Information providing device

Abstract

To enable an occurrence status of vehicle standstill to be accurately assessed with a simple configuration.SOLUTION: An information provision device 10 comprises: an information acquisition section 111 which acquires travel information including positional information of a vehicle traveling within a predetermined region and vehicle information including at least one of a vehicle class and a vehicle weight, map information including a road map, and weather information corresponding to the predetermined region; a prediction section 112 which recognizes a travel state in the predetermined region of a specific vehicle belonging to a predetermined vehicle class or having weight equal to or greater than predetermined weight based on the travel information when the weather information indicates that snowfall has occurred within the predetermined region during a predetermined period from a certain past time to the present time and predicts an occurrence of vehicle standstill in the predetermined region based on a recognition result; and an output section 113 which outputs vehicle standstill risk information in which a prediction result by the prediction section 112 is associated with the road map within the predetermined region.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information providing device that provides information regarding the occurrence of vehicles being stranded on a road. [Background technology]

[0002] Conventionally, there have been known devices that predict the risk of traffic disruptions occurring on roads on which vehicles are traveling based on congestion level information and weather information (see, for example, Patent Document 1). The device described in Patent Document 1 predicts the occurrence of traffic disruptions based on the amount of snowfall per hour and the congestion level. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-55207 Summary of the Invention [Problem to be solved by the invention]

[0004] However, once vehicles become stranded due to snow accumulation, the stranded vehicles can hinder snow removal work, leading to a large-scale stranding, and in some cases, roads may be closed for several days, paralyzing traffic functions. Therefore, there is a need to predict and prevent stranding from occurring. However, the configuration described in Patent Document 1, which predicts the occurrence of traffic disruptions based on congestion levels, has difficulty predicting stranding due to snow accumulation, which is not correlated with congestion levels. [Means for solving the problem]

[0005] An information providing device according to one aspect of the present invention comprises a driving information acquisition unit that acquires driving information including position information of a vehicle traveling in a specified area and vehicle information including at least one of information on the vehicle's class and weight; a map information acquisition unit that acquires map information including a road map; a weather information acquisition unit that acquires weather information corresponding to the specified area; a recognition unit that, when the weather information indicates that snowfall has occurred in the specified area during a specified period from a specified point in the past to the present, recognizes the driving conditions within the specified area of ​​a specific vehicle having a specified class or a specified weight or more based on the driving information acquired by the driving information acquisition unit; a prediction unit that predicts the occurrence of a vehicle becoming stuck in the specified area based on the recognition result of the recognition unit; and an output unit that outputs stuck risk information that matches the prediction result by the prediction unit with a road map of the specified area. The recognition unit recognizes at least one of the number of specific vehicles traveling within the predetermined area and the proportion of the specific vehicles among all vehicles traveling within the predetermined area as the driving conditions. The prediction unit predicts a higher degree of likelihood of vehicles becoming stuck within the predetermined area as the value of the number or proportion of the specific vehicles indicated by the driving conditions recognized by the recognition unit increases. [Effects of the Invention]

[0006] According to the present invention, the occurrence of a vehicle being stuck can be grasped with a simple configuration. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a diagram showing an example of the configuration of an information providing system including an information providing device according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing the configuration of a main part of the in-vehicle device. [Figure 3] 1 is a block diagram showing a configuration of a main part of an information providing device according to an embodiment of the present invention; [Figure 4] FIG. 10 is a diagram showing an example of display of stranding risk information. [Figure 5A] 4 is a flowchart showing an example of processing executed by the calculation unit of FIG. 3. [Figure 5B] 10 is a flowchart showing another example of the processing executed by the calculation unit of FIG. 3. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment of the present invention will be described with reference to Figs. 1 to 5B. An information providing device according to an embodiment of the present invention is a device for providing information regarding the occurrence of a vehicle being stuck on a road (hereinafter referred to as "stuck vehicle"). Fig. 1 is a diagram showing an example of the configuration of an information providing system including an information providing device according to this embodiment. As shown in Fig. 1, the information providing system 1 includes an information providing device 10 and an in-vehicle device 30. The information providing device 10 is configured as a server device. The in-vehicle device 30 is configured to be able to communicate with the information providing device 10 via a communication network 2.

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

[0010] The in-vehicle device 30 is mounted on a vehicle 20. The vehicle 20 includes a plurality of vehicles 20-1, 20-2, ..., 20-n. The vehicle 20 may be a manually driven vehicle or an automatically driven vehicle. The vehicle 20 may also include vehicles of different models and grades.

[0011] 2 is a block diagram showing the configuration of the main parts of the in-vehicle device 30 according to this embodiment. The in-vehicle device 30 includes an electronic control unit (ECU) 31, a positioning unit 32, an internal sensor group 33, and a TCU (Telematic Control Unit) 34.

[0012] The positioning unit (GNSS unit) 32 is, for example, a GPS sensor that receives positioning signals transmitted from GPS satellites and detects the absolute position (latitude, longitude, etc.) of the vehicle 20. Note that the positioning unit 32 includes not only GPS sensors 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 internal sensor group 33 is a collective term for a plurality of sensors (internal sensors) that detect the driving state of the vehicle 20. For example, the internal sensor group 33 includes sensors that detect the operation of the accelerator pedal, the operation of the brake pedal, the operation of the steering wheel, etc.

[0014] The TCU (Telematic Control Unit) 34 is an ECU that performs wireless communication with external devices such as the information providing device 10 via the communication network 2. The TCU 34 may be configured as a part of the ECU 31.

[0015] 2, the ECU 31 includes a computer having a calculation 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 calculation unit 310 executes a program stored in advance in the storage unit 320, thereby functioning as a sensor value acquisition unit 311 and a communication control unit 312.

[0016] The sensor value acquisition unit 311 acquires information detected by the positioning unit 32 (the absolute position of the vehicle 20) at predetermined intervals.

[0017] The communication control unit 312 transmits travel information including position information indicating the sensor value (absolute position of the vehicle 20) of the positioning unit 32 acquired by the sensor value acquisition unit 311 to the information providing device 10 at predetermined intervals via the TCU 34. The travel information includes a vehicle ID (vehicle identification information) that can identify the vehicle 20. The travel information also includes transmission date and time information that indicates the date and time when the travel information was transmitted. Re do.

[0018] 3 is a block diagram showing the configuration of the main parts of the information providing device 10 according to this embodiment. The information providing device 10 includes a computer having a calculation unit 11 such as a CPU, a storage unit 12 such as a ROM and a RAM, and other peripheral circuits (not shown) such as an I / O interface. The storage unit 12 stores map information including a road map (hereinafter referred to as a road map) and various information processed by the calculation unit 11.

[0019] The calculation unit 11 executes the programs stored in the storage unit 12 to function as an information acquisition unit 111 , a prediction unit 112 , an output unit 113 , and a communication control unit 114 .

[0020] The information acquisition unit 111 acquires driving information. More specifically, the information acquisition unit 111 receives driving information from the in-vehicle devices 30 of each of a plurality of vehicles 20 (20-1, 20-2, . . . , 20-n) traveling on a road via the communication control unit 114. The information acquisition unit 111 can identify the vehicle 20 that transmitted the driving information from among the plurality of vehicles 20 traveling on the road, based on the vehicle identification information included in the driving information. The information acquisition unit 111 stores the driving information received from the plurality of vehicles 20 (in-vehicle devices 30) in the storage unit 12. When the communication control unit 114 receives an instruction to output strandedness risk information, the information acquisition unit 111 identifies the vehicles 20 whose current driving positions are included in the designated area, i.e., the vehicles 20 traveling within the designated area, based on the transmission date and time information and location information included in the driving information received from each vehicle 20. Note that the designated area can be set by the user, and information indicating the designated area is included in the instruction to output strandedness risk information. It is possible to set multiple designated areas. For example, in FIG. 4 described later, City A, City B, City C, and City D may be set as designated areas. The instruction to output the stuck road risk information is transmitted from a terminal of a road management company or the like. The stuck road risk information will be described later with reference to FIG. 4.

[0021] Furthermore, the information acquisition unit 111 reads map information from the storage unit 12 and acquires a road map included in the map information. More specifically, when an output instruction for stuck-state risk information is received by the communication control unit 114, the information acquisition unit 111 reads a road map including the specified area from the storage unit 12. Furthermore, the information acquisition unit 111 acquires information about the weather in the specified area (hereinafter referred to as weather information) via the communication control unit 114 from an external server (not shown) that distributes weather information (hereinafter referred to as weather information server).

[0022] The prediction unit 112 predicts the occurrence of vehicle stranding in the designated area when the weather information for the designated area acquired by the information acquisition unit 111 indicates that snowfall has occurred within a specified time period from the current time, i.e., within a specified period from a time point in the past before the specified time period to the current time. The specified time period can be set by the user, and information indicating the specified time period is included in the output instruction for the stranding risk information. The specified time period may be a predetermined time period.

[0023] A stuck vehicle occurs when a vehicle becomes stuck on a road due to snow accumulation. A stuck vehicle occurs when the tires of a vehicle stopped on a packed snow road sink into the packed snow, forming a depression in the road surface and preventing the tire from escaping. The depression formed on the packed snow road surface becomes deeper the heavier the stopped vehicle. Therefore, when a heavy vehicle such as a truck (hereinafter referred to as a specific vehicle) stops on a packed snow road surface, it is more likely to become stuck. Furthermore, if another specific vehicle is among the vehicles following the stuck specific vehicle, that specific vehicle may become the starting point for a new stuck vehicle. In this way, when there are many specific vehicles on a road after snow accumulation, a stuck vehicle is more likely to occur and the scale of the stuck vehicle may increase. Taking this into consideration, the prediction unit 112 predicts the occurrence of a stuck vehicle based on the driving status of the specific vehicle among the vehicles traveling within the specified area.

[0024] Here, the prediction of the occurrence of a vehicle being stuck by the prediction unit 112 will be described in detail. First, the prediction unit 112 determines whether the vehicle 20 is traveling within a designated area based on the transmission date and time information and location information included in the traveling information of the vehicle 20 stored in the memory unit 12. If it is determined that the vehicle 20 is traveling within the designated area, the prediction unit 112 classifies the vehicle 20 into a designated vehicle or a general vehicle other than the designated vehicle based on the vehicle identification information included in the traveling information of the vehicle 20. More specifically, the prediction unit 112 recognizes the model and grade of the vehicle 20 based on the vehicle identification information. When the vehicle identification information includes a vehicle identification number, the prediction unit 112 accesses a database (not shown) managed by the manufacturer of the vehicle 20, etc., via the communication control unit 114. Specifically, the database stores vehicle information such as the model and grade associated with the vehicle identification number, and recognizes the model and grade of the vehicle 20. The prediction unit 112 further recognizes the rank and weight of the vehicle 20 based on the model and grade. The prediction unit 112 classifies the vehicle 20 as a specific vehicle when the vehicle 20 has a predetermined vehicle class or when the weight of the vehicle 20 is equal to or greater than a predetermined weight. On the other hand, when the vehicle 20 does not have the predetermined vehicle class or when the weight of the vehicle 20 is less than the predetermined weight, the prediction unit 112 classifies the vehicle 20 as a general vehicle. The predetermined vehicle class is a vehicle class in which the vehicle is expected to have a weight equal to or greater than a predetermined weight. The vehicle class and weight for classifying the vehicle 20 as a specific vehicle or a general vehicle may be set by the user. In other words, the output instruction for the stuck-stand risk information may include information indicating the vehicle class and weight for classifying the vehicle 20 as a specific vehicle or a general vehicle.

[0025] Next, the prediction unit 112 counts the number of vehicles 20 classified as specific vehicles (hereinafter, may be referred to as specific vehicles 20) and recognizes the count result as the driving status of the specific vehicles in the designated area. Finally, the prediction unit 112 predicts the occurrence of a vehicle stall in the designated area based on the driving status of the specific vehicles in the designated area. Specifically, the prediction unit 112 predicts that the greater the number of specific vehicles 20 in the designated area, the higher the likelihood of a vehicle stall occurring in the designated area. Note that the prediction unit 112 may recognize the proportion of specific vehicles 20 in the total number of vehicles 20 traveling in the designated area as the driving status of the specific vehicles in the designated area. In this case, the prediction unit 112 predicts that the greater the proportion of specific vehicles 20 in the total number of vehicles 20 traveling in the designated area, the higher the likelihood of a vehicle stall occurring in the designated area.

[0026] The prediction unit 112 generates stuck-vehicle risk information by associating the predicted result of vehicle stuckness with the road map acquired by the information acquisition unit 111. The output unit 113 outputs the stuck-vehicle risk information generated by the prediction unit 112.

[0027] The communication control unit 114 controls a communication unit (not shown) to transmit and receive data to and from external devices, etc. Specifically, the communication control unit 114 acquires weather information, map information, etc. periodically or at any timing from various servers connected to the communication network 2. The communication control unit 114 stores the information acquired from the various servers in the storage unit 12. The communication control unit 114 also transmits and receives data (such as driving information) to and from the on-board device 30 of the vehicle 20 via the communication network 2. Furthermore, the communication control unit 114 transmits and receives data to and from terminals of users (hereinafter referred to as user terminals) such as road management companies. More specifically, the communication control unit 114 receives an output instruction for stranded road risk information transmitted from the user terminal via the communication network 2. When the output unit 113 outputs the stranded road risk information in response to the output instruction, the communication control unit 114 transmits the stranded road risk information to the user terminal that sent the output instruction via the communication network 2. When the stuck-vehicle risk information is information that can be displayed on a display device such as a display, the user can operate the user terminal to display the stuck-vehicle risk information on a display that the user terminal has or is connected to the user terminal, thereby confirming the predicted results of the occurrence of a vehicle being stuck in the specified area.

[0028] FIG. 4 is a diagram showing an example of the road-struck risk information output by the output unit 113. FIG. 4 shows an example of road-struck risk information when the user sets City A, City B, City C, and City D as the specified area. In the example of FIG. 4, road sections AR2, AR5, and AR6 predicted to have a high degree of possibility of a vehicle becoming stuck (hereinafter also referred to as the risk of a vehicle becoming stuck) are indicated by solid-line frames, road section AR3 predicted to have a medium risk of a vehicle becoming stuck is indicated by a dashed-dotted-line frame, and road sections AR1 and AR4 predicted to have a low risk of a vehicle becoming stuck are indicated by dashed-line frames. The other road sections are road sections predicted to have an extremely low risk of a vehicle becoming stuck or road sections predicted to have no possibility of a vehicle becoming stuck. This allows the user to recognize road sections where a vehicle becoming stuck has occurred and the level of risk of a vehicle becoming stuck on those road sections. Note that road sections filled in black indicate road sections where vehicle 20 has never traveled and where it is not possible to obtain driving information about vehicle 20 and predict whether a vehicle will become stuck. In the example of Figure 4, the risk of a vehicle becoming stuck is displayed in three stages (high, medium, low), but the risk may also be displayed in two stages or four or more stages.

[0029] 5A and 5B are flowcharts showing an example of processing executed in accordance with a predetermined program by the calculation unit 11 (CPU) of the information providing device 10. The processing shown in the flowcharts of Fig. 5A and 5B is repeated at predetermined intervals while the information providing device 10 is running.

[0030] 5A shows a flowchart of the reception process of travel information. First, in step S11, it is determined whether travel information has been received from the in-vehicle device 30 of the vehicle 20. If the result in step S11 is negative, the process ends. If the result in step S11 is positive, the travel information received in step S11 is stored in the memory unit 12 in step S12.

[0031] FIG. 5B shows a flowchart illustrating the output process of stranding risk information. First, in step S21, it is determined whether an output instruction for stranding risk information has been input (received). If the result in step S21 is negative, the process is terminated. If the result in step S21 is positive, in step S22, map information is read from the memory unit 12, and a road map is acquired from the map information. At this time, a road map including the designated area is acquired based on the output instruction received in step S21. Next, in step S23, weather information is acquired from the weather information server. At this time, weather information for the designated area corresponding to the period from a time point in the past, a specified time before the current time, to the current time (designated period) is acquired based on the output instruction received in step S21. In step S24, travel information is acquired from the memory unit 12. More specifically, by referring to the transmission date and time information and position information included in the travel information of each vehicle 20 stored in the memory unit 12, travel information of vehicles 20 whose current travel position is included in the designated area, i.e., vehicles 20 traveling within the designated area, is read from the memory unit 12. In step S25, the driving status of the specific vehicle within the designated area is recognized for each road section of a predetermined length based on the road map acquired in step S22, the weather information acquired in step S23, and the driving information acquired in step S24. More specifically, based on the driving information acquired in step S24, i.e., the driving information (vehicle identification information) of the vehicle 20 driving within the designated area, the vehicles 20 driving within the designated area are classified into specific vehicles and general vehicles. Then, the driving status of the specific vehicle is recognized for each road section of a predetermined length. Specifically, the number of vehicles 20 classified as specific vehicles (specific vehicles 20) is counted for each road section of a predetermined length, and the count result is recognized as the driving status of the specific vehicle in each road section. Alternatively, the total number of vehicles 20 and the number of specific vehicles 20 may be counted for each road section of a predetermined length, the proportion of specific vehicles 20 to the total number of vehicles 20 driving each road section may be calculated, and the calculation result may be recognized as the driving status of the specific vehicle in each road section. In step S26, the occurrence of a vehicle being stranded in each road section is predicted based on the traveling conditions of the specific vehicle recognized for each road section in step S25.In step S27, stranding risk information including the prediction result of step S26 is generated, and the generated stranding risk information is output. The stranding risk information is output via communication network 2 to the user terminal that sent the output instruction for the stranding risk information and to a predetermined output destination terminal.

[0032] According to the embodiment of the present invention, the following advantageous effects can be achieved. (1) The information providing device 10 includes an information acquisition unit 111 that acquires travel information including location information of a vehicle 20 traveling in a predetermined area (designated area) and vehicle information including at least one of the vehicle class and weight of the vehicle 20, map information including a road map, and weather information corresponding to the predetermined area. When the weather information indicates that snowfall occurred in the predetermined area during a predetermined period from a predetermined time point in the past to the present, the information acquisition unit 111 recognizes the travel status of a specific vehicle having a predetermined class or a predetermined weight or more within the predetermined area based on the travel information acquired by the information acquisition unit 111, and predicts the occurrence of a vehicle being stranded within the predetermined area based on the recognition result. An output unit 113 outputs stranding risk information that associates the prediction result by the prediction unit 112 with a road map of the predetermined area. This allows the device to accurately provide a user, such as a road management company, with a simple configuration. Furthermore, the user can grasp the risk of being stranded based on the information provided in this manner. As a result, measures can be taken quickly, such as prohibiting traffic on road sections where there is a high risk of getting stuck, or encouraging drivers of vehicles entering such road sections to use chains.

[0033] (2) The prediction unit 112 recognizes at least one of the number of specific vehicles traveling within a predetermined area and the proportion of specific vehicles among all vehicles traveling within the predetermined area as the driving conditions, and predicts that the greater the value of the number of specific vehicles or the proportion of specific vehicles indicated by the recognized driving conditions, the higher the likelihood that vehicles will become stuck within the predetermined area. This allows for accurate prediction of the risk of vehicles becoming stuck.

[0034] The above embodiment can be modified in various ways. Modifications will be described below. In the above embodiment, when weather information acquired by the information acquisition unit 111 as a weather information acquisition unit indicates that snowfall has occurred within a predetermined area during a predetermined period from a predetermined time point in the past to the present, the prediction unit 112 as a recognition unit recognizes the driving status of a specific vehicle within the predetermined area based on the driving information acquired by the information acquisition unit 111 as a driving information acquisition unit. However, the recognition unit may estimate the departure point of a specific vehicle 20 traveling within the predetermined area based on the transition of the driving position of the specific vehicle 20 indicated by the driving information (location information) acquired by the driving information acquisition unit, and recognize at least one of the number of specific vehicles 20 traveling within the predetermined area whose departure points are in a non-snowfall area and the proportion of specific vehicles 20 whose departure points are in a non-snowfall area among all vehicles traveling within the predetermined area as the driving status of the specific vehicle 20 within the predetermined area. In this case, the prediction unit 112 predicts a higher likelihood of vehicle stranding within the predetermined area as the number of specific vehicles 20 traveling within the predetermined area whose starting point is a non-snowfall area or the proportion of specific vehicles 20 whose starting point is a non-snowfall area among all vehicles traveling within the predetermined area increases. In this way, by predicting the occurrence of vehicle stranding based on the number or proportion of specific vehicles driven by drivers who are assumed to be inexperienced at driving in snowfall areas, a more accurate prediction result that takes into account the driving characteristics of the drivers can be obtained. Note that the recognition unit may estimate, as the departure point of the specific vehicle 20, a point where the specific vehicle 20 stayed with its engine stopped for a predetermined time or more before entering the predetermined area, or may recognize, as the departure point, the area where the specific vehicle 20 spent the longest traveling time (stayed for the longest time) based on the traveling information of the specific vehicle 20 stored in the memory unit 12 (traveling information obtained over a certain period of time). In addition, the recognition unit may determine whether the starting point is in a non-snowfall area based on the position of the starting point on a road map, based on the place name of the starting point obtained from the road map, or based on other information.

[0035] In the above embodiment, the prediction unit 112 recognizes at least one of the number of specific vehicles traveling within a predetermined area and the proportion of specific vehicles among all vehicles traveling within the predetermined area as the traveling conditions of the specific vehicles within the predetermined area, and predicts the occurrence of a vehicle getting stuck based on the traveling conditions. As described above, depressions on a packed snow road surface, which are a cause of a stuck vehicle, are formed when vehicles stop on the packed snow road surface. Therefore, at intersections where many vehicles stop in response to traffic signals, etc., many such depressions are likely to form. Once a vehicle stops on a packed snow road surface with many depressions, the driver may have difficulty starting the vehicle due to the unevenness of the road surface caused by the depressions. In particular, if the stopped vehicle is a specific vehicle, its weight makes it difficult for the driver to escape from the depression, making it even more difficult for the driver to start the vehicle, and in some cases, the vehicle may get stuck. In consideration of this, the recognition unit may identify the location of an intersection located within a predetermined area based on a road map acquired by the information acquisition unit 111 as a map information acquisition unit, and recognize the change in the traveling position of a specific vehicle stopped at the intersection (more specifically, within the intersection or within a predetermined range including the intersection) when the specific vehicle starts moving from a stopped state as the traveling status of the specific vehicle within the predetermined area. Then, based on this traveling status, the prediction unit 112 may calculate the time it takes for the traveling position of the specific vehicle to change a predetermined distance after starting from a stopped state at the intersection (hereinafter referred to as the starting time), and predict the likelihood of the vehicle becoming stuck within the predetermined area to be higher when the calculated starting time is equal to or longer than the predetermined length than when the calculated starting time is shorter than the predetermined length. In this case, the sensor value acquisition unit 311 of the vehicle 20 (on-board device 30) acquires information indicating the on / off state of an acceleration device such as an accelerator pedal (hereinafter referred to as acceleration control information) detected by the internal sensor group 33. The communication control unit 312 includes the acceleration control information in the traveling information transmitted to the information providing device 10. The recognition unit recognizes that the specific vehicle has started moving when it detects a change in the acceleration device of the specific vehicle from an off state to an on state based on the acceleration control information included in the driving information acquired by the driving information acquisition unit.Furthermore, the recognition unit calculates the time (start time) until the specific vehicle's driving position changes a predetermined distance after the specific vehicle starts from a stopped state at an intersection, based on the change in the specific vehicle's driving position indicated by the position information included in the driving information acquired by the driving information acquisition unit after the specific vehicle starts.

[0036] Note that the above-described situation in which a driver has difficulty starting a vehicle may also occur at locations other than intersections. For example, on uphill sections where the road gradient is equal to or greater than a predetermined value or at locations where vehicle congestion frequently occurs (hereinafter referred to as "traffic congestion locations"), multiple depressions may form on the packed snow road surface for similar reasons, potentially causing the driver to have difficulty starting the vehicle. Therefore, the recognition unit may identify the locations of uphill sections and traffic congestion locations included in a predetermined area based on the road map acquired by the map information acquisition unit, and recognize the change in the traveling position of a specific vehicle stopped in those sections when it starts from a stopped state as the traveling status of the specific vehicle within the predetermined area. Based on this traveling status, the prediction unit 112 may calculate the departure time of the specific vehicle from those sections, and predict a higher likelihood of the vehicle becoming stuck within the predetermined area when the calculated departure time is equal to or greater than a predetermined length than when the calculated departure time is less than the predetermined length. In addition, when the road map does not contain information about traffic congestion, the recognition unit may obtain information about traffic congestion via the communication control unit 114 from an external server (not shown) that distributes road congestion information, etc. (hereinafter referred to as the road information server), and identify the locations of traffic congestion frequent points included in the specified area.

[0037] In the above embodiment, the output unit 113 outputs the stranded risk information to the user terminal, but when the information providing device 10 is equipped with an output device such as a display, the output unit may output the stranded risk information to the output device. Vehicle strandedThe information (FIG. 4) that associates the predicted state of occurrence of a vehicle stuck in a predetermined area with the road map acquired by the map information acquisition unit is generated as the stuck-vehicle risk information. However, as long as the user can recognize the state of occurrence of a vehicle stuck in a predetermined area, the stuck-vehicle risk information may be generated in a manner different from that of FIG. 4. Also, while FIG. 4 shows an example in which an administrative district (such as a city, town, or village) is set as the designated area, a road section (such as road section AR1 in FIG. 4) may be set as the designated area. Also, the designated area may be set based on information such as latitude, longitude, and road name. Furthermore, in the above embodiment, the communication control unit 114 receives an output instruction for stuck-vehicle risk information transmitted from a terminal of a road management company or the like. However, the output instruction for stuck-vehicle risk information may be transmitted from the on-board device 30 of the vehicle 20 or a communication terminal possessed by the driver of the vehicle 20. In other words, the user terminal is not limited to a terminal of a road management company or the like, but may be a communication terminal possessed by the on-board device 30 of the vehicle 20 or the driver of the vehicle 20.

[0038] The above description is merely an example, and the present invention is not limited to the above-described embodiment and modifications, as long as the features of the present invention are not impaired. One or more of the above-described embodiment and modifications can be arbitrarily combined, and modifications can also be combined with each other. [Explanation of symbols]

[0039] 10 Information providing device, 20, 20-1 to 20-n Vehicle, 30 In-vehicle device, 11 Calculation unit, 111 Information acquisition unit, 112 Prediction unit, 113 Output unit, 114 Communication control unit, 12 Storage unit

Claims

1. a travel information acquisition unit that acquires travel information including position information of a vehicle traveling in a predetermined area and vehicle information including at least one of the vehicle class and weight of the vehicle; a map information acquisition unit that acquires map information including a road map; a weather information acquisition unit that acquires weather information corresponding to the predetermined area; a recognition unit that recognizes, when the weather information indicates that snow has fallen within the specified area during a specified period from a specified time point in the past to the present, a driving situation of a specific vehicle having a specified vehicle class or a specified weight or more within the specified area based on the driving information acquired by the driving information acquisition unit; a prediction unit that predicts the occurrence of a vehicle being stuck in the predetermined area based on the recognition result of the recognition unit; an output unit that outputs stranding risk information that associates the result of the prediction by the prediction unit with the road map of the predetermined area, the recognition unit recognizes, as the driving status, at least one of the number of the specific vehicles traveling within the predetermined area and the proportion of the specific vehicles to all vehicles traveling within the predetermined area; The information providing device is characterized in that the prediction unit predicts a higher degree of possibility of vehicles becoming stuck within the specified area the larger the value of the number or percentage of the specific vehicles indicated by the driving conditions recognized by the recognition unit.

2. A driving information acquisition unit that acquires driving information including position information of a vehicle traveling in a predetermined area and vehicle information including at least one of information on the vehicle class and weight of the vehicle; a map information acquisition unit that acquires map information including a road map; a weather information acquisition unit that acquires weather information corresponding to the predetermined area; a recognition unit that recognizes, when the weather information indicates that snow has fallen within the specified area during a specified period from a specified time point in the past to the present, a driving situation of a specific vehicle having a specified vehicle class or a specified weight or more within the specified area based on the driving information acquired by the driving information acquisition unit; a prediction unit that predicts the occurrence of a vehicle being stuck in the predetermined area based on the recognition result of the recognition unit; an output unit that outputs stranding risk information that associates the result of the prediction by the prediction unit with the road map of the predetermined area, the recognition unit estimates a departure point of the vehicle traveling within the specified area based on the traveling information acquired by the traveling information acquisition unit, and recognizes at least one of the number of the specific vehicles traveling within the specified area and having departure points in a non-snowfall area, and the proportion of the specific vehicles traveling within the specified area and having departure points in a non-snowfall area, as the traveling status; The information providing device is characterized in that the prediction unit predicts a higher degree of possibility of vehicles becoming stuck within the specified area as the number or proportion of the specific vehicles indicated by the driving conditions recognized by the recognition unit increases.

3. A driving information acquisition unit that acquires driving information including position information of a vehicle traveling in a predetermined area and vehicle information including at least one of information on the vehicle class and weight of the vehicle; a map information acquisition unit that acquires map information including a road map; a weather information acquisition unit that acquires weather information corresponding to the predetermined area; a recognition unit that recognizes, when the weather information indicates that snow has fallen within the specified area during a specified period from a specified time point in the past to the present, a driving situation of a specific vehicle having a specified vehicle class or a specified weight or more within the specified area based on the driving information acquired by the driving information acquisition unit; a prediction unit that predicts the occurrence of a vehicle being stuck in the predetermined area based on the recognition result of the recognition unit; an output unit that outputs stranding risk information that associates the result of the prediction by the prediction unit with the road map of the predetermined area, the travel information further includes acceleration control information indicating whether an acceleration device of the vehicle traveling in the predetermined area is on or off; the recognition unit identifies the positions of intersections, uphill slopes with a predetermined gradient or more, or congestion-prone points included in the predetermined area on the road map based on the map information acquired by the map information acquisition unit, and recognizes, as the driving situation, a change in the driving position of the specific vehicle when it starts from a stopped state at the intersection based on the driving information acquired by the driving information acquisition unit; The prediction unit calculates the time it takes for the specific vehicle to change its driving position by a predetermined distance after starting from the stopped state at the intersection, the uphill slope of the predetermined gradient or more, or the congestion-prone location, based on the driving conditions recognized by the recognition unit, and predicts a higher degree of possibility of the vehicle becoming stuck within the predetermined area when the calculated time is equal to or greater than the predetermined length than when the calculated time is less than the predetermined length.

4. In the information providing device according to claim 3, The recognition unit further recognizes, as the driving status, at least one of the number of the specific vehicles traveling within the predetermined area and the proportion of the specific vehicles to all vehicles traveling within the predetermined area; The information providing device is characterized in that the prediction unit predicts a higher degree of possibility of vehicles becoming stuck within the specified area the larger the value of the number or percentage of the specific vehicles indicated by the driving conditions recognized by the recognition unit.

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