Information processing apparatus and information processing method

Abstract

The invention provides a technique for improving diagnosis of driving conditions of a driver of a vehicle. An information processing device is provided with: a control unit that performs processing for acquiring prescribed data from a traveling vehicle; according to specified data, determining a starting point at which the vehicle starts to turn left and an ending point at which the vehicle ends the left turn at the determined intersection; an estimation unit that estimates a travel trajectory of the vehicle traveling from the start point to the end point on the basis of predetermined data; and diagnosing the driving tendency of the driver of the vehicle on the basis of the difference between the estimated driving trajectory and an ideal trajectory recommended when turning left at the determined intersection.

Description

Technical Field

[0001] This invention relates to an information processing device and an information processing method. Background Technology

[0002] Previously, techniques for diagnosing a vehicle driver's driving tendencies were known. For example, Patent Document 1 discloses a technique that diagnoses vehicle driving by comparing an ideal trajectory corresponding to the shape of the road the vehicle travels on with the actual driving trajectory.

[0003] Patent Document 1: Japanese Patent Application Publication No. 2014-194620 Summary of the Invention

[0004] When making a left turn at an intersection, drivers sometimes lack clarity regarding the appropriate driving trajectory, leading to either a narrow or wide turn. However, Patent Document 1 does not disclose diagnostic indicators that allow drivers to objectively perceive their driving tendencies when making left turns. Therefore, there is room for improvement in the technology for diagnosing a driver's driving condition.

[0005] In view of this situation, the object of the present invention is to improve the technology for diagnosing the driving condition of a vehicle driver.

[0006] An information processing apparatus according to one embodiment of the present invention includes a control unit that performs the following processing: acquiring predetermined data measured by sensors mounted on a moving vehicle; determining, based on the predetermined data, a starting point for the vehicle to begin a left turn at a predetermined intersection and an ending point for the left turn; estimating, based on the predetermined data, the driving trajectory of the vehicle traveling in the interval from the starting point to the ending point; and diagnosing the driving tendency of the vehicle's driver based on the difference between the estimated driving trajectory and the ideal trajectory recommended when making a left turn at the predetermined intersection.

[0007] An information processing apparatus according to one embodiment of the present invention includes a control unit that performs the following processing: acquiring predetermined data from a moving vehicle; determining, based on the predetermined data, the starting point for the vehicle to begin a left turn at a predetermined intersection and the ending point for the left turn; estimating, based on the predetermined data, the driving trajectory of the vehicle traveling in the interval from the starting point to the ending point; and diagnosing the driving tendency of the vehicle's driver based on the difference between the estimated driving trajectory and the ideal trajectory recommended when making a left turn at the predetermined intersection.

[0008] An embodiment of the present invention relates to an information processing method that performs the following processing via an information processing device: acquiring predetermined data from a moving vehicle; determining, based on the predetermined data, the starting point and the ending point of the left turn at a predetermined intersection; estimating, based on the predetermined data, the driving trajectory of the vehicle in the interval from the starting point to the ending point; and diagnosing the driving tendency of the vehicle's driver based on the difference between the estimated driving trajectory and the ideal trajectory recommended when making a left turn at the predetermined intersection.

[0009] Invention Effects

[0010] According to one embodiment of the present invention, the technology for diagnosing the driving condition of a vehicle driver is improved. Attached Figure Description

[0011] Figure 1 This is a block diagram illustrating a schematic structural example of a system according to an embodiment of the present invention.

[0012] Figure 2 It is a flowchart illustrating the operation of an information processing device.

[0013] Figure 3 It is a standardized graph that compares the driving trajectory of a vehicle when turning left at an intersection with its ideal trajectory. Detailed Implementation

[0014] (Summary of the implementation method)

[0015] refer to Figure 1 The following is a summary description of system 1 according to an embodiment of the present invention. System 1 includes a vehicle 10, an information processing device 20, and a terminal device 30. The vehicle 10, the information processing device 20, and the terminal device 30 are communicatively connected, for example, to a network 2 including the Internet and mobile communication networks.

[0016] Vehicle 10 may be, for example, a car, but is not limited to this, and may be any vehicle. A car may be a gasoline car, a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), or a fuel cell electric vehicle (FCEV), etc., but is not limited to these.

[0017] The information processing device 20 is, for example, a computer such as a server. The information processing device 20 can communicate with the vehicle 10 and the terminal device 30 via the network 2.

[0018] The terminal device 30 is a smartphone held by the driver 3 of the vehicle 10. However, the terminal device 30 is not limited to a smartphone and can be any information processing terminal. The terminal device 30 can communicate with the vehicle 10 and the information processing device 20 via the network 2.

[0019] (Vehicle structure)

[0020] like Figure 1 As shown, the vehicle 10 includes a communication unit 11, a measurement unit 12, a storage unit 13, and a control unit 14.

[0021] The communication unit 11 has a communication interface for wireless connection to network 2. The communication interface for connection to network 2 is compatible with mobile communication standards such as 4th Generation (4G) or 5th Generation (5G), but is not limited to these.

[0022] The measurement unit 12 is equipped with a sensor 12A. The sensor 12A may be a front-facing camera, a 3D-LiDAR, a millimeter-wave sensor, an accelerometer, a vehicle speed sensor, a gyroscope sensor, or a GPS sensor, but the sensor 12A is not limited to these.

[0023] The storage unit 13 includes one or more memory units. These memory units may be, for example, semiconductor memory, magnetic memory, or optical memory, but are not limited to these. Each memory unit included in the storage unit 13 may function as a main storage device, an auxiliary storage device, or a cache memory. The storage unit 13 stores any information related to the operation of the vehicle 10.

[0024] The control unit 14 includes one or more processors, one or more programmable circuits, one or more dedicated circuits, or combinations thereof. The processor may be, for example, a general-purpose processor such as a Central Processing Unit (CPU) or a Graphics Processing Unit (GPU), or a dedicated processor for specific processing, but is not limited to these. The programmable circuit may be, for example, a Field-Programmable Gate Array (FPGA), but is not limited to these. The dedicated circuit may be, for example, an Application Specific Integrated Circuit (ASIC), but is not limited to these. The control unit 14 controls the overall movement of the vehicle 10.

[0025] (Composition of information processing device)

[0026] like Figure 1As shown, the information processing device 20 includes a communication unit 21, a storage unit 22, and a control unit 23.

[0027] The communication unit 21 includes one or more communication interfaces connected to the network 2. These communication interfaces may correspond to, for example, mobile communication standards, wired local area network (LAN) standards, or wireless LAN standards, but may also correspond to any communication standard.

[0028] The storage unit 22 includes one or more memory units. These memory units may be, for example, semiconductor memory, magnetic memory, or optical memory, but are not limited to these. Each memory unit included in the storage unit 22 may function as a main storage device, an auxiliary storage device, or a cache memory. The storage unit 22 stores any information used for the operation of the information processing device 20. For example, the storage unit 22 may include a database 22A that stores predetermined information received from the vehicle 10.

[0029] The control unit 23 includes one or more processors, one or more programmable circuits, one or more dedicated circuits, or combinations thereof. The control unit 23 controls the overall operation of the information processing device 20.

[0030] (Structure of the terminal device)

[0031] like Figure 1 As shown, the terminal device 30 includes a communication unit 31, an output unit 32 with a display 32A, a storage unit 33, and a control unit 34. Detailed descriptions of the structure of the terminal device 30 are omitted.

[0032] (The operation flow of the information processing device)

[0033] Figure 2 It is a timing diagram representing the action examples of the system. Figure 3 This is a standardized graph comparing the trajectory of vehicle 10 as it makes a left turn at intersection cr with its ideal trajectory. (Reference) Figure 2 and Figure 3 The operation of the information processing apparatus 20 according to this embodiment will be explained.

[0034] S101: Vehicle 10 begins to move.

[0035] S102: During the operation of the vehicle 10, the measuring unit 12 of the vehicle 10 continuously measures a specified data d by the sensor 12A mounted on the vehicle 10.

[0036] Sensor 12A includes, but is not limited to, a front-facing camera, 3D-LiDAR, millimeter-wave sensor, accelerometer, vehicle speed sensor, gyroscope sensor, and GPS sensor. The specified data d includes the vehicle 10's GPS timestamp, vehicle speed, steering angle, yaw rate, and turn signal W (left turn signal LW and right turn signal RW). The specified data d can also be signals from the vehicle 10's Controller Area Network (CAN).

[0037] S103: The control unit 14 of the vehicle 10 sends the continuously measured, specified data d to the information processing device 20.

[0038] S104-S105: The control unit 23 of the information processing device 20 stores the specified data d each time it acquires the specified data d.

[0039] Each time the control unit 23 acquires the specified data d continuously sent from the control unit 14, it stores the acquired specified data d in the database 22A provided by the storage unit 22.

[0040] S106: Control unit 14 confirms whether vehicle 10 has reached its destination. If vehicle 10 has reached its destination, information processing ends; otherwise, it returns to S102.

[0041] S107: The control unit 23 determines the starting point sp of the vehicle 10 starting to turn left at the designated intersection cr and the ending point ep of the left turn based on the acquired specified data d.

[0042] The designated intersection CR is not limited to one location; there can be multiple intersections within the section from the origin to the destination of vehicle 10. In the case of multiple designated intersections CR, the control unit 23 performs information processing from S107 to S109 on each of the multiple designated intersections CR.

[0043] The specified data d includes GPS timestamp recording time and GPS latitude and longitude coordinates. Control unit 23 uses the GPS timestamps to detect when vehicle 10 approaches or enters the designated intersection cr. For example... Figure 3 As shown in (a), vehicle 10, entering the designated intersection cr, flashes its left turn signal WL, begins to turn left at the starting point sp, and follows the driving trajectory indicated by the dashed line, ending the left turn at the ending point ep.

[0044] The control unit 23 determines the starting point for the vehicle 10 to begin a left turn based on the turn signal W and yaw rate included in the specified data d. For example, the control unit 23 can determine the starting point sp for the vehicle 10 to begin a left turn at the specified intersection cr as the location where the left turn signal LW is turned ON and the absolute value of the yaw angle exceeds a specified angle (e.g., the location where the absolute value of the yaw angle is > 5 degrees).

[0045] The yaw rate included in the specified data d is the angular velocity (deg / sec) of the rotational direction of vehicle 10, i.e., the velocity at which vehicle 10 intends to change its orientation. The yaw angle is the angle (deg) representing the direction in which vehicle 10 is facing. The yaw angle is the cumulative value of the yaw rate, calculated by integrating the yaw rate over time.

[0046] The control unit 23 determines the endpoint ep where the vehicle 10 ends its left turn based on the yaw rate included in the specified data d. The control unit 23 determines the endpoint ep where the yaw angle at the starting point sp of the vehicle 10 changes by 90 degrees in the left-turn direction after the start of the left turn (strictly speaking, 80 degrees < yaw angle < 100 degrees), and the change in yaw angle compared to a specified time (e.g., 0.5 seconds before) is less than a specified angle (e.g., < 1 degree).

[0047] S108: The control unit 23 estimates the driving trajectory Tev of the vehicle 10 in the interval S from the starting point sp to the ending point ep based on the acquired specified data d.

[0048] The control unit 23 estimates the driving trajectory Tev in the interval S from the starting point sp to the ending point ep based on the vehicle speed and yaw rate included in the specified data d.

[0049] Figure 3 Example of the estimated driving trajectory Tev of vehicle 10 is shown in (b). In this case, when (i) the left turn signal LW turns ON and the absolute value of the steering angle is >10 degrees, (ii) the yaw angle, which is the cumulative value of the yaw rate from the starting point sp to the ending point ep, is other than 80 degrees < yaw angle < 100 degrees, and (iii) the intersection radius is estimated based on GPS coordinate data and the turning radius of vehicle 10 is <8 m or >18 m, the control unit 23 does not determine that vehicle 10 has made a left turn and does not estimate the driving trajectory Tev.

[0050] S109: The control unit 23 diagnoses the driving tendency of the driver 3 of the vehicle 10 based on the difference between the estimated driving trajectory Tev and the ideal trajectory Tid recommended when turning left at the intersection cr.

[0051] The ideal trajectory Tid is obtained by averaging the driving trajectory of a test driver with high driving skills when making a left turn at a predetermined intersection cr. The ideal trajectory Tid is stored in the database 22A of the storage unit 22 for each intersection.

[0052] exist Figure 3 In example (b), the estimated driving trajectory Tev is located further inside than the ideal trajectory Tid. In this case, driver 3 is diagnosed as "having a tendency to make small turns within the intersection".

[0053] The control unit 23 can also diagnose the vehicle speed and the start time of the left turn of the driver 3 of the vehicle 10 when entering the intersection cr by comparing with the ideal trajectory Tid.

[0054] Furthermore, the control unit 23 can derive the difference between the driving trajectory Tev and the ideal trajectory Tid as the small turning amount α, and diagnose the driving tendency of the driver 3 of the vehicle 10 based on the derived small turning amount α.

[0055] refer to Figure 3 In example (b), the control unit 23 extracts the first coordinate point c1(x1,y1) with the lowest vehicle speed among the coordinate points with the highest yaw rate on the ideal trajectory Tid, and the second coordinate point c2(x2,y2) with the lowest vehicle speed among the coordinate points with the highest yaw rate on the driving trajectory Tev. The control unit 23 derives the small turning amount α from the distance between the extracted first coordinate point c1(x1,y1) and the second coordinate point c2(x2,y2).

[0056] Moreover, with Figure 3 In contrast to example (b), if the estimated driving trajectory Tev is located further out than the ideal trajectory Tid, it is diagnosed that driver 3 "has a tendency to make sharp turns within the intersection." In this case, control unit 23 can derive the difference between the driving trajectory Tev and the ideal trajectory Tid as the sharp turn amount β, and diagnose the driving tendency of driver 3 of vehicle 10 based on the derived sharp turn amount β. Furthermore, for example, if the driving trajectory Tev of vehicle 10 extends beyond the oncoming lane and rotates significantly, that is, if the driving trajectory Tev... Figure 3 If the standardization range of (b) is exceeded, the control unit 23 can derive the large turning amount β as the excess amount β′.

[0057] The large turning amount β and the excess amount β′ are derived using the same method as the small turning amount α. Additionally, the small turning amount α, which is closer to the inner side than the ideal trajectory, can be set to a positive value, while the large turning amount β and the excess amount β′, which are on the outer side, can be set to negative values.

[0058] S110: The control unit 23 sends the diagnostic results of the driver 3's driving tendency to the terminal device 30 held by the driver 3.

[0059] S111: The control unit 34 of the terminal device 30 displays the diagnostic results of the driver 3's driving tendency on the display 32A.

[0060] The diagnostic results of driving tendency include Figure 3 Example (b) shows one or more of the following: a chart, a small turning amount α or a large turning amount β, and information that prompts the driver to change their driving behavior.

[0061] As described above, the information processing device 20 of this embodiment performs the following processing: acquiring predetermined data d from the moving vehicle 10; determining the starting point sp and the ending point ep of the left turn at the predetermined intersection cr based on the predetermined data d; estimating the driving trajectory Tev of the vehicle 10 in the interval S from the starting point sp to the ending point ep based on the predetermined data d; and diagnosing the driving tendency of the driver 3 of the vehicle 10 based on the difference between the estimated driving trajectory Tev and the ideal trajectory Tid recommended when turning left at the predetermined intersection cr.

[0062] According to this structure, the driving trajectory Tev of vehicle 10 is estimated based on prescribed data obtained from the vehicle 10 in motion. Then, by deriving the difference between the driving trajectory Tev and the ideal trajectory Tid, it is possible to diagnose whether the driver 3 is driving along the inner side or the outer side of the ideal trajectory Tid. Therefore, the driver of vehicle 10 can obtain an indicator that allows for an objective evaluation of their driving tendency when making left turns. Thus, from the viewpoint of increasing the possibility of driver 3 improving their driving tendency (driving habits) in small / large turns, this technique for diagnosing the driver's driving condition in a vehicle is improved.

[0063] Although the present invention has been described with reference to the accompanying drawings and embodiments, those skilled in the art should note that various modifications and alterations can be made according to the present invention. Therefore, it should be understood that such modifications and alterations are included within the scope of the present invention. For example, the functions included in each component or step can be reconfigured in a logically consistent manner, and multiple components or steps can be combined into one or divided.

[0064] For example, in the above embodiments, it is also possible to implement an embodiment in which the structure and operation of the information processing device 20 are distributed among multiple computers capable of communicating with each other. For example, the structure could be as follows: the information processing device 20 is divided into a server that receives predetermined data d from the vehicle 10 and stores it in a database, and a computer that retrieves the predetermined data d stored in the server, estimates the driving trajectory Tev, and diagnoses the difference between the driving trajectory Tev and the ideal trajectory Tid. With this structure, it is possible to analyze large amounts of data received from a large number of vehicles.

[0065] Furthermore, for example, it is also possible to implement a general-purpose computer as the information processing apparatus 20 described in the above embodiments. Specifically, a program containing processing content for implementing the various functions of the information processing apparatus 20 described in the above embodiments is stored in the memory of a general-purpose computer, and the program is read and executed by a processor. Therefore, the present invention can also be implemented as a program executable by a processor or as a non-transitory computer-readable medium storing the program.

[0066] Symbol Explanation

[0067] 1-System, 2-Network, 3-Driver, 10-Vehicle, 11, 21, 31-Communication Unit, 12-Measurement Unit, 12A-Sensor, 13, 22, 33-Storage Unit, 14, 23, 34-Control Unit, 20-Information Processing Device, 22A-Database, 30-Terminal Device, 32-Output Unit, 32A-Display.

Claims

1. An information processing device, characterized in that, have: The control unit performs the following processing: acquiring prescribed data from a moving vehicle measured by sensors mounted on the vehicle; and determining, based on the prescribed data, the starting point for the vehicle to begin a left turn at a predetermined intersection and the ending point for the left turn. Based on the specified data, estimate the driving trajectory of the vehicle in the interval from the starting point to the ending point; and diagnose the driving tendency of the driver of the vehicle based on the difference between the estimated driving trajectory and the recommended ideal trajectory when turning left at the specified intersection.

2. An information processing device, characterized in that, have: The control unit performs the following processing: acquiring specified data from the moving vehicle; and determining, based on the specified data, the starting point for the vehicle to begin a left turn at a designated intersection and the ending point for the left turn. Based on the specified data, estimate the driving trajectory of the vehicle in the interval from the starting point to the ending point; and diagnose the driving tendency of the driver of the vehicle based on the difference between the estimated driving trajectory and the recommended ideal trajectory when turning left at the specified intersection.

3. The information processing device according to claim 2, characterized in that, The specified data includes the vehicle's GPS timestamp, speed, steering angle, yaw rate, and turn signal.

4. The information processing apparatus according to claim 3, characterized in that, The control unit performs the following processing: determining the starting point based on the turn signal and the yaw rate included in the specified data; determining the ending point based on the yaw rate included in the specified data; and estimating the driving trajectory based on the vehicle speed and the yaw rate included in the specified data.

5. The information processing apparatus according to claim 3, characterized in that, The difference is the small turning amount. The control unit performs the following processing: extracts the first coordinate point where the vehicle speed is lowest among the coordinate points where the yaw rate is maximum on the ideal trajectory, and the second coordinate point where the vehicle speed is lowest among the coordinate points where the yaw rate is maximum on the driving trajectory; derives the distance from the extracted first coordinate point to the second coordinate point as the small turning amount; and diagnoses the driving tendency of the vehicle's driver based on the derived small turning amount.

6. An information processing method, characterized in that, The following processing is performed by the information processing device: Obtain the prescribed data from vehicles in motion; Based on the specified data, determine the starting point and ending point of the left turn for the vehicle at the designated intersection; Based on the specified data, estimate the driving trajectory of the vehicle in the interval from the starting point to the ending point; and The driver's driving tendency is diagnosed based on the difference between the estimated driving trajectory and the ideal trajectory recommended when turning left at the designated intersection.

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