function of vehicle 100 with vehicle ID = 1, and classifies the individual cause as U4: "LKAS function degradation."

[0087] After step S405, in step S406, the analysis unit 23 creates individual attention information by associating an individual cause event, an individual cause classification, and a vehicle ID in the vehicle 100 with vehicle ID = v, and stores the individual attention information in the individual cause storage unit 26.

[0088] If the answer in step S404 is No, or after step S406, in step S407, the analysis unit 23 increments the counter v of the vehicle ID for which individual cause classification is to be performed by 1. Thereafter, in step S408, the analysis unit 23 determines whether the counter v of the vehicle ID is less than or equal to VD. If the counter v of the vehicle ID in step S408 is less than or equal to VD, the analysis unit 23 determines that there is a vehicle 100 for which individual cause classification has not been determined, and returns to the process of step S404. If the counter v of the vehicle ID in step S408 is greater than VD, the analysis unit 23 determines that individual cause classification has been determined for all the vehicles 100, and returns to the process of step S401.

[0089] In the above description, the analysis unit 23 determines the individual cause classification for each vehicle ID. However, here the vehicle ID is an example of an individual ID that identifies the vehicle 100 or the driver of the vehicle 100. The analysis unit 23 may determine the individual cause classification based on a personal ID that identifies the driver instead of the vehicle ID, or may determine the individual cause classification based on both the vehicle ID and the personal ID. Thereby, even when a plurality of drivers drive the same vehicle 100, or when the same driver drives a plurality of vehicles 100, it becomes possible to accurately determine the individual cause classification.

[0090] <B-3. Effect> In the information collection and analysis device 202 according to this embodiment, the probe information includes the position information of a specific location where a specific event has occurred and an individual ID unique to the vehicle or the driver of the vehicle. The analysis unit determines whether the specific event is an individual cause event that has occurred due to an individual cause unique to the vehicle or the driver based on the position information of the specific location and the individual ID, specifies the individual cause that has caused the individual cause event as an individual cause classification based on the driving mode, and creates attention-required information linking the individual cause event, the individual cause classification, and the individual ID. Therefore, according to the information collection and analysis device 202, the cause of the individual cause event can be accurately classified based on the driving mode.

[0091] Also, in the information collection and analysis device 202, when a specific event occurs for a plurality of individual IDs at the same specific location, the analysis unit 23 defines the same specific location as a general specific location, and when the ratio of the specific locations where a specific event occurs for a specific individual ID that is different from the general specific location is equal to or greater than a predetermined threshold, the analysis unit 23 determines the specific event that has occurred for the specific individual ID as an individual cause event. Thereby, the information collection and analysis device 202 can accurately classify, based on the driving mode, the individual cause of the specific event that has occurred for the vehicle 100, which is a vehicle where a specific event occurs at a location different from that of a general vehicle, that is attributable to the vehicle 100 or the driver.

[0092] <B-4. Modified Example> The timing of the individual cause classification process shown in FIG. 10 may be different from the timing of the environmental cause analysis process described in Embodiment 1. For example, when the information collection unit 21 acquires probe information about a specific location different from the defined general specific location Q(m), the analysis unit 23 may perform an individual cause classification process on the probe information. In this case, since there is a high possibility that an individual cause event unique to the vehicle 100 or the driver has occurred at a specific location different from the defined general specific location Q(m), the analysis is executed in a timely manner.

[0093] Furthermore, when the information collecting unit 21 acquires probe information about different anomalous locations from one vehicle 100 a predetermined number of times or more within a predetermined time period, the analyzing unit 23 may perform individual cause classification processing on the probe information. In this case, it becomes possible to detect reckless driving or driver abnormalities of the vehicle 100 at an early stage.

[0094] 9, for example, in response to a request from a manager of the vehicle 100. In this case, the request may include the vehicle ID of the vehicle for which individual cause classification is to be performed, and the information collection and analysis device 201 may perform the individual cause classification process for the vehicle with that vehicle ID.

[0095] The probe information may also include additional information such as vehicle type, vehicle class, mileage, driving time, or intended use. In this case, the information collection and analysis device 202 that collects the probe information may perform individual cause classification processing at a timing that corresponds to this additional information. For example, the analysis unit 23 may shorten the cycle of the individual cause classification processing for buses, trucks, or taxis, since they are always on the road, and may lengthen the cycle of the individual cause classification processing for vehicles that are not used for commuting or business. The analysis unit 23 may also shorten the cycle of the individual cause classification processing for vehicles 100 that have long driving distances or long driving times.

[0096] The analysis unit 23 may repeatedly perform the individual cause classification on a driving unit, a monthly unit, a yearly unit, or the like, and store the attention-requiring information related to the vehicle's individual cause classification as time-series information in the individual cause storage unit 26. The analysis unit 23 may then further subdivide the individual cause classification based on changes in the individual cause classification over time. The analysis unit 23 may also delete old attention-requiring information from the individual cause storage unit 26.

[0097] For example, suppose that the frequency of probe information transmission from a vehicle 100 that has not previously been determined to have individual cause classification U1: "poor driving skill" increases, and then the individual cause classification of that vehicle 100 is determined to have U1: "poor driving skill," and the frequency of probe information transmission from that vehicle 100 exceeds a predetermined threshold. In this case, the analysis unit 23 may add a sub-individual cause classification such as "significant decline in driving skill" to the individual cause classification U1: "poor driving skill" of that vehicle 100. This can be used as information to determine skill decline due to aging.

[0098] In other words, if the number of specific points where an individual causal event occurs in a specific road section for a specific individual ID increases over time, the analysis unit 23 may classify the individual cause of the individual causal event that occurred for the specific individual ID as a decline in the driver's driving skills.

[0099] If a vehicle 100 that has not previously been judged as having individual cause classification U2: "rough driving" is judged as having individual cause classification U2: "rough driving" on that day, the analysis unit 23 may add a sub-individual cause classification such as "emotional instability" to the individual cause classification U2: "rough driving" of that vehicle 100.

[0100] For example, when the frequency of probe information distribution from a certain vehicle 100 exceeds a predetermined threshold, the analysis unit 23 may add a sub-individual cause classification such as "related to tailgating" to the individual cause classification of the vehicle 100. In this case, if the vehicle 100 has previously been determined to be in individual cause classification U2: "aggressive driving," the vehicle 100 can be determined to be the perpetrator of tailgating. Furthermore, if the vehicle 100 has not previously been determined to be in individual cause classification U2: "aggressive driving," the vehicle 100 can be determined to be the victim of tailgating.

[0101] If the driver of vehicle 100 is changed due to the sale or purchase of vehicle 100 or for other reasons, analysis unit 23 may delete from individual cause memory unit 26, among the cautionary information corresponding to the vehicle ID of vehicle 100, cautionary information relating to cause classifications specific to the driver, such as individual cause classifications U1 and U2.

[0102] Also, when the driver switches to a new vehicle, the analysis unit 23 may inherit the attention-required information corresponding to the driver's personal ID as the attention-required information corresponding to the vehicle ID of the new vehicle.

[0103] The vehicle 100 may include a DMS that detects a driver state such as a distracted state, a drowsy state, or an absent-minded state of the driver. Then, the probe information generation unit 14 may include the driver state in the probe information as additional information. In this case, in the information collection and analysis apparatus 201 that has collected the probe information, the analysis unit 23 can add a sub-individual cause classification considering the driver state to the individual cause classification of the vehicle. For example, the analysis unit 23 may add a sub-individual cause classification such as "easily distracted" to the individual cause classification U1 "low driving skill" according to the driver state.

[0104] <C. Embodiment 3> <C-1. Configuration> FIG. 12 is a block diagram showing the configuration of an information collection and analysis system 1003 according to Embodiment 3. The information collection and analysis system 1003 is different from the information collection and analysis system 1003 according to Embodiment 1 in that it includes an information collection and analysis apparatus 203 instead of the information collection and analysis apparatus 201. The information collection and analysis apparatus 203 is different from the information collection and analysis apparatus 201 in that the cause storage unit 24 includes an environmental cause storage unit 25 and an individual cause storage unit 26.

[0105] The information collection and analysis device 203 according to the present embodiment analyzes the environmental causes of specific events that occurred at specific locations in general (environmental cause analysis process). The information collection and analysis device 202 according to the second embodiment analyzed individual causes that are specific to the vehicle 100 or the driver for specific events that occurred at specific locations other than general specific locations (individual cause analysis process). When a specific event occurs in the vehicle 100, the information collection and analysis device 203 according to the present embodiment determines whether the specific event is a driving environment cause event resulting from the driving environment or an individual cause event resulting from an individual cause of the vehicle 100 or the driver, and performs an environmental cause analysis process for the driving environment cause event and an individual cause analysis process for the individual cause event.

[0106] <C-2. Operation> The operation of the probe information generation device 101 in the present embodiment is as described in FIG. 2 in the first embodiment. The information collection process in the information collection and analysis device 203 is as described in FIG. 3 in the first embodiment.

[0107] The environmental cause analysis process in the information collection and analysis device 203 is as described in FIG. 5 in the first embodiment. Note that in step S306, the attention information including environmental cause classification is stored in the environmental cause storage unit 25. [[ID=\\(11\\)]]

[0108] Also, the individual cause analysis process in the information collection and analysis device 203 is generally the same as that described in FIG. 10 in the second embodiment. However, the individual cause analysis process in the information collection and analysis device 203 is performed on the assumption that the environmental cause analysis process has already ended, that is, on the assumption that the general specific location information has already been obtained. That is, in step S401 of FIG. 10, when the analysis unit 23 determines the analysis timing, the process of step S402 is skipped and the processes after step S403 are executed. In step S406, the attention information including individual cause classification is stored in the individual cause storage unit 26.

[0109] <C-\\(3\\). Effect> According to the information collection and analysis device 203 according to Embodiment 3, when a specific event occurs in a certain vehicle 100, if a specific event also occurs in another vehicle at or near the location where the specific event occurred, the location where the specific event occurred in that vehicle 100 is classified as a general specific location, and the driving environment that caused the specific event at the general specific location is specified as an environmental cause classification based on the driving mode of the vehicle 100 at the time of the specific event. Further, according to the information collection and analysis device 203, when a large number of locations different from the general specific locations are included among the locations where a specific event occurred in a certain vehicle 100, it is determined that there is a cause for the specific event in that vehicle 100 or the driver, and the cause is specified as an individual cause classification based on the driving mode of the vehicle 100 at the time of the specific event. In this way, according to the information collection and analysis device 203, in addition to the effects of Embodiments 1 and 2, it is possible to determine whether the specific event that occurred in the vehicle 100 is an environmental cause event caused by the driving environment or an individual cause event caused by the vehicle 100 or the driver.

[0110] <D. Embodiment 4> <D-1. Configuration> FIG. 13 is a block diagram showing the configuration of the information collection and analysis system 1004 according to Embodiment 4. The information collection and analysis system 1004 includes a probe information generation device 104 instead of the probe information generation device 101, an information collection and analysis device 204 instead of the information collection and analysis device 203, and a presentation device 54 in the vehicle 100, as compared with the information collection and analysis system 1003 according to Embodiment 3.

[0111] The information collection and analysis device 204 includes a distribution unit 27 that distributes attention-required information to the wide area communication network 301 in addition to the configuration of the information collection and analysis device 203. The distribution unit 27 retrieves the attention-required information stored in the cause storage unit 24 as needed and distributes it outside the information collection and analysis device 204. The distribution destination is, for example, the vehicle 100.

[0112] Note that the information collection and analysis system 1004 shown in FIG. 13 is configured to distribute both the attention-required information including environmental cause classification and the attention-required information including individual cause classification, and is obtained by adding a configuration related to distribution to the information collection and analysis system 1003 according to Embodiment 3. However, the information collection and analysis system 1004 may be obtained by adding a configuration related to distribution to the information collection and analysis system 1001 according to Embodiment 1 or the information collection and analysis system 1002 according to Embodiment 2.

[0113] The probe information generation device 104 includes an information presentation unit 17 in addition to the configuration of the probe information generation device 101. The information presentation unit 17 causes the presentation device 54 mounted on the vehicle 100 to present the attention-required information received by the vehicle communication unit 16 from the information collection and analysis device 204 through the wide area communication network 301. The presentation mode is at least one of display or voice.

[0114] The presentation device 54 is, for example, a display device mounted on the vehicle 100. In this case, the information presentation unit 17 performs display control on the presentation device 54 for the attention-required information.

[0115] <D-2. Operation> The distribution unit 27 distributes attention-required information including environmental cause classification of general specific locations, for example, when receiving a request from the outside or at a predetermined timing such as during environmental cause analysis. FIG. 14 shows an example in which the attention-required information including environmental cause classification of general specific locations distributed from the distribution unit 27 to the vehicle 100 is displayed on the presentation device 54. In the example of FIG. 14, the current position and the driving route 61 of the vehicle 100 are displayed, and furthermore, general specific locations Q(1) and Q(2) are shown on the driving route 61. Furthermore, an environmental cause classification of "LKAS inoperative location" is displayed at the general specific location Q(1), and an environmental cause classification of "location where driving attention level decreases" is displayed at the general specific location Q(2).

[0116] Thereby, the driver of the vehicle 100 can grasp that there is an LKAS inoperative location ahead of the vehicle 100 and that sufficient attention should be paid to driving.

[0117] In addition, the position display of the general specific points Q(1) and Q(2) as shown in FIG. 14 may be performed when the vehicle 100 approaches within a certain distance, such as within 500 m from the general specific point. Further, when the vehicle 100 is traveling at the second driving level and approaches within a certain distance from the general specific point of the environmental cause classification R4: "LKAS inoperative point", a warning regarding the general specific point may be given by the presentation device 54.

[0118] Although FIG. 14 shows an example in which the attention-required information including the environmental cause classification is distributed to the vehicle 100, the attention-required information including the environmental cause classification may be distributed to the road administrator. Thereby, an effect of giving an opportunity to prompt the road administrator to repair the road can be obtained.

[0119] The distribution unit 27 distributes the attention-required information including the individual cause classification at a predetermined timing such as when receiving a request from the outside or at the time of individual cause analysis. The distribution destinations of the attention-required information including the individual cause classification include, for example, the vehicle 100 in which the individual cause classification is determined, the administrator of the vehicle 100, the traffic control agency, or the driver's license issuing agency.

[0120] By distributing the attention-required information including the individual cause classification to the vehicle 100, the driver can recognize the low driving skill of himself / herself, his / her rough driving, or abnormalities such as the tires or the LKAS function of the vehicle 100. In addition, the vehicle administrator or the traffic control agency to which the attention-required information including the individual cause classification is distributed can give an opportunity to a corresponding driver to perform a predetermined procedure or process for safe driving or safe traveling. Further, the driver's license issuing agency to which the attention-required information including the individual cause classification is distributed can give advice such as license return to the license renewer.

[0121] <D-3. Effect><000043​​

[0122] <E. Hardware Configuration> The position information acquisition unit 11, lane departure detection unit 12, control information acquisition unit 13, probe information generation unit 14, probe information transmission unit 15, vehicle communication unit 16, and information presentation unit 17 in the above-described probe information generation devices 101 and 104 are realized by the processing circuit 81 shown in FIG. 15. That is, the processing circuit 81 includes the position information acquisition unit 11, lane departure detection unit 12, control information acquisition unit 13, probe information generation unit 14, probe information transmission unit 15, vehicle communication unit 16, and information presentation unit 17 (hereinafter, "position information acquisition unit 11, etc.") in the probe information generation devices 101 and 104.

[0123] Further, the information collection unit 21, collected information storage unit 22, analysis unit 23, cause storage unit 24, and distribution unit 27 in the information collection and analysis devices 201 to 204 are realized by a processing circuit 81 different from the processing circuit 81 that realizes the probe information generation devices 101 and 104. That is, this different processing circuit 81 includes the information collection unit 21, collected information storage unit 22, analysis unit 23, cause storage unit 24, and distribution unit 27 (hereinafter, "information collection unit 21, etc.") in the information collection and analysis devices 201 to 204.

[0124] Dedicated hardware may be applied to each of these processing circuits 81, or a processor that executes a program stored in a memory may be applied. The processor is, for example, a central processing unit, a processing device, an arithmetic device, a microprocessor, a microcomputer, a DSP (Digital Signal Processor), or the like.

[0125] When the processing circuit 81 is dedicated hardware, the processing circuit 81 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 location information acquisition unit 11 or the information collection unit 21 may be realized by a plurality of processing circuits 81, or the functions of each unit may be realized by a single processing circuit.

[0126] When the processing circuitry 81 is a processor, the functions of the location information acquisition unit 11, etc. or the information collection unit 21, etc. are realized by a combination of software, etc. (software, firmware, or software and firmware). The software, etc. is written as a program and stored in a memory. As shown in FIG. 16, the processor 82 applied to the processing circuitry 81 realizes the functions of each unit by reading and executing a program stored in a memory 83. That is, the probe information generation devices 101, 104 include a memory 83 for storing a program that, when executed by the processing circuitry 81, results in the function of the location information acquisition unit 11, etc. being executed. The information collection and analysis devices 201-204 also include a memory 83 for storing a program that, when executed by the processing circuitry 81, results in the function of the information collection unit 21, etc. being executed. In other words, this program can be said to cause a computer to execute the procedure or method of the location information acquisition unit 11, etc. or the information collection unit 21, etc. Here, the memory 83 may be, for example, a 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, mini disk, DVD (Digital Versatile Disk) and its drive device, or any storage medium to be used in the future.

[0127] The above describes a configuration in which each function of the location information acquisition unit 11 etc. or the information collection unit 21 etc. is realized either by hardware or software, etc. However, this is not limited to this, and a configuration in which part of the location information acquisition unit 11 etc. or the information collection unit 21 etc. is realized by dedicated hardware and another part is realized by software, etc.

[0128] As described above, the processing circuit can realize each of the above-mentioned functions by hardware, software, etc., or a combination of these. Note that the collected information storage unit 22 and the cause storage unit 24 are configured from memory 83, but they may be configured from a single memory 83, or each may be configured from an individual memory.

[0129] It should be noted that the embodiments can be freely combined, and each embodiment can be modified or omitted as appropriate. The above description is an example in all respects. It is understood that countless variations not illustrated can be envisioned. [Explanation of symbols]

[0130] 11 position information acquisition unit, 12 lane departure detection unit, 13 control information acquisition unit, 14 probe information generation unit, 15 probe information transmission unit, 16 vehicle communication unit, 17 information presentation unit, 21 information collection unit, 22 collected information storage unit, 23 analysis unit, 24 cause storage unit, 25 environmental cause storage unit, 26 individual cause storage unit, 27 distribution unit, 51 positioning device, 52 surrounding detection device, 53 automatic driving control device, 54 presentation device, 61 driving route, 81 processing circuit, 82 processor, 83 memory, 100 vehicle, 101, 104 probe information generation device, 201-204 information collection and analysis device, 301 wide area communication network, 1001-1004 information collection and analysis system.

Claims

1. an information collection unit that, when a specific event including lane departure or LKAS operation occurs in a vehicle capable of automatic driving control by an automatic driving control device, collects probe information from the vehicle that is linked to information on the specific event and information on a driving mode that indicates the degree of automatic driving control at the time the specific event occurs; an analysis unit that identifies a cause of the specific event as a cause classification based on the operation mode and creates caution-requiring information that links the specific event with the cause classification; Equipped with The operation mode is a first driving mode in which the driver operates the steering wheel of the vehicle, and the automatic driving control device does not perform the steering wheel operation; a second driving mode in which the driver normally operates the steering wheel, and when the automatic driving control device detects the risk of lane departure, the automatic driving control device intervenes in the steering wheel operation and executes the LKAS; a third driving mode in which the automatic driving control device always controls the steering operation of the vehicle; Information collection and analysis device.

2. the probe information includes location information of a specific point where the specific event occurred and an individual ID unique to the vehicle or the driver of the vehicle; The analysis unit determining whether the peculiar event is an environmentally-caused event caused by the vehicle's running environment based on the location information of the peculiar point and the individual ID; classifying the driving environment that caused the environmentally caused event as an environmental cause classification based on the driving mode; creating the caution information by linking the environmental cause event, the environmental cause classification, and the location information of the anomalous point where the environmental cause event occurred; The information collection and analysis device according to claim 1 .

3. the probe information includes location information of a specific point where the specific event occurred and an individual ID unique to the vehicle or the driver of the vehicle; The analysis unit determining whether the singular event is an individual cause event caused by an individual cause specific to the vehicle or the driver based on the location information of the singular point and the individual ID; Identifying the individual causes that caused the individual cause event based on the operation mode as an individual cause classification; creating the caution information linking the individual cause event, the individual cause classification, and the individual ID; 3. The information collection and analysis device according to claim 1.

4. a distribution unit that distributes the caution-required information to an outside of the information collection and analysis device; The information collection and analysis device according to claim 1 .

5. The probe information and the caution information include lane-by-lane position information of the specific point where the specific event occurred. The information collection and analysis device according to claim 2 .

6. the information collection unit collects the probe information, including lane-by-lane position information of the singular point obtained using a high-precision map database having road shape data for each lane, and a high-precision positioning device having sub-meter-level positioning accuracy and outputting the position and driving lane of the vehicle, from the vehicle, the high-precision map database having road shape data for each lane, and the high-precision positioning device. The information collection and analysis device according to claim 5 .

7. The analysis unit determining the singular events occurring in the same singular point for a plurality of the individual IDs as the environmentally caused events; If lane departure occurs in the first driving mode and lane departure does not occur in the second driving mode or the third driving mode at the same specific point where the environmentally caused event occurred, the same specific point is classified as a point where the driver's driving attention is likely to decrease. The information collection and analysis device according to claim 2 .

8. The analysis unit determining the singular events occurring in the same singular point for a plurality of the individual IDs as the environmentally caused events; If lane departure occurs in the first driving mode at the same specific point where the environmentally caused event occurred, and if LKAS is activated and lane departure occurs in the second driving mode, the same specific point is classified as a point where lane departure is likely to occur due to a road shape. The information collection and analysis device according to claim 2 .

9. The analysis unit determining the singular events occurring in the same singular point for a plurality of the individual IDs as the environmentally caused events; If the LKAS does not operate and lane departure occurs in the second driving mode at the same specific point where the environmentally caused event occurred, and if lane departure occurs in the third driving mode, the same specific point is classified as a point where the LKAS does not operate. The information collection and analysis device according to claim 2 .

10. The analysis unit determining the singular events occurring in the same singular point for a plurality of the individual IDs as the environmentally caused events; If a lane departure occurs in the second driving mode or the third driving mode at the same specific point where the environmentally caused event occurred, and the LKAS operation rate at that time decreases over time, the same specific point is classified as a point where road conditions are deteriorating and LKAS operation is unstable. The information collection and analysis device according to claim 2 .

11. The analysis unit When the singular event occurs in a plurality of the individual IDs at the same singular point, the same singular point is defined as a general singular point; When a ratio of the specific points where the specific event occurred in the specific individual ID that is different from the general specific points is equal to or greater than a predetermined threshold, the specific event that occurred in the specific individual ID is determined to be the individual causal event. The information collection and analysis device according to claim 3 .

12. The analysis unit In the individual cause event occurring in the specific individual ID, when lane departure occurs in the first driving mode and LKAS is activated in the second driving mode, the individual cause of the individual cause event occurring in the specific individual ID is classified as poor driving skill of the driver. The information collection and analysis device according to claim 3 .

13. The analysis unit If the number of specific points where the individual cause event occurred in a specific road section for a specific individual ID increases over time, the individual cause of the individual cause event that occurred in the specific individual ID is classified as a decline in the driver's driving skill. The information collection and analysis device according to claim 3 .

14. The analysis unit For a particular individual ID, When the ratio of the specific point of the first specific event, which is the specific event in which the LKAS does not operate and lane departure occurs in the second driving mode, and the specific point of the second specific event, which is the specific event in which lane departure occurs in the third driving mode, that differs from the general specific point is equal to or greater than a predetermined threshold value, determining the first specific event and the second specific event as the individual cause events, and classifying the individual causes of the first specific event and the second specific event as deterioration of LKAS function; The information collection and analysis device according to claim 11.

15. the probe information includes a driver state indicating a driving fitness state related to the driver's inattentiveness or decreased alertness, The analysis unit assigns a sub-environmental cause classification, based on the driver state, of a dozing-off-the-driver-prone spot or a distracted-driver-prone spot to the singular point of the environmental cause event that has been classified as a spot where the driver's driving attention is likely to decrease. The information collection and analysis device according to claim 7.

16. the probe information includes a driver state indicating a driving fitness state related to the driver's inattentiveness or decreased alertness, When the driver state indicates a good driving aptitude state, the analysis unit assigns a sub-environmental cause classification of a point requiring particular driving caution to the singular point of the environmental cause event that has been subjected to the environmental cause classification of a point having a road shape where lane departure is likely to occur. The information collection and analysis device according to claim 8.

17. a probe information generating device that creates and transmits probe information of a vehicle that can be automatically controlled by an automatic driving control device; an information collection and analysis device that receives the probe information from the probe information generation device, The probe information generating device an information acquisition unit that acquires a driving mode indicating a mode of the automatic driving control by the automatic driving control device and an operating status of the LKAS by the automatic driving control device; a lane departure detection unit that detects lane departure of the vehicle; a probe information generating unit configured to generate, when a specific event including the lane departure or the LKAS operation occurs, the probe information including information on the specific event and information on the driving mode at the time of the specific event occurrence; a probe information transmitting unit that transmits the probe information to the information collection and analysis device, The information collection and analysis device an information collection unit that receives the probe information from the probe information generation device; an analysis unit that identifies a cause of the specific event as a cause classification based on the operation mode and creates caution-requiring information that links the specific event with the cause classification; Equipped with The operation mode is a first driving mode in which the driver operates the steering wheel of the vehicle, and the automatic driving control device does not perform the steering wheel operation; a second driving mode in which the driver normally operates the steering wheel, and when the automatic driving control device detects the risk of lane departure, the automatic driving control device intervenes in the steering wheel operation and executes the LKAS; a third driving mode in which the automatic driving control device always controls the steering operation of the vehicle; Information collection and analysis system.

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