Information processing device

Abstract

To provide a technique for guiding a safe route to a pedestrian who walks in the vicinity of vehicles.SOLUTION: An information processing device comprises a control section. The control section executes: acquiring a current position and a destination of a pedestrian; and acquiring measurement results related to positions of a vehicle, the measurement result being the degrees of risk of driving by drivers of the vehicles. The control section also executes: retrieving a route from the acquired current position to the acquired destination of the pedestrian so as to avoid a position, where a vehicle with the high degree of risk is present, in accordance with the acquired measurement results of the degrees of risk; and outputting the retrieved route.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device. [Background technology]

[0002] Patent document 1 proposes a pedestrian-vehicle communication system that is configured to transmit a crossing request signal from a pedestrian terminal to the terminal of a vehicle that may be traveling on the vehicle path that the pedestrian is attempting to cross, and to notify the pedestrian that they are permitted to cross the vehicle path when the pedestrian terminal does not receive a vehicle presence signal from the vehicle terminal or when it receives a crossing permission signal. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-145203 Summary of the Invention [Problem to be solved by the invention]

[0004] One object of the present disclosure is to provide a technology for guiding pedestrians walking near a vehicle along a safe walkable route. [Means for solving the problem]

[0005] The information processing device of the present disclosure includes a control unit. The control unit is configured to acquire a current location and a destination of a pedestrian, and acquire a measurement result of a driving risk level of a vehicle driver, the measurement result being associated with the location of the vehicle. The control unit is also configured to search for the acquired route from the current location of the pedestrian to the destination in accordance with the acquired measurement result of the risk level so as to avoid locations where vehicles with a high risk level are present, and output the searched route. [Effects of the Invention]

[0006] According to the present disclosure, it is possible to guide pedestrians walking near a vehicle along a safe walking route. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 schematically illustrates an example of a situation to which the present disclosure is applied. [Figure 2] FIG. 2 is a diagram illustrating an example of the hardware configuration and functional configuration of the information processing device, the vehicle, and the server according to this embodiment. [Figure 3] FIG. 3 shows an example of information relating to the risk level in driving a vehicle according to this embodiment. [Figure 4] FIG. 4 is a flowchart showing an example of a processing procedure related to control by the vehicle terminal according to this embodiment. [Figure 5] FIG. 5 is a flowchart showing an example of a processing procedure related to control by the server according to this embodiment. [Figure 6] FIG. 6 is a flowchart showing an example of a processing procedure related to control by the information processing device according to this embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Conventionally, a pedestrian-to-vehicle communication system has been proposed that allows pedestrians to check whether vehicles in the vicinity of the location where the pedestrian is about to cross are allowing the pedestrian to cross. The pedestrian-to-vehicle communication system of Patent Document 1 transmits a crossing request signal from a pedestrian terminal to a pedestrian about to cross. The system transmits a signal to the terminal of a vehicle that may be traveling on the vehicle path. The pedestrian's terminal can then inform the pedestrian that they are permitted to cross the vehicle path when they do not receive a vehicle presence signal from the terminal of a nearby vehicle or when they receive a crossing permission signal. However, the present inventors have discovered the following problems with these conventional methods. For example, in the system described in Patent Document 1, the driver of a vehicle that receives a pedestrian's crossing request signal is required to respond to the signal by operating the terminal to grant or deny permission. However, if the driver is not in a position to respond, i.e., if the driver is absent-minded, dozing, or distracted, the system described in Patent Document 1 does not work. Therefore, there is a need for a system that can guide pedestrians walking near a vehicle along a safe walking route even when the driver is not in a position to respond.

[0009] In contrast, the device according to the embodiment of the present disclosure includes a control unit that acquires the current location and destination of the pedestrian and acquires a measurement result of the driving risk of the vehicle driver, the measurement result being associated with the location of the vehicle.

[0010] According to the present disclosure, a route from the acquired pedestrian's current location to a destination is searched for so as to avoid locations where vehicles with high driving risks are present. The searched route is then output, for example, to a terminal owned by the pedestrian. The pedestrian can walk by following the output route, avoiding locations where vehicles with high driving risks are present. Therefore, according to the present disclosure, a safe walking route can be guided to a pedestrian walking near a vehicle.

[0011] [1 Application example] 1 schematically shows an example of a situation to which the present disclosure is applied. Information processing system 1 is a system for processing information related to vehicle 10 and pedestrian 40. A driver 15 rides in vehicle 10. Pedestrian 40 owns a pedestrian terminal 30 that is his / her own terminal. Server 20 is a server that manages information related to vehicle 10.

[0012] In the information processing system 1, the vehicle 10, the server 20, and the pedestrian terminal 30 are interconnected by a network N. The network N may be, for example, a Wide Area Network (WAN), which is a global public communication network such as the Internet, or a telephone communication network such as a mobile phone. It may be adopted.

[0013] [2 Configuration Examples] FIG. 2 is a diagram schematically illustrating the hardware configuration and functional configuration of each of the vehicle 10, the server 20, and the pedestrian terminal 30. As shown in FIG.

[0014] (vehicle) Vehicle 10 is exemplified by a vehicle driven by a driver. Vehicle 10 may be an engine vehicle or an electric vehicle (including hybrid vehicles, etc.). Vehicle 10 includes a sensor 11, an Electronic Control Unit (ECU) 12, a communication unit 13, and a short-range communication unit 14. The vehicles 10 can communicate with each other using a predetermined in-vehicle communication standard. Examples of the predetermined in-vehicle communication standard include Controller Area Network (CAN) and Local Interconnect Network (LIN).

[0015] The sensor 11 is a sensor for detecting biological information of the driver 15. The sensor 11 is exemplified by a biosensor that detects biological information. The sensor 11 detects biological information of the driver 15 who drives the vehicle 10. The biosensor is provided in, for example, a wearable terminal that can be worn on the head of the driver 15. The biosensor can detect the brain waves of the driver 15.

[0016] The sensor 11 may include a camera mounted within the interior of the vehicle 10 to capture an image of the driver 15 . The camera can capture an image of the face of the driver 15 and detect the line of sight of the driver 15. The camera may also detect information relating to the opening and closing of the eyelids of the driver 15 (hereinafter also referred to as eyelid information). The eyelid information can be exemplified by the proportion of time that the eyelids, i.e., the eyes, of the driver 15 are closed (hereinafter also referred to as eye-closure time). A known method can be used to detect the line of sight and eyelid information of the driver 15 using a camera.

[0017] The biosensor and the camera constantly detect moment-to-moment brain wave, line of sight, and eyelid information of the driver 15 who is driving the vehicle 10. The sensor 11 is not limited to these.

[0018] The ECU 12 is a computer for controlling various devices mounted on the vehicle 10. The ECU 12 includes a processor 120 and a storage unit 127. The ECU 12 may include a clock. The clock can measure, for example, the time when the processor 120 acquires the biometric information of the driver 15 from the sensor 11.

[0019] The processor 120 is, for example, a central processing unit (CPU) or a digital signal processor (DSP). The processor 120 includes, as functional units, a sensor information acquisition unit, 121, a measurement unit 122, a position information acquisition unit 123, a determination unit 124, a generation unit 125, and an output unit 126.

[0020] The processor 120 operates as a sensor information acquisition unit 121 and acquires biometric information of the driver 15 detected by the sensor 11. Examples of the biometric information acquired by the sensor information acquisition unit 121 include brain waves, line of sight, and eyelid information of the driver 15. The measurement unit 122 may acquire, from the sensor 11, image data of the face of the driver 15 captured by a camera, which is an example of the sensor 11.

[0021] The processor 120 operates as a measurement unit 122 and measures the acquired biological information. The measurement unit 122 determines the degree of risk in driving the vehicle 10 by the driver 15 (hereinafter referred to as driving risk level) according to the acquired biological information. The measurement unit 122 determines whether the driving risk level is high or not, for example, by the method described below. Then, the measurement unit 122 measures the state of the driver 15 for the biological information determined to indicate a high driving risk level. Examples of the state of the driver 15 that can be measured include absentmindedness, drowsiness, drowsiness, and inattentiveness. (1) Inattentive: When the acquired electroencephalogram value is less than a predetermined threshold, the measurement unit 122 determines that the driver 15 is not concentrating and that the driving risk is high. Then, the measurement unit 122 determines that the state of the driver 15 is inattentive. (2) Drowsiness: When the acquired percentage of time that the eyelids of the driver 15 are closed is equal to or greater than a predetermined threshold, the measurement unit 122 determines that the driving risk is high. Then, the measurement unit 122 measures that the driver 15 is feeling drowsy. (3) Drowsy: If the acquired percentage of time the driver 15 has their eyelids closed is equal to or greater than a threshold set higher than the threshold for the percentage of time the eyes are closed set for drowsiness, the measurement unit 122 determines that the driving risk is high. Then, the measurement unit 122 determines that the driver 15 is dozing. (4) Looking aside: When the acquired line of sight of the driver 15 is not directed ahead of the vehicle 10 for a predetermined period of time or more, the measurement unit 122 determines that the driving risk is high. Then, the measurement unit 122 determines that the driver 15 is looking aside.

[0022] The processor 120 operates as a location information acquisition unit 123 and acquires location information of the vehicle 10. The vehicle 10 is equipped with, for example, a Global Positioning System (GPS) receiver. The information acquisition unit 123 can acquire the location information of the vehicle 10 detected by the GPS receiver.

[0023] The processor 120 operates as a determination unit 124 and determines whether the state of the driver 15 is absent-minded, drowsy, dozing, or inattentive, depending on the measurement result of the biological information by the measurement unit 122. For example, if the measurement result includes "absentmindedness," the determining unit 124 can determine that the state of the driver 15 corresponds to at least one of absentmindedness, drowsiness, dozing, and inattentiveness.

[0024] The determination unit 124 may determine whether or not the pedestrian terminal 30 is present within a predetermined range from the vehicle 10. The determination unit 124, for example, refers to the connection state between the short-range communication unit 14 (described later) and the pedestrian terminal 30. Then, when the short-range communication unit 14 can confirm a connectable pedestrian terminal 30, the determination unit 124 can determine that the pedestrian terminal 30 is present within a predetermined range from the vehicle 10.

[0025] The processor 120 operates as a generation unit 125 and generates a predetermined notification when the pedestrian terminal 30 is present within a predetermined range from the vehicle 10. An example of the predetermined notification is a notification (hereinafter referred to as a warning notification) that warns the pedestrian that a vehicle 10 with a high driving risk is present within a predetermined range from the pedestrian terminal 30. The warning notification includes at least any one of information such as text, images, and audio.

[0026] The processor 120 operates as the output unit 126 and outputs predetermined information to the outside of the vehicle 10. For example, the output unit 126 transmits, as the predetermined information, information relating to the risk level of the vehicle 10 (hereinafter referred to as risk level information) to the server 20 via the network N. Examples of the risk level information include information for identifying the vehicle 10 (hereinafter referred to as vehicle identification information), the time when the biometric information was acquired from the sensor 11, location information of the vehicle 10 corresponding to the time when the biometric information was acquired, and information in which the measurement results of the driving risk level are associated with each other.

[0027] The output unit 126 may transmit the attention alert notification generated by the generation unit 125 to the pedestrian terminal 30 via short-range wireless communication via the short-range communication unit 14 (described later). The pedestrian terminal 30 receives and outputs the attention alert notification. The pedestrian 40 can check the attention alert notification output to the pedestrian terminal 30. The pedestrian 40 who checks the attention alert notification can avoid walking near the vehicle 10 that is within a predetermined range from the pedestrian terminal 30 and that is determined to be at high risk.

[0028] The storage unit 127 includes a main storage unit and an auxiliary storage unit. The main storage unit is, for example, a random access memory (RAM). The auxiliary storage unit is, for example, a read only memory (ROM), a hard disk drive (HDD), or a flash memory. The auxiliary storage unit is, for example, a removable The removable medium may include a medium (portable recording medium), such as a USB memory, an SD card, or a disc recording medium such as a CD-ROM, a DVD disc, or a Blu-ray disc.

[0029] The auxiliary storage unit stores an operating system (OS), various programs, various information tables, etc. The processor 120 loads the programs stored in the auxiliary storage unit into the main storage unit and executes them, thereby realizing the information processing of this embodiment. Some or all of the functions of the ECU 12 can be realized by hardware circuits such as an Application Specific Integrated Circuit (ASIC) or a Field-Programmable Gate Array (FPGA). The ECU 12 does not need to be realized by a single physical configuration, and may be made up of multiple computers that work together.

[0030] The auxiliary storage unit stores predetermined information, such as the vehicle identification information of the vehicle 10.

[0031] The communication unit 13 connects the vehicle 10 to the network N. The communication unit 13 communicates with the network N using a predetermined wireless communication standard such as 4th Generation (4G) or Long Term Evolution (LTE). It communicates with the server 20 via the network N.

[0032] The short-range communication unit 14 connects the vehicle 10 to a device outside the vehicle via short-range wireless communication. For example, the short-range communication unit 14 connects the vehicle 10 to a pedestrian terminal 30 that is present within a predetermined range from the vehicle 10. Examples of short-range wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), and the like. trademark), and Bluetooth Low Energy (BLE) (registered trademark).

[0033] (server) The server 20 includes a processor 21, a storage unit 22, and a communication unit 23.

[0034] The processor 21 is, for example, a central processing unit (CPU) or a digital signal processor (DSP). The processor 21 includes an acquisition unit 211 as a functional unit.

[0035] The processor 21 operates as the acquisition unit 211, and acquires (receives) risk level information of the driver 15 who drives the vehicle 10 from the vehicle 10 via the network N. The risk level information acquired by the processor 21 is exemplified by vehicle identification information of the vehicle 10, the time when the biometric information of the driver 15 was acquired from the sensor 11, location information of the vehicle 10, and information in which the measurement results of the driving risk level are associated with each other. The acquisition unit 211 stores the acquired risk level information in the risk level information DB 221.

[0036] The storage unit 22 includes a main storage unit and an auxiliary storage unit. The main storage unit and the auxiliary storage unit of the storage unit 22 are similar to the main storage unit and the auxiliary storage unit of the storage unit 127, and therefore detailed description thereof will be omitted.

[0037] The memory unit 22 has a risk level information database (Database (DB)) 221. The risk level information DB 221 stores information related to the driving risk level of the driver 15. The risk level information DB 221 has a risk level information table. Figure 3 shows an example of information stored in the risk level information table. Items in the risk level information table may include an information ID, a vehicle ID, a time, vehicle location information, and a measurement result of the driving risk level. The information ID is information for identifying information in this information table. The vehicle ID is vehicle identification information of the vehicle 10. The time is the time when the biometric information related to the driving risk level was acquired. The vehicle location information is the location information of the vehicle 10 corresponding to the time when the biometric information was acquired. The measurement result of the driving risk level is the measurement result of the driving by the driver 15 measured by the measurement unit 122 of the vehicle 10.

[0038] The communication unit 23 connects the server 20 to the network N. The communication unit 23 has the same functions as the communication unit 13, and therefore a detailed description thereof will be omitted.

[0039] (Pedestrian terminal) The pedestrian terminal 30 is a terminal carried by a pedestrian 40. The pedestrian 40 is a person who may be walking near the vehicle 10. Examples of the pedestrian terminal 30 include a smartphone, a tablet computer, a personal computer, and a wearable terminal. The pedestrian terminal 30 is not limited to these. In this embodiment, the pedestrian terminal 30 is an example of an "information processing device."

[0040] The pedestrian terminal 30 includes an input / output unit 31, a processor 32, a memory unit 33, a communication unit 34, and a short-range communication unit 35. The pedestrian terminal 30 may include a GPS receiver. The pedestrian terminal 30 may also include a clock for measuring the current time. In this embodiment, the processor 32 is an example of a "control unit."

[0041] The input / output unit 31 receives information input from the pedestrian 40. The input / output unit 31 can output predetermined information. The predetermined information can be, for example, a warning notification that the pedestrian terminal 30 receives from the vehicle 10 via the network N. The predetermined information can also be a route from the current location of the pedestrian 40 to the destination, which is searched for by a search unit 323 (described later).

[0042] The processor 32 is, for example, a central processing unit (CPU) or a digital signal processor (DSP). The processor 21 includes, as a functional unit, a pedestrian information acquisition unit 32. 1. Includes a vehicle information acquisition unit 322, a search unit 323, and an output unit 324.

[0043] The processor 32 operates as a pedestrian information acquisition unit 321 and acquires the current location of the pedestrian 40. In detail, the pedestrian information acquisition unit 321 acquires current location information of the pedestrian terminal 30 acquired by a GPS receiver provided in the pedestrian terminal 30. The pedestrian information acquisition unit 321 may acquire, from a clock provided in the pedestrian terminal 30, a current time measured by the clock and corresponding to the current location information. The pedestrian information acquisition unit 321 may associate the acquired current location information of the pedestrian terminal 30 with the current time corresponding to the current location information and store them in the storage unit 33, which will be described later.

[0044] The pedestrian information acquisition unit 321 may acquire information about the destination of the pedestrian 40. For example, the pedestrian information acquisition unit 321 may acquire, from the input / output unit 31, a destination input by the pedestrian 40 to the input / output unit 31. If the storage unit 33 stores map information, the pedestrian information acquisition unit 321 may refer to the map information to acquire location information corresponding to the destination. Here, the map information may include information about the average walking time when the pedestrian 40 walks from the current location to the destination. In this case, the pedestrian information acquisition unit 321 can refer to the information about the average walking time included in the map information. The pedestrian information acquisition unit 321 applies the average walking time related to the referenced information to the acquired current time. As a result, the pedestrian information acquisition unit 321 can calculate and acquire an estimated time of arrival at the destination when walking from the current time to the destination. The pedestrian information acquisition unit 321 may store in the memory unit 33 the acquired location information corresponding to the destination of the pedestrian 40 and the estimated time of arrival at the destination in association with the current location information of the pedestrian terminal 30 and the current time corresponding to the current location information.

[0045] The processor 32 may function as a vehicle information acquisition unit 322 and acquire information related to the vehicle 10. The vehicle information acquisition unit 322 can acquire (receive), for example, attention calling information transmitted from the vehicle 10 via the network N. The acquired attention calling information can be passed to the input / output unit 31 and output.

[0046] The vehicle information acquisition unit 322 may acquire danger level information of the vehicle 10 from the server 20 as information related to the vehicle 10. The vehicle information acquisition unit 322 can access the server 20 via the network N, for example. The vehicle information acquisition unit 322 can acquire danger level information of the vehicle 10 including position information corresponding to each position from the current location of the pedestrian 40 to the destination from the server 20. The vehicle information acquisition unit 322 can store the acquired danger level information in the storage unit 33, which will be described later.

[0047] The processor 32 functions as a search unit 323, and searches for a route from the current location of the pedestrian 40 to the destination, in accordance with the measurement results of the driving risk stored in the risk information DB 331 of the storage unit 33, so as to avoid locations where vehicles 10 with a high risk are present. Examples of search methods used by the search unit 323 include the following methods.

[0048] Method 1: The search unit 323 first searches for multiple routes from the current location of the pedestrian 40 to the destination, without using the measurement results of the driving risk of the vehicle 10, by referring to the current location of the pedestrian 40, the destination of the pedestrian 40, and map information stored in the memory unit 33. Next, the search unit 323 The search unit 323 refers to the location information of the vehicle 10 and the measurement results of the driving risk level included in the acquired risk level information, and eliminates from the multiple searched routes any route that includes a location where a vehicle 10 with a high driving risk level is located. Then, the search unit 323 determines one or more routes searched by the above process as the route to be presented to the pedestrian 40.

[0049] Method 2: The search unit 323 refers to the current location of the pedestrian 40, the destination of the pedestrian 40, map information, and the position information of the vehicle 10 and the measurement results of the driving risk level contained in the acquired risk level information stored in the memory unit 33. Then, the search unit 323 searches for one or more routes from the current location of the pedestrian 40 to the destination that do not include a location where a vehicle 10 with a high driving risk level is located. The search unit 323 determines one or more routes searched by the above processing as the routes to be presented to the pedestrian 40.

[0050] The measurement results of driving risk referred to by the search unit 323 in the search process include at least one of absentmindedness, drowsiness, dozing at the wheel, and inattentiveness. Avoiding locations where vehicles 10 with high driving risk exist in the search process of the search unit 323 may include avoiding areas where at least one of absentmindedness, drowsiness, dozing at the wheel, and inattentiveness included in the measurement results occurs frequently. A "zone where at least one of absentmindedness, drowsiness, dozing at the wheel, and inattentiveness occurs frequently" refers to a certain belt-like area having a certain extent, where the total number of occurrences of absentmindedness, drowsiness, dozing at the wheel, and inattentiveness in a specified period is equal to or exceeds a predetermined threshold. Note that the area includes one or more locations. For example, the threshold may be set to 4, and the specified period may be set to one hour. Here, assume that the measurement results of driving risk in a certain area include two measurement results of absentmindedness and one measurement result each of drowsiness, dozing at the wheel, and inattentiveness in an arbitrary one-hour period. In this case, the total number of times that absentmindedness, drowsiness, dozing, and inattentiveness were measured is 5, which is greater than the total number of 4 set as the threshold. Therefore, the area is determined to be an area where at least one of absentmindedness, drowsiness, dozing, and inattentiveness frequently occurs. Then, the search unit 323 searches for a route from the current location to the destination while avoiding the determined area. By searching for a route from the current location to the destination in this manner, a route that pedestrian 40 can walk safely from the current location to the destination can be found.

[0051] Alternatively, the search unit 323 may search for a route by avoiding routes with a high frequency of measurement results of higher driving risk, such as absentmindedness, drowsiness, dozing at the wheel, and inattentiveness. For example, among the conditions of absentmindedness, drowsiness, dozing at the wheel, and inattentiveness, absentmindedness refers to a state in which the driver 15's concentration on driving is reduced, but the driver 15's gaze is directed to a certain extent ahead of the vehicle 10. Drowsiness refers to a state in which the eyelids are closed more than a set threshold, but the driver 15's gaze is directed to a certain extent ahead of the vehicle 10. In contrast, dozing refers to a state in which the eyelids are closed more than a set threshold, which is higher than the threshold set for drowsiness, so it is difficult to say that the driver 15's gaze is directed to a certain extent ahead of the vehicle 10. In addition, inattentiveness refers to a state in which the driver 15's gaze is not directed to a certain extent ahead of the vehicle 10 for a certain period of time or more. Therefore, when the driver 15 drives the vehicle 10 while dozing and looking away, it can be said that there is a higher possibility that the vehicle 10 will veer off the roadway and enter the sidewalk compared to when the driver is driving while drowsy. In other words, dozing and looking away can be said to pose a higher driving risk to the pedestrian 40 compared to when the driver is distracted or drowsy. Therefore, it may be more important for the pedestrian 40 to avoid walking near areas where dozing and looking away are common when driving the vehicle 10.

[0052] Therefore, the following method is exemplified as a process for realizing the above requirement. First, a threshold for the total number of times that absentmindedness, drowsiness, dozing off, and inattentiveness occurred in a certain area during a predetermined period is set as a first threshold. Next, a threshold for the total number of times that dozing off and inattentiveness occurred in a certain area during a predetermined period is set as a second threshold. The second threshold is set to a value smaller than the first threshold. Then, the search unit 323 searches for an area in which the total number of times that at least one of absentmindedness, drowsiness, dozing off, and inattentiveness occurred in a certain area during a predetermined period is equal to or greater than the first threshold. The search unit 323 searches for a route from the current location of the pedestrian 40 to the destination. Furthermore, the search unit 323 searches for a route from the current location of the pedestrian 40 to the destination so as to avoid areas where the total number of occurrences of at least one of dozing off and looking aside within a predetermined period of time in a certain area is equal to or exceeds a second threshold. As a result, even if the total number of occurrences of absentmindedness, drowsiness, dozing off, and looking aside is less than the first threshold, areas where the total number of occurrences of dozing off and looking aside is equal to or exceeds the second threshold can be excluded from the route from the current location of the pedestrian 40 to the destination searched for by the search unit 323. Therefore, this method can search for a route that further takes into consideration safe walking for the pedestrian 40 and provide guidance to the pedestrian 40.

[0053] Alternatively, avoiding locations where vehicles 10 with high driving risk are present may be processed based on the period from the current time at the pedestrian's current location to the estimated arrival time at the destination. For example, a past period corresponding to the period from the current time to the estimated arrival time is referred to as a target period. The search unit 323 may search for a route so as to avoid areas where at least one of absentmindedness, drowsiness, dozing, and inattentiveness associated with a time included in the target period occurred above a predetermined threshold. In this case, the search unit 323 may refer to the current time corresponding to the current location information of the pedestrian terminal 30 stored in the storage unit 33 and the estimated arrival time of the pedestrian 40 at the destination. The search unit 323 may also refer to the risk information stored in the risk information DB 331. That is, for the risk information, the search unit 323 refers to the location information of the vehicle 10 and the measurement results of the driving risk associated with a past time included in the target period. Next, the search unit 323 calculates the total number of absentmindedness, drowsiness, dozing, and inattentiveness, which indicate measurement results associated with past times included in the target period, for a certain zone.The search unit 323 can then search for a route from the current location of the pedestrian 40 to the destination so as to avoid zones where the calculated total number is equal to or greater than a predetermined threshold.In this manner, a safe route can be searched for based on the period in which the pedestrian 40 will walk from the current location to the destination, i.e., the time period, and guidance can be provided to the pedestrian 40.

[0054] The search unit 323 may refer to the position information of the vehicle 10 and the measurement results of the driving risk included in the risk level information for a time included in a target period for the same day of the week as the day of the week for the period from the current time at the current location of the pedestrian 40 to the estimated arrival time at the destination. Here, the search unit 323 calculates the total number of absentmindedness, drowsiness, dozing, and inattentiveness, which indicate measurement results associated with the position information of the vehicle 10 included in a certain zone, for the target period for the same day of the week. The search unit 323 may then search for a route from the current location of the pedestrian 40 to the destination so as to avoid zones where the total number is equal to or greater than a predetermined threshold. This makes it possible to search for a safe walking route based on the period (time zone) and day of the week for the pedestrian 40 to walk from the current location to the destination, and to provide guidance to the pedestrian 40.

[0055] The processor 32 functions as the output unit 324 and can output predetermined information. As an example, the output unit 324 transfers attention alert information received from the vehicle 10 by the vehicle information acquisition unit 322 to the input / output unit 31. Furthermore, the output unit 324 transfers the route from the current location of the pedestrian 40 to the destination searched for by the search unit 323 to the input / output unit 31. The input / output unit 31 can output the attention alert information transferred from the output unit 324 or the searched route. This makes it possible to urge the pedestrian 40 who has confirmed the attention alert information output to the input / output unit 31 to avoid walking near the vehicle 10, which poses a high driving risk. Furthermore, in the present disclosure, it is possible to guide the pedestrian 40 who has confirmed the route output to the input / output unit 31 to a safe walking route.

[0056] The output unit 324 may output the area where the vehicle 10 with high driving risk is present by outputting the route searched by the search unit 323 and a map showing the area where the vehicle 10 with high driving risk is present to the input / output unit 31. In this case, the pedestrian 40 can check the map showing the area where the vehicle 10 with high driving risk is present along with the output route. Therefore, the pedestrian 40 who has checked the route and map can check the area where the vehicle 10 with high driving risk is present on the route from the current location to the destination. Areas with high driving risks can be clearly recognized, and therefore, pedestrians 40 can be encouraged to avoid walking in areas with high driving risks.

[0057] The storage unit 33 includes a main storage unit and an auxiliary storage unit. The main storage unit and the auxiliary storage unit of the storage unit 33 are similar to the main storage unit and the auxiliary storage unit of the storage unit 127, and therefore detailed description thereof will be omitted.

[0058] The storage unit 33 has a risk level information database (Database (DB)) 331. The risk level information DB 331 stores information relating to the driving risk level of the driver 15 who drives the vehicle 10, as shown in Fig. 3. The information relating to the driving risk level stored in the risk level information DB 331 is similar to the information stored in the risk level information DB 221 related to the server 20, and therefore a detailed description thereof will be omitted.

[0059] The communication unit 34 connects the pedestrian terminal 30 to the network N. The communication unit 34 has the same functions as the communication unit 13, and therefore a detailed description thereof will be omitted.

[0060] The short-range communication unit 35 connects the pedestrian terminal 30 to devices present around the pedestrian terminal 30 via short-range wireless communication. The short-range communication unit 14 connects the pedestrian terminal 30 to a vehicle 10 present within a predetermined range from the pedestrian terminal 30, for example. Examples of short-range wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), and Bluetooth Low Energy (BLE) ( Registered trademark) is an example.

[0061] [3 Example of operation] (Vehicle terminal processing) 4 is a flowchart showing an example of a processing procedure relating to control by the ECU 12, which is an example of a vehicle terminal according to this embodiment. The following processing procedure is an example of a control method executed by a computer associated with the ECU 12.

[0062] The processor 120 included in the ECU 12 operates as a sensor information acquisition unit 121 and acquires biometric information of the driver 15 detected by the sensor 11 (step S101). Examples of the biometric information acquired by the sensor information acquisition unit 121 include brain waves, line of sight, and eyelid information of the driver 15 while driving the vehicle 10.

[0063] The processor 120 operates as the measurement unit 122 and measures the driving risk level according to the acquired biological information of the driver 15 (step S102). In detail, the measurement unit 122 determines whether the driving risk level is high for each of the brain wave, gaze, and eyelid information. Then, when the measurement unit 122 determines that the driving risk level is high for any of the brain wave, gaze, and eyelid information, it measures the state of the driver 15 as at least one of absentmindedness, drowsiness, drowsiness, and inattentiveness.

[0064] Processor 120 operates as determination unit 124, and with reference to the measurement results of the biological information by measurement unit 122, determination unit 124 determines whether the driving of vehicle 10 by driver 15 corresponds to at least one of absentmindedness, drowsiness, dozing off, and looking aside (step S103). If determination unit 124 determines that the measurement results correspond to at least one of absentmindedness, drowsiness, dozing off, and looking aside (YES determination in step S103), the process proceeds to step S104. If determination unit 124 determines that the measurement results do not correspond to any of absentmindedness, drowsiness, dozing off, and looking aside (NO determination in step S103), processor 120 ends the process.

[0065] In step S104, the processor 120 operates as the location information acquisition unit 123 to acquire location information of the vehicle 10. The location information acquisition unit 123 can acquire location information of the vehicle 10 detected by a GPS receiver provided in the vehicle 10.

[0066] The processor 120 operates as the output unit 126 and transmits risk level information of the vehicle 10 to the server 20 via the network N. The risk level information is, for example, information in which the vehicle identification information of the vehicle 10, the time when the biometric information of the driver 15 was acquired from the sensor 11, the location information of the vehicle 10 corresponding to that time, and the measurement results of the driving risk level are associated with each other (step S105).

[0067] The determination unit 124 determines whether or not the pedestrian terminal 30 is present within a predetermined range from the vehicle 10, i.e., in the vicinity of the vehicle 10 (step S106). If the determination unit 124 can confirm the presence of a connectable pedestrian terminal 30 via the short-range communication unit 14 (determined as YES in step S106), it determines that the pedestrian terminal 30 is present in the vicinity of the vehicle 10, and the process proceeds to step S107. Otherwise (determined as NO in step S106), the processor 120 ends the process.

[0068] In step S107, the processor 120 operates as the generation unit 125 and generates a warning notification to be transmitted to the pedestrian terminal 30.

[0069] The output unit 126 transmits the generated warning notification to the pedestrian terminal 30 via the short-range communication unit 14 via short-range wireless communication (step S108).

[0070] (Server processing) 5 shows an example of the procedure of information processing by the server 20 according to this embodiment. The following processing procedure is an example of a control method executed by the computer associated with the server 20.

[0071] The processor 21 included in the server 20 operates as an acquisition unit 211 and acquires (receives) risk level information of the driver 15 from the vehicle 10 via the network N. The risk level information acquired by the processor 21 is exemplified by information in which the vehicle identification information of the vehicle 10, the time when the biometric information of the driver 15 was acquired from the sensor 11, the location information of the vehicle 10 corresponding to that time, and the measurement results of the driving risk level are associated with each other (step S201). The acquisition unit 211 stores the acquired risk level information in the risk level information DB 221 (step S202).

[0072] (Pedestrian terminal processing) 6 shows an example of the procedure of information processing by the processor 32 of the pedestrian terminal 30 according to this embodiment. The following processing procedure is an example of a control method executed by the computer associated with the pedestrian terminal 30.

[0073] The processor 32 operates as the pedestrian information acquisition unit 321 and acquires the current location and destination of the pedestrian 40 (step S301). In particular, the pedestrian information acquisition unit 321 acquires current location information of the pedestrian terminal 30 acquired by a GPS receiver provided in the pedestrian terminal 30. The pedestrian information acquisition unit 321 may also acquire, from the input / output unit 31, a destination input by the pedestrian 40 to the input / output unit 31. If the storage unit 33 stores map information, the pedestrian information acquisition unit 321 may refer to the map information and acquire location information corresponding to the destination.

[0074] The processor 32 functions as the vehicle information acquisition unit 322 and acquires the measurement results of the driving risk level associated with the position of the vehicle 10 (step S302). In particular, the vehicle information acquisition unit 322 acquires risk level information of the vehicle 10 from the server 20, including positions corresponding to each position from the current position of the pedestrian 40 to the destination. The risk level information of the vehicle 10 is exemplified by information in which the vehicle identification information of the vehicle 10, the time when the biometric information of the driver 15 was acquired from the sensor 11, the position information of the vehicle 10 corresponding to that time, and the measurement results of the driving risk level are associated with each other. Note that the processing of steps S301 and S302 may be executed in reverse order.

[0075] The processor 32 functions as a search unit 323 and searches for a route from the current location of the pedestrian 40 to the destination, according to the measurement result of the driving risk level, so as to avoid locations where vehicles 10 with high driving risk levels are present (step S303). As an example, the measurement result includes at least one of absentmindedness, drowsiness, dozing off, and looking aside while driving by the driver 15. The search unit 323 then searches for a route that avoids areas between the current location and the destination of the pedestrian 40 where at least one of absentmindedness, drowsiness, dozing off, and looking aside is frequently observed.

[0076] The processor 32 functions as the output unit 324 and outputs the route from the current location of the pedestrian 40 to the destination searched for by the search unit 323 to the input / output unit 31 (step S304). As a result, according to the present disclosure, it is possible to guide the pedestrian 40 walking near the vehicle 10 along a safe walking route.

[0077] [4 Variations] In the present embodiment, the pedestrian terminal 30 searches for and outputs the acquired route from the current location of the pedestrian 40 to the destination so as to avoid locations where vehicles 10 with a high driving risk are present. However, the present embodiment is not limited to this. The processor 21 of the server 20 may execute information processing similar to that of the pedestrian terminal 30 of the present embodiment. In this case, the server 20 may further include a pedestrian information acquisition unit, a search unit, and an output unit, similar to the processor 32 of the pedestrian terminal 30. The pedestrian terminal 30 may further include a route acquisition unit for acquiring the route searched by the server 20. The pedestrian information acquisition unit of the server 20 may acquire the current location and destination of the pedestrian 40 from the pedestrian terminal 30 via the network N. The search unit may search for a route from the current location of the pedestrian 40 to the destination so as to avoid locations where vehicles 10 with a high driving risk are present, based on the measurement result of the driving risk level for the vehicle 10 stored in the risk level information DB 221. The output unit may output the searched route to the pedestrian terminal 30. The route acquisition unit of the pedestrian terminal 30 may acquire (receive) the output route via the network N. The input / output unit 31 may output the acquired route. This allows the pedestrian 40 to walk according to the route output to the input / output unit 31. Therefore, similar to the present embodiment, this modification also makes it possible to guide the pedestrian 40 walking near the vehicle 10 to a safe route to walk.

[0078] (Other embodiments) Although the embodiments of the present disclosure have been described in detail above, the above description is merely an example of the present disclosure in every respect. It goes without saying that various improvements and modifications can be made without departing from the scope of the present disclosure. [Explanation of symbols]

[0079] 1. Information Processing System 10··Vehicle, 11··Sensor, 12··ECU, 120··Processor, 127 Memory unit, 13 Communication unit, 14 Short-range communication unit 15. Driver 20. Server, 21. Processor, 22. Storage unit, 23. Communication unit 30 Pedestrian terminal, 31 Input / output unit, 32 Processor, 33 Memory unit, 34 Communication unit, 35 Short-range communication unit 40··Pedestrian, N··Network

Claims

1. An information processing device including a control unit, The control unit Obtaining the current location and destination of pedestrians; obtaining a measurement of driving riskiness by a driver of a vehicle, the measurement being associated with the location of the vehicle; According to the acquired measurement result of the risk level, searching for a route from the acquired current location of the pedestrian to the destination so as to avoid a location where a vehicle with a high risk level is present; and outputting the searched route; configured to perform Information processing device.

2. The measurement results include at least one of absentmindedness, drowsiness, drowsiness, and inattentiveness during driving by the driver, avoiding locations where high-risk vehicles exist includes avoiding areas where at least one of absentmindedness, drowsiness, dozing off, and inattentiveness is common; The information processing device according to claim 1 .

3. avoiding locations where high-risk vehicles are present includes avoiding at least one of a zone where at least one of absentmindedness, drowsiness, dozing off, and looking away occurs at a first threshold or more within a predetermined period of time, and a zone where at least one of dozing off and looking away occurs at a second threshold or more that is smaller than the first threshold or more within the predetermined period of time. The information processing device according to claim 2 .

4. The control unit is further configured to obtain a current time and an estimated time of arrival at the destination; searching for a route from the current location to the destination includes searching for a route from the current location of the pedestrian to the destination in accordance with the acquired measurement result of the risk level for a target period corresponding to a period from the current time to the estimated arrival time; avoiding a location where a vehicle with a high risk is present includes avoiding a zone where at least one of absentmindedness, drowsiness, dozing, and inattentiveness occurs above a predetermined threshold during the target period. The information processing device according to claim 2 .

5. and outputting the searched route includes outputting a map showing the area where the high-risk vehicle is present together with the searched route.

5. The information processing device according to claim 3 or 4.

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