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

Information collection and analysis device and information collection and analysis system

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

[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 these to the driver.

[0003] Japanese Patent Application Laid-Open No. 2004-126888

[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 departure and the like at the singular point.

[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.

[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, and 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.

[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.

[0008] 1 is a block diagram showing the configuration of an information collection and analysis system according to a first embodiment. FIG. 2 is a flowchart showing the operation of a probe information generation device. FIG. 3 is a flowchart showing information collection processing by the information collection and analysis device. FIG. 4 is a diagram showing probe information according to the first embodiment. FIG. 5 is a flowchart showing environmental analysis processing by the information collection and analysis device. FIG. 6 is a diagram showing the relationship between specific points and general specific points. FIG. 7 is a diagram showing the relationship between environmental cause events and environmental cause classifications. FIG. 8 is a diagram showing caution-requiring information stored in a cause storage unit. FIG. 9 is a block diagram showing the configuration of an information collection and analysis system according to a second embodiment. FIG. 10 is a flowchart showing individual analysis processing by the information collection and analysis device. FIG. 11 is a diagram showing the relationship between individual cause events and individual cause classifications. FIG. 12 is a block diagram showing the configuration of an information collection and analysis system according to a third embodiment. FIG. 13 is a block diagram showing the configuration of an information collection and analysis system according to a fourth embodiment. FIG. 14 is a diagram showing an example of display of cause information in a vehicle. FIG. 15 is a diagram showing the hardware configuration of an information collection and analysis device or a probe information generation device. FIG. 16 is a diagram showing the hardware configuration of an information collection and analysis device or a probe information generation device.

[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. Information collection and analysis system 1001 is configured to include a plurality of vehicles 100, an information collection and analysis device 201, and a wide area communication network 301 that connects each vehicle 100 to information collection and analysis device 201. Although Fig. 1 shows only one vehicle 100, information collection and analysis system 1001 includes a plurality of vehicles 100.

[0010] The vehicle 100 is configured to include a probe information generating device 101, a positioning device 51, a surroundings detecting device 52, and an automatic driving control device 53. The probe information generating device 101 creates probe information and transmits it to the information collection and analysis device 201 when an unusual event occurs in the vehicle 100, such as lane departure or LKAS activation.

[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 lane departure, 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 automatic 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 lane departure has occurred in the vehicle 100 based on 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 control information acquired from the control information acquisition unit 13. In this specification, lane departure of the vehicle 100 or 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 position information of the unusual point where the unusual event occurred and transmits the 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 unusual event based on the unusual event and the operating mode at the time the unusual event occurred. The causes of the unusual event classified by the analysis unit 23 are referred to as cause classifications. The analysis unit 23 links the unusual event with its cause classification to create caution information.

[0023] In this embodiment, the analysis unit 23 classifies the causes of driving environment causal events, which are unique events caused by the driving environment, into environmental cause classifications. Driving environment causal events are not caused by factors specific to the vehicle 100 or its driver, but are caused by the driving environment, such as the shape of the road, and can occur in other vehicles 100 under the same driving environment. The analysis unit 23 links the driving environment causal events with the environmental cause classifications to create environmental caution information, which is caution information related to the driving environment causal events.

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

[0025] <A-2. Operation> Fig. 2 is a flowchart showing the operation of the probe information generating device 101. The operation of the probe information generating device 101 will be described below in accordance with the flow 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 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 currently being executed from the automatic driving control device 53.

[0028] After step S103, in step S104, the probe information generation unit 14 determines whether 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 unique events that can occur in the vehicle 100 are divided into three unique events A, B, and C. The unique event A is an event in which the LKAS does not operate and lane departure occurs. The unique point where the unique event A occurs is the lane departure location. The unique event A can occur in the first, second, and third driving modes. The unique event B is an event in which the LKAS operates but lane departure occurs. The unique point where the unique event B occurs may be the lane departure location or the LKAS operation location. The unique event A can occur in the second and third driving modes. The unique event C is an event in which the LKAS operates but lane departure does not occur. The unique point where the unique event C occurs is the LKAS operation location. The unique event C can occur in the second driving mode. In the third driving mode, the vehicle 100 is steered by the automatic driving control device 53 and travels near the center of the lane, so the LKAS does not operate.

[0030] If an unusual event has occurred in step S104, the processing of the probe information generating device 101 proceeds to step S105. In step S105, the probe information generating unit 14 generates probe information Prove (P, EV, V, M) by associating the position P of the unusual point where the unusual event occurred, the unusual event EV, the vehicle ID V, and the driving mode M. Then, the probe information transmitting 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 unusual 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, 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 generated 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 multitasking, 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. Each piece of probe information is assigned an information ID for identifying the probe information. For example, this information ID is assigned a number in chronological order in which the probe information was collected. Probe information Probe(n) with information ID=n includes at least the position P(n) of the anomalous point, vehicle ID V(n), anomalous event EV(n), and driving mode M(n). In the example of FIG. 4, the probe information Probe(n) includes time T(n) and additional information INFO(n), which will be described later in a modified example.

[0036] 5 is a flowchart of the environmental cause analysis process performed by the information collection and analysis device 201. The environmental cause analysis process performed 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 is determined that it is now the timing to analyze, the process proceeds to step S302, and if it is determined that it is not the timing to analyze, the process of step S301 is repeated.

[0037] 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 collection unit 21 acquires special probe information, such as information indicating that the LKAS has not been activated and the vehicle has deviated from its lane. Alternatively, the analysis timing may be when an analysis instruction is received from a server administrator (not shown).

[0038] In step S302, the analysis unit 23 loads probe information such as that illustrated in FIG. 4 from the collected information storage unit 22 and extracts general peculiar points Q(m) from the probe information acquired from the plurality of vehicles 100. Specifically, the analysis unit 23 defines a point where peculiar points frequently occur in the plurality of vehicles as a general peculiar point Q(m) and counts the number MD of general peculiar points Q(m). 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 obtain the number of vehicles 100 that have traveled through the point A during the period TA from a VICS (Vehicle Information and Communication System, 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 to be 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. Furthermore, the road including the singular points P(m1), P(m2), ... P(mKm) may be divided into sublinks of 10-m units, 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 a singular point P(n) and a general singular point Q(m) on a map. 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) exist 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] 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, at a certain general singular point Q(m), if lane departure occurs 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, 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 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 wheel is operated 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 lane departure occurs at a general peculiar point Q(m) in the second or third driving mode, i.e., if pattern A2 or A3 occurs, the general peculiar point Q(m) is classified as an "LKAS non-operating point" under environmental cause category R4. A general peculiar point Q(m) classified as environmental cause category R4 is highly 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, according to the table of Figure 7, that the cause CAUSE of the singular event at general singular point Q(2) is environmentally caused event R, and further analyzes the classification CLASS of environmentally caused event R as environmentally caused classification R1 (point of reduced driving attention).

[0051] For example, assume 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 CAUSE of the singular event at general singular point Q(1) to be environmental cause event R according to the table of FIG. 7 , and further determines the classification CLASS of environmental cause event R to be 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 either environmental cause classification R3 or R4, whichever has the most frequent occurrence 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 requiring 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, environmental cause classification, and 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 1 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 for 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, and 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), and the processing by the analysis unit 23 returns to step S301.

[0055] 8 shows the environmental caution information stored in the environmental cause storage unit 25. In the environmental caution information, QID(m), which is the ID of the general peculiar point, the position Q(m) of the general peculiar point, the environmental cause event CAUSE(m), and the environmental cause classification CLASS(m) are linked together.

[0056] <A-3. Effects> As described above, the information collection and analysis system 1001 according to the first embodiment includes the probe information generation device 101 and the information collection and analysis device 201. The information collection and analysis device 201 includes an information collection unit 21 that, when a unique event including lane departure or LKAS operation occurs in a vehicle 100 capable of autonomous driving control by an autonomous driving control device 53, collects probe information from the vehicle that links information about the unique event with information about a driving mode that indicates the degree of autonomous driving control at the time the unique event occurred, and an analysis unit 23 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 with the cause classification. The driving modes include 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 perform any steering operation; a second driving mode in which the driver normally operates the steering wheel and the automatic driving control device 53 intervenes in the steering operation and executes the LKAS if it detects the risk of lane departure; and a third driving mode in which the automatic driving control device 53 always controls the steering operation of the vehicle 100.

[0057] With the above configuration, the information collection and analysis device 201 can identify the cause of an unusual event as a detailed cause classification according to the operation mode.

[0058] Furthermore, in this embodiment, the probe information includes location information of the singular point where the singular event occurred, and an individual ID unique to the vehicle 100 or the driver of the vehicle 100. Then, based on the location information of the singular point and the individual ID, the analysis unit 23 determines whether the singular event is an environmentally caused event caused by the driving environment of the vehicle 100, classifies the driving environment that caused the environmentally caused event as an environmental cause classification based on the driving mode, and creates attention-requiring information that links the environmentally caused event, the environmental cause classification, and the location information of the singular point where the environmentally caused event occurred.

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

[0060] In this embodiment, roads are represented by two roads, one going up and one going down. The environmental cause classifications are then separated into uphill and downhill. Furthermore, the probe information may include information about the lane in which the vehicle 100 is traveling as additional information, as shown in FIG. 4 . In this case, the positioning device 51 or the surroundings detection device 52 has a high-precision map database containing road shape data for each lane, and a high-precision positioning device (HDL) with sub-meter-level positioning accuracy or a function for detecting the lane in which the vehicle 100 is traveling using image processing. This allows the analysis unit 23 of the information collection and analysis device 201, which has collected the probe information, to perform environmental cause classification for each lane. That is, the analysis unit 23 uses probe information collected from the same lane to determine the environmental cause classification according to the table in FIG. 7 .

[0061] The probe information generating 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 generating device 101 may not transmit to the information collection and analysis device 201 probe information that meets predetermined exclusion conditions. Here, the predetermined exclusion conditions may 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, blinkers, 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 as additional information in the probe 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 cycle, 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 be determined that the environmental cause has been improved, and the environmental caution information for that general peculiar point may be deleted from the environmental cause storage unit 25.

[0065] Furthermore, if the rate at which a general singular point is probed as a singular 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 singular 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 the general peculiar point 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 is activated at that time 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 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 collects the probe information may 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] Furthermore, when the driver's state at a general peculiar point determined to be a "point with caution regarding road shape" of environmental cause classification R2 is appropriate for driving, and the driver is not in a distracted state, drowsy state, or absent-minded state, the analysis unit 23 may add a sub-environmental cause classification of "particular caution required when driving" to the environmental cause classification of the general peculiar point. In other words, the general peculiar point is treated as a point where lane departure may occur even if the driver drives carefully.

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

[0071] The information collection and analysis device 201 according to the first embodiment analyzes the environmental causes of a singular event that occurs at a general singular point. In contrast, the information collection and analysis device 202 according to the present embodiment analyzes individual causes that are specific to the vehicle 100 or the driver for a singular event that occurs at a singular point that is not a general singular point.

[0072] <B-2. Operation> Fig. 10 is a flowchart showing the individual cause analysis process by the information collection and analysis device 202. The individual cause analysis process will be described below with reference to the flow in Fig. 10 .

[0073] First, steps S401 and S402 are similar to steps S301 and S302 in FIG. 5, and therefore a 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 individually causal 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 a 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 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 matches 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 DN(v) of individual peculiar points 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 the 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. In other words, 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 anomalous 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: "(Driver's) driving skill is poor."

[0083] For example, suppose that pattern A1 and pattern B2 occurred at an individual anomalous 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 could not 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 manner 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 peculiar 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, the 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 peculiar 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 the 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 peculiar 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 being activated at a point different from that of a typical vehicle. Therefore, the 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 caution information for the vehicle 100 with vehicle ID = v by linking the individual cause event, individual cause classification, and vehicle ID, and stores the individual caution information in the individual cause memory unit 26.

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

[0089] In the above description, the analysis unit 23 determines the individual cause classification for each vehicle ID. However, the vehicle ID here 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 an individual 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 individual ID. This makes it possible to accurately determine the individual cause classification even when multiple drivers drive the same vehicle 100 or when the same driver drives multiple vehicles 100.

[0090] <B-3. Effects> In the information collection and analysis device 202 according to this embodiment, the probe information includes location information of the specific point where the specific event occurred and an individual ID unique to the vehicle or the vehicle's driver. The analysis unit determines whether the specific event is an individual cause event caused by an individual cause unique to the vehicle or the driver based on the location information of the specific point and the individual ID, identifies the individual cause that caused the individual cause event as an individual cause classification based on the driving mode, and creates attention-requiring information linking the individual cause event, the individual cause classification, and the individual ID. Therefore, the information collection and analysis device 202 can accurately classify the cause of the individual cause event based on the driving mode.

[0091] Furthermore, in the information collection and analysis device 202, when a singular event occurs for multiple individual IDs at the same singular point, the analysis unit 23 defines the same singular point as a general singular point, and when the rate at which the singular event for a specific individual ID occurs that is different from the general singular points is equal to or greater than a predetermined threshold, the analysis unit 23 determines that the singular event that occurred for the specific individual ID is an individual cause event. This allows the information collection and analysis device 202 to accurately classify, for a vehicle 100 in which a singular event occurs at a point different from that of a general vehicle, the individual cause of the singular event that occurs in the vehicle 100, which is attributable to the vehicle 100 or the driver, based on the driving mode.

[0092] <B-4. Modifications> 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 singular point different from the predefined general singular point Q(m), the analysis unit 23 may perform individual cause classification process on the probe information. In this case, since there is a high possibility that an individual cause event specific to the vehicle 100 or the driver has occurred at the singular point different from the predefined general singular point Q(m), the analysis is performed 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 aggressive driving or driver abnormalities of the vehicle 100 at an early stage.

[0094] 9, for example, in response to a request from an administrator 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 because 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 distribution 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 U1 of the vehicle 100 is determined to have "poor driving skill," and the frequency of probe information distribution from the 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 the vehicle 100. This can be used as information for determining 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 to have individual cause classification U2: "rough driving" is judged to have 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, if 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 aggressive driving" to the individual cause classification of the vehicle 100. In this case, if the vehicle 100 has previously been determined to be classified as individual cause classification U2: "aggressive driving," the vehicle 100 can be determined to be the perpetrator of aggressive driving. Furthermore, if the vehicle 100 has not previously been determined to be classified as individual cause classification U2: "aggressive driving," the vehicle 100 can be determined to be the victim of aggressive driving.

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

[0102] Furthermore, when a driver switches to a new vehicle, the analysis unit 23 may take over the caution information corresponding to the driver's personal ID as caution information corresponding to the vehicle ID of the new vehicle.

[0103] The vehicle 100 may be equipped with a DMS that detects the driver's state, such as whether the driver is looking away, drowsy, or absent-minded. The probe information generation unit 14 may then include the driver's state as additional information in the probe information. In this case, the analysis unit 23 of the information collection and analysis device 201 that has collected the probe information can add a sub-individual cause classification that takes the driver's state into consideration to the individual cause classification of the vehicle. For example, the analysis unit 23 may add a sub-individual cause classification such as "frequent distraction" to the individual cause classification U1 "poor driving skill" according to the driver's state.

[0104] <C. Third Embodiment> <C-1. Configuration> Fig. 12 is a block diagram showing the configuration of an information collection and analysis system 1003 according to a third embodiment. Information collection and analysis system 1003 differs from information collection and analysis system 1003 according to the first embodiment in that it includes an information collection and analysis device 203 instead of information collection and analysis device 201. Information collection and analysis device 203 differs from information collection and analysis device 201 in that 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 201 according to the first embodiment analyzed the environmental causes of a peculiar event that occurred at a general peculiar point (environmental cause analysis processing). The information collection and analysis device 202 according to the second embodiment analyzed individual causes, which are causes specific to the vehicle 100 or the driver, for a peculiar event that occurred at a peculiar point that is not a general peculiar point (individual cause analysis processing). When a peculiar event occurs in the vehicle 100, the information collection and analysis device 203 according to the present embodiment determines whether the peculiar event is a driving environment-related cause event resulting from the driving environment, or an individual cause event resulting from a cause specific to the vehicle 100 or the driver, and performs environmental cause analysis processing for the driving environment-related cause event and individual cause analysis processing for the individual cause event.

[0106] <C-2. Operation> The operation of the probe information generation device 101 in this embodiment is as described in embodiment 1 with reference to Fig. 2. The information collection process in the information collection and analysis device 203 is as described in embodiment 1 with reference to Fig. 3.

[0107] The environmental cause analysis process in the information collection and analysis device 203 is as described in Fig. 5 in embodiment 1. In step S306, the caution information including the environmental cause classification is stored in the environmental cause storage unit 25.

[0108] The individual cause analysis processing in the information collection and analysis device 203 is generally similar to that described in FIG. 10 in the second embodiment. However, the individual cause analysis processing in the information collection and analysis device 203 is performed assuming that the environmental cause analysis processing has already been completed, i.e., that general anomalous spot information has already been obtained. That is, in step S401 of FIG. 10, when the analysis unit 23 determines that it is time to analyze, it skips the processing in step S402 and executes the processing from step S403 onward. In step S406, the attention-requiring information including the individual cause classification is stored in the individual cause storage unit 26.

[0109] <C-3. Effects> According to the information collection and analysis device 203 of the third embodiment, when a unique event occurs in a certain vehicle 100, if a unique event also occurs in another vehicle at or near the location where the unique event occurred, the location where the unique event occurred in the certain vehicle 100 is classified as a general unique location, and the driving environment that caused the unique event at the general unique location is identified as an environmental cause classification based on the driving mode of the vehicle 100 at the time the unique event occurred. Furthermore, according to the information collection and analysis device 203, if the locations where the unique event occurred in the certain vehicle 100 include many locations that are different from general unique locations, it is determined that the vehicle 100 or the driver is the cause of the unique event, and the cause is identified as an individual cause classification based on the driving mode of the vehicle 100 at the time the unique event occurred. In this way, in addition to the effects of the first and second embodiments, the information collection and analysis device 203 makes it possible to determine whether the unique event occurring in the vehicle 100 is an environmentally caused 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 an information collection and analysis system 1004 according to embodiment 4. Compared to information collection and analysis system 1003 according to embodiment 3, information collection and analysis system 1004 includes a probe information generation device 104 instead of probe information generation device 101, an information collection and analysis device 204 instead of information collection and analysis device 203, and a presentation device 54 in vehicle 100.

[0111] In addition to the configuration of the information collection and analysis device 203, the information collection and analysis device 204 includes a distribution unit 27 that distributes caution-required information to the wide area communication network 301. The distribution unit 27 retrieves caution-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] 13 is configured to distribute both caution-required information including environmental cause classifications and caution-required information including individual cause classifications, and is configured by adding a distribution-related configuration to the information collection and analysis system 1003 according to embodiment 3. However, the information collection and analysis system 1004 may also be configured by adding a distribution-related configuration 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 components 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-requiring information received by the vehicle communication unit 16 from the information collection and analysis device 204 via the wide area communication network 301. The presentation is made in the form of at least one of a display and an audio.

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

[0115] <D-2. Operation> The distribution unit 27 distributes caution-required information including the environmental cause classification of a general peculiar point at a predetermined timing, such as when an external request is received or during environmental cause analysis. FIG. 14 shows an example in which caution-required information including the environmental cause classification of a general peculiar point, 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 of the vehicle 100 and a travel route 61 are displayed, and general peculiar points Q(1) and Q(2) are also shown on the travel route 61. Furthermore, the general peculiar point Q(1) is displayed with an environmental cause classification of "LKAS non-operating point," and the general peculiar point Q(2) is displayed with an environmental cause classification of "point of reduced driving attention."

[0116] This allows the driver of the vehicle 100 to know that there is an LKAS non-operating point ahead of the vehicle 100 and that he or she should drive with caution.

[0117] 14 may be displayed when the vehicle 100 approaches within a certain distance, such as within 500 meters, from the general singular point. Also, when the vehicle 100 approaches within a certain distance from a general singular point of environmental cause classification R4: "LKAS non-operating point" while traveling at the second driving level, a warning regarding the general singular point may be issued by the presentation device 54.

[0118] 14 shows an example in which caution information including an environmental cause classification is distributed to the vehicle 100, but caution information including an environmental cause classification may also be distributed to a road administrator, which has the effect of providing an opportunity for the road administrator to prompt road repairs.

[0119] The distribution unit 27 distributes the caution information including the individual cause classification at a predetermined timing, for example, when an external request is received, or when an individual cause analysis is performed, etc. The recipients of the caution information including the individual cause classification include, for example, the vehicle 100 whose individual cause classification has been determined, the manager of the vehicle 100, a driving enforcement agency, or a driver's license issuing agency.

[0120] By delivering the caution information including the individual cause classification to the vehicle 100, the driver can recognize his / her poor driving skills, his / her reckless driving, or abnormalities in the tires or LKAS function of the vehicle 100. In addition, a vehicle manager or road enforcement agency that has received the caution information including the individual cause classification can provide the relevant driver with an opportunity to implement predetermined procedures or processes for safe driving or safe travel. In addition, a driver's license issuing agency that has received the caution information including the individual cause classification can provide advice to a license renewer, such as surrendering their license.

[0121] <D-3. Effects> Information collection and analysis device 204 according to the fourth embodiment includes distribution unit 27 that distributes caution-required information to the outside of information collection and analysis device 204. Therefore, caution-required information created by information collection and analysis device 204 can be used for driving assistance for vehicle 100, road repairs, and the like.

[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 a 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 referred to as "position information acquisition unit 11, etc.") in the probe information generation devices 101 and 104.

[0123] Furthermore, 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 201-204 are realized by a processing circuit 81 separate from the processing circuit 81 that realizes the probe information generation devices 101 and 104. That is, this separate 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, referred to as "information collection unit 21" etc.) in the information collection and analysis devices 201-204.

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

[0125] When the processing circuitry 81 is dedicated hardware, the processing circuitry 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 position 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 together 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 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 memory 83. That is, the probe information generation devices 101 and 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. 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. In other words, this program can be said to cause a computer to execute a 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 a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), or an EEPROM (Electrically Erasable Programmable Read Only Memory), a HDD (Hard Disk Drive), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD (Digital Versatile Disk) and its drive device, or any storage medium that will 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, the present invention 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 the above-mentioned functions by hardware, software, 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.

[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 Travel 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 and analysis device comprising: an information collection unit that, when a peculiar 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 linked to information on the peculiar event and information on a driving mode indicating the degree of the automatic driving control at the time the peculiar event occurred, from the vehicle; and an analysis unit that identifies the cause of the peculiar event as a cause classification based on the driving mode, and creates attention requiring information linking the peculiar event with the cause classification, wherein 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 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 a risk of lane departure, intervenes in the steering wheel operation and executes LKAS; and a third driving mode in which the automatic driving control device always controls the steering wheel operation of the vehicle.

2. The information collection and analysis device described in claim 1, wherein the probe information includes location information of the singular point where the singular event occurred and an individual ID unique to the vehicle or the driver of the vehicle, and the analysis unit determines whether the singular event is an environmentally caused event caused by the driving environment of the vehicle based on the location information of the singular point and the individual ID, classifies the driving environment that caused the environmentally caused event as an environmental cause classification based on the driving mode, and creates the attention requiring information linking the environmentally caused event, the environmental cause classification, and the location information of the singular point where the environmentally caused event occurred.

3. The information collection and analysis device described in claim 1 or claim 2, wherein the probe information includes location information of the singular point where the singular event occurred and an individual ID unique to the vehicle or the driver of the vehicle, and the analysis unit determines whether the singular event is an individual cause event caused by an individual cause unique to the vehicle or the driver based on the location information of the singular point and the individual ID, identifies the individual cause that caused the individual cause event as an individual cause classification based on the driving mode, and creates the attention requiring information linking the individual cause event, the individual cause classification, and the individual ID.

4. The information collection and analysis device according to claim 1, further comprising a distribution unit that distributes the caution information to an outside of the information collection and analysis device.

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

6. The information collection and analysis device described in claim 5, wherein the information collection unit collects the probe information from the vehicle equipped with a high-precision map database having road shape data on a lane-by-lane basis and a high-precision positioning device having sub-meter-level positioning accuracy and outputting the vehicle's position and driving lane, the probe information including lane-by-lane position information of the singular point obtained using the high-precision map database and the high-precision positioning device.

7. The information collection and analysis device described in claim 2, wherein the analysis unit determines that the peculiar events occurring for multiple individual IDs at the same peculiar point are environmentally caused events, and if lane departure occurs in the first driving mode but does not occur in the second driving mode or the third driving mode at the same peculiar point where the environmentally caused event occurs, classifies the same peculiar point as a point where the driver's driving attention is likely to be reduced.

8. The information collection and analysis device described in claim 2, wherein the analysis unit determines that the peculiar events occurring for multiple individual IDs at the same peculiar point are environmentally caused events, and if lane departure occurs in the first driving mode at the same peculiar point where the environmentally caused event occurs, and if lane departure occurs in the second driving mode due to the activation of the LKAS, the analysis unit classifies the same peculiar point as a point with a road shape where lane departure is likely to occur.

9. The information collection and analysis device described in claim 2, wherein the analysis unit determines that the peculiar events occurring for multiple individual IDs at the same peculiar point are environmentally caused events, and if, at the same peculiar point where the environmentally caused event occurred, the LKAS does not operate and lane departure occurs in the second driving mode, and lane departure occurs in the third driving mode, classifies the same peculiar point as a point where the LKAS does not operate.

10. The information collection and analysis device described in claim 2, wherein the analysis unit determines that the peculiar events occurring in multiple individual IDs at the same peculiar point are environmentally caused events, and if lane departure occurs in the second driving mode or the third driving mode at the same peculiar point where the environmentally caused event occurred and the rate of LKAS operation at that time decreases over time, classifies the same peculiar point as a point where road conditions are deteriorating and LKAS operation is unstable.

11. The information collection and analysis device described in claim 3, wherein when the singular event occurs for multiple individual IDs at the same singular point, the analysis unit defines the same singular point as a general singular point, and when a ratio of the singular points at which the singular event occurred for a specific individual ID that differ from the general singular points is equal to or greater than a predetermined threshold, determines that the singular event that occurred for the specific individual ID is the individual causal event.

12. The information collection and analysis device described in claim 3, wherein the analysis unit classifies the individual cause of the individual cause event that has occurred in the specific individual ID as the driver having poor driving skills when lane departure occurs in the first driving mode and LKAS is activated in the second driving mode in the individual cause event that has occurred in the specific individual ID.

13. The information collection and analysis device described in claim 3, wherein the analysis unit classifies the individual cause of the individual cause event occurring in the specific individual ID as a decline in the driver's driving skills when the number of specific points where the individual cause event occurred in a specific road section for a specific individual ID increases over time.

14. The information collection and analysis device described in claim 11, wherein, for a specific individual ID, when the ratio of the specific point of a first specific event, which is the specific event in which lane departure occurs without the LKAS operating in the second driving mode, and the specific point of a 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, the analysis unit determines that the first specific event and the second specific event are individually caused events and classifies the individual cause of the first specific event and the second specific event as a deterioration of an LKAS function.

15. The information gathering and analysis device described in claim 7, wherein the probe information includes a driver state that indicates the driving aptitude state regarding the driver's inattentiveness or decreased alertness, and the analysis unit assigns a sub-environmental cause classification of a point where dozing occurs frequently or a point where inattentiveness occurs frequently based on the driver state to the singular point of the environmentally caused event that has been classified as a point where the driver's driving attention is likely to decrease.

16. The information gathering and analysis device described in claim 8, wherein the probe information includes a driver state indicating the driving suitability state regarding the driver's inattentiveness or reduced alertness, and when the driver state indicates a good driving suitability state, the analysis unit assigns a sub-environmental cause classification of a point where special caution should be exercised when driving to the singular point of the environmentally caused event that has been subjected to the environmental cause classification of a point on a road shape where lane departure is likely to occur.

17. An information collection and analysis system comprising: a probe information generating device that creates and transmits probe information of a vehicle capable of automatic driving control by an automatic driving control device; and an information collection and analysis device that receives the probe information from the probe information generating device, wherein the probe information generating device comprises: an information acquiring unit that acquires a driving mode representing a mode of automatic driving control by the automatic driving control device and an operating status of an LKAS by the automatic driving control device; a lane departure detecting unit that detects lane departure of the vehicle; a probe information generating unit that generates the probe information including information on the peculiar event and information on the driving mode at the time of the occurrence of the peculiar event when the peculiar event including the lane departure or LKAS operation occurs; and a probe information transmitting unit that transmits the probe information to the information collection and analysis device, wherein the information collection and analysis device comprises: an information collecting unit that receives the probe information from the probe information generating device; and an analysis unit that identifies a cause of the peculiar event as a cause classification based on the driving mode, and creates attention requiring information linking the peculiar event with the cause classification, wherein the driving mode is An information collection and analysis system including: a first driving mode in which a driver operates the steering wheel of the vehicle and the automatic driving control device does not perform the steering operation; a second driving mode in which the driver normally operates the steering wheel and the automatic driving control device intervenes in the steering wheel operation and executes LKAS when it detects a risk of lane departure; and a third driving mode in which the automatic driving control device always controls the steering wheel operation of the vehicle.

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