Information providing device

Abstract

This system allows for the assessment of visibility impairment using a simple configuration. [Solution] The information providing device 10 includes an information acquisition unit 111 that acquires driving information including position information indicating the driving position of each of several vehicles in motion, time information indicating the driving time corresponding to the driving position, and steering information which is steering operation information; a generation unit 112 that generates steering error information indicating the steering prediction error, which is the error between the predicted value of steering and the measured value of steering for each of several vehicles on a predetermined road, based on the driving information; a prediction unit 113 that calculates the average of the steering prediction errors for each of a first predetermined period and a second predetermined period that is earlier than the first predetermined period, based on the steering error information, and predicts that visibility impairment occurred on the predetermined road during the first predetermined period when the average for the first predetermined period is greater than the average for the second predetermined period; and an output unit 114 that outputs visibility impairment information including the prediction result of the prediction unit 113.

Description

[Technical Field]

[0001] This invention relates to an information-providing device that provides information regarding the occurrence of visibility impairment. [Background technology]

[0002] Conventionally, a device of this type is known that is mounted on a vehicle and measures the particle size and number of flying snow particles, and calculates visibility at the vehicle's location based on the measurements of the flying snow particle count (see, for example, Patent Document 1). [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2003-44977 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] However, the configuration described in Patent Document 1 requires a dedicated vehicle equipped with a snow particle counting device to be driven each time a measurement is taken, making it difficult to efficiently grasp the occurrence of visibility impairment. [Means for solving the problem]

[0005] An information providing device according to one aspect of the present invention includes: a driving information acquisition unit that acquires driving information including position information indicating the driving position of each of a plurality of vehicles in motion, time information indicating the time of driving corresponding to the driving position, and steering information which is steering operation information; a road information acquisition unit that acquires road map information; a generation unit that generates steering error information indicating the steering prediction error, which is the error between the predicted value of steering and the measured value of steering for each of a plurality of vehicles on a predetermined road, based on the driving information and the road map information; a prediction unit that calculates the average of the steering prediction errors for a first predetermined period and a second predetermined period that is earlier than the first predetermined period, based on the steering error information, and predicts that visibility impairment occurred on the predetermined road during the first predetermined period when the average for the first predetermined period is greater than the average for the second predetermined period; and an output unit that outputs visibility impairment information including the prediction result of the prediction unit. [Effects of the Invention]

[0006] According to the present invention, the occurrence of visibility impairment can be grasped with a simple configuration. [Brief explanation of the drawing]

[0007] [Figure 1] A schematic diagram showing the overall configuration of an information provision system equipped with an information provision device according to an embodiment of the present invention. [Figure 2] A block diagram showing the main components of an in-vehicle terminal. [Figure 3] A block diagram showing the main components of the driving information storage device. [Figure 4] A block diagram showing the main components of an information providing device according to an embodiment of the present invention. [Figure 5] A diagram to explain steering prediction errors. [Figure 6A] A diagram showing an example of steering prediction error. [Figure 6B] A diagram illustrating another example of steering prediction error. [Figure 7] A flowchart showing an example of the processing performed in the calculation unit of Figure 4. [Figure 8] A flowchart showing the details of the process in step S15 of Figure 7. [Figure 9] A diagram showing an example of how visibility impairment information is displayed. [Modes for carrying out the invention]

[0008] Embodiments of the present invention will be described below with reference to Figures 1 to 9. An information providing device according to an embodiment of the present invention is a device for providing information on the occurrence of visibility obstruction on a road while a vehicle is traveling. Figure 1 is a diagram showing an example of the configuration of an information providing system equipped with the information providing device according to this embodiment. As shown in Figure 1, the information providing system 1 comprises an information providing device 10, an in-vehicle terminal 30, and a driving information storage device (hereinafter simply referred to as storage device) 40. The information providing device 10 and the storage device 40 are configured as a server device. The in-vehicle terminal 30 is configured to communicate with the information providing device 10 and the storage device 40 via a communication network 2.

[0009] Communication network 2 includes not only public wireless communication networks such as the Internet and mobile phone networks, but also closed communication networks established in designated management areas, such as wireless LAN, Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0010] The in-vehicle terminal 30 is installed in the vehicle 20. The vehicle 20 includes multiple vehicles 20-1, 20-2, ..., 20-n. The vehicle 20 may be a manually driven vehicle or an autonomous vehicle. Furthermore, the vehicle 20 may include vehicles of different make and model.

[0011] Figure 2 is a block diagram showing the main components of the in-vehicle terminal 30 according to this embodiment. The in-vehicle terminal 30 includes an electronic control unit (ECU) 31, a positioning sensor 32, an acceleration sensor 33, a steering angle sensor 34, a vehicle speed sensor 35, and a TCU (Telematic Control Unit) 36.

[0012] The positioning sensor 32 is, for example, a GPS sensor, which receives the positioning signal transmitted from GPS satellites and detects the absolute position (latitude, longitude, etc.) of the vehicle 20. Note that the positioning sensor 32 includes not only a GPS sensor but also sensors that perform positioning using radio waves transmitted from satellites of various countries called GNSS satellites including quasi-zenith orbit satellites.

[0013] The acceleration sensor 33 detects the acceleration in the left-right direction of the vehicle 20, that is, the lateral acceleration. Note that the acceleration sensor 33 may be configured to detect the acceleration in the front-rear direction and the acceleration in the up-down direction together with the lateral acceleration of the vehicle 20. The steering angle sensor 34 detects the steering angle of the steering wheel (not shown) of the vehicle 20. The vehicle speed sensor 35 detects the vehicle speed of the vehicle 20.

[0014] As shown in FIG. 2, the ECU 31 includes a computer having an arithmetic unit 310 such as a CPU, a storage unit 320 such as a ROM and a RAM, and other peripheral circuits (not shown) such as an I / O interface. The arithmetic unit 310 functions as a sensor value acquisition unit 311 and a communication control unit 312 by executing a program stored in the storage unit 320 in advance.

[0015] The sensor value acquisition unit 311 acquires the detection values of the respective sensors 33 to 36 and the absolute position of the vehicle 20 detected by the positioning sensor 32 at a predetermined period. The communication control unit 312 transmits the information (hereinafter referred to as driving information) acquired by the sensor value acquisition unit 311 to the communication network 2 at a predetermined period via the TCU 36 together with a vehicle ID capable of identifying the vehicle 20.

[0016] FIG. 3 is a block diagram showing a main part configuration of the storage device 40 according to the present embodiment. The storage device 40 includes a computer having an arithmetic unit 41 such as a CPU, a storage unit 42 such as a ROM and a RAM, a communication unit 43, and other peripheral circuits (not shown) such as an I / O interface. The arithmetic unit 41 functions as an information reception unit 411 by executing a program stored in the storage unit 42. The communication unit 43 is a communication interface that connects the storage device 40 to the communication network 2.

[0017] The information receiving unit 411 receives driving information transmitted from the in-vehicle terminals 30 of each vehicle 20 traveling on the road. The information receiving unit 411 stores the driving information received from multiple vehicles 20 (in-vehicle terminals 30) in the storage unit 42. The vehicle 20 that transmitted the driving information can be identified by the vehicle ID associated with the driving information.

[0018] The driving information includes position information indicating the location of the vehicle 20, driving time information indicating the time the vehicle 20 traveled to that location, and acceleration information indicating the acceleration of the vehicle 20. The acceleration information includes information on the lateral acceleration of the vehicle 20 detected by the acceleration sensor 33. The driving information also includes vehicle speed information indicating the speed at which the vehicle 20 is traveling. The vehicle speed information shows the sensor value from the vehicle speed sensor 35, i.e., the measured value of the vehicle 20's speed. Furthermore, the driving information includes steering angle information indicating the steering angle of the vehicle 20's steering wheel. The steering angle information shows the sensor value from the steering angle sensor 34, i.e., the measured value of the vehicle 20's steering angle.

[0019] Figure 4 is a block diagram showing the main components of the information providing device 10 according to this embodiment. The information providing device 10 predicts the occurrence of visibility obstruction based on driving information of multiple vehicles 20 stored in the storage device 40. The information providing device 10 outputs information including the prediction result (hereinafter referred to as visibility obstruction information) to a terminal owned by a road management company or the like.

[0020] The information providing device 10 is comprised of a computer having an arithmetic unit 110 such as a CPU, a storage unit 120 such as ROM and RAM, a communication unit 13, and other peripheral circuits (not shown) such as an I / O interface. The storage unit 120 stores map information, including road maps, and various information processed by the arithmetic unit 110. The communication unit 13 is a communication interface that connects the information providing device 10 to the communication network 2.

[0021] The arithmetic unit 110 functions as an information acquisition unit 111, a generation unit 112, a prediction unit 113, and an output unit 114 by executing a program stored in the storage unit 120.

[0022] The information acquisition unit 111 acquires driving information of multiple vehicles 20 traveling in a designated area from the storage device 40 via the communication unit 13. More specifically, when the information acquisition unit 111 receives an instruction to output visibility obstruction information via the communication unit 13, it identifies the vehicle 20 whose current driving position is included in the designated area, that is, the vehicle 20 that is traveling within the designated area. Visibility obstruction information will be described later using Figure 9. Whether or not the current driving position is included in the designated area can be determined based on the driving information of each vehicle 20 stored in the storage device 40, specifically the position information and driving time information. The information acquisition unit 111 acquires the driving information of the identified vehicle 20 from the storage device 40.

[0023] The designated area can be set by the user, and the output instruction for visibility impairment information shall include information indicating the designated area (hereinafter referred to as "designated area information"). Multiple designated areas may be set. For example, in Figure 9 described later, cities A, B, C, and D may be set as designated areas. The output instruction for visibility impairment information is transmitted from a terminal of a road management company or similar entity.

[0024] Furthermore, the information acquisition unit 111 reads map information from the storage unit 12 and obtains the road map included in the map information. More specifically, when the information acquisition unit 111 receives an instruction to output visibility impairment information via the communication unit 13, it reads the road map including the specified area from the storage unit 12.

[0025] The generation unit 112 generates steering error information for each of the multiple vehicles 20 traveling in the designated area, based on the driving information and road map information acquired by the information acquisition unit 111. This information represents the steering prediction error, which is the error between the predicted steering value and the measured value. Hereinafter, the steering prediction error will also be referred to as the steering prediction error. The steering prediction error represents the complexity of the driver's steering operation.

[0026] Here, the generation of steering error information will be described. The generation unit 112 predicts the steering angle of a predetermined point based on the steering angle information corresponding to a plurality of points (hereinafter referred to as reference points) in front of the traveling direction from a predetermined point within the designated area acquired by the information acquisition unit 111. The predetermined point is a point that the vehicle 20 traveling in the evaluation target section passes at a predetermined time interval or a predetermined distance interval. The generation unit 112 calculates a steering prediction error based on the predicted steering angle of the predetermined point. More specifically, the generation unit 112 calculates the difference between the predicted steering angle of the predetermined point and the steering angle indicated by the steering angle information corresponding to the predetermined point acquired by the information acquisition unit 111 as the steering prediction error.

[0027] The generation unit 112 generates steering error information associating the traveling position with the steering prediction error at that traveling position for each road section of a predetermined length included in the designated area. The predetermined length is set to the maximum distance of the visibility (for example, 200 m) that may cause a visibility obstacle or a value larger than that. The visibility obstacle occurs, for example, when snow particles are lifted in front of the vehicle 20 due to snowfall or strong wind after snowfall, thereby shortening the visibility.

[0028] FIG. 5 is a diagram for explaining the steering prediction error. θ(t n ) in the figure is the steering angle indicated by the steering angle information corresponding to the predetermined point (traveling position at time t n ) acquired by the information acquisition unit 111. θp(t n ) is the steering angle of the predetermined point predicted based on the steering angle information corresponding to the reference points (traveling positions at times t n-1 , t n-2 , t n-3 ) in front of the traveling direction from the predetermined point. e(t n ) is the difference between θ(t n ) and θp(t n ), that is, the steering prediction error at the predetermined point.

[0029] The generation unit 112 generates steering error information indicating the steering prediction error, calculated based on the driving information of the vehicle 20 that was driving in the designated area during a predetermined past period (hereinafter referred to as the comparison period). The generation unit 112 also generates steering error information indicating the steering prediction error, calculated based on the driving information of the vehicle 20 that is currently driving in the designated area, more specifically, based on the driving information of the vehicle 20 that was driving in the designated area during a predetermined period from the present to a predetermined past time.

[0030] The generation unit 112 determines the comparison period from a period without snowfall (such as summer). Specifically, the generation unit 112 obtains weather information for a specified area from an external server (not shown, hereinafter referred to as the weather information server) that distributes weather information, identifies a period without snowfall and strong winds after snowfall based on the obtained weather information, and determines that period as the comparison period. The generation unit 112 may also determine the comparison period based on instructions from the user. That is, the output instruction for visibility impairment information may include information specifying the comparison period.

[0031] The prediction unit 113 predicts the occurrence of visibility impairment in a visibility impairment based on the steering error information generated by the generation unit 112. Here, the prediction of the occurrence of visibility impairment will be explained.

[0032] Figure 6A shows an example of steering prediction error calculated based on driving information of vehicle 20 traveling in a designated area during the comparison period. Figure 6B shows an example of steering prediction error calculated based on driving information of vehicle 20 currently traveling in a designated area, more specifically, based on driving information of vehicle 20 traveling in a designated area during a predetermined period from the present to a predetermined point in the past. Characteristics P1 in Figure 6A and characteristics P2 in Figure 6B show the steering prediction error for each driving position, calculated based on driving information obtained from one vehicle 20 traveling on a road within the designated area.

[0033] Comparing the steering prediction error during the comparison period (characteristic P1) with the current steering prediction error (characteristic P2), the steering prediction error at each driving position is greater for characteristic P2 than for characteristic P1. Thus, when the current steering prediction error is greater than the steering prediction error during the comparison period, it can be estimated that visibility impairment is currently occurring on the road where vehicle 20 is traveling, making the driver's steering operation more difficult.

[0034] The prediction unit 113 then calculates the average value of the absolute values ​​of the steering prediction errors of each vehicle 20 that is traveling in the designated area during the comparison period (hereinafter referred to as the normal average) and the average value of the absolute values ​​of the steering prediction errors of each vehicle 20 that is currently traveling in the designated area (hereinafter referred to as the current average). The prediction unit 113 then predicts whether or not visibility impairment will occur in the designated area according to the difference (deviation) between the current average and the normal average. Specifically, when the deviation is less than the threshold Th, the prediction unit 113 predicts that visibility impairment will not occur. On the other hand, when the deviation is greater than or equal to the threshold Th, it predicts that visibility impairment will occur. Note that the deviation is not limited to the difference between the normal average and the current average, but may be expressed by other values.

[0035] The prediction unit 113 may predict the level of visibility impairment in a specified area according to the degree of deviation between the current average and the normal average. Specifically, when the degree of deviation is less than the threshold Th_a1 (>Th), the generation unit 112 predicts the level of visibility impairment in the affected section as "low" (visibility: 200~100m). Also, when the degree of deviation is greater than or equal to the threshold Th_a1 and less than the threshold Th_a2 (>Th_a1), the generation unit 112 predicts the level of visibility impairment in the affected section as "medium" (visibility: 100~50m). Furthermore, when the degree of deviation is greater than or equal to the threshold Th_a2, the generation unit 112 predicts the level of visibility impairment in the affected section as "high" (visibility: less than 50m).

[0036] The thresholds Th, Th_a1, and Th_a2 mentioned above are pre-stored in the memory unit 12. Furthermore, the thresholds Th, Th_a1, and Th_a2 may be values ​​obtained by multiplying the normal average by a predetermined multiplier, or they may be values ​​determined based on past observation results or driving simulation results. In addition, the level of visibility impairment is not limited to the three stages of "low," "medium," and "high," but may be classified into, for example, four or more stages.

[0037] The output unit 114 outputs information that associates the prediction result of the visibility impairment by the prediction unit 113 with the road information acquired by the information acquisition unit 111 as visibility impairment information to the terminal that sent the instruction to output the visibility impairment information. The output unit 114 may also output the visibility impairment information to a predetermined output destination (such as a display device or terminal).

[0038] Figure 7 is a flowchart showing an example of processing performed by the arithmetic unit 110 (CPU) of the information providing device 10 according to a predetermined program. The processing shown in this flowchart is repeated at predetermined intervals while the information providing device 10 is running. First, in step S11, it is determined whether or not an output instruction for visibility obstruction information has been input (received). As mentioned above, the output instruction includes specified area information indicating a specified area.

[0039] If the result in step S11 is negative, the process terminates. If the result in step S11 is positive, in step S12, road information included in the map information stored in the storage unit 120 is obtained. More specifically, road information for the specified area is obtained. In step S13, driving information of vehicles 20 currently traveling in the specified area is obtained from the storage device 40 via the communication unit 13. More specifically, driving information is obtained in which the time indicated by the driving time information is included in a predetermined period from the present to a predetermined past time, and the position indicated by the position information is included in the specified area. In this case, if there are multiple vehicles 20 traveling in the specified area, driving information corresponding to each of the multiple vehicles 20 is obtained.

[0040] In step S14, past driving information of the vehicle 20 is obtained from the storage device 40 via the communication unit 13. More specifically, driving information is obtained in which the driving time indicated by the driving time information is included in the comparison period and the driving position indicated by the location information is included in the specified area. At this time, if there are multiple vehicles 20 that have driven in the specified area during the comparison period, driving information corresponding to each of the multiple vehicles 20 is obtained.

[0041] In step S15, the visibility impairment prediction process is executed. Here, the process in step S15 will be explained in detail using Figure 8. Figure 8 is a flowchart detailing the visibility impairment prediction process (the process in step S15 of Figure 7). Note that the processes in steps S21 to S25 are executed for each predetermined section of roads within the designated area, more specifically, for each section of a predetermined length along the direction of travel of the road. Furthermore, if the designated area includes multiple roads, more specifically, multiple roads with different names (for example, National Highway X, Prefectural Highway Y), the visibility impairment prediction process is executed for each road.

[0042] In step S21, the steering prediction error (current steering prediction error) of the vehicle 20 currently traveling in a predetermined section is calculated based on the driving information acquired in step S13, i.e., the current driving information. If there are multiple vehicles 20 currently traveling in the predetermined section, the current steering prediction error corresponding to each of the multiple vehicles 20 is calculated.

[0043] In step S22, the steering prediction error (past steering prediction error) of a vehicle 20 traveling in a predetermined section during the comparison period is calculated based on the driving information acquired in step S14, i.e., the driving information corresponding to the comparison period. If there are multiple vehicles 20 traveling in a predetermined section during the comparison period, the past steering prediction error corresponding to each of the multiple vehicles 20 is calculated. In step S23, it is determined whether the deviation between the average absolute value of the current steering prediction error and the average absolute value of the past steering prediction error is greater than or equal to a predetermined threshold.

[0044] If the result in step S23 is positive, then in step S24, it is predicted that visibility impairment occurs in the predetermined section. On the other hand, if the result in step S23 is negative, then in step S25, it is predicted that visibility impairment does not occur in the predetermined section.

[0045] In step S26, it is determined whether there is a section in the specified area where the prediction of visibility impairment (processing in steps S21 to S26) has not been performed. If this is denied in step S26, the process returns to step S21. On the other hand, if it is confirmed in step S26, the process terminates.

[0046] Returning to the explanation of Figure 7, in step S16, after step S15, visibility impairment information is generated by associating the result of the visibility impairment prediction process in step S15 with the road information obtained in step S12. In step S17, the visibility impairment information generated in step S16 is output. This allows the user to recognize early whether or not visibility impairment has occurred in the specified area.

[0047] Figure 9 shows an example of visibility impairment information display. Figure 9 shows an example of visibility impairment information when cities A, B, C, and D are specified by the user as designated areas. In the example in Figure 9, roads RD1, RD2, and RD3, which include sections where visibility impairment is predicted to occur among the roads included in the designated area, are highlighted with dashed lines. The other roads are roads where visibility impairment is not predicted to occur, that is, roads where visibility is predicted to be greater than 200m and visibility is good. Roads filled in black are roads where vehicle 20 has never traveled, etc., and therefore vehicle 20 travel information cannot be obtained and the occurrence of visibility impairment cannot be predicted.

[0048] Furthermore, sections within roads RD1, RD2, and RD3 where visibility impairment is predicted may be displayed using colors or patterns corresponding to the level of visibility impairment. For example, sections where visibility is predicted to be less than 50m, sections where visibility is predicted to be between 100m and 50m, and sections where visibility is predicted to be between 200m and 100m may be displayed using different colors or patterns. This allows users to recognize not only roads where visibility impairment is occurring, but also the sections within those roads where visibility impairment is occurring and the level of visibility impairment in those sections.

[0049] This embodiment can provide the following effects and advantages. (1) The information providing device 10 includes an information acquisition unit 111 that acquires driving information including location information indicating the driving position of each of the multiple vehicles 20 in motion, time information indicating the time of driving corresponding to the driving position, and steering information which is steering operation information, as well as road map information; a generation unit 112 that generates steering error information indicating the steering prediction error, which is the error between the actual value and the predicted value of steering for each of the multiple vehicles 20 on a predetermined road, based on the driving information and road map information; a prediction unit 113 that calculates the average of the steering prediction errors for each of the first predetermined period and the second predetermined period which is earlier than the first predetermined period, based on the steering error information, and predicts that visibility impairment occurred on the predetermined road during the first predetermined period when the average for the first predetermined period is greater than the average for the second predetermined period; and an output unit 114 that outputs information including the prediction result of the prediction unit 113.

[0050] This allows information regarding the occurrence of visibility impairment to be provided to users such as road management companies with a simple configuration. Furthermore, based on the information provided in this way, users can quickly take action such as prohibiting vehicles from passing through road sections where visibility impairment is occurring or notifying drivers of the occurrence of visibility impairment. As a result, traffic safety can be improved.

[0051] (2) The information acquisition unit 111, acting as a receiving unit, receives an output instruction for visibility obstruction information specifying a designated road. The output unit 114 transmits the visibility obstruction information to the terminal that sent the output instruction. The designated road is a road belonging to the administrative district (City A, City B, City C, and City D in Figure 9) specified in the output instruction. This allows the user to understand the visibility obstruction situation on the designated road.

[0052] (3) Visibility impairment information is information that can be displayed on a display device, and the output unit 114 outputs the visibility impairment information to a display device such as a display. This allows the user to visually recognize the visibility impairment information.

[0053] The above embodiment can be modified into various forms. Several modifications are described below. In the above embodiment, the prediction unit 113 predicts that visibility impairment occurred on the predetermined road during the first predetermined period when the average steering prediction error of a vehicle 20 traveling on the predetermined road during the first predetermined period, which is a predetermined period from the present to a predetermined past time, is greater than the average steering prediction error of a vehicle 20 traveling on the predetermined road during the second predetermined period, which is earlier than the first predetermined period. However, the first predetermined period may be a predetermined period from the first predetermined past time to the second predetermined past time. In addition, the output instruction for visibility impairment information may include information specifying the first predetermined period. With this configuration, the user can grasp the visibility impairment situation at any point in the past on the specified road.

[0054] Furthermore, in the above embodiment, the generation unit 112 generates steering error information indicating the steering prediction error for each of the multiple vehicles 20 on a predetermined road, based on the driving information of the multiple vehicles 20 acquired by the information acquisition unit 111 as a driving information acquisition unit and the road map information acquired by the information acquisition unit 111 as a road information acquisition unit. However, when generating steering error information, the generation unit may exclude the driving information of a vehicle 20 that is changing lanes from the driving information of the multiple vehicles 20 acquired by the driving information acquisition unit. This can improve the accuracy of predicting the occurrence of visibility impairment. In this case, the generation unit may detect a vehicle 20 that is changing lanes by comparing the position information of each of the multiple vehicles 20 with the road map information. Also, if the driving information of each of the multiple vehicles 20 includes turn signal information indicating the operation of the turn signal, the generation unit may detect a vehicle 20 that is changing lanes based on the turn signal information.

[0055] Furthermore, in the above embodiment, the system predicts the occurrence of visibility impairment for roads belonging to the administrative district specified in the output instruction (Figure 9). However, the designated roads that are subject to visibility impairment prediction are not limited to these. They may also be designated roads, roads with road names specified in the output instruction, or roads belonging to the map mesh specified in the output instruction.

[0056] Furthermore, in the above embodiment, the prediction unit 113 predicts the occurrence of visibility obstruction on a predetermined road based on steering prediction errors in a first predetermined period and a second predetermined period prior to the first predetermined period on the predetermined road. However, the configuration of the prediction unit is not limited to this. When visibility obstruction occurs, the driver of the vehicle 20 may lean forward to operate the vehicle in order to search for a target object that can be distinguished from snow in the space in front of the vehicle 20. Taking this into consideration, the prediction unit may predict that visibility obstruction is occurring on the predetermined road when a forward-leaning posture of the driver of the vehicle 20 traveling on the predetermined road is detected. That is, the prediction unit may predict the occurrence of visibility obstruction using information indicating the driving posture of the driver of the vehicle 20 (hereinafter referred to as posture information) instead of, or together with, the steering prediction error. In this case, the communication control unit 312 includes information detected by a seating posture sensor (not shown) provided in the driver's seat of the vehicle 20 (hereinafter referred to as posture information) in the driving information transmitted to the information providing device 10. The prediction unit detects the forward lean posture of the driver of the vehicle 20 based on the posture information included in the driving information.

[0057] Furthermore, in the above embodiment, the storage device 40 stores driving information of multiple vehicles 20, and the information acquisition unit 111 acquires driving information of multiple vehicles 20 corresponding to the road under evaluation from the storage device 40 via the communication unit 13. However, the driving information of multiple vehicles 20 may also be stored in the storage unit 120 of the information providing device 10. In that case, the information acquisition unit reads and acquires the driving information of multiple vehicles 20 corresponding to the road under evaluation from the storage unit 120. Moreover, in the above embodiment, the information providing device 10 was configured with a single server device, but the information providing device may be configured with multiple devices.

[0058] The above description is merely an example, and the present invention is not limited by the embodiments and modifications described above, as long as the features of the present invention are not impaired. It is also possible to arbitrarily combine one or more of the above embodiments and modifications, and to combine modifications with each other. [Explanation of Symbols]

[0059] 10 Information provision device, 20, 20-1 to 20-n Vehicle, 30 In-vehicle terminal, 40 Driving information storage device, 110 Calculation unit, 111 Information acquisition unit, 112 Generation unit, 113 Prediction unit, 114 Output unit, 120 Storage unit

Claims

1. A driving information acquisition unit acquires driving information including position information indicating the driving position of each of several vehicles in motion, time information indicating the time of travel corresponding to the driving position, and steering information which is steering operation information. A road information acquisition unit that acquires road map information, A generation unit generates steering error information that indicates the steering prediction error, which is the error between the predicted steering value and the measured value, for each of the plurality of vehicles on a predetermined road, based on the aforementioned driving information and the aforementioned road map information. Based on the steering error information, the predictive unit calculates the average of the steering prediction error for a first predetermined period and a second predetermined period preceding the first predetermined period, and predicts that visibility impairment occurred on the predetermined road during the first predetermined period when the average for the first predetermined period is greater than the average for the second predetermined period. An information providing device characterized by comprising: an output unit that outputs visibility obstruction information including the prediction results of the prediction unit.

2. In the information providing device described in claim 1, The system further includes a receiving unit that receives an output instruction for the visibility obstruction information, The information providing device is characterized in that the predetermined road is a road that has been given the road name specified in the output instruction.

3. In the information providing device described in claim 1, The system further includes a receiving unit that receives an output instruction for the visibility obstruction information, The information providing device is characterized in that the predetermined road is a road belonging to a map mesh or administrative district specified in the output instruction.

4. In the information providing device described in claim 1, The system further includes a receiving unit that receives an output instruction for the visibility obstruction information, The information providing device is characterized in that the output unit transmits the visibility obstruction information to the terminal that sent the output instruction.

5. In the information providing device according to any one of claims 1 to 3, The aforementioned visibility impairment information is information that can be displayed on a display device. The information providing device is characterized in that the output unit outputs the visibility obstruction information to the display device.

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