Target vehicle speed pattern data generation method and test method

Abstract

A target vehicle speed pattern data generation method according to the present invention includes: a step ST1 of reading original vehicle speed pattern data; a step ST2 of acquiring a designated value for a driving index; a step ST3 of generating corrected vehicle speed pattern data by shaping a high-frequency component, having a higher frequency than a predetermined cut-off frequency, in the original vehicle speed pattern data; a step ST5 of calculating an evaluation value of the driving index for the corrected vehicle speed pattern data by evaluating the corrected vehicle speed pattern data with reference to the original vehicle speed pattern data; and a step ST9 of storing corrected vehicle speed pattern data, which causes the difference between the designated value and the evaluation value to be less than a determination value, as target vehicle speed pattern data in a storage medium.

Description

Target vehicle speed pattern data generation method and test method

[0001] The present invention relates to a target vehicle speed pattern data generating method and a testing method, and more particularly to a target vehicle speed pattern data generating method for generating target vehicle speed pattern data used in a bench test in which a test subject is operated by an automatic driving device, and a testing method using this target vehicle speed pattern data.

[0002] Bench tests such as durability tests, exhaust gas purification performance evaluation tests, fuel economy measurement tests, and OBD (On-Board Diagnostics) tests are conducted by running an actual vehicle on the rollers of a chassis dynamometer. During the vehicle development stage, an automatic driving device may drive the actual vehicle instead of a human (see, for example, Patent Document 1). The automatic driving device operates the accelerator pedal, brake pedal, shift lever, and the like of the vehicle by driving various actuators in accordance with vehicle speed pattern data defined by national regulations such as WLTP and JC08.

[0003] Japanese Patent Application Publication No. 9-113418

[0004] In the development of products such as vehicles and vehicle parts, there is a demand for automated driving systems to reproduce a wide range of driving behaviors for the purposes of adjusting driving performance, identifying product problems, and replicating driving behaviors by users in the actual market. However, automated driving systems used in the above-mentioned bench tests are basically designed to follow commands with high accuracy. Therefore, when vehicle speed pattern data is specified by regulations, it is difficult for conventional automated driving systems to reproduce a wide range of driving behaviors.

[0005] As described above, similar issues arise not only when an automatic driving device drives a real vehicle, but also when a human driver drives a real vehicle. That is, although an experienced driver can reflect their driving skill to some extent in the driving of the real vehicle, it is difficult to quantify such driving skill so that it can be objectively evaluated, or to reproduce it repeatedly with high accuracy.

[0006] An object of the present invention is to provide a target vehicle speed pattern data generation method and a test method for generating target vehicle speed pattern data that can reproduce a wide range of driving behaviors by an automatic driving device or a person.

[0007] (1) A target vehicle speed pattern data generation method according to the present invention is a method for generating target vehicle speed pattern data by a computer for use in a bench test in which a test object, which is a vehicle or a vehicle part, is operated by an automatic driving device or a human driver, the method comprising: (A) a step of acquiring original vehicle speed pattern data; (B) a step of acquiring a designated value for at least one driving index; and (C) a step of generating corrected vehicle speed pattern data by shaping the original vehicle speed pattern data based on the designated value, and generating corrected vehicle speed pattern data by using the corrected vehicle speed pattern data that satisfies a predetermined condition as the target vehicle speed pattern data, thereby assisting the driving operation of the automatic driving device or the driver. and storing the corrected vehicle speed pattern data in a storage medium readable by an auxiliary device, wherein step (C) comprises: (C-1) generating the corrected vehicle speed pattern data by shaping high-frequency components of the original vehicle speed pattern data that are higher than a predetermined cut-off frequency; (C-2) calculating an evaluation value of the driving index for the corrected vehicle speed pattern data by evaluating the corrected vehicle speed pattern data based on the original vehicle speed pattern data; and (C-3) storing the corrected vehicle speed pattern data that makes the difference between the designated value and the evaluation value less than a predetermined judgment value in the storage medium as the target vehicle speed pattern data.

[0008] (2) In this case, in step (C-1), it is preferable to extract the high-frequency components from the original vehicle speed pattern data, multiply the high-frequency components by a predetermined first gain, and add the resultant value to the original vehicle speed pattern data to generate the corrected vehicle speed pattern data, and in step (C-3), it is preferable to search for the corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value by repeatedly executing steps (C-1) and (C-2) while changing the values ​​of the cutoff frequency and the first gain.

[0009] (3) In this case, in step (C-1), the corrected vehicle speed pattern data is generated by multiplying a predetermined second gain with vehicle speed pattern data generated by multiplying the high-frequency component by the first gain and adding the value to the original vehicle speed pattern data, and in step (C-3), steps (C-1) and (C-2) are repeatedly executed while changing the values ​​of the cutoff frequency, the first gain, and the second gain, thereby preferably searching for the corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value.

[0010] (4) In this case, in step (B), it is preferable to acquire a designated value for at least one of a first driving index related to workload and a second driving index related to vehicle speed tracking ability.

[0011] (5) The testing method of the present invention is a method for performing the bench test on the test object using the target vehicle speed pattern data generated by the target vehicle speed pattern data generation method described in any one of (1) to (4) and the automatic driving device, and is characterized by comprising: (D) a step in which the automatic driving device reads the target vehicle speed pattern data stored in the storage medium; and (E) a step in which the automatic driving device operates the test object in accordance with the target vehicle speed pattern data.

[0012] (6) A testing method according to the present invention is a method for performing the bench test on the test object using the target vehicle speed pattern data generated by the target vehicle speed pattern data generation method described in any one of (1) to (4) and the driving assistance device, and is characterized by comprising: (F) a step in which the driving assistance device reads the target vehicle speed pattern data stored in the storage medium; and (G) a step in which the driving assistance device displays driving assistance information generated based on the target vehicle speed pattern data on a monitor located in a position visible to the driver, and prompts the driver to operate the test object in accordance with the target vehicle speed pattern data.

[0013] (1) In the present invention, in step (A), predetermined original vehicle speed pattern data (e.g., vehicle speed pattern data specified by laws and regulations) are acquired, in step (B), a designated value for a driving index is acquired, and in step (C), modified vehicle speed pattern data is generated by shaping the original vehicle speed pattern data based on the designated value, and the modified vehicle speed pattern data that satisfies predetermined conditions is stored as target vehicle speed pattern data in a storage medium readable by an automatic driving device or a driving assistance device. Step (C) also includes step (C-1) of generating modified vehicle speed pattern data by shaping high-frequency components of the original vehicle speed pattern data that are higher than a predetermined cutoff frequency, step (C-2) of calculating an evaluation value of a driving index for the modified vehicle speed pattern data by evaluating the modified vehicle speed pattern data based on the original vehicle speed pattern data, and storing the modified vehicle speed pattern data that makes the difference between the designated value acquired in step (B) and the evaluation value calculated in step (C-2) less than a judgment value in the storage medium as target vehicle speed pattern data. Thus, according to the present invention, an operator can shape predetermined original vehicle speed pattern data and generate target vehicle speed pattern data corresponding to the designated values ​​simply by providing a designated value for the driving index to a computer. Therefore, according to the present invention, a wide range of driving behaviors can be reproduced by an automatic driving device or a driver by using not only predetermined original vehicle speed pattern data but also target vehicle speed pattern data newly generated from the original vehicle speed pattern data. Furthermore, human driving behaviors of the accelerator pedal, brake pedal, etc. tend to vary significantly when the vehicle speed changes suddenly. Therefore, in step (C-1), by generating corrected vehicle speed pattern data by shaping high-frequency components above the cutoff frequency of the original vehicle speed pattern data, variations in human driving behaviors of the accelerator pedal, brake pedal, etc. can be reflected in the target vehicle speed pattern data.

[0014] (2) In the present invention, in step (C-1), high-frequency components are extracted from the original vehicle speed pattern data, and the value obtained by multiplying the high-frequency components by a first gain is added to the original vehicle speed pattern data to generate corrected vehicle speed pattern data. In step (C-3), steps (C-1) and (C-2) are repeatedly executed while changing the values ​​of the cutoff frequency and the first gain to search for corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value. This makes it possible to generate different target vehicle speed pattern data for each specified value of the driving index.

[0015] (3) In the present invention, in step (C-1), modified vehicle speed pattern data is generated by multiplying a value obtained by multiplying a high-frequency component by a first gain and adding the value obtained by multiplying the first gain to the original vehicle speed pattern data, and in step (C-3), steps (C-1) and (C-2) are repeatedly executed while changing the values ​​of the cutoff frequency, the first gain, and the second gain, thereby searching for modified vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value. This makes it possible to generate different target vehicle speed pattern data for each specified value of the driving index.

[0016] (4) In the present invention, step (B) acquires designated values ​​for at least one of a first driving index related to workload and a second driving index related to vehicle speed tracking. According to the present invention, by generating target vehicle speed pattern data based on designated values ​​for at least one of the first and second driving indexes, it is possible to reflect in the target vehicle speed pattern data variations in the driving behavior of the accelerator pedal, the brake pedal, etc., depending on the driver, more specifically variations in the roughness or smoothness of the vehicle driving behavior depending on the driver.

[0017] (5) In the test method according to the present invention, in step (D), the automatic driving device reads target vehicle speed pattern data stored in a storage medium, and in step (E), the automatic driving device operates the test subject in accordance with the target vehicle speed pattern data. This allows the automatic driving device to reproduce a wide range of driving behaviors.

[0018] (6) In the test method according to the present invention, in step (F), the driving assistance device reads the target vehicle speed pattern data stored in the storage medium, and in step (G), the driving assistance device displays driving assistance information generated based on the target vehicle speed pattern data on a monitor provided in a position visible to the driver, and prompts the driver to operate the test object in accordance with the target vehicle speed pattern data. As described above, since the target vehicle speed pattern data reflects the designated value of the driving index, the human driver can reproduce a wide range of driving behaviors simply by operating the test object while looking at the driving assistance information displayed on the monitor.

[0019] The present invention relates to a method for generating target vehicle speed pattern data, a control system for a vehicle testing system, a method for generating target vehicle speed pattern data, a flowchart for generating target vehicle speed pattern data, a display screen for displaying target vehicle speed pattern data, and a flowchart for generating target vehicle speed pattern data.

[0020] 1 is a diagram showing the configuration of a control system of a vehicle testing system S to which a method for generating target vehicle speed pattern data according to this embodiment is applied.

[0021] The vehicle testing system S includes a vehicle speed pattern data generating device 1, an automatic driving device 2, and a controlled object 3. The controlled object 3 includes, for example, a chassis dynamometer that generates running resistance simulating an actual road surface, and a vehicle as a test object for a bench test using the chassis dynamometer. The driver's seat of the vehicle is equipped with a vehicle operation device that operates devices necessary for driving the vehicle, such as an accelerator pedal, a brake pedal, a shift lever, and an ignition switch, in response to commands.

[0022] As will be described below, in this embodiment, the target vehicle speed pattern data generated by the vehicle speed pattern data generating device 1 is used in a bench test in which the vehicle itself is the test subject, but the present invention is not limited to this. The target vehicle speed pattern data generated by the vehicle speed pattern data generating device 1 may also be used in a bench test in which vehicle components (e.g., a vehicle drive train, tires, etc.) that constitute the vehicle are the test subjects.

[0023] The vehicle speed pattern data generating device 1 is a computer that generates time series data (hereinafter also referred to as "target vehicle speed pattern data") of a target vehicle speed command that is to be input to the automatic driving device 2 and that is to be realized in a vehicle mounted on a chassis dynamometer, according to a procedure that will be described later with reference to Figures 2 and 3, and stores this target vehicle speed pattern data in a storage medium that can be read by the automatic driving device 2 or a driving assistance device described later.

[0024] When performing a bench test on a test subject using the target vehicle speed pattern data generated by vehicle speed pattern data generation device 1, automatic driving device 2 first reads the target vehicle speed pattern data stored in the storage medium of vehicle speed pattern data generation device 1. Automatic driving device 2 then operates the test subject by controlling the driving operation devices in accordance with the read target vehicle speed pattern data. More specifically, automatic driving device 2 controls the driving operation devices so as to achieve the target vehicle speed command specified by the read target vehicle speed pattern data at each time (in other words, so that the actual vehicle speed traces the target vehicle speed command).

[0025] 1 only shows the part of the multiple actuators that make up the driving operation device that is involved in determining the accelerator opening command, which is input to the accelerator actuator. The driving operation device includes not only the accelerator actuator that operates the accelerator pedal of the vehicle, but also actuators that operate the brake pedal, shift lever, etc., but the configuration that determines the input to these will not be shown in the figure or described in detail.

[0026] The automatic driving device 2 performs tracking control of the target vehicle speed command by a control method that combines feedforward control using a driving force characteristic map and PI control, as shown in FIG. 1, for example.

[0027] The target driving force calculation unit 20 calculates a target driving force based on the target vehicle speed command generated by the vehicle speed pattern data generation device 1 , and inputs the calculated target driving force to the driving force characteristic map calculation unit 21 .

[0028] The driving force characteristic map calculation unit 21 has a driving force characteristic map (not shown) that associates predetermined inputs (target vehicle speed command and target driving force) with the accelerator pedal depression of the vehicle. This driving force characteristic map is created by conducting experiments in advance on the vehicle to be tested. When the target vehicle speed command transmitted from the vehicle speed pattern data generation device 1 and the target driving force calculated by the target driving force calculation unit 20 are input, the driving force characteristic map calculation unit 21 searches the driving force characteristic map and determines the accelerator pedal depression corresponding to these inputs.

[0029] Vehicle speed feedback calculation unit 22 includes a vehicle sensitivity calculation unit 23, a proportional calculation unit 24, an integral calculation unit 25, and an adder 26. Vehicle sensitivity calculation unit 23 calculates the reciprocal of the vehicle sensitivity (change in driving force / change in accelerator opening) using the same driving force characteristic map as that included in driving force characteristic map calculation unit 21. Proportional calculation unit 24 multiplies the vehicle speed deviation (target vehicle speed command - actual vehicle speed) by a proportional gain that is variable depending on the vehicle sensitivity. Integral calculation unit 25 integrates the output of proportional calculation unit 24. Adder 26 adds the output of proportional calculation unit 24 and the output of integral calculation unit 25 together.

[0030] The outputs of the driving force characteristic map calculation unit 21 and the vehicle speed feedback calculation unit 22 are added by an adder 27 and input to the controlled object 3 as an accelerator pedal opening command corresponding to the accelerator pedal opening. The controlled object 3, which is a vehicle and chassis dynamometer system, is divided into a vehicle drivetrain 31 including a vehicle operation device, an adder 32, and a vehicle inertia system 33. When an accelerator pedal opening command is input, the vehicle drivetrain 31 generates a driving force corresponding to the accelerator pedal opening command. The vehicle inertia system 33 receives an acceleration force of the vehicle obtained by subtracting the running resistance generated by the chassis dynamometer system from the driving force generated by the vehicle drivetrain 31. When the acceleration force of the vehicle is input, the vehicle inertia system 33 generates a vehicle speed corresponding to the acceleration force.

[0031] Although the specific configuration of the automatic driving device 2 has been described above, the present invention is not limited to this. The automatic driving device 2 may be any device that has the function of making the vehicle speed follow the waveform of the target vehicle speed command generated by the vehicle speed pattern data generating device 1.

[0032] Fig. 2 is a flowchart showing the procedure for generating target vehicle speed pattern data by the vehicle speed pattern data generating device 1. Each step shown in Fig. 2 is executed mainly by the vehicle speed pattern data generating device 1, which is a computer, based on a computer program installed in the vehicle speed pattern data generating device 1.

[0033] First, in step ST1, the vehicle speed pattern data generating device 1 reads vehicle speed pattern data designated by an operator from among a plurality of types of vehicle speed pattern data stored in a storage medium (not shown) as original vehicle speed pattern data, and then proceeds to step ST2. The storage medium stores a plurality of vehicle speed pattern data defined by national regulations such as WLTP and JC08. The operator can designate one of the plurality of vehicle speed pattern data stored in the storage medium by operating a user interface (not shown).

[0034] Next, in step ST2, the vehicle speed pattern data generating device 1 acquires a value designated by the operator for at least one driving index, and then proceeds to step ST3. Here, the driving index is an index characterizing the driving manner of the accelerator pedal, brake pedal, etc., of a human driver (i.e., the roughness or smoothness of the driver's driving of the vehicle, etc.). The vehicle speed pattern data generating device 1 is provided with a plurality of driving indexes defined by WLTP regulations. More specifically, the vehicle speed pattern data generating device 1 is provided with a plurality of driving indexes defined in WLTP and SAEJ2951, such as an IWR (Inertial Work Rating) relating to the amount of work and an RMSSE (Root Mean Squared Speed ​​Error) relating to vehicle speed tracking capability. The operator can input designated values ​​for these driving indexes (IWR, RMSSE, etc.) via a user interface (not shown). In the following, the vehicle speed pattern data generating device 1 will be described as acquiring designated values ​​for both IWR and RMSSE in step ST2, but the present invention is not limited to this. The vehicle speed pattern data generating device 1 may acquire designated values ​​for only either IWR or RMSSE, or may acquire designated values ​​for driving indices other than IWR and RMSSE.

[0035] Next, in steps ST3 to ST9, the vehicle speed pattern data generating device 1 generates corrected vehicle speed pattern data by shaping the original vehicle speed pattern data based on the specified value acquired in step ST2, and stores the corrected vehicle speed pattern data that satisfies predetermined conditions as target vehicle speed pattern data in a storage medium that can be read by the automatic driving device 2 or a driving assistance device described below, and then ends the processing shown in Fig. 2. Below, the detailed procedure for generating target vehicle speed pattern data by shaping the original vehicle speed pattern data in the processing of each of steps ST3 to ST9 will be described in order.

[0036] First, in step ST3, the vehicle speed pattern data generating device 1 generates corrected vehicle speed pattern data by shaping frequency components higher than a predetermined cutoff frequency in the original vehicle speed pattern data, and then proceeds to step ST4. More specifically, the vehicle speed pattern data generating device 1 extracts frequency components higher than the cutoff frequency from the original vehicle speed pattern data by using a high-pass filter that attenuates frequency components lower than the cutoff frequency and passes frequency components higher than the cutoff frequency, and generates corrected vehicle speed pattern data by multiplying the extracted high-frequency components by a predetermined first gain and adding the result to the original vehicle speed pattern data, and then proceeds to step ST4.

[0037] Here, assuming that the original vehicle speed pattern data is "Vr", the cutoff frequency is "Fc", the first gain is "G1", the high frequency components extracted by passing the original vehicle speed pattern data through a high-pass filter are "HPF(Vr, Fc)", and the corrected vehicle speed pattern data is "Vs'", the calculation process by the vehicle speed pattern data generating device 1 is expressed by the following equation (1): Vs'=Vr+HPF(Vr, Fc)·G1 (1)

[0038] Next, in step ST4, the vehicle speed pattern data generating device 1 generates corrected vehicle speed pattern data by shaping the gain of the corrected vehicle speed pattern data Vs' generated through step ST3, and then proceeds to step ST5. More specifically, the vehicle speed pattern data generating device 1 shapes the gain of the corrected vehicle speed pattern data Vs' by multiplying the corrected vehicle speed pattern data Vs' generated through step ST3 by a predetermined second gain G2, as shown in the following equation (2): Vs=Vs'·G2 (2)

[0039] Next, in step ST5, the vehicle speed pattern data generating device 1 evaluates the corrected vehicle speed pattern data Vs generated in step ST4 using the original vehicle speed pattern data Vr as a reference, thereby calculating evaluation values ​​of the driving indices (IWR and RMSSE) for the corrected vehicle speed pattern data Vs, and then proceeds to step ST6. More specifically, the vehicle speed pattern data generating device 1 performs the calculation by inputting the corrected vehicle speed pattern data Vs and the original vehicle speed pattern data Vr, which is the reference for the corrected vehicle speed pattern data Vs, into an evaluation function that is predetermined for each type of driving index, for example.

[0040] Next, in step ST6, the vehicle speed pattern data generation device 1 calculates an evaluation function value proportional to the difference between the designated value and the evaluation value for the driving index, and determines whether this evaluation function value is less than a predetermined judgment value. More specifically, when the operator can designate designated values ​​for two or more driving indices, the vehicle speed pattern data generation device 1 calculates, as an evaluation function value cost, the norm of the difference vector between a designated value vector DIset having the designated values ​​for each driving index as components and an evaluation value vector DIresult having the evaluation values ​​for each driving index as components, as shown in the following equation (3), and determines whether this evaluation function value cost is less than a predetermined judgment value. If the determination result in step ST6 is YES, the vehicle speed pattern data generation device 1 proceeds to step ST8, and if the determination result is NO, the vehicle speed pattern data generation device 1 proceeds to step ST7. cost = ∥DIset - DIresult∥ (3)

[0041] In step ST7, the vehicle speed pattern data generation device 1 determines whether the processing of steps ST3 to ST6 has been executed a predetermined number of times or more. If the determination result of step ST7 is YES, the vehicle speed pattern data generation device 1 proceeds to step ST8. If the determination result of step ST7 is NO, the vehicle speed pattern data generation device 1 changes the values ​​of the cutoff frequency Fc, the first gain G1, and the second gain G2, and then executes the processing of steps ST3 to ST6 again.

[0042] As described above, the vehicle speed pattern data generating device 1 searches for corrected vehicle speed pattern data that makes the evaluation function value cost less than the judgment value by repeatedly executing the optimization process shown in steps ST3 to ST7 based on a known optimization algorithm such as PSO (Particle Swarm Optimization) or a genetic algorithm.

[0043] In step ST8, the vehicle speed pattern data generating device 1 displays the result information relating to the results of the optimization processing shown in steps ST3 to ST7 on a display that can be seen by the operator, and prompts the operator to confirm the result information. If the vehicle speed pattern data generating device 1 receives a confirmation operation from the operator, it proceeds to step ST9.

[0044] FIG. 3 is a diagram showing an example of a result image displayed on the display in the process of step ST8.

[0045] As shown in FIG. 3, the result image includes a vehicle speed pattern data display field 3A, a first driving index display field 3B, and a second driving index display field 3C.

[0046] 3, the vehicle speed pattern data generating device 1 displays the original vehicle speed pattern data and the corrected vehicle speed pattern data that makes the evaluation function value cost less than the judgment value (if corrected vehicle speed pattern data that makes the evaluation function value cost less than the judgment value cannot be found, the corrected vehicle speed pattern data that minimizes the evaluation function value cost) in an overlapping manner in the vehicle speed pattern data display field 3A. By displaying the original vehicle speed pattern data and the corrected vehicle speed pattern data in an overlapping manner in this manner, the operator can easily grasp the parts that have been corrected from the original vehicle speed pattern data.

[0047] As shown in Fig. 3, the vehicle speed pattern data generation device 1 plots, on a two-dimensional coordinate system, the designated values ​​and evaluation values ​​of two types of driving indices (IWR (vertical axis) and RMSSE (horizontal axis) in the example of Fig. 3) that have been designated in advance by the operator from among a plurality of types of driving indices in the first driving index display field 3B. By plotting the designated values ​​and evaluation values ​​of the two types of driving indices designated by the operator in this manner, the operator can easily grasp whether corrected vehicle speed pattern data that reproduces the two types of driving indices that the operator considers important from among the plurality of driving indices has been generated.

[0048] As shown in Fig. 3, the vehicle speed pattern data generating device 1 displays designated values ​​and evaluation values ​​of a plurality of types of driving indices (12 types in the example of Fig. 3) in the second driving index display field 3C in the form of a radar chart. This allows the operator to easily understand whether corrected vehicle speed pattern data that fully reflects the designated values ​​for each driving index that the operator inputs has been generated.

[0049] Returning to FIG. 2 , in step ST9, the vehicle speed pattern data generation device 1 stores the modified vehicle speed pattern data that has been confirmed by the operator (i.e., modified vehicle speed pattern data that makes the evaluation function value cost less than the judgment value, or modified vehicle speed pattern data that minimizes the evaluation function value cost) as target vehicle speed pattern data in a storage medium that can be read by the automatic driving device 2 or a driving assistance device described below, and then ends the processing shown in FIG. 2 . At this time, it is preferable that the vehicle speed pattern data generation device 1 stores the target vehicle speed pattern data generated by the above procedure in the storage medium in association with information that identifies the original vehicle speed pattern data, information related to the designated values ​​and evaluation values ​​of each driving index, etc. In this way, when multiple target vehicle speed pattern data are stored in the storage medium, the operator can quickly search for data corresponding to the type of original vehicle speed pattern data and the value of each driving index from among these multiple target vehicle speed pattern data and start a test using the automatic driving device 2.

[0050] The target vehicle speed pattern data generating method and testing method according to this embodiment have the following advantages.

[0051] (1) In the target vehicle speed pattern data generating method, in step ST1, predetermined original vehicle speed pattern data (e.g., vehicle speed pattern data defined by regulations) is acquired, in step ST2, a designated value for a driving index is acquired, and in steps ST3 to ST9, modified vehicle speed pattern data is generated by shaping the original vehicle speed pattern data based on the designated value, and the modified vehicle speed pattern data that satisfies predetermined conditions is stored as target vehicle speed pattern data in a storage medium readable by the automatic driving device 2. In addition, in steps ST3 to ST9, modified vehicle speed pattern data is generated by shaping high-frequency components of the original vehicle speed pattern data that are higher than a predetermined cutoff frequency Fc (see step ST3), and the modified vehicle speed pattern data is evaluated based on the original vehicle speed pattern data to calculate an evaluation value of a driving index for the modified vehicle speed pattern data (see step ST5), and the modified vehicle speed pattern data that makes an evaluation function value cost proportional to the difference between the designated value acquired in step ST2 and the evaluation value calculated in step ST5 less than a judgment value is stored in the storage medium as target vehicle speed pattern data (see step ST9). As described above, according to the target vehicle speed pattern data generation method of this embodiment, the operator can shape the predetermined original vehicle speed pattern data and generate target vehicle speed pattern data corresponding to the designated value simply by providing the computer with a designated value for the driving index. Therefore, according to the target vehicle speed pattern data generation method of this embodiment, a wide range of driving behaviors can be reproduced by the automatic driving device 2 by using not only the predetermined original vehicle speed pattern data but also target vehicle speed pattern data newly generated from the original vehicle speed pattern data. Furthermore, the driving behavior of the accelerator pedal, brake pedal, etc., by a human driver tends to vary significantly when the vehicle speed changes suddenly. Therefore, in step ST3, the original vehicle speed pattern data is shaped to generate corrected vehicle speed pattern data, thereby allowing the target vehicle speed pattern data to reflect variations in the driving behavior of the accelerator pedal, brake pedal, etc., depending on the person.

[0052] (2) In the target vehicle speed pattern data generating method according to this embodiment, high-frequency components are extracted from the original vehicle speed pattern data, and the high-frequency components are multiplied by the first gain G1 and added to the original vehicle speed pattern data to generate corrected vehicle speed pattern data. Steps ST3 to ST7 are then repeatedly executed while changing the values ​​of the cutoff frequency Fc and the first gain G1 to search for corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value. This makes it possible to generate different target vehicle speed pattern data for each specified value of the driving index.

[0053] (3) In the target vehicle speed pattern data generating method according to this embodiment, modified vehicle speed pattern data Vs' is generated by multiplying the high-frequency component by the first gain G1 and adding the result to the original vehicle speed pattern data, and the modified vehicle speed pattern data Vs is generated by multiplying the modified vehicle speed pattern data Vs' by a predetermined second gain G2. Steps ST3 to ST7 are repeatedly executed while changing the values ​​of the cutoff frequency Fc, the first gain G1, and the second gain G2, thereby searching for modified vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value. This makes it possible to generate different target vehicle speed pattern data for each specified value of the driving index.

[0054] (4) In the target vehicle speed pattern data generating method according to this embodiment, step ST2 acquires a designated value for at least one of IWR related to workload and RMSSE related to vehicle speed tracking. According to the target vehicle speed pattern data generating method according to this embodiment, by generating target vehicle speed pattern data based on designated values ​​for at least one of IWR and RMSSE, it is possible to reflect in the target vehicle speed pattern data variations in the driver's driving behavior of the accelerator pedal, the brake pedal, etc., more specifically variations in the roughness or smoothness of the driver's driving of the vehicle.

[0055] (5) In the test method according to this embodiment, the automated driving device 2 reads the target vehicle speed pattern data stored in the storage medium according to the above-described procedure, and then operates the test subject in accordance with the target vehicle speed pattern data. This allows the automated driving device 2 to reproduce a wide range of driving situations.

[0056] Although one embodiment of the present invention has been described above, the present invention is not limited to this, and the detailed configuration may be modified as appropriate within the scope of the spirit of the present invention.

[0057] For example, in the above embodiment, the vehicle speed pattern data generating device 1 calculates the evaluation function value cost according to the above formula (3), but the present invention is not limited to this. Because multiple driving indices may interfere with each other, it may be impossible to find corrected vehicle speed pattern data Vs that makes the evaluation function value cost defined by the above formula (3) less than the judgment value. In such cases, the vehicle speed pattern data generating device 1 may define the evaluation function value cost' as the absolute value of the inner product of the difference vector between the designated value vector DIset and the evaluation value vector DIresult, and a weight vector wn whose components are weights for each driving indices, as shown in the following formula (4). When driving indices interfere with each other as described above, it is possible to find a corrected vehicle speed vector that makes the evaluation function value cost' less than the judgment value by adjusting the value of the weight vector wn. cost' = |(DIset - DIresult) · wn | (4)

[0058] Furthermore, for example, in the above embodiment, a case has been described in which the automated driving device 2, which is a machine, automatically operates the test subject on behalf of a person, but the present invention is not limited to this. The present invention can also be applied to a bench test in which a human driver manually operates the test subject with the assistance of a driving assistance device known as a driver's aid. Here, the driving assistance device is a computer that assists the driver in appropriately driving the test subject by displaying predetermined driving assistance information on a monitor installed in a position visible to the driver seated in the driver's seat of the test subject (e.g., in front of the test subject in the direction of travel).

[0059] When performing a bench test using such a driving assistance device, the driving assistance device first reads the target vehicle speed pattern data stored in the storage medium of the vehicle speed pattern data generating device 1. Next, the driving assistance device displays driving assistance information generated based on the target vehicle speed pattern data on the monitor, thereby prompting the driver to drive the test subject in accordance with the target vehicle speed pattern data. Here, the driving assistance information displayed on the monitor includes, for example, the waveform of the target vehicle speed pattern data itself, the target vehicle speed command specified by the target vehicle speed pattern data, the actual vehicle speed, the deviation between the actual vehicle speed and the target vehicle speed command, and appropriate shift timing for tracing the target vehicle speed pattern data. By displaying the driving assistance information generated based on such target vehicle speed pattern data on the monitor, the driving assistance device allows the driver to reproduce a wide range of driving behaviors simply by operating the test subject while viewing the driving assistance information displayed on the monitor.

[0060] S... Vehicle test system 1... Vehicle speed pattern data generator 2... Automatic driving device 3... Control target

Claims

1. A method for generating target vehicle speed pattern data by a computer to generate target vehicle speed pattern data to be used in a bench test in which a test subject, which is a vehicle or vehicle part, is operated by an automatic driving device or a human driver, the method comprising: (A) a step of acquiring original vehicle speed pattern data; (B) a step of acquiring a designated value for at least one driving index; and (C) a step of generating modified vehicle speed pattern data by shaping the original vehicle speed pattern data based on the designated value, and storing the modified vehicle speed pattern data that satisfies predetermined conditions as the target vehicle speed pattern data in a storage medium readable by the automatic driving device or a driving assistance device that assists driving operations by the driver, wherein step (C) comprises: (C-1) a step of generating the modified vehicle speed pattern data by shaping frequency components higher than a predetermined cutoff frequency in the original vehicle speed pattern data; and (C-2) a step of calculating an evaluation value of the driving index for the modified vehicle speed pattern data by evaluating the modified vehicle speed pattern data based on the original vehicle speed pattern data. (C-3) A method for generating target vehicle speed pattern data, characterized by comprising a step of storing the corrected vehicle speed pattern data, which makes the difference between the specified value and the evaluation value less than a predetermined judgment value, in the storage medium as the target vehicle speed pattern data.

2. In step (C-1), the high frequency components are extracted from the original vehicle speed pattern data, and the high frequency components are multiplied by a predetermined first gain and the resulting value is added to the original vehicle speed pattern data to generate the corrected vehicle speed pattern data; and in step (C-3), steps (C-1) and (C-2) are repeatedly executed while changing the values ​​of the cutoff frequency and the first gain to search for the corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value.

3. In step (C-1), the corrected vehicle speed pattern data is generated by multiplying a predetermined second gain with vehicle speed pattern data generated by multiplying the high frequency component by the first gain and adding the value to the original vehicle speed pattern data, and in step (C-3), steps (C-1) and (C-2) are repeatedly executed while changing the values ​​of the cutoff frequency, the first gain, and the second gain, thereby searching for the corrected vehicle speed pattern data that makes the difference between the specified value and the evaluation value less than the judgment value.

4. The method for generating target vehicle speed pattern data according to claim 3, wherein step (B) acquires designated values ​​for at least one of a first driving index relating to workload and a second driving index relating to vehicle speed tracking ability.

5. A test method for performing the bench test on the test object using the target vehicle speed pattern data generated by the target vehicle speed pattern data generation method described in any one of claims 1 to 4 and the automatic driving device, characterized in that the test method comprises: (D) a step in which the automatic driving device reads the target vehicle speed pattern data stored in the storage medium; and (E) a step in which the automatic driving device operates the test object in accordance with the target vehicle speed pattern data.

6. A testing method for performing the bench test on the test subject using the target vehicle speed pattern data generated by the target vehicle speed pattern data generation method of any one of claims 1 to 4 and the driving assistance device, comprising: (F) a step in which the driving assistance device reads the target vehicle speed pattern data stored in the storage medium; and (G) a step in which the driving assistance device displays driving assistance information generated based on the target vehicle speed pattern data on a monitor located in a position visible to the driver, and prompts the driver to operate the test subject in accordance with the target vehicle speed pattern data.

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