Evaluation system and evaluation method

Abstract

This invention provides a technique for evaluating the acceleration characteristics of a vehicle without relying on the operator's perception. An evaluation system includes: an acceleration processing unit that performs an acceleration process to increase the vehicle's speed by autonomously controlling a vehicle equipped with a driving motor; an acquisition unit that acquires recorded data containing vehicle speed values ​​and torque values ​​related to the motor's drive torque during the acceleration process; and an evaluation unit that uses the acquired recorded data to evaluate the vehicle's acceleration characteristics.

Description

Technical Field

[0001] This invention relates to an evaluation system and evaluation method. Background Technology

[0002] Patent document 1 discloses a technology for driving a vehicle autonomously or remotely during the vehicle manufacturing process.

[0003] Patent Document 1: Japanese Patent Publication No. 2017-538619 Summary of the Invention

[0004] In vehicle manufacturing or inspection plants, vehicle acceleration characteristics are sometimes evaluated. Traditionally, these evaluations relied on the operator's perception while driving the vehicle. A technology is desired that utilizes autonomous driving to evaluate vehicle acceleration characteristics without relying on operator perception.

[0005] The present invention can be implemented in the following manner.

[0006] (1) According to one aspect of the present invention, an evaluation system is provided. The evaluation system comprises: an acceleration processing unit that causes a vehicle having a driving motor to move under autonomous driving control via the autonomous driving control, thereby performing an acceleration processing that increases the vehicle speed; an acquisition unit that acquires recorded data that records values ​​related to the vehicle speed in the acceleration processing, namely vehicle speed values, and torque values ​​related to the driving torque of the motor in the acceleration processing; and an evaluation unit that uses the acquired recorded data to evaluate the acceleration characteristics of the vehicle.

[0007] According to this method, the acceleration characteristics of a vehicle can be evaluated using unmanned driving control without relying on the operator's perception.

[0008] (2) In the above method, the evaluation unit evaluates the acceleration characteristics by comparing the recorded data with reference data that predefines the reference values ​​for the vehicle speed and torque according to the vehicle's specifications. According to this method, the acceleration characteristics of vehicle 100 can be evaluated more appropriately according to the vehicle's specifications.

[0009] (3) In the above method, it can be as follows: the acceleration processing unit increases the vehicle speed while the wheel is supported by a roller that can rotate while supporting the wheel of the vehicle. According to this method, by rotating the wheel on the roller, recorded data can be acquired to evaluate the acceleration characteristics without moving the vehicle.

[0010] (4) In the above method, it can be as follows: the acceleration processing unit causes the vehicle to travel from a first location where a first process related to the vehicle is performed toward a second location where a second process, which is a follow-up to the first process, is performed. According to this method, during the sequential performance of vehicle-related processes, the vehicle is driven from the first location toward the second location by unmanned driving, thereby enabling the evaluation of acceleration characteristics.

[0011] In addition to the above-described form as an evaluation system, the present invention can also be implemented as a control device, an evaluation method, a program for implementing the evaluation method, a program product containing the program, etc. Attached Figure Description

[0012] Figure 1 This is an explanatory diagram of the evaluation system in the first embodiment.

[0013] Figure 2 This is an explanatory diagram showing a roller device.

[0014] Figure 3 This is a flowchart illustrating the processing steps for vehicle driving control in the first embodiment.

[0015] Figure 4 This is a flowchart illustrating the processing steps of the evaluation process in the first embodiment.

[0016] Figure 5 This is a diagram illustrating an example of acceleration characteristic evaluation.

[0017] Figure 6 This is an explanatory diagram of the accelerated processing in the second embodiment.

[0018] Figure 7 This is an explanatory diagram showing the general structure of the system in the third embodiment.

[0019] Figure 8 This is a flowchart illustrating the processing steps for vehicle driving control in the third embodiment. Detailed Implementation

[0020] A. Implementation Method 1:

[0021] Figure 1 This is an explanatory diagram of the evaluation system 50 in the first embodiment. The evaluation system 50 includes one or more vehicles 100, a server 200, and one or more external sensors 300. Furthermore, in this embodiment, the evaluation system 50 includes a roller device 500.

[0022] The vehicle 100 is equipped with a motor 103 for driving. The vehicle 100 is configured to drive by consuming electricity from a battery (not shown) installed in the vehicle 100 to drive the motor 103.

[0023] Vehicle 100 may be an electric vehicle, such as a Battery Electric Vehicle (BEV), a Hybrid Electric Vehicle (HEV), a Plug-in Hybrid Electric Vehicle (PHEV), or a Fuel Cell Electric Vehicle (FCEV). Vehicle 100 may be a vehicle that travels on an unlimited track, such as a car, truck, bus, two-wheeled vehicle, four-wheeled vehicle, or construction vehicle.

[0024] Vehicle 100 is configured to operate autonomously. "Autonomous driving" refers to driving without relying on occupant-based driving operations. Driving operations refer to operations related to at least one of "driving," "turning," or "stopping" of vehicle 100. Autonomous driving is achieved through automatic or manual remote control using devices located outside vehicle 100, or through autonomous control of vehicle 100. In the autonomously operating vehicle 100, occupants who do not perform driving operations can ride on board. Occupants who do not perform driving operations include, for example, people who simply sit in the seats of vehicle 100, or people performing tasks different from driving operations such as assembly, inspection, or switching operations on vehicle 100. Furthermore, driving based on occupant-based driving operations is sometimes referred to as "manned driving."

[0025] In this specification, "remote control" includes "full remote control," which completely determines all actions of vehicle 100 from outside the vehicle 100, and "partial remote control," which determines some actions of vehicle 100 from outside the vehicle 100. Furthermore, "autonomous control" includes "full autonomous control," where vehicle 100 autonomously controls its own actions without receiving any information from external devices, and "partial autonomous control," where vehicle 100 autonomously controls its own actions using information received from external devices.

[0026] In addition, controls used to achieve driverless driving, such as remote control or autonomous control, are also called driverless control. And controls used to achieve manned driving are also called manned control.

[0027] In this embodiment, the evaluation system 50 is used in the factory FC that manufactures the vehicle 100. The reference coordinate system of the factory FC is the global coordinate system GC, and any position within the factory FC can be represented by the X, Y, and Z coordinates in the global coordinate system GC. The factory FC has a first location PL1 and a second location PL2. The first location PL1 and the second location PL2 are connected by a travel route TR that the vehicle 100 can travel on. In the first location PL1, a first process related to the vehicle 100 is performed, and in the second location PL2, a second process related to the vehicle 100 is performed. The second process is a subsequent process of the first process. Furthermore, in this embodiment, the first process and the second process are respectively equivalent to the manufacturing process of the vehicle 100. The vehicle 100 moves from the first location PL1 to the second location PL2 via the travel route TR using autonomous driving. In this embodiment, a roller device 500 is arranged in the second location PL2.

[0028] Figure 2 This is an explanatory diagram showing the roller device 500 in this embodiment. The roller device 500 is an example of an inspection device for inspecting the vehicle 100. Figure 2 As shown, the roller device 500 includes a roller 510, a roller control device 520, and a device sensor 530.

[0029] Rollers 510 are installed, for example, on the road surface of a factory FC or on a roller platform capable of carrying vehicles 100, so that vehicles 100 can drive onto rollers 510. Rollers 510 are configured to rotate while supporting the wheels 101 of the vehicle 100. In this embodiment, the roller device 500 has a roller unit 511 for each wheel 101. In this embodiment, the roller unit 511 has two rollers 510: a front roller 510A and a rear roller 510B. The front roller 510A is located on the +X direction side of the rear roller 510B. That is, the roller device 500 is configured to support each wheel 101 with two rollers 510, and has a total of eight rollers 510. Figure 2 In the diagram, roller 510 is marked with a shaded line. Alternatively, in another embodiment, a roller unit 511 can be provided on each of the pair of front wheels and the pair of rear wheels, configured to support both left and right wheels 101 together. Furthermore, the roller unit 511 can be configured, for example, to support one front wheel with roller 510 and one rear wheel with two rollers 510, or it can be configured to support one front wheel with two rollers 510 and one rear wheel with two rollers 510.

[0030] The device sensor 530 includes a circumferential speed sensor for detecting the circumferential speed of the roller 510. The circumferential speed sensor may be, for example, a speed sensor for detecting the rotational speed of the roller 510.

[0031] The roller control device 520 controls various parts of the roller equipment 500. The roller control device 520 is composed of a computer equipped with a processor 521, a memory 522, an input / output interface 523, and an internal bus. The processor 521, memory 522, and input / output interface 523 are bidirectionally connected via the internal bus. The roller control device 520 has a communication device (not shown) capable of communicating with other devices, such as the server 200, via wired or wireless communication. The processor 521 executes the program PG3 stored in the memory 522 to perform various functions.

[0032] The roller device 500 in this embodiment has a following rotation function. The following rotation function is the function of causing the roller 510 to rotate following the rotation of the wheels 101 on the roller 510. In this embodiment, in the second location PL2, the following rotation function of the roller device 500 is used to perform the acceleration characteristic evaluation described later. When the roller 510 is rotated by the following rotation function, the vehicle speed or acceleration of the vehicle 100 can be detected using the detection result of the circumferential speed sensor included in the device sensor 530. The roller device 500 with the following rotation function is also referred to as a "drum testing machine".

[0033] like Figure 1 As shown, in the factory FC, multiple external sensors 300 are installed along the driving route TR. The positions of each external sensor 300 in the factory FC are pre-adjusted. The external sensors 300 are sensors located outside the vehicle 100. In this embodiment, the external sensor 300 is composed of a camera. The camera, serving as the external sensor 300, captures images of the vehicle 100 and outputs the image as a detection result. The external sensor 300 is equipped with a communication device (not shown) and can communicate with other devices such as the server 200 via wired or wireless communication.

[0034] The vehicle 100 includes: a vehicle control unit 110 for controlling various parts of the vehicle 100; an actuator assembly 120 including one or more actuators driven under the control of the vehicle control unit 110; a communication unit 130 for communicating with external devices such as a server 200 via wireless communication; and one or more internal sensors 140. The actuator assembly 120 includes actuators for a drive mechanism to accelerate the vehicle 100, actuators for a steering mechanism to change the direction of travel of the vehicle 100, and actuators for a braking mechanism to decelerate the vehicle 100. The drive mechanism includes a battery for driving, a motor 103, and drive wheels rotated by the motor 103. The actuator of the drive mechanism includes the motor 103.

[0035] The internal sensor 140 is a sensor mounted on the vehicle 100. The internal sensor 140 includes a vehicle speed sensor for detecting the vehicle speed, an acceleration sensor for detecting the vehicle acceleration, and a torque sensor for detecting the drive torque of the motor 103. In addition to the vehicle speed sensor, acceleration sensor, and torque sensor, the internal sensor 140 may also include various other sensors such as cameras, LiDAR, millimeter-wave radar, ultrasonic sensors, GPS sensors, wheel speed sensors, gyroscope sensors, shift position sensors, and encoders for detecting the movement of various parts of the vehicle 100. Furthermore, the wheel speed sensor can be used as a vehicle speed sensor. And, as a torque sensor, for example, an ammeter for detecting the input current value input to the motor 103 can be used.

[0036] The vehicle control unit 110 comprises a computer equipped with a processor 111, a memory 112, an input / output interface 113, and an internal bus 114. The processor 111, memory 112, and input / output interface 113 are bidirectionally connected via the internal bus 114. An actuator assembly 120 and a communication device 130 are connected to the input / output interface 113. The processor 111 executes a program PG1 stored in the memory 112 to perform various functions, including those of the vehicle control unit 115.

[0037] The vehicle control unit 115 drives the vehicle 100 by controlling the actuator assembly 120. The vehicle control unit 115 can drive the vehicle 100 by controlling the actuator assembly 120 using a driving control signal received from the server 200. The driving control signal is a control signal used to drive the vehicle 100. In this embodiment, the driving control signal includes the acceleration and steering angle of the vehicle 100 as parameters. In another embodiment, the driving control signal may replace the acceleration of the vehicle 100, or may include the speed of the vehicle 100 as a parameter in addition to the acceleration. Furthermore, in this embodiment, the vehicle control unit 115 generates driving control values ​​for controlling the actuator assembly 120 based on the parameters included in the received driving control signal, and uses the generated driving control values ​​to control the actuator assembly 120. The driving control values ​​include a torque indication value for indicating the drive torque of the motor 103 and a steering angle indication value for indicating the steering angle.

[0038] Server 200 is a computer comprising a processor 201, a memory 202, an input / output interface 203, and an internal bus 204. The processor 201, memory 202, and input / output interface 203 are bidirectionally connected via the internal bus 204. A communication device 205 for communicating with various external devices is connected to the input / output interface 203. The communication device 205 can communicate wirelessly with vehicle 100 and can communicate with various external sensors 300 via wired or wireless communication. The memory 202 stores program PG2, detection model DM, reference path RR, database DB, etc. The processor 201 executes program PG2 stored in memory 202 to implement various functions, including those of a remote control unit 210, an acquisition unit 220, and an evaluation unit 230.

[0039] The remote control unit 210 generates a driving control signal for controlling the actuator group 120 of the vehicle 100 and sends the driving control signal to the vehicle 100, thereby enabling the vehicle 100 to drive remotely.

[0040] In this embodiment, the remote control unit 210 functions as the acceleration processing unit 211. The acceleration processing unit 211 performs acceleration processing. Acceleration processing is the process of increasing the speed of the vehicle 100, i.e., the circumferential speed of the wheels 101, by moving the vehicle 100 through autonomous driving control. Acceleration processing is performed in order to generate the recording data described later.

[0041] In this embodiment, the acceleration process is performed while the wheel 101 is supported by the roller 510. More specifically, in the acceleration process, the acceleration processing unit 211 generates a driving control signal to increase the vehicle speed of the vehicle 100, i.e., the circumferential speed of the wheel 101, while the vehicle 100 is supported by the roller 510, and sends the generated driving control signal to the vehicle 100 on the roller 510, thereby increasing the vehicle speed of the vehicle 100.

[0042] Furthermore, in the acceleration process of this embodiment, the acceleration processing unit 211 performs driving feedback control. Driving feedback control includes at least one of vehicle speed feedback control and acceleration feedback control. Vehicle speed feedback control refers to providing feedback control on vehicle speed to achieve a specified vehicle speed. Acceleration feedback control refers to providing feedback control on acceleration to achieve a specified acceleration. In such feedback control, the acceleration processing unit 211 increases the drive torque of the motor 103 when the actual vehicle speed is lower than the specified vehicle speed, and decreases the drive torque of the motor 103 when the actual vehicle speed is higher than the specified vehicle speed. Additionally, in this embodiment, the remote control unit 210 performs driving feedback control not only during acceleration processing but also when the vehicle 100 is driven within the factory FC using autonomous driving control.

[0043] The acquisition unit 220 acquires recorded data. The recorded data includes data recording the vehicle speed value and torque value of the vehicle 100 during acceleration processing. The vehicle speed value is a value related to vehicle speed. The vehicle speed value includes, for example, at least one of vehicle speed and acceleration. The torque value is a value related to the drive torque of the motor 103. In this embodiment, the recorded data records the relationship between the vehicle speed value and the torque value of the vehicle 100 during acceleration processing. More specifically, the recorded data includes vehicle speed change data representing the time-series change of the vehicle speed value during acceleration processing and torque change data representing the time-series change of the torque value during acceleration processing. The vehicle speed value in the vehicle speed change data and the torque value in the torque change data correspond in time and are indirectly correlated via time.

[0044] In this embodiment, the recorded data is generated based on the detection results of the internal sensor 140. More specifically, in this embodiment, the vehicle speed value represents the vehicle speed detected using the vehicle speed sensor, which is the internal sensor 140. The torque value represents the drive torque detected using the torque sensor, which is the internal sensor 140. In other embodiments, the recorded data may be generated, for example, based on the detection results of the device sensor 530. Furthermore, in other embodiments, the drive torque in the recorded data may, for example, be the drive torque based on the torque indication value. This is because, typically, the difference between the drive torque based on the torque indication value and the actual drive torque is extremely small, thus allowing the drive torque based on the torque indication value to approximate the actual drive torque.

[0045] The evaluation unit 230 performs an acceleration characteristic evaluation using recorded data acquired by the acquisition unit 220 to evaluate the acceleration characteristics of the vehicle 100. The acceleration characteristic refers to the acceleration mode of the vehicle 100 when the drive unit is controlled in a way that accelerates the vehicle 100, and affects the acceleration feel of the vehicle 100.

[0046] In this embodiment, the evaluation unit 230 evaluates acceleration characteristics by comparing recorded data with reference data SD. Reference data SD is data predefined based on the specifications of vehicle 100, including a vehicle speed reference value as a reference value and a torque reference value as a reference value. The specifications of vehicle 100 mentioned here refer to, for example, specifications affecting the acceleration characteristics of vehicle 100, and more specifically, model, class, body type, vehicle weight, overall dimensions, wheel 101 specifications, motor 103 specifications, etc. Body type indicates a classification corresponding to the appearance or purpose of vehicle 100, such as "SUV," "sedan," "station wagon," "van," "minivan," "car," or "light vehicle." Wheel 101 specifications include, for example, wheel type, diameter, width, and coefficient of friction. Motor 103 specifications include, for example, motor type, rated voltage, rated output, rated speed, rated torque, input / output efficiency, starting torque, and maximum torque.

[0047] The baseline data SD is used as a benchmark for evaluating acceleration characteristics. The baseline data SD is prepared, for example, by recording the relationship between the vehicle speed and torque values ​​of an ideal vehicle 100 with anomalies related to acceleration characteristics, based on specifications for each vehicle 100. Furthermore, the baseline data SD can be prepared, for example, based on the results of simulations simulating the acceleration of the ideal vehicle 100.

[0048] In this embodiment, the reference data SD is stored in the database DB. The database DB stores specification information related to the specifications of the vehicle 100 and the reference data SD in an associated manner. Specification information includes, for example, identification information such as the vehicle identification number (VIN) or specification values ​​representing the specifications of the vehicle 100. Furthermore, in this embodiment, the acquisition unit 220 uses the specification information to acquire the reference data SD by referring to the database DB.

[0049] Furthermore, in this embodiment, the vehicle speed reference value is included in the vehicle speed reference data. The vehicle speed reference data is data that defines the vehicle speed reference values ​​along a time series and is included in the reference data SD. Furthermore, in this embodiment, the torque reference value is used as a reference value to determine the reference range of torque; more specifically, it is defined as the lower limit and upper limit of the reference range of torque values.

[0050] Figure 3 This is a flowchart illustrating the processing steps for driving control of the vehicle 100 in the first embodiment. Figure 3 In the processing steps, the processor 201 of the server 200 functions as a remote control unit 210 by executing program PG2. Furthermore, the processor 111 of the vehicle 100 functions as a vehicle control unit 115 by executing program PG1.

[0051] In step S1, the processor 201 of the server 200 uses the detection results output from the external sensor 300 to acquire vehicle position information. This vehicle position information is the basis for generating driving control signals. In this embodiment, the vehicle position information includes the position and orientation of the vehicle 100 in the global coordinate system GC of the factory FC. Specifically, in step S1, the processor 201 uses video images acquired from a camera, which is the external sensor 300, to acquire the vehicle position information.

[0052] Specifically, in step S1, the processor 201 obtains the position of the vehicle 100, for example, by detecting the shape of the vehicle 100 from the camera image and calculating the coordinates of the vehicle 100's location points in the camera image's coordinate system, i.e., the local coordinate system, and converting the calculated coordinates into coordinates in the global coordinate system GC. The shape of the vehicle 100 contained in the camera image can be detected, for example, by inputting the camera image into a detection model DM utilizing artificial intelligence. The detection model DM is prepared, for example, within or outside the evaluation system 50 and pre-stored in the memory 202 of the server 200. As the detection model DM, for example, a learned machine learning model that learns in a manner that achieves either semantic segmentation or instance segmentation can be used. As this machine learning model, for example, a convolutional neural network (hereinafter, CNN) learned through supervised learning using a learning dataset can be used. The learning dataset, for example, has multiple training images including the vehicle 100 and labels indicating which region in the training images represents the vehicle 100 and which region outside the vehicle 100 it represents. During CNN learning, it is preferable to update the CNN parameters by using backpropagation (error backpropagation method) to reduce the error between the output of the detection model DM and the label. Furthermore, the processor 201 can estimate the orientation of the vehicle 100, for example, by using optical flow and calculating the orientation of the vehicle 100's movement vector based on the positional changes of the vehicle 100's feature points between frames of the camera image.

[0053] In step S2, the processor 201 of the server 200 determines the next target location that the vehicle 100 should head for. In this embodiment, the target location is represented by the X, Y, and Z coordinates in the global coordinate system GC. The server 200's memory 202 pre-stores the path that the vehicle 100 should travel, i.e., the reference path RR. The path is represented by nodes indicating the starting point, nodes indicating intermediate points, nodes indicating the destination, and links connecting the nodes. The processor 201 uses the vehicle's position information and the reference path RR to determine the next target location that the vehicle 100 should head for. The processor 201 determines the target location on the reference path RR, which is further ahead than the vehicle 100's current position.

[0054] In step S3, the processor 201 of the server 200 generates a driving control signal to cause the vehicle 100 to move towards the determined target position. The processor 201 calculates the vehicle 100's speed based on its position shift and compares the calculated speed with the target speed. Generally, when the speed is lower than the target speed, the processor 201 determines acceleration by accelerating the vehicle 100; when the speed is higher than the target speed, the processor 201 determines acceleration by decelerating the vehicle 100. Furthermore, when the vehicle 100 is on the reference path RR, the processor 201 determines the steering angle and acceleration to ensure the vehicle 100 does not leave the reference path RR; when the vehicle 100 is not on the reference path RR—in other words, when the vehicle 100 has left the reference path RR—the processor 201 determines the steering angle and acceleration to ensure the vehicle 100 returns to the reference path RR.

[0055] In step S4, the processor 201 of the server 200 sends the generated driving control signal to the vehicle 100. The processor 201 repeatedly performs tasks such as acquiring vehicle position information, determining target position, generating driving control signals, and sending driving control signals at a predetermined cycle.

[0056] In step S5, the processor 111 of vehicle 100 receives a driving control signal sent from server 200. In step S6, the processor 111 of vehicle 100 uses the received driving control signal to control the actuator assembly 120, causing vehicle 100 to travel at the acceleration and steering angle represented by the driving control signal. The processor 111 repeatedly receives the driving control signal and controls the actuator assembly 120 at a predetermined cycle. According to the evaluation system 50 in this embodiment, vehicle 100 can be driven remotely, and vehicle 100 can be moved without using conveying equipment such as cranes or conveyor belts.

[0057] Figure 4 This is a flowchart illustrating the processing steps of the evaluation process used to implement the evaluation method in this embodiment. The evaluation process is performed to evaluate the acceleration characteristics of vehicle 100. In this embodiment, the evaluation process is executed by the processor 201 of server 200 at the moment when each wheel 101 of the target vehicle 100 is on each roller 510. The target vehicle 100 refers to the vehicle 100 that is being evaluated in the evaluation process.

[0058] In step S100, the acquisition unit 220 acquires the specification information of the target vehicle 100. In step S110, the acquisition unit 220 uses the specification information acquired in step S100 to acquire reference data SD corresponding to the specifications of the target vehicle 100 by referring to the database DB. Alternatively, in other embodiments, step S100 or step S110 may be performed, for example, when the vehicle 100 is not located on the roller 510, i.e., when the wheels 101 are not supported by the roller 510.

[0059] In step S120, the acceleration processing unit 211 performs acceleration processing. More specifically, in step S120, the acceleration processing unit 211 accelerates the target vehicle 100 according to a predetermined acceleration mode, that is, increases the speed of the target vehicle 100. The acceleration mode is used to evaluate acceleration characteristics, for example, representing the time series change of vehicle speed or the time series change of acceleration. Furthermore, in the acceleration processing of step S120, the vehicle speed value and torque value of the target vehicle 100 during acceleration are recorded, thereby generating recorded data.

[0060] In step S130, the acquisition unit 220 acquires the recorded data based on the accelerated processing in step S120.

[0061] In steps S140 and S145, the evaluation unit 230 performs an acceleration characteristic evaluation of the target vehicle 100 by comparing the recorded data obtained in step S130 with the baseline data SD obtained in step S110.

[0062] First, in step S140, the evaluation unit 230 compares the recorded data and the reference data SD. More specifically, in step S140, the evaluation unit 230 calculates the vehicle speed difference by comparing the vehicle speed values ​​in the recorded data and the vehicle speed reference values ​​included in the reference data SD along a time series. The vehicle speed difference is the difference between the vehicle speed value in the recorded data (i.e., the recorded vehicle speed value) and the vehicle speed reference value in the reference data SD. In this embodiment, the vehicle speed difference is calculated as the maximum value of the difference. Furthermore, in step S140, the evaluation unit 230 compares the torque value in the recorded data (i.e., the recorded torque value) with the lower limit and upper limit value of the torque reference value in the reference data SD.

[0063] In step S145, the evaluation unit 230 evaluates the acceleration characteristics based on the comparison results of step S140. More specifically, in step S145 of this embodiment, the evaluation unit 230 evaluates the acceleration characteristics as abnormal if at least one of the following conditions is met: the vehicle speed difference is greater than or equal to a predetermined reference difference, or the torque recording value is outside the reference range. Conversely, the evaluation unit 230 evaluates the acceleration characteristics as normal if the vehicle speed difference is less than the reference difference and the torque recording value is within the reference range.

[0064] Figure 5 This is a diagram illustrating an example of acceleration characteristic evaluation. In Figure 5 The example shown illustrates the use of recorded data RD to evaluate acceleration characteristics. Recorded data RD includes acceleration data AD (acceleration indication value AP), torque change data TC, and vehicle speed change data VC, all recorded during acceleration processing. Furthermore, in... Figure 5 In the example, the vehicle speed reference value Vs and torque reference value Ts included in the vehicle speed reference data VD represent the reference values ​​when the vehicle accelerates to 100 km / h according to the acceleration data AD. In other embodiments, the recording data RD may replace the acceleration data AD, or, in addition to the acceleration data AD, may include data recording the vehicle speed indication value or the torque indication value during the acceleration process. Furthermore, the recording data RD may also exclude data recording such indication values.

[0065] exist Figure 5 In the example, Figure 4 In step S140, the vehicle speed difference DV is calculated by comparing the vehicle speed recorded value Va included in the vehicle speed change data VC with the vehicle speed reference value Vs included in the vehicle speed reference data VD. Furthermore, the torque recorded value Ta included in the torque change data TC is compared with the lower limit T1 and upper limit T2, which serve as the torque reference value Ts, to determine whether the torque recorded value Ta is within the reference range R determined by the lower limit T1 and upper limit T2.

[0066] exist Figure 4 In step S145, if the evaluation result of the acceleration characteristic is normal, the evaluation unit 230 ends the evaluation process. If the evaluation result of the acceleration characteristic is abnormal, in step S150, the evaluation unit 230 notifies the user of a notification message. The notification message in step S150 may include information indicating an abnormality. In step S150, the evaluation unit 230 may use an output device (not shown) to send the notification message. The output device may be a display device that outputs visual information, a speaker that outputs sound information, a printing device, etc. The output device may be a mobile terminal such as a tablet computer owned by the user. Alternatively, for example, not limited to cases where the evaluation result of the acceleration characteristic is abnormal, the user may also be notified of a notification message indicating a normal evaluation result if the evaluation result is normal.

[0067] Furthermore, in the event of an abnormal acceleration characteristic evaluation result, the remote control unit 210 can, for example, use autonomous driving control to move the vehicle 100 to a repair location (not shown) for repairing the abnormality of the vehicle 100. In this case, for example, the comparison result between the recorded data and the reference data SD can be sent to the operator or work equipment at the repair location. In this way, the operator or work equipment can use the comparison result to more effectively repair the abnormality of the vehicle 100.

[0068] Furthermore, the evaluation unit 230 can, for example, issue repair-related instructions to the operator or work equipment at the repair site based on the comparison results of the recorded data and the reference data SD. In the acceleration process of this embodiment, since the aforementioned driving feedback control is performed, a speed difference less than the reference difference and a torque recording value greater than the upper limit value indicate that a greater driving torque than anticipated is required to achieve the desired speed or acceleration. This increase in required driving torque is caused, for example, by foreign objects in the drive unit. Such foreign objects are, for example, foreign objects stuck in the bearings of the drive wheels. Therefore, when the speed difference is less than the reference difference and the torque recording value is greater than the upper limit value, the evaluation unit 230 preferably issues a repair instruction to perform inspection or repair of the drive unit. Furthermore, for example, when the speed difference is greater than the reference difference, the speed feedback function in the vehicle control device 110 may malfunction. In this case, the evaluation unit 230 preferably issues a repair instruction to perform inspection or repair of the server 200 or the vehicle control device 110.

[0069] According to the evaluation system 50 in this embodiment described above, by using the recorded data RD which records the vehicle speed and torque values ​​during acceleration processing, the acceleration characteristics of the vehicle 100 can be evaluated using unmanned driving control without relying on the operator's senses.

[0070] Furthermore, in this embodiment, the acceleration characteristics of the vehicle 100 are evaluated by comparing the recorded data RD with the baseline data SD corresponding to the specifications of the vehicle 100. Therefore, the acceleration characteristics of the vehicle 100 can be evaluated more appropriately according to the specifications of the vehicle 100.

[0071] Furthermore, in this embodiment, during the acceleration process, the vehicle speed of the vehicle 100 increases while the wheel 101 is supported by the roller 510, so that the recorded data RD can be obtained to evaluate the acceleration characteristics without moving the vehicle 100.

[0072] B. Second Implementation Method:

[0073] Figure 6 This is an explanatory diagram of the accelerated processing in the second embodiment. (See diagram below.) Figure 6As shown, in the second embodiment, unlike the first embodiment, the acceleration processing unit 211 causes the vehicle 100 to travel from the first location PL1 towards the second location PL2 during the acceleration process. More specifically, in this embodiment, the acceleration processing unit 211 performs the acceleration process within a predetermined acceleration zone AS on the walking TR. During the acceleration process, the vehicle 100 is controlled by autonomous driving to travel along a straight route within the acceleration zone AS. Furthermore, the roller device 500 is not provided in the factory FC of this embodiment. Additionally, points not specifically described in the evaluation system 50 of the second embodiment are the same as in the first embodiment. According to this embodiment, during the sequential execution of processes related to the vehicle 100, the vehicle 100 is driven from the first location PL1 towards the second location PL2 by autonomous driving, thereby enabling the evaluation of the acceleration characteristics of the vehicle 100. Therefore, in the factory FC, the acceleration characteristics of the vehicle 100 can be evaluated more effectively, and the vehicle 100 can be manufactured more efficiently. Furthermore, the acceleration characteristics of the vehicle 100 can be evaluated without using the roller device 500.

[0074] Furthermore, in the second embodiment, the acceleration processing unit 211 can be configured to perform acceleration processing in multiple sections of the walking TR. In this case, the reference data SD can be prepared, for example, based on the section or based on the walking conditions of the section. Walking conditions include, for example, the slope of the road surface, the unevenness of the road surface, the material of the road surface, and the coefficient of friction of the road surface. In this case, the evaluation unit 230 can correct the reference data SD based on the walking conditions of the section and use the corrected reference data SD for acceleration characteristic evaluation. Furthermore, in the acceleration processing, the vehicle 100 is not limited to a straight route; for example, it can also travel along a curved route.

[0075] C. Third implementation method:

[0076] Figure 7 This is an explanatory diagram showing the schematic structure of system 50v in the third embodiment. In this embodiment, system 50v differs from the first embodiment in that it does not include server 200. The vehicle's device structure in this embodiment is the same as in the first embodiment; therefore, for convenience, the vehicle in this embodiment is referred to as vehicle 100. Furthermore, vehicle 100 in this embodiment can be driven through autonomous control. Other structures are the same as in the first embodiment unless otherwise specified.

[0077] In this embodiment, the communication device 130 of the vehicle 100 can communicate with the external sensor 300 and the roller device 500. The processor 111 of the vehicle control device 110 functions as the vehicle control unit 115v, the acquisition unit 220, and the evaluation unit 230 by executing the program PG1 stored in the memory 112. The vehicle control unit 115v generates a driving control signal and outputs the generated driving control signal to activate the actuator assembly 120, thereby enabling the vehicle 100 to move autonomously. Furthermore, the vehicle control unit 115v functions as the acceleration processing unit 211. In this embodiment, in addition to the program PG1, the memory 112 also stores the detection model DM, the reference path RR, and the database DB in advance.

[0078] Figure 8 This is a flowchart illustrating the processing steps of the driving control of the vehicle 100 in the third embodiment. Figure 8 In the processing steps, the processor 111 of the vehicle 100 functions as the vehicle control unit 115v by executing program PG1.

[0079] In step S901, the processor 111 of the vehicle control device 110 acquires vehicle position information using detection results output from the camera, which is an external sensor 300. In step S902, the processor 111 determines the next target location that the vehicle 100 should go to. In step S903, the processor 111 generates a driving control signal to cause the vehicle 100 to travel to the determined target location. In step S904, the processor 111 uses the generated driving control signal to control the actuator assembly 120, causing the vehicle 100 to travel according to the parameters represented by the driving control signal. The processor 111 repeats the acquisition of vehicle position information, determination of target location, generation of driving control signal, and control of actuators at a predetermined cycle. According to the system 50v in this embodiment, the vehicle 100 can be driven autonomously without remote control of the vehicle 100 via the server 200.

[0080] In this embodiment, the vehicle control unit 115v performs the operation... Figure 4 The same evaluation process. For example, in Figure 4 In step S120, the vehicle speed of vehicle 100 is increased through autonomous control of vehicle 100. Furthermore, in this embodiment, the target vehicle 100 refers to the self-vehicle. Also, in the third embodiment, the acceleration process can be performed on the roller 510 in the same manner as in the first embodiment, or on the walking TR in the same manner as in the second embodiment.

[0081] The system 50v in the third embodiment described above can also be used to evaluate the acceleration characteristics of the vehicle 100 without relying on the feelings of the inspector.

[0082] D. Other implementation methods:

[0083] (D1) In the above embodiments, the acceleration characteristics are evaluated by comparing the recorded data and the benchmark data SD, but this is not a limitation. For example, the evaluation unit 230 may use an evaluation model that has been learned by using the recorded data as input and outputting the evaluation results of the acceleration characteristics, or a rule-based system constructed based on the recorded data, to evaluate the acceleration characteristics.

[0084] (D2) In the above embodiments, the recorded data includes vehicle speed change data and torque change data, but is not limited thereto. For example, the recorded data may be data that directly records the relationship between vehicle speed and torque values ​​during acceleration processing. Furthermore, the torque value in the recorded data may, for example, be an integral value of a value related to the drive torque during acceleration processing. Also, in the above embodiments, the reference data SD includes vehicle speed reference data and torque reference values ​​as reference values ​​for determining the reference range of torque, but is not limited thereto. For example, the reference data SD may be data that directly defines the relationship between vehicle speed and torque values. Furthermore, the reference data SD may include torque reference data that defines torque reference values ​​along a time series. Furthermore, the reference data SD may be a reference value of an integral value related to the drive torque.

[0085] (D3) In the above embodiments, driving feedback control is performed during acceleration processing, but it may not be performed. Even in this case, the evaluation unit 230 can use the recorded data to verify, for example, whether the desired vehicle speed or acceleration is achieved according to the control of the drive device, and whether the drive torque required to achieve the desired vehicle speed or acceleration is generated by the motor 103, and evaluate the acceleration characteristics.

[0086] (D4) In the above embodiments, the external sensor 300 is not limited to a camera, but may also be a ranging device, for example. The ranging device may be, for example, a Light Detection and Ranging (LiDAR) device. In this case, the detection result output by the external sensor 300 may be three-dimensional point cloud data representing the vehicle 100.

[0087] (D5) In the first embodiment described above, the server 200 performs the process from obtaining vehicle location information to generating a driving control signal. In contrast, the vehicle 100 may perform at least a portion of the process from obtaining vehicle location information to generating a driving control signal. For example, it may be performed in the manner described in (1) to (3) below.

[0088] (1) Server 200 can obtain vehicle location information, determine the next target location that vehicle 100 should go to, and generate a path from the current location of vehicle 100 as indicated in the obtained vehicle location information to the target location. Server 200 can generate a path from the current location to the target location, or a path to the destination. Server 200 can send the generated path to vehicle 100. Vehicle 100 can perform the following processing: generate a driving control signal to make vehicle 100 drive on the path received from server 200, and use the generated driving control signal to control actuator group 120.

[0089] (2) Server 200 can obtain vehicle location information and send the obtained vehicle location information to vehicle 100. Vehicle 100 can perform the following processing: determine the next target location that vehicle 100 should go to, generate a path from the current location of vehicle 100 represented by the received vehicle location information to the target location, generate a driving control signal to make vehicle 100 drive on the generated path, and use the generated driving control signal to control actuator group 120.

[0090] (3) In the methods described in (1) and (2) above, an internal sensor may be mounted on the vehicle 100, and the detection results output from the internal sensor may be used in at least one of the path generation and the generation of the driving control signal. For example, in the method described in (1) above, the server 200 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the path when generating the path. In the method described in (1) above, the vehicle 100 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the driving control signal when generating the driving control signal. In the method described in (2) above, the vehicle 100 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the path when generating the path. In the method described in (2) above, the vehicle 100 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the driving control signal when generating the driving control signal.

[0091] (D6) In the third embodiment described above, the vehicle 100 is equipped with an internal sensor, and the detection results output from the internal sensor can be used in at least one of the path generation and the generation of the driving control signal. For example, the vehicle 100 can acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the path when generating the path. The vehicle 100 can also reflect the detection results of the internal sensor in the driving control signal when acquiring the detection results of the internal sensor and generating the driving control signal.

[0092] (D7) In the third embodiment described above, the vehicle 100 uses the detection results of the external sensor 300 to acquire vehicle position information. Alternatively, an internal sensor can be mounted on the vehicle 100. The vehicle 100 uses the detection results of the internal sensor to acquire vehicle position information, determines the next target position that the vehicle 100 should face, generates a path from the current position of the vehicle 100 as indicated in the acquired vehicle position information to the target position, generates a driving control signal for driving the generated path, and uses the generated driving control signal to control the actuator assembly 120. In this case, the vehicle 100 can drive without using the detection results of the external sensor 300. Furthermore, the vehicle 100 can acquire the target arrival time or congestion information from outside the vehicle 100 and reflect the target arrival time or congestion information in at least one of the path and the driving control signal. Moreover, all functional structures of the system 50v can be set within the vehicle 100. That is, the processing implemented by the system 50v in this invention can be implemented independently by the vehicle 100.

[0093] (D8) In the first embodiment described above, the server 200 automatically generates a driving control signal to be sent to the vehicle 100. Alternatively, the server 200 can generate a driving control signal to be sent to the vehicle 100 according to the operation of an external operator located outside the vehicle 100. For example, the server 200 can generate a driving control signal corresponding to the operation applied to the operating device by an external operator operating a control device equipped with a display showing camera images output from external sensors 300, a steering wheel for remotely operating the vehicle 100, an accelerator pedal, a brake pedal, and a communication device for communicating with the server 200 via wired or wireless communication.

[0094] (D9) In the above embodiments, the vehicle 100 only needs to have a structure that allows it to move autonomously, for example, it can be in the form of a platform with the structure described below. Specifically, in order to perform the three functions of "driving," "turning," and "stopping" through autonomous driving, the vehicle 100 only needs to have a vehicle control device 110 and an actuator assembly 120. When the vehicle 100 obtains information from the outside for autonomous driving, the vehicle 100 only needs to further have a communication device 130. That is, the vehicle 100 that can move autonomously may not have at least some of the interior parts such as the driver's seat or dashboard installed, may not have at least some of the exterior parts such as bumpers or fenders installed, and may not have a body shell installed. In this case, the remaining parts such as the body shell can be installed on the vehicle 100 before the vehicle 100 is shipped from the factory FC, or the remaining parts such as the body shell can be installed on the vehicle 100 after the vehicle 100 is shipped from the factory FC, even if the remaining parts are not installed on the vehicle 100. Each component can be installed from any direction, such as the top, bottom, front, rear, right, or left side of the vehicle 100, or from the same direction, or from different directions. Furthermore, the platform can be positioned in the same way as the vehicle 100 in the first embodiment.

[0095] (D10) The vehicle 100 can be manufactured by combining multiple modules. A module refers to a unit consisting of one or more parts combined according to the structure or function of the vehicle 100. For example, the platform of the vehicle 100 can be manufactured by combining a front module constituting the front part of the platform, a central module constituting the central part of the platform, and a rear module constituting the rear part of the platform. In addition, the number of modules constituting the platform is not limited to three, and can be two or less or four or more. Furthermore, in addition to the platform, or instead of the platform, parts of the vehicle 100 that are different from the platform can also be modularized. Furthermore, various modules can include any external parts such as bumpers or grilles, or any internal parts such as seats or consoles. Such modules can be manufactured by joining multiple parts together, for example, by welding or fasteners, or by casting to integrally form at least a part of the module as a single part. The molding method of integrally forming at least a part of the module as a single part is also called integral die casting or monolithic casting. By using integral die casting, the various parts of the vehicle 100, which were previously formed by joining multiple parts, can be formed into a single part. For example, the aforementioned front module, central module, or rear module can be manufactured using integrated die casting.

[0096] (D11) The method of transporting vehicle 100 using the driving of driverless vehicle 100 is also referred to as "autonomous transport". Furthermore, the structure used to realize autonomous transport is also referred to as a "vehicle remote-controlled autonomous driving transport system". And the production method of producing vehicle 100 using autonomous transport is also referred to as "autonomous production". In autonomous production, for example, in factory FC where vehicle 100 is manufactured, at least a portion of the transport of vehicle 100 is achieved through autonomous transport.

[0097] This invention is not limited to the embodiments described above, and can be implemented in various structures without departing from its spirit. For example, to address some or all of the above-described issues, or to achieve some or all of the above-described effects, the technical features of embodiments corresponding to the technical features of each form described in the summary section of the invention can be appropriately replaced or combined. Furthermore, if a technical feature is not described as essential in this specification, it can be appropriately deleted.

[0098] Symbol Explanation

[0099] 50, 50V - System; 100 - Vehicle; 101 - Wheel; 103 - Motor; 110 - Vehicle Control Unit; 111 - Processor; 112 - Memory; 113 - Input / Output Interface; 114 - Internal Bus; 115, 115V - Vehicle Control Unit; 120 - Actuator Group; 130 - Communication Device; 140 - Internal Sensor; 200 - Server; 201 - Processor; 202 - Memory; 203 - Input / Output Interface 204-Internal bus, 205-Communication device, 210-Remote control unit, 211-Acceleration processing unit, 220-Acquisition unit, 230-Evaluation unit, 300-External sensor, 500-Roller device, 510-Roller, 510A-Front roller, 510B-Rear roller, 511-Roller unit, 520-Roller control device, 521-Processor, 522-Memory, 523-Input / output interface, 530-Equipment sensor.

Claims

1. An evaluation system, characterized by have: The acceleration processing unit causes the vehicle, which is a vehicle equipped with a driving motor and capable of driving under autonomous driving control, to move through the autonomous driving control, thereby performing acceleration processing to increase the speed of the vehicle. The acquisition unit acquires and records data of vehicle speed values ​​and torque values ​​related to the driving torque of the motor during the acceleration process. and The evaluation department uses the acquired recorded data to evaluate the acceleration characteristics of the vehicle.

2. The evaluation system according to claim 1, characterized in that, The evaluation unit evaluates the acceleration characteristics by comparing the recorded data with reference data that predefines the reference values ​​for the vehicle speed and torque according to the vehicle's specifications.

3. The evaluation system according to claim 1 or 2, characterized in that, The acceleration processing unit increases the vehicle speed while the wheel is supported by a roller that can rotate while supporting the wheel of the vehicle.

4. The evaluation system according to claim 1 or 2, characterized in that, In the acceleration process, the acceleration processing unit causes the vehicle to travel from a first location where a first process related to the vehicle is performed toward a second location where a second process, which is a follow-up to the first process, is performed.

5. An evaluation method characterized by, Perform the following steps: The autonomous driving control enables the vehicle, which is a vehicle equipped with a motor for driving, to move under autonomous driving control, thereby performing an acceleration process that increases the speed of the vehicle. Acquire recorded data containing vehicle speed values ​​and torque values ​​related to the driving torque of the motor during the acceleration process. and The acquired recorded data is used to evaluate the vehicle's acceleration characteristics.

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