Information processing device and program

Abstract

To provide a detection device, an on-vehicle device, and a detection method that are capable of detecting that a driver's state is a rush driving state with high accuracy.SOLUTION: A detection device according to an aspect of an embodiment includes a control unit. The control unit detects driving state information indicating a driving state related to at least either of a vehicle and a driver of the vehicle. The control unit analyzes the detected driving state information and calculates rush driving information indicating a level of tendency of rush driving with the driver. On the basis of the calculated rush driving information, the control unit detects that the driver's state is a state of rush driving.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a detection device, an in-vehicle device, and a detection method.

Background Art

[0002] Conventionally, various techniques have been proposed for detecting that the state of a vehicle driver is in a state of driving in a hurry (hereinafter, referred to as "hurry driving") (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, there has been room for improvement in the prior art in terms of accurately detecting the state of hurry driving.

[0005] The present invention has been made in view of the above, and an object thereof is to provide a detection device, an in-vehicle device, and a detection method capable of accurately detecting that the state of a driver is in a state of hurry driving.

Means for Solving the Problems

[0006] In order to solve the above problems and achieve the object, the present invention has a control unit in a detection device. The control unit detects driving state information indicating a driving state related to at least one of a vehicle and a driver of the vehicle. The control unit analyzes the detected driving state information to calculate hurry driving information indicating the degree of the tendency of hurry driving in the driver. The control unit detects that the state of the driver is in a state of hurry driving based on the calculated hurry driving information.

Effects of the Invention

[0007] According to the present invention, it is possible to accurately detect whether the driver is in a state of rushed driving. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a diagram showing an overview of a detection system including a detection device according to an embodiment. [Figure 2] Figure 2 is a block diagram showing an example configuration of a detection system according to an embodiment. [Figure 3] Figure 3 is a block diagram showing an example of the configuration of an in-vehicle device. [Figure 4] Figure 4 is a block diagram showing an example of the configuration of a detection device. [Figure 5] Figure 5 shows an example of trend determination criteria information. [Figure 6] Figure 6 shows the display of the in-vehicle device that notified the driver that a state of rushed driving had been detected. [Figure 7] Figure 7 is a flowchart showing the processing steps performed by the detection device. [Modes for carrying out the invention]

[0009] The embodiments of the detection device, in-vehicle device, and detection method disclosed herein will be described in detail below with reference to the attached drawings. However, the present invention is not limited to the embodiments described below.

[0010] <Overview of the detection system> First, an overview of the detection system including the detection device according to the embodiment will be described using Figure 1. Figure 1 is a diagram showing an overview of the detection system including the detection device according to the embodiment.

[0011] The detection system 1 according to this embodiment is a system that detects hasty driving (driving in a hurry) that may occur due to psychological states such as the driver's anxiety. Furthermore, the detection system 1 is a system that notifies the driver when hasty driving is detected.

[0012] As shown in Figure 1, the detection system 1 according to this embodiment includes a detection device 10 and an on-board device 100 mounted on a vehicle V.

[0013] The detection device 10 is a server that performs various processes, such as detecting whether the driver of vehicle V is in a state of rushed driving. For example, the detection device 10 may be implemented as a cloud server that provides cloud services via a network such as the Internet or a mobile phone network, or it may be configured to perform distributed processing using multiple servers.

[0014] The in-vehicle device 100 is a device that includes various sensors, such as a camera sensor (hereinafter referred to as "camera"), a memory device, a microcomputer, and the like. In addition to the camera, the in-vehicle device 100 is also equipped with a GPS (Global Positioning System) sensor, a speed sensor, an acceleration sensor, and the like, which will be described later with reference to Figure 3.

[0015] The camera described above can, for example, capture images of the area around vehicle V and the interior of vehicle V, and output the captured image data. The image data is video data, but is not limited to video; it may also be still image data, etc.

[0016] The in-vehicle device 100 has a communication function that communicates via a communication network. For example, a drive recorder can be used as the in-vehicle device 100.

[0017] By the way, in the prior art, for example, when the average speed of the host vehicle is greater than that of other vehicles, or when the number of other vehicles overtaken by the host vehicle exceeds a predetermined value, the system is configured to detect that the driver's state is a state of aggressive driving. However, if configured as in the prior art, for example, when the speed of other vehicles traveling around is relatively slow, even during normal driving (non-aggressive driving), it may be detected as aggressive driving. Thus, in the prior art, since aggressive driving is detected based on relative values depending on other vehicles traveling around the host vehicle, such as comparison of average speeds and the number of other vehicles overtaken, there is a risk that the detection accuracy of aggressive driving may decrease depending on the driving state of other vehicles, leaving room for improvement.

[0018] Therefore, in the detection device 10 according to the present embodiment, the configuration is such that the state of the driver being in a state of aggressive driving can be accurately detected.

[0019] Specifically, as shown in FIG. 1, the detection device 10 acquires the outputs of various sensors such as a camera (step S1). For example, the detection device 10 acquires surrounding image data obtained by imaging the front or rear of the vehicle V from the camera. In addition, the detection device 10 acquires in-vehicle image data obtained by imaging the interior of the vehicle V from the camera.

[0020] Next, the detection device 10 detects driving state information indicating the driving state of the vehicle V and the driver of the vehicle V based on the acquired sensor outputs (step S2). Such driving state information includes, for example, lane change information. Note that the driving state information according to the present embodiment includes, in addition to lane change information, for example, traffic signal driving information, inter-vehicle distance information, line-of-sight information, and speed information, etc., which will be described later with reference to FIG. 4.

[0021] Lane change information refers to information about vehicle V changing lanes. For example, the detection device 10 detects the lane on the road that vehicle V is traveling on, the distance between vehicle V and the vehicle in front, and the distance between vehicle V and the vehicle behind by analyzing surrounding image data. The detection device 10 then detects lane change information such as the number of times vehicle V has changed lanes in a predetermined period, the distance between vehicle V and the vehicle in front after changing lanes, and the distance between vehicle V and the vehicle behind after changing lanes.

[0022] Next, the detection device 10 analyzes the above-mentioned driving state information and calculates impatient driving information that indicates the degree of the driver's tendency to drive impatiently (step S3). Here, impatient driving information is information that scores, for example, the number of times the driver's tendency to drive impatiently was detected, and the duration for which the tendency to drive impatiently continued.

[0023] For example, the detection device 10 analyzes lane change information, which is driving state information, to calculate information indicating haste in driving. Specifically, the detection device 10 detects a tendency towards haste in driving if the number of times vehicle V changes lanes within a predetermined period exceeds a predetermined number of changes. In other words, it estimates that haste in driving may be occurring. The predetermined period mentioned above is set to a relatively short arbitrary period (for example, 30 seconds). The predetermined number of changes is set to the number of lane changes that can occur within a predetermined period during normal driving (non-haste driving) (for example, 3 times).

[0024] Therefore, if the detection device 10 detects that the number of times vehicle V has changed lanes exceeds a predetermined number of changes, it estimates that the number of lane changes exceeds the number that can occur during normal driving, and that vehicle V is performing continuous overtaking and passing in a relatively short predetermined period, thus detecting a tendency towards hasty driving, or in other words, it estimates that hasty driving may be occurring.

[0025] Furthermore, the detection device 10 detects a tendency towards hasty driving when the distance between the vehicle in front after a lane change, or the distance between the vehicle behind after a lane change, is shorter than a predetermined distance after the change. The predetermined distance after the change is set to, for example, the braking distance at which vehicle V can avoid contact with the vehicle in front when the vehicle in front brakes suddenly (in other words, the braking distance at which the vehicle behind can avoid contact with the vehicle in front, vehicle V, when vehicle V brakes suddenly). The predetermined distance after the change is a variable value depending on the speed of vehicle V; for example, as the speed of vehicle V increases, the predetermined distance after the change also increases.

[0026] Therefore, if the following distance after a lane change is shorter than the predetermined distance after the change, the detection device 10 detects that vehicle V is making an aggressive cut-in without maintaining the predetermined distance after the change, and thus estimates that there is a tendency for hasty driving, or in other words, that hasty driving is likely occurring.

[0027] The detection device 10 then scores the number of times the above-mentioned tendency for hasty driving is detected and calculates hasty driving information (in other words, score information) that indicates the degree of the driver's tendency for hasty driving. For example, the detection device 10 scores the vehicle V as follows: 1 point if the number of lane changes is one more than a predetermined number of changes, 2 points if it is two more, and 1 point if the distance between vehicles after a lane change is shorter than a predetermined distance after the change. The detection device 10 then calculates the hasty driving information. It should be noted that the scoring is shown specifically above, but this is merely an example and not an exhaustive list.

[0028] Next, the detection device 10 detects that the driver is in a state of urgent driving based on the calculated urgent driving information (score information) (step S4). For example, the detection device 10 compares the urgent driving information with a preset detection threshold value, and if the urgent driving information (score information) is equal to or greater than the detection threshold value, it detects that the driver is in a state of urgent driving. The detection threshold value is set to a value greater than the urgent driving information (score information) calculated when a typical driver is driving normally (not urgent driving) (for example, twice the value), but it is not limited to this and can be set to any value.

[0029] Therefore, for example, if the hasty driving information (score information) is above the detection threshold value, the detection device 10 detects that there is a relatively large tendency towards hasty driving, and that the degree of this tendency is relatively strong, indicating that the driver's state is one of hasty driving caused by psychological states such as impatience. Conversely, if the hasty driving information (score information) is below the detection threshold value, the detection device 10 determines that the degree of the tendency towards hasty driving is relatively weak or absent, and therefore the driver's state is not one of hasty driving; in other words, it determines that the driver is in a normal driving state.

[0030] As described above, the detection device 10 according to this embodiment detects driving state information related to the vehicle V, analyzes the detected driving state information to calculate rush driving information indicating the degree of the driver's tendency to drive hastily, and detects whether the driver's state is one of rush driving based on the calculated rush driving information.

[0031] As a result, in this embodiment, it is possible to accurately detect whether the driver is in a state of rushed driving. That is, the detection device 10 according to this embodiment does not use relative values ​​that depend on other vehicles traveling around the vehicle V (such as the average speed of other vehicles or the number of other vehicles overtaken), but rather uses driving conditions that are unlikely to occur during normal driving (for example, the number of lane changes is greater than a predetermined number of changes, or the distance between the vehicle and the vehicle in front after a lane change is shorter than a predetermined distance after the change) as the criteria for determination. Therefore, it is possible to make it less susceptible to the influence of the driving conditions of other vehicles, and thus it is possible to accurately detect whether the driver is in a state of rushed driving.

[0032] Next, the detection device 10 notifies the driver via the in-vehicle device 100 that the driver is in a state of rushed driving (step S5). This allows the detection device 10 to make the driver aware that they are in a state of rushed driving and to encourage them to stop rushing.

[0033] <Overall configuration of the detection system> Figure 2 is a block diagram showing an example configuration of the detection system 1 according to the embodiment. Note that block diagrams such as Figure 2 only show the components necessary to explain the features of the embodiment, and descriptions of general components are omitted.

[0034] In other words, each component shown in block diagrams such as Figure 2 is a functional concept and does not necessarily need to be physically configured as shown. For example, the specific forms of distribution and integration of each block are not limited to those shown, and it is possible to configure all or part of them by functionally or physically distributing and integrating them in any unit according to various loads and usage conditions.

[0035] Furthermore, in the explanations from Figure 2 onward, components that have already been explained may be simplified or omitted.

[0036] As shown in Figure 2, the detection system 1 according to this embodiment includes a detection device 10 and an in-vehicle device 100. The detection device 10 and the in-vehicle device 100 are connected to each other via a communication network N. In Figure 2, for the sake of simplicity, only one in-vehicle device 100 is shown, but there may be multiple in-vehicle devices 100.

[0037] <Configuration of in-vehicle equipment> First, the configuration of the in-vehicle device 100 will be explained with reference to Figure 3. Figure 3 is a block diagram showing an example configuration of the in-vehicle device 100. As shown in Figure 3, the in-vehicle device 100 includes a communication unit 101, a GPS sensor 102, a speed sensor 103, an acceleration sensor 104, a front camera 105, a rear camera 106, an interior camera 107, an output unit 108, a control unit 110, and a storage unit 120. Note that the control unit 110 is an example of an in-vehicle device control unit.

[0038] The communication unit 101 is a communication interface that connects to the communication network N in a bidirectional manner and transmits and receives information with the detection device 10 and the like.

[0039] The GPS sensor 102 detects the vehicle's position and outputs position information indicating the detected vehicle's position to the control unit 110. The speed sensor 103 detects the vehicle's speed and outputs speed sensor information indicating the detected speed to the control unit 110. The acceleration sensor 104 detects the acceleration acting on the vehicle and outputs acceleration sensor information indicating the detected acceleration to the control unit 110.

[0040] The front camera 105 captures images of the area in front of the vehicle and outputs the captured front image data (surrounding image data) to the control unit 110. The rear camera 106 captures images of the area behind the vehicle and outputs the captured rear image data (surrounding image data) to the control unit 110. The interior camera 107 captures images of the interior of the vehicle and outputs the captured interior image data to the control unit 110.

[0041] The output unit 108 outputs various types of information, such as notifications when hasty driving is detected. For example, the output unit 108 includes an audio output unit such as a speaker and a display unit such as a screen, and outputs various types of information, such as notifications, to the vehicle driver. The display in the output unit 108 may also display image data (video) captured by each of the cameras 105, 106, and 107.

[0042] The storage unit 120 is a storage unit composed of storage devices such as non-volatile memory, data flash, and hard disk drives. Image data captured by each of the cameras 105, 106, and 107, as well as various programs, are stored in this storage unit 120.

[0043] The control unit 110 comprises an acquisition unit 111 and a processing unit 112, and includes, for example, a computer and various circuits having a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), input / output ports, etc.

[0044] The computer's CPU functions as the acquisition unit 111 and processing unit 112 of the control unit 110, for example, by reading and executing a program stored in ROM. Alternatively, at least one part or all of the acquisition unit 111 and processing unit 112 of the control unit 110 can be configured using hardware such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0045] The acquisition unit 111 of the control unit 110 acquires the outputs of various sensors and transmits the acquired output information from the various sensors to the detection device 10. For example, the acquisition unit 111 acquires location information from the GPS sensor 102. The acquisition unit 111 also acquires speed sensor information from the speed sensor 103 and acceleration sensor information from the acceleration sensor 104. The acquisition unit 111 then transmits the acquired location information, speed sensor information, and acceleration sensor information to the detection device 10 via the communication unit 101.

[0046] For example, the acquisition unit 111 acquires forward image data from the front camera 105. The acquisition unit 111 also acquires rear image data from the rear camera 106 and interior image data from the interior camera 107. The acquisition unit 111 then transmits each acquired image data to the detection device 10 via the communication unit 101 and stores it in the storage unit 120.

[0047] The processing unit 112 can output and display image data (video) captured by each camera 105, 106, and 107 on the display of the output unit 108. Furthermore, if the processing unit 112 receives a notification from the detection device 10 indicating, for example, that hasty driving has been detected, it will output such notification to the output unit 108. Additionally, if the processing unit 112 detects an impact due to a contact accident based on acceleration sensor information, it may perform a process to prevent overwriting of image data for a predetermined period before and after the detection.

[0048] <Configuration of the detection device> Next, the configuration of the detection device 10 will be described with reference to Figure 4. Figure 4 is a block diagram showing an example of the configuration of the detection device 10. As shown in Figure 4, the detection device 10 comprises a communication unit 11, a control unit 20, and a storage unit 30.

[0049] The communication unit 11 is a communication interface that connects to the communication network N in a bidirectional manner and transmits and receives information with the in-vehicle device 100 and the like.

[0050] Furthermore, the memory unit 30 is a memory unit composed of storage devices such as non-volatile memory, data flash, and hard disk drives. This memory unit 30 stores operating status information 31, trend judgment criterion information 32, score information 33, and detection criterion information 34, etc.

[0051] Driving status information 31 is information indicating the driving status of the vehicle and the driver of the vehicle. As described above, driving status information 31 includes lane change information 31a, traffic light driving information 31b, following distance information 31c, gaze information 31d, and speed information 31e.

[0052] As described above, lane change information 31a is information related to a vehicle's lane change. For example, the control unit 20 analyzes surrounding image data (specifically, forward image data and rear image data) to detect the lane of the road the vehicle is traveling on, the distance between the vehicle and the vehicle in front, and the distance between the vehicle and the vehicle behind. The control unit 20 then stores information such as the number of times the vehicle has changed lanes in a predetermined period, the distance between the vehicle and the vehicle in front after the lane change, and the distance between the vehicle and the vehicle behind after the lane change in the storage unit 30 as lane change information 31a.

[0053] Traffic light driving information 31b is information indicating the driving status of a vehicle on a road equipped with traffic lights. For example, the control unit 20 analyzes surrounding image data (more specifically, forward image data) to detect the display status of traffic lights and stop lines present on the road the vehicle is traveling on (more precisely, the road in the direction of travel). The display status of traffic lights includes, but is not limited to, the display status of red or yellow lights that instruct the vehicle to stop, or green lights that instruct the vehicle to proceed. Furthermore, when the display status of traffic lights or stop lines are detected, the control unit 20 analyzes speed sensor information and acceleration sensor information to detect the vehicle's driving status, such as whether the vehicle is moving, stopped, transitioning from moving to stopped, or transitioning from stopped to moving. The control unit 20 then associates (links) the detected traffic light display status or stop line with the vehicle's driving status and stores it in the storage unit 30 as traffic light driving information 31b.

[0054] The inter-vehicle distance information 31c is information relating to the inter-vehicle distance while the vehicle is in motion. For example, the control unit 20 analyzes surrounding image data and speed sensor information to detect the inter-vehicle distance between the vehicle and the vehicle in front while the vehicle is in motion. The information indicating the inter-vehicle distance and the speed at which the inter-vehicle distance was detected are associated and stored in the storage unit 30 as inter-vehicle distance information 31c.

[0055] The gaze information 31d is information related to the driver's gaze. For example, the control unit 20 analyzes the interior image data to detect the orientation of the driver's face and eyes contained in the interior image data, and detects the driver's gaze (more precisely, the direction of their gaze). The control unit 20 then stores the detected information indicating the driver's gaze as gaze information 31d in the storage unit 30.

[0056] Speed ​​information 31e is information relating to the vehicle's speed. For example, the control unit 20 stores information indicating the speed obtained from the speed sensor as speed information 31e in the storage unit 30. In addition, the control unit 20 detects pedestrians present on the road the vehicle is traveling on (more precisely, the road in the direction of travel) by analyzing the surrounding image data. When a pedestrian is detected, the control unit 20 stores the speed at which the vehicle passes near the pedestrian as speed information 31e in the storage unit 30.

[0057] The tendency judgment criteria information 32 is information that shows the criteria for determining the tendency of a driver to drive hastily; in other words, it is information that shows the criteria for which it can be estimated that hastily driving is occurring in a vehicle.

[0058] Here, we will explain the trend determination criteria information 32 using Figure 5. Figure 5 is a diagram showing an example of the trend determination criteria information 32.

[0059] As shown in Figure 5, the trend judgment criteria information 32 includes items such as "type of driving status information," "urgent trend judgment," and "score," and the data for each item is related to each other.

[0060] The "Type of Driving State Information" indicates the type of driving state information used to determine a driver's tendency towards rushing. Examples of registered "Types of Driving State Information" include lane change information, traffic light driving information, following distance information, gaze information, and speed information.

[0061] The "Haste Tendency Assessment" is information that provides criteria for determining a driver's tendency to drive hastily. The following are specific examples of the "Haste Tendency Assessment," but these are merely illustrative and not limiting.

[0062] For example, "Frequent lane changes" is registered as a "tendency to rush" indicator. Specifically, "Frequent lane changes" indicates that if a vehicle changes lanes more times than a predetermined number of times within a specified period, a tendency towards rushed driving is detected. In other words, it indicates that it is estimated that rushed driving may be occurring.

[0063] Furthermore, for example, "short following distance after lane change" is registered as a "tendency to rush" detection. Specifically, "short following distance after lane change" indicates that a tendency to rush is detected when the following distance to the vehicle in front or the following vehicle after a lane change is shorter than a predetermined distance after the change.

[0064] Furthermore, for example, "passing through a red or yellow light" is registered as a "tendency to rush" detection. Specifically, "passing through a red or yellow light" indicates that if a vehicle continues to drive through a traffic light on the road it is traveling on (more precisely, the road in the direction of travel) even though the traffic light is red or yellow, a tendency to rush is detected. In other words, if a vehicle does not stop when it should, it is presumed that rushing may be occurring due to the driver's psychological state, such as impatience.

[0065] Furthermore, for example, "vehicle starting to move before the traffic light changes from red to green" is registered as a "tendency to rush" detection. Specifically, "vehicle starting to move before the traffic light changes from red to green" indicates that a tendency to rush is detected when the vehicle transitions from a stopped state to a moving state (i.e., the vehicle starts moving) before the traffic light on the road the vehicle is traveling on (more precisely, the road in the direction of travel) changes from red to green. In other words, if the vehicle starts moving even though the traffic light is red and the vehicle should still be stopped, it is presumed that rush driving may be occurring.

[0066] Furthermore, for example, "Failure to Stop at Stop Sign" is registered as a "tendency to rush" detection. Specifically, "Failure to Stop at Stop Sign" indicates that if a vehicle passes a stop sign without stopping, even though a stop sign exists on the road it is traveling on (more precisely, the road in the direction of travel), it will be detected as a tendency to rush. In other words, if a vehicle does not stop at a stop sign when it should, it is presumed that it may be driving in a hurry.

[0067] Furthermore, for example, "short following distance" is registered under "determining tendency to rush ahead." Specifically, "short following distance" indicates that a tendency to rush ahead is detected when the distance between a vehicle and the vehicle in front is shorter than a predetermined following distance while the vehicle is in motion. The predetermined following distance is a value that is set in advance, and is set to a value that allows the vehicle to stop safely in the event of sudden braking by the vehicle in front, but is not limited to this and can be set to any value. In addition, the predetermined following distance is a value that varies according to the vehicle's speed, and for example, the predetermined following distance increases as the vehicle's speed increases. Therefore, here it is assumed that rushing ahead may be occurring when a vehicle is not maintaining a safe following distance.

[0068] Furthermore, for example, "Lack of checking left and right at intersections" is registered as a "tendency to rush ahead" indicator. Specifically, "Lack of checking left and right at intersections" indicates that a tendency to rush ahead is detected when, for example, the driver's gaze does not check left and right as the vehicle passes through an intersection. In other words, for example, if the driver's gaze does not check left and right when the vehicle starts from an intersection and proceeds straight or turns left or right, even though the driver should be doing so, it is presumed that rushed driving may be occurring.

[0069] Furthermore, for example, "frequent distractions while driving" is registered under "tendency to rush." ​​Specifically, "frequent distractions while driving" indicates that a tendency to rush is detected when, for example, the driver's gaze frequently moves from side to side or is not directed forward while the vehicle is in motion (for example, when driving at speeds of 30 km / h or higher). In other words, if the driver's gaze is not directed in the appropriate direction while the vehicle is in motion, it is presumed that rush driving may be occurring.

[0070] Furthermore, for example, "driving at an excessive speed limit" is registered under "determining a tendency to rush." ​​Specifically, "driving at an excessive speed limit" indicates that a tendency to rush is detected when, for example, the vehicle's speed exceeds the legal speed limit. In other words, if the vehicle is not adhering to the legal speed limit, it is presumed that rush driving may be occurring. The legal speed limit is information included in the map information of the location where the vehicle is traveling. The map information may be information stored in the storage unit 30 in advance, or it may be information obtained from an external server (not shown).

[0071] Furthermore, for example, the "Determination of a tendency to rush" includes the registration of "Driving at a speed above the predetermined speed even when pedestrians are present ahead." Specifically, "Driving at a speed above the predetermined speed even when pedestrians are present ahead" indicates that a tendency to rush is detected when, for example, a vehicle is traveling near pedestrians at a predetermined speed (e.g., 20 km / h) or higher, even though pedestrians are present on the road it is traveling on (more precisely, the road in the direction of travel). In other words, if a vehicle is traveling near pedestrians at a predetermined speed (e.g., 20 km / h) or higher, even though there are pedestrians present and the vehicle should slow down or stop, it is presumed that rush driving may be occurring.

[0072] The "score" is information that indicates the score added to the score information, which is the rush driving information, when a tendency towards rush driving is detected in the corresponding "rushing tendency judgment". In the example shown in Figure 5, for convenience, the "score" is abstractly written as "A01", but it is assumed that "A01" stores specific information.

[0073] Furthermore, the "score" may be weighted information. Such weighting is set according to the content that is determined to be a tendency to rush, for example. For example, "passing through with a red or yellow light" is set to a relatively high weight because it is a dangerous tendency to rush, but this is just an example and not an exhaustive one.

[0074] In the example of trend judgment criteria information 32 shown in Figure 5, the type of driving state information is "lane change information," the haste tendency judgment is "frequent lane changes," and the score is "A01."

[0075] Returning to the explanation of Figure 4, score information 33 is score information that indicates the degree of the driver's tendency to drive hastily, and is an example of hastily driving information.

[0076] The detection criterion information 34 is information that indicates the detection criterion value described above. In other words, the detection criterion information 34 is a detection criterion value that is compared with the score information, which is the information on driving in a hurry. If the information on driving in a hurry (score information) is equal to or greater than the detection criterion value, it is detected that the driver is driving in a hurry.

[0077] Returning to the explanation of Figure 4, the control unit 20 comprises a detection unit 21, an analysis unit 22, a detection unit 23, and a notification unit 24, and includes, for example, a computer and various circuits having a CPU, ROM, RAM, a hard disk drive, input / output ports, etc. The computer's CPU functions as the detection unit 21, analysis unit 22, detection unit 23, and notification unit 24 of the control unit 20 by, for example, reading and executing a program stored in the ROM.

[0078] Furthermore, at least one part or all of the detection unit 21, analysis unit 22, detection unit 23, and notification unit 24 of the control unit 20 can be configured using hardware such as an ASIC or FPGA.

[0079] The detection unit 21 detects driving status information that indicates the driving status of the vehicle and the vehicle's driver. For example, the detection unit 21 analyzes surrounding image data (specifically, forward image data and rear image data) and detects lane change information 31a as driving status information, which is then stored in the storage unit 30.

[0080] Furthermore, the detection unit 21 analyzes, for example, surrounding image data (specifically, forward image data), speed sensor information, and acceleration sensor information, and detects traffic signal driving information 31b as driving state information, which is then stored in the storage unit 30. In addition, the detection unit 21 analyzes surrounding image data and speed sensor information, and detects inter-vehicle distance information 31c as driving state information, which is then stored in the storage unit 30.

[0081] Furthermore, the detection unit 21 analyzes, for example, indoor image data and detects gaze information 31d as driving state information, which is then stored in the storage unit 30. Additionally, the detection unit 21 analyzes, for example, speed sensor information and surrounding image data (specifically, forward image data) and detects speed information 31e as driving state information, which is then stored in the storage unit 30.

[0082] The lane change information 31a, traffic light driving information 31b, following distance information 31c, and speed information 31e described above are examples of driving state information indicating the driving state of the vehicle, and the gaze information 31d is an example of driving state information indicating the driving state of the vehicle's driver. Furthermore, although the detection unit 21 is configured to detect all of the lane change information 31a, traffic light driving information 31b, following distance information 31c, gaze information 31d, and speed information 31e in the above description, it is not limited to this configuration, and a configuration that detects only some of them is also possible. In other words, the detection device 10 only needs to detect driving state information indicating the driving state of at least one of the vehicle and the vehicle's driver.

[0083] The analysis unit 22 analyzes the detected driving state information and calculates impatient driving information that indicates the degree of the driver's tendency to drive impatiently. For example, the analysis unit 22 analyzes the lane change information 31a, which is driving state information, and detects an impatient driving tendency if the number of times the vehicle changed lanes in a predetermined period exceeds a predetermined number of changes based on the tendency judgment criteria information 32, and adds a corresponding score to the impatient driving information (score information).

[0084] Furthermore, the analysis unit 22 analyzes the lane change information 31a and, based on the tendency judgment criteria information 32, detects a tendency towards hasty driving if the distance to the vehicle in front after the lane change or the distance to the vehicle behind after the lane change is shorter than a predetermined distance after the change, and adds the corresponding score to the hasty driving information (score information). In this way, the analysis unit 22 can accurately calculate the hasty driving information (score information) by using the lane change information 31a.

[0085] Furthermore, the analysis unit 22 analyzes the traffic signal driving information 31b and, based on the trend judgment criteria information 32, detects a tendency for hasty driving when a vehicle drives past a traffic signal even though the signal is red or yellow, and adds the corresponding score to the hasty driving information (score information).

[0086] Furthermore, the analysis unit 22 analyzes the traffic signal driving information 31b and, based on the trend judgment criteria information 32, detects a tendency for hasty driving if the vehicle starts driving before the traffic signal changes from red to green, and adds the corresponding score to the hasty driving information (score information).

[0087] Furthermore, the analysis unit 22 analyzes the signal traffic information 31b and, based on the trend judgment criteria information 32, detects a tendency towards rushing driving when a vehicle passes a stop line without stopping, and adds a corresponding score to the rushing driving information (score information). In this way, the analysis unit 22 can accurately calculate the rushing driving information (score information) by using the signal traffic information 31b.

[0088] Furthermore, the analysis unit 22 analyzes the inter-vehicle distance information 31c and, based on the trend judgment criteria information 32, detects a tendency towards hasty driving when the inter-vehicle distance to the vehicle in front is shorter than a predetermined inter-vehicle distance, and adds the corresponding score to the hasty driving information (score information). In this way, the analysis unit 22 can accurately calculate the hasty driving information (score information) by using the inter-vehicle distance information 31c.

[0089] Furthermore, the analysis unit 22 analyzes the gaze information 31d and, based on the tendency judgment criteria information 32, detects a tendency towards rushing driving if the driver's gaze is not checking left and right when the vehicle passes through an intersection, and adds the corresponding score to the rushing driving information (score information).

[0090] Furthermore, the analysis unit 22 analyzes the gaze information 31d and, based on the trend judgment criteria information 32, detects a tendency towards hasty driving when the driver's gaze frequently moves from side to side while the vehicle is in motion, or when the driver's gaze is not directed forward, and adds a corresponding score to the hasty driving information (score information). In this way, the analysis unit 22 can accurately calculate the hasty driving information (score information) by using the gaze information 31d.

[0091] Furthermore, the analysis unit 22 analyzes the speed information 31e and, based on the trend judgment criteria information 32, detects a tendency towards rushed driving if the vehicle's speed exceeds the legal speed limit, and adds the corresponding score to the rushed driving information (score information).

[0092] Furthermore, the analysis unit 22 analyzes the speed information 31e and, based on the trend judgment criteria information 32, detects a tendency towards hasty driving when the vehicle is traveling near pedestrians at a predetermined speed or higher despite the presence of pedestrians on the road, and adds a corresponding score to the hasty driving information (score information). In this way, the analysis unit 22 can accurately calculate the hasty driving information (score information) by using the speed information 31e.

[0093] The detection unit 23 detects that the driver is in a state of urgent driving based on the urgent driving information (score information) calculated as described above. For example, the detection unit 23 detects that the driver is in a state of urgent driving if the urgent driving information (score information) is equal to or greater than the detection standard value, based on the score information 33 and the detection standard information 34.

[0094] As a result, in this embodiment, it is possible to accurately detect whether the driver is in a state of rushed driving. In other words, in this embodiment, instead of using relative values ​​that depend on other vehicles traveling around vehicle V, the judgment criteria are based on driving conditions that are unlikely to occur during normal driving (for example, the number of lane changes being more than a predetermined number). Therefore, it is possible to reduce the influence of the driving conditions of other vehicles, and thus accurately detect whether the driver is in a state of rushed driving.

[0095] If the notification unit 24 detects that the driver is in a state of rushed driving, it outputs to the in-vehicle device 100 via the communication unit 11 that a state of rushed driving has been detected.

[0096] Here, we will explain the notification of the detection of a state of rushed driving, referring to Figure 6. Figure 6 is a diagram showing the output unit (display) 108 of the in-vehicle device 100 that has been notified of the detection of a state of rushed driving.

[0097] As shown in Figure 6, the notification unit 24 notifies the driver of information indicating that a state of rushed driving has been detected and displays it in the display area 200 of the output unit (display) 108. The display area 200 displays a message indicating that a state of rushed driving has been detected, such as "Are you driving in a hurry? Please drive safely." This makes the driver aware that they are driving in a hurry and encourages them to stop driving in a hurry. In the above example, the message is displayed in the output unit (display) 108, but this is not the only way to notify the driver. For example, the message may be output from the speaker of the output unit 108.

[0098] <Control processing of the detection device> Next, an example of a specific processing procedure in the detection device 10 will be explained using Figure 7. Figure 7 is a flowchart showing the processing procedure executed by the detection device 10.

[0099] As shown in Figure 7, the control unit 20 of the detection device 10 detects driving status information indicating the driving status of vehicle V and the driver of vehicle V based on the output of various sensors such as the front camera 105 (step S10).

[0100] Next, the control unit 20 analyzes the driving status information and calculates score information (an example of rushed driving information) that indicates the degree of the driver's tendency to drive hastily (step S11). Next, the control unit 20 determines whether the calculated score information (rushed driving information) is equal to or greater than the detection threshold value (step S12).

[0101] If the control unit 20 determines that the score information is above the detection threshold value (step S12, Yes), it detects that the driver is in a state of rushed driving (step S13). Next, the control unit 20 notifies the driver that the driver is in a state of rushed driving (step S14).

[0102] On the other hand, if the control unit 20 determines that the score information is not equal to or greater than the detection threshold value (step S12, No), that is, if the score information is less than the detection threshold value, it skips the processing in steps S13 and S14.

[0103] As described above, the detection device 10 according to the embodiment has a control unit 20. The control unit 20 detects driving state information indicating the driving state of at least one of the vehicle and the driver of the vehicle. The control unit 20 analyzes the detected driving state information and calculates hasty driving information indicating the degree of the driver's tendency to drive hastily. Based on the calculated hasty driving information, the control unit 20 detects that the driver's state is one of hasty driving. This makes it possible to accurately detect that the driver's state is one of hasty driving.

[0104] In the above description, the detection device 10 performs processing to detect whether the driver is in a state of rushed driving. However, the system is not limited to this, and for example, the in-vehicle device 100 may be configured to perform all or part of the processing performed by the detection device 10. That is, for example, the control unit (an example of an in-vehicle device control unit) 110 of the in-vehicle device 100 may be configured to detect driving state information indicating the driving state of at least one of the vehicle and the vehicle's driver, analyze the detected driving state information to calculate rushed driving information indicating the degree of the driver's tendency to rush, and detect whether the driver is in a state of rushed driving based on the calculated rushed driving information. Even with such a configuration, it is possible to accurately detect whether the driver is in a state of rushed driving.

[0105] Furthermore, if the control unit 20 of the detection device 10 or the control unit 110 of the in-vehicle device 100 detects a state of rushed driving, it may perform a process (overwrite prevention process) to save various information, such as image data and driving state information 31, from the state of rushed driving to the storage unit 30 or storage unit 120. This makes it possible, for example, to provide the saved information as educational material for traffic safety education to the driver who was driving rushed or to other drivers.

[0106] (modified version) Next, I will explain the modified version. The detection criteria value described above is set to the urgent driving information (score information) calculated when an average driver is driving normally, but it is not limited to this. In other words, in the modified version, the detection criteria value is set to the urgent driving information (score information) calculated when the driver themselves is driving normally (not urgent driving).

[0107] Therefore, the detection unit 23 of the control unit 20 compares the urgent driving information (score information) calculated this time with the urgent driving information (score information; in this case, the detection criterion value) calculated during normal driving, and detects that the driver's state is that of urgent driving based on the comparison result.

[0108] In more detail, the detection unit 23 detects that if the hasty driving information (score information) is above a detection threshold value, which is the score information calculated when the driver is driving normally, the driver's state is different from the normal state and is a state of hasty driving caused by a psychological state such as impatience.

[0109] In this modified example, by comparing the current driving with the driver's normal driving (non-urgent driving), it is possible to accurately detect whether the driver is in a state of urgency.

[0110] Further effects and modifications can be readily derived by those skilled in the art. Therefore, broader aspects of the present invention are not limited to the specific details and representative embodiments expressed and described above. Accordingly, various modifications are possible without departing from the spirit or scope of the overall concept of the invention as defined by the appended claims and their equivalents. [Explanation of symbols]

[0111] 1. Detection System 10 Detection device 20 Control Unit 100 Onboard equipment 110 Control Unit

Claims

1. A method for calculating a score of a specific behavior based on the number of times that the behavior of the vehicle relative to the lane corresponds to a specific behavior from outside image information of the vehicle's surroundings or sensor information of the vehicle, Calculating the number of times the driver has looked away from the vehicle as a score of the looking away from the vehicle from information on the driver's line of sight based on in-vehicle image information obtained by capturing an image of the interior of the vehicle; Calculating the number of times that the inter-vehicle distance between the vehicle and another vehicle is less than a reference value from the vehicle exterior image information or the vehicle sensor information as a score of the inter-vehicle distance; A control unit is provided for comparing the scores of the specific behavior, the distracted driving, and the vehicle distance with the scores of the items during past driving to display a driving tendency. Information processing device.

2. The control unit is If the score for each of the items is higher than the score for the previous driving, a message encouraging safe driving is displayed on the display of the vehicle. The information processing device according to claim 1 .

3. The control unit is Correcting the score of each of the items according to a weighting coefficient previously assigned to each of the items; If the corrected score is higher than the score from the previous driving, a message encouraging safe driving is displayed on the display of the vehicle. The information processing device according to claim 1 .

4. The control unit is Calculating the number of times that the number of lane changes of the vehicle exceeds a preset reference number as a score of the specific behavior.

4. The information processing device according to claim 1.

5. The control unit is calculating a score for the inter-vehicle distance after a lane change based on the outside-vehicle image information or the sensor information of the vehicle, the number of times that the inter-vehicle distance with the front vehicle or the rear vehicle after a lane change is less than a reference value; In addition to each of the above items, a score regarding the following distance after the lane change is further displayed.

5. The information processing device according to claim 1.

6. The judgment reference value is set to a larger value as the speed of the vehicle increases. The information processing device according to claim 5 .

7. The control unit is Detecting the display state of a traffic light from the outside-vehicle image information, and calculating the number of times the vehicle has passed through a red or yellow light as a score related to the traffic light; In addition to each of the items, a score regarding the traffic light is further displayed.

7. The information processing device according to claim 1.

8. The control unit: obtaining the outside image information, the sensor information of the vehicle, or the inside image information from an in-vehicle device via a communication network; 8. The information processing device according to claim 1.

9. A method for calculating a score of a specific behavior based on the number of times that the behavior of the vehicle relative to the lane corresponds to a specific behavior from outside image information of the surroundings of the vehicle or sensor information of the vehicle, Calculating the number of times the driver has looked away from the vehicle as a score of the looking away from the vehicle from information on the driver's line of sight based on in-vehicle image information obtained by capturing an image of the interior of the vehicle; Calculating the number of times that the inter-vehicle distance between the vehicle and another vehicle is less than a reference value from the vehicle exterior image information or the vehicle sensor information as a score of the inter-vehicle distance; Displaying a driving tendency by comparing scores relating to each of the specific behavior, the distracted driving, and the vehicle-to-vehicle distance with scores for each of the items during past driving. A program that causes a computer to execute a process.

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