Road surface information production device and vehicle control system

Abstract

The present invention relates to a road surface information production device and a vehicle control system. The cloud (CL1) includes a server (41) and a storage device (42). The storage device (42) has a road surface information map (42a). When the first sampling distance (d1) is greater than or equal to the first threshold distance (dth1), the server (41) performs resampling of the map production data by interpolating the data in such a manner that there are sampling positions at each second sampling distance (d2) and the unsprung displacement (z1) of the sampling positions. Based on the resampled map production data, the server (41) stores the sectional unsprung displacement (Z1) in the storage area corresponding to the section (Gd) in the road surface information map (42a).

Description

Technical Field

[0001] The present invention relates to a road surface information creation device for creating a road surface information map for predictive shock absorption control, and a vehicle control system including the road surface information creation device. Background Art

[0002] In the conventionally known predictive shock absorption control, in order to compensate for the delay of control, the force acting between the sprung mass and the unsprung mass is controlled based on a road surface displacement correlation value associated with the vertical displacement of the road surface in front of the vehicle, thereby reducing the vibration of the sprung mass (see Patent Document 1). That is, the predictive shock absorption control pre-reads the road surface displacement correlation value to control the shock absorption force. The conventional methods for pre-reading road surface information include: storing the road surface displacement correlation value in the cloud to construct a database, and acquiring the road surface displacement correlation value from the database through communication during the travel of the vehicle.

[0003] Prior Art Documents

[0004] Patent Documents

[0005] Patent Document 1: U.S. Patent Application Publication No. 2018 / 0154723 Summary of the Invention

[0006] The inventors of the present application have studied a road surface information map as a database. In the road surface information map, a virtual area corresponding to a specified section of a road is divided into a plurality of partitions of the same size, and a partition road surface displacement correlation value correlated with the vertical displacement of the road surface corresponding to each partition is stored in a storage area set to correspond to each partition. Moreover, the inventors of the present application have studied a road surface information creation device for creating a road surface information map.

[0007] When the vehicle travels in a specified section of a road, the road surface information creation device acquires a road surface displacement correlation value based on a sensor value acquired by a sensor mounted on the vehicle at a detection target position of the sensor (for example, the position of a wheel). The road surface information creation device stores the partition road surface displacement correlation value in the storage area corresponding to the partition to which the sampling position belongs, which is the position where the road surface displacement correlation value is acquired.

[0008] However, it has been found that the road surface information creation device has the following problems. The road surface displacement correlation value is obtained at a frequency (sampling frequency) corresponding to a certain sampling time, based on the sensor values obtained by the sensors mounted on the vehicle. Therefore, the faster the vehicle speed, the longer the interval between the sampling positions of the road surface displacement correlation value compared to the distance of one side of the section. For example, when the sampling frequency is set to 100 Hz and the vehicle speed is 72 km / h, the distance between the sampling positions for obtaining the road surface displacement correlation value becomes 200 mm, which is longer than the distance of one side of the section (e.g., 100 mm). As a result, there are cases where, although it is a section through which the detection target position of the sensor passes, no road surface displacement correlation value is obtained for that section. In such a case, the road surface information creation device cannot store the section road surface displacement correlation value in the storage area corresponding to that section, and thus cannot efficiently create a road surface information map.

[0009] Moreover, the faster the vehicle speed, the fewer the number of road surface displacement correlation values obtained for one section (e.g., reduced to only one). As a result, when the vehicle speed is relatively high and there is a deviation in the vertical displacement of the road surface in the road portion corresponding to one section, the section road surface displacement correlation value corresponding to one section will deviate from the true value of the average of the road surface displacement correlation values of the road portion corresponding to that one section. Therefore, the accuracy of the section road surface displacement correlation value stored in the storage area corresponding to the section will be lowered.

[0010] The present invention has been made to address the above problems. That is, one of the objects of the present invention is to provide a road surface information creation device and a vehicle control system that can efficiently create a highly accurate road surface information map. Hereinafter, the road surface information creation device of the present invention is sometimes referred to as "the road surface information creation device of the present invention". The vehicle control system of the present invention is sometimes referred to as "the vehicle control system of the present invention".

[0011] The road surface information creation device (CL1) of the present invention includes: a storage device (42) having a road surface information map (42a), in which a virtual area (DRj) corresponding to a specified section (ARj) of the road is divided into a plurality of sections (Gd), and a section road surface displacement correlation value related to the vertical displacement of the road surface corresponding to each of the plurality of sections is stored in each storage area set to correspond to each of the sections; and an information processing device (41) that stores the section road surface displacement correlation value in the storage area of the road surface information map.

[0012] The information processing device is configured to: obtain first data from the vehicle (10) through communication, the first data including: sensor values detected by the road surface related information sensors (RS1, 31, 32, 33) provided in the vehicle and required for calculating the partition road surface displacement related value, and the moments when the sensor values are detected, while the vehicle travels in the specified section; and position information correlated with the position of the vehicle and the moments when the position information is obtained, which are obtained by the position information obtaining device provided in the vehicle while the vehicle travels in the specified section (step 505), obtain second data based on the first data, the second data including time series data for obtaining a data set, the data set including a group of road surface displacement related values associated with the up-and-down displacement of the road surface and sampling positions as the detection positions of the road surface displacement related values (step 510), obtain the data set from the second data (step 515), calculate a first sampling distance corresponding to the distance between two adjacent sampling positions in the data set (step 525), in a case where the first sampling distance is longer than a first threshold distance (judged as "yes" in step 530), re-obtain the data set from the data obtained by resampling the second data, in the resampling, interpolation processing is performed such that each of the distances between multiple adjacent two sampling positions becomes equal to or less than the first threshold distance, and there is a road surface displacement related value corresponding to each of the sampling positions (steps 535, step 715), use the data set, calculate, for each partition determined to be the partition to which the sampling position belongs among the multiple partitions, a first average value representing the average of the road surface displacement related values of the sampling positions included in the determined partition, and store the calculated first average value in the storage area corresponding to the determined partition as the partition road surface displacement related value (steps 540, steps 605 to step 635).

[0013] According to the road surface information production device of the present invention, in a case where the first sampling distance is longer than the distance of one side of the partition, the second data is resampled. Thereby, the possibility of not obtaining a road surface displacement related value for a partition corresponding to a road section passed by the detection object position of the road surface related information sensor can be reduced. Moreover, the number of road surface displacement related values for one partition increases, and thus the partition road surface displacement related value approaches the true value of the average of the road surface displacement related values of the road section corresponding to one partition. Therefore, the road surface information production device of the present invention can efficiently produce a highly accurate road surface information map.

[0014] In one aspect of the road surface information production device of the present invention, the information processing device is further configured to obtain the vehicle speed of the vehicle while the vehicle travels in the specified section from the vehicle through the communicationFigure 7 In step 505), the information processing device is configured to obtain, as the second data, the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor from the first data (steps 505 and 705). The information processing device is configured to calculate the first sampling distance by multiplying the vehicle speed by the longer sampling time interval among the sampling time intervals of the time series data of the road surface displacement correlation value and the sampling time interval of the time series data of the detection object position of the road surface correlation information sensor (step 710).

[0015] According to the above solution, the first sampling distance is obtained (calculated) based on the vehicle speed and the above sampling time interval. Thus, when the first sampling distance becomes longer than the distance of one side of the partition due to the increase in the vehicle speed, the second data is resampled. Therefore, the road surface information production device of the present invention can efficiently produce a highly accurate road surface information map.

[0016] In one solution of the road surface information production device of the present invention, the information processing device is further configured to obtain, through the communication, the vehicle speed of the vehicle when the vehicle travels in the specified section Figure 5 In step 505), the information processing device is configured to obtain the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor from the first data Figure 5 In steps 505 and 510), in such a manner that the road surface displacement correlation value and the detection object position exist at the sampling moment of the time series data with a shorter sampling time interval among the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor, interpolation processing is performed on one of the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor, and data including the interpolated data that is the interpolated one of the time series data and the time series data of the other of the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor is obtained as the second data Figure 5 In step 515), the information processing device is configured to calculate the first sampling distance by multiplying the vehicle speed by the sampling time interval of the time series data with a shorter sampling time interval Figure 5 In step 525).

[0017] According to the above solution, the first sampling distance is obtained by calculating based on the vehicle speed and the above sampling time interval. Thus, when the first sampling distance becomes longer than the distance of one side of the partition due to the increase in the vehicle speed, the second data is resampled. Therefore, the road surface information production device of the present invention can efficiently produce a road surface information map with high accuracy.

[0018] In one solution of the road surface information production device of the present invention, the information processing device is configured to perform the resampling in such a manner that each of the distances between the two adjacent sampling positions among the plurality of sampling positions becomes a certain second sampling distance that is equal to or less than the first threshold distance.

[0019] According to the above solution, the resampling is performed in such a manner that each of the distances between the two adjacent sampling positions among the plurality of sampling positions becomes a certain second sampling distance that is equal to or less than the first threshold distance, and there is a road surface displacement correlation value corresponding to each of the sampling positions. In this case, the second sampling distance d2 is shorter than the first sampling distance d1. Therefore, the number of road surface displacement correlation values (for example, the displacement z1 under the spring) obtained for one partition Gd increases.

[0020] In one solution of the road surface information production device of the present invention, the information processing device is configured to perform the resampling (in step 535 of Figure 8 ) when the first sampling distance is equal to or less than a second threshold distance that is set to be shorter than the second sampling distance (when it is determined as "Yes" in step 810 of Figure 8 ).

[0021] According to the above solution, when the distance between the sampling positions is too short compared to the distance of one side of the partition, the second data is also resampled. Thus, the above solution can reduce the possibility that the road surface displacement correlation values obtained when the vehicle speed is slow are greatly reflected in the partition road surface displacement correlation values.

[0022] In one solution of the road surface information production device of the present invention, the information processing device is configured to, when the storage area corresponding to the determined partition already stores the partition road surface displacement correlation value, newly store the second average value in the storage area corresponding to the determined partition as the partition road surface displacement correlation value, where the second average value represents the average of the road surface displacement correlation values of the sampling positions included in the determined partition and the already stored partition road surface displacement correlation value (steps 605 to 635).

[0023] According to the above-described solution, when the partition road surface displacement-related values are already stored, the second average value is newly stored in the storage area corresponding to the partition as the partition road surface displacement-related value, and the second average value represents the average of the road surface displacement correlation value at the sampling position and the stored set road surface displacement-related value. Therefore, the more the number of road surface displacement correlation values obtained for the partition by many vehicles driving in a specified section of the road, the closer the partition road surface displacement-related value stored in the storage area corresponding to the partition is to the true value of the average of the road surface displacement correlation values of the road section corresponding to the partition. Thus, the above-described solution can create a road surface information map with higher accuracy.

[0024] In one solution of the road surface information creation device of the present invention, the road surface displacement correlation value is the unsprung displacement representing the up-and-down displacement of the vehicle below the spring, and the sensor value is the up-and-down acceleration above the spring of the vehicle and the up-and-down relative displacement between above and below the spring, or the sensor value is the unsprung acceleration.

[0025] According to the above-described solution, the unsprung displacement is used as the road surface displacement correlation value. The unsprung displacement is a value representing the up-and-down displacement of the unsprung part that actually moves in the up-and-down direction due to the displacement of the road surface when the vehicle actually travels on the road surface. Therefore, the possibility of the unsprung displacement containing errors is low. Thus, the above-described solution can create a road surface information map with higher accuracy.

[0026] The vehicle control system of the present invention is a vehicle control system including a road surface information creation device (CL1), a first vehicle (10), and a second vehicle (10) configured to be able to communicate with each other.

[0027] The road surface information creation device (CL1) includes: a storage device (42) having a road surface information map (42a), in which a virtual area (DRj) corresponding to a specified section (ARj) of the road is divided into a plurality of partitions (Gd), and partition road surface displacement-related values having a correlation with the up-and-down displacement of the road surface corresponding to each of the plurality of partitions are stored in respective storage areas set to correspond to the respective partitions; and an information processing device (41) that stores the partition road surface displacement-related values in the storage areas of the road surface information map.

[0028] The information processing device is configured to: obtain first data from the first vehicle through communication, the first data including: sensor values detected by the road surface related information sensors (RS1, 31, 32, 33) of the first vehicle when the first vehicle travels in the specified section and required for calculating the partition road surface displacement related value, and the time when the sensor values are detected; and position information related to the position of the first vehicle and the time when the position information is obtained, which are obtained by the position information obtaining device of the first vehicle when the first vehicle travels in the specified section (step 505), obtain second data based on the first data, the second data including time series data for obtaining a data set, the data set including a group of a plurality of road surface displacement related values associated with the up and down displacement of the road surface and sampling positions as the detection positions of the road surface displacement related values (step 510), obtain the data set from the second data (step 515), calculate a first sampling distance corresponding to the distance between two adjacent sampling positions of the data set (step 525), in the case where the first sampling distance is longer than a first threshold distance (determined as "yes" in step 530), obtain the data set again from the data obtained by resampling the second data, and in this resampling, interpolation processing is performed in such a way that the distance between each of a plurality of adjacent two sampling positions becomes less than or equal to the first threshold distance, and there is a road surface displacement related value corresponding to each of the sampling positions (steps 535, step 715).

[0029] Using the data set, for each partition determined to be the partition to which the sampling position belongs among the plurality of partitions, calculate a first average value representing the average of the road surface displacement related values of the sampling positions included in the determined partition, and store the calculated first average value in the storage area corresponding to the determined partition as the partition road surface displacement related value (steps 540, steps 605 to step 635).

[0030] At least one of the first vehicle and the second vehicle is configured to: receive control data for vehicle control from the road surface information production device, the control data including the position information of the partition obtained based on the road surface information map and the partition road surface displacement related value associated with the position information.

[0031] According to the vehicle control system of the present invention, when the first sampling distance is longer than the distance on one side of the first sampling distance ratio partition, the second data is resampled. Thus, the possibility of not obtaining the road surface displacement correlation value for the partition corresponding to the road section passed by the detection object position of the sensor can be reduced. Moreover, the number of road surface displacement correlation values for one partition increases, so the partition road surface displacement related value approaches the true value of the average of the road surface displacement correlation values corresponding to the road section of one partition. Therefore, according to the vehicle control system of the present invention, a highly accurate road surface information map can be efficiently created. Further, in the vehicle control system of the present invention, at least one of the first vehicle and the second vehicle can receive control data for vehicle control from the road surface information map created in this way, and the control data includes the position information of the partition and the partition road surface displacement related value associated with the position information.

[0032] In the above description, to help understand the present invention, the components of the invention corresponding to the embodiments described later are added with the names and / or reference numerals used in the embodiments in parentheses. However, each component of the present invention is not limited to the embodiments defined by the said names and / or reference numerals. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic configuration diagram of a predictive vibration damping control system including a road surface information creation device according to an embodiment of the present invention.

[0034] Figure 2 is a schematic configuration diagram of a vehicle.

[0035] Figure 3A is a diagram for explaining a road section.

[0036] Figure 3B is a diagram for explaining a road surface information map.

[0037] Figure 4 is a diagram for explaining an outline of the operation of a road surface information creation device.

[0038] Figure 5 is a flowchart showing a routine executed by the CPU of a server.

[0039] Figure 6 is a flowchart showing a map update routine executed by the CPU of a server.

[0040] Figure 7 is a flowchart showing a routine executed by the CPU of a server.

[0041] Figure 8 is a flowchart showing a routine executed by the CPU of a server.

[0042] Description of reference numerals:

[0043] 10 Vehicle, 20 On-vehicle device, 30 Electronic control device, 31FL to 31RR Vertical acceleration sensors, 32FL to 32RR Stroke sensors, 33 Anticipation sensor, 34 Vehicle state quantity sensor, 35 Position information acquisition device, 36 Wireless communication device, 41 Server, 42 Storage device, 42a Road surface information map, CL1 Cloud, RS1 Road surface related information sensor. Detailed implementation manners

[0044] <<First implementation manner>>

[0045] <Configuration>

[0046] Figure 1 The figure shows an anticipatory damping control system (vehicle control system) including a road surface information production device (cloud CL1) according to the first implementation manner of the present invention. The anticipatory damping control system includes a plurality of vehicles 10, on-vehicle devices 20, and cloud CL1. It should be noted that, in Figure 1 the figure, only four vehicles 10 with the same configuration are shown as the plurality of vehicles 10.

[0047] As Figure 2 shown in the figure, the vehicle 10 includes a left front wheel 11FL, a right front wheel 11FR, a left rear wheel 11RL, and a right rear wheel 11RR, and wheel support members 12FL to 12RR. It should be noted that the left front wheel 11FL to the right rear wheel 11RR are referred to as "wheel 11" when there is no need to distinguish them. Similarly, the wheel support members 12FL to 12RR are referred to as "wheel support member 12". The wheel 11 is supported by the wheel support member 12 so as to be rotatable.

[0048] The vehicle 10 further includes a left front wheel suspension 13FL, a right front wheel suspension 13FR, a left rear wheel suspension 13RL, and a right rear wheel suspension 13RR.

[0049] The left front wheel suspension 13FL suspends the left front wheel 11FL from the vehicle body 10a, and includes a suspension arm 14FL, a shock absorber 15FL, and a suspension spring 16FL. A left front wheel active actuator 17FL is provided between the vehicle body 10a and the shock absorber 15FL.

[0050] The right front wheel suspension 13FR suspends the right front wheel 11FR from the vehicle body 10a, and includes a suspension arm 14FR, a shock absorber 15FR, and a suspension spring 16FR. A right front wheel active actuator 17FR is provided between the vehicle body 10a and the shock absorber 15FR.

[0051] The left rear wheel suspension 13RL suspends the left rear wheel 11RL from the vehicle body 10a, and includes a suspension arm 14RL, a shock absorber 15RL, and a suspension spring 16RL. A left rear wheel active actuator 17RL is provided between the vehicle body 10a and the shock absorber 15RL.

[0052] The right rear wheel suspension 13RR suspends the right rear wheel 11RR from the vehicle body 10a, and includes a suspension arm 14RR, a shock absorber 15RR, and a suspension spring 16RR. A right rear wheel active actuator 17RR is provided between the vehicle body 10a and the shock absorber 15RR.

[0053] It should be noted that the left front wheel suspension 13FL to the right rear wheel suspension 13RR are referred to as "suspension 13" without distinguishing them. Similarly, the suspension arms 14FL to 14RR are referred to as "suspension arm 14". Similarly, the shock absorbers 15FL to 15RR are referred to as "shock absorber 15". Similarly, the suspension springs 16FL to 16RR are referred to as "suspension spring 16". Similarly, the left front wheel active actuators 17FL to the right rear wheel active actuators 17RR are referred to as "wheel actuator 17".

[0054] The suspension arm 14 connects the wheel support member 12 that supports the wheel 11 to the vehicle body 10a.

[0055] The shock absorber 15 is disposed between the vehicle body 10a and the suspension arm 14, and is connected to the vehicle body 10a at the upper end and to the suspension arm 14 at the lower end. The suspension spring 16 is elastically installed between the vehicle body 10a and the suspension arm 14 via the shock absorber 15. That is, the upper end of the suspension spring 16 is connected to the vehicle body 10a, and the lower end of the suspension spring 16 is connected to the cylinder of the shock absorber 15. It should be noted that in this example, the shock absorber 15 is a shock absorber with non-variable damping force, but the shock absorber 15 can also be a shock absorber with variable damping force.

[0056] The wheel actuator 17 is arranged side by side with the shock absorber 15 and the suspension spring 16. The wheel actuator 17 functions as an actuator that variably generates a force acting between the vehicle body 10a and the wheel 11 in a hydraulic or electromagnetic manner. The wheel actuator 17 cooperates with the shock absorber 15, the suspension spring 16, etc. to form an active suspension. The wheel actuator 17 can be an actuator with any known configuration in the technical field as long as it can generate a force (hereinafter referred to as "control force Fc") acting between the vehicle body 10a and the wheel 11 under the control of an electronic control device 30 (hereinafter referred to as "ECU 30") described later.

[0057] Refer again to Figure 1, the vehicle 10 is equipped with an in-vehicle device 20. The in-vehicle device 20 includes an ECU 30, vertical acceleration sensors 31FL, 31FR, 31RL, 31RR, stroke sensors 32FL, 32FR, 32RL, 32RR, a prediction sensor 33, a vehicle state quantity sensor 34, a position information acquisition device 35, and a wireless communication device 36. The vertical acceleration sensors 31FL to 31RR are referred to as "vertical acceleration sensors 31" without distinguishing them. Similarly, the stroke sensors 32FL to 32RR are referred to as "stroke sensors 32".

[0058] The ECU 30 is a control unit (Electronic Control Unit) with a microcomputer as the main part, and is also referred to as a controller. The microcomputer includes a CPU, a ROM, a RAM, and an interface (I / F), etc. The CPU realizes various functions by executing instructions (programs, routines) stored in the ROM.

[0059] The ECU 30 is connected to each of the vertical acceleration sensors 31, the stroke sensors 32, the prediction sensor 33, the vehicle state quantity sensor 34, and the position information acquisition device 35.

[0060] The vertical acceleration sensor 31 detects the vertical acceleration of the vehicle body 10a (above the spring) of the vehicle 10 and generates a signal representing the vertical acceleration above the spring. The ECU 30 acquires the signal representing the vertical acceleration from the vertical acceleration sensor 31 every time a certain sampling time elapses. Moreover, the ECU 30 acquires the time when the signal representing the vertical acceleration is obtained based on a clock built in the ECU 30. It should be noted that above the spring includes the vehicle body 10a of the vehicle 10 and the part on the vehicle body 10a side of the suspension spring 16 in components such as the shock absorber 15.

[0061] The stroke sensor 32 is provided on the suspension 13. The stroke sensor 32 detects the vertical stroke of the suspension 13 and generates a signal representing the vertical stroke. The vertical stroke is the relative displacement in the vertical direction between above the spring corresponding to the position of the wheel 11 and below the spring corresponding to the position of the wheel 11. The ECU 30 acquires the signal representing the vertical stroke from the stroke sensor 32 every time a certain sampling time elapses. Moreover, the ECU 30 acquires the time when the signal representing the vertical stroke is detected based on a clock built in the ECU 30. It should be noted that below the spring includes the wheel 11 of the vehicle 10 and the part on the wheel 11 side of the suspension spring 16 in components such as the shock absorber 15.

[0062] The prediction sensor 33 is composed of at least one of a camera sensor and a LiDAR (Light Detection and Ranging) (refer to Japanese Unexamined Patent Application Publication No. 2017-171156 and Japanese Unexamined Patent Application Publication No. 2020-26187). The prediction sensor 33 detects the vertical displacement of the road surface at a position a predetermined distance ahead of the front wheels 11 of the vehicle 10 and generates a signal representing the vertical displacement of the road surface. The ECU 30 acquires the signal representing the vertical displacement of the road surface from the prediction sensor 33 every time a certain sampling time elapses. Moreover, the ECU 30 acquires the time when the vertical displacement of the road surface is detected based on a clock built in the ECU 30.

[0063] The above-described vertical acceleration sensor 31, stroke sensor 32, and prediction sensor 33 function as sensors that acquire sensor values representing the road surface displacement correlation values at the detection target positions of the respective sensors or sensor values that can calculate the road surface displacement correlation values at the detection target positions of the respective sensors.

[0064] These sensor values are information representing the state quantity of the vehicle 10 that changes due to the unevenness of the road surface or the unevenness of the road surface. Hereinafter, for convenience, these sensors are also referred to as "road surface correlation information sensors RS1". The road surface displacement correlation value is information related to the vertical displacement of the road surface representing the undulation of the road surface. Specifically, the road surface displacement correlation value is the road surface displacement z0 as the vertical displacement of the road surface or the unsprung displacement z1 as the vertical displacement of the unsprung mass. In this example, the road surface displacement correlation value is the unsprung displacement z1, and the sensor values that can calculate the unsprung displacement z1 at the detection target positions of the respective sensors are acquired by the vertical acceleration sensor 31 and the stroke sensor 32.

[0065] The vehicle state quantity sensor 34 includes a variety of sensors that detect the motion state of the vehicle 10. The vehicle state quantity sensor 34 includes a vehicle speed sensor that detects the traveling speed (vehicle speed) of the vehicle 10, a longitudinal acceleration sensor that detects the longitudinal acceleration of the vehicle 10, a lateral acceleration sensor that detects the lateral acceleration of the vehicle 10, a yaw rate sensor that detects the yaw rate of the vehicle 10, and the like.

[0066] The position information acquisition device 35 includes a GNSS (Global Navigation Satellite System) receiver and a map database. The GNSS receiver receives "signals from artificial satellites constituting the GNSS (i.e., GNSS signals)" for detecting the current position of the vehicle 10 at the current time. Information including road map information is stored in the map database.

[0067] The position information acquisition device 35 determines the position information (e.g., latitude and longitude) and the current time of the vehicle 10 based on the GNSS signal every time a certain sampling time elapses, and outputs a signal representing the determined position information and the current time.

[0068] In this example, the sampling time of the position information acquisition device 35 is set to a time longer than the sampling time of the sensor values of the road surface related information sensor RS1. The ECU 30 acquires a signal representing the determined position information and the current time every time a certain sampling time elapses.

[0069] It should be noted that the current position of the vehicle 10 acquired by the position information acquisition device 35 corresponds to the mounting position of the GNSS receiver. Position relationship data representing the position relationship between the mounting position of the GNSS receiver and the detection target positions of the respective sensors of the road surface related information sensor RS1 is stored in advance in the ROM of the ECU 30. Therefore, the ECU 30 determines the detection target positions of the respective sensors of the road surface related information sensor RS1 every time a certain sampling time elapses by referring to the current position of the vehicle 10, the traveling direction of the vehicle 10, and the above position relationship data. The detection target position is the position where each sensor outputs a detected signal, that is, the absolute position where each sensor acquires a sensor value, and is represented by, for example, latitude and longitude. It should be noted that it is also possible that the position information acquisition device 35 determines the detection target positions of the respective sensors of the road surface related information sensor RS1 and sends the determined detection target positions to the ECU 30.

[0070] The wireless communication device 36 is a wireless communication terminal for performing information communication with the cloud CL1 via the communication line IN1.

[0071] The ECU 30 stores the sensor values and detection target positions of the respective sensors together with the detection time at which each of them is detected in a non-volatile storage device (not shown). The ECU 30 generates "time series data of sensor values and time series data of detection target positions" for each road section by arranging the stored "sensor values and detection target positions" in time series order for each road section having a certain distance. It should be noted that information on the detection time at which the sensor values and position information are detected is attached to each of these data. And the ECU 30 uses the wireless communication device 36 to send the "time series data of sensor values and time series data of detection target positions" of the respective sensors to the cloud CL1 every time it passes through a road section. For convenience, the "time series data of sensor values and time series data of detection target positions" is sometimes referred to as "first data".

[0072] It should be noted that the above-mentioned certain road section is called the "target section". The "time series data of sensor values and time series data of detection target positions" of each sensor sent by the ECU 30 to the cloud CL1 is called the "target section driving data". The time series data of sensor values obtained by the road surface related information sensor RS1 in the target section driving data is called the "target section sensing data". The time series data of detection target positions of each sensor in the target section driving data is called the "target section position information data".

[0073] Moreover, the ECU 30 calculates the vehicle speed V (average vehicle speed) when the vehicle 10 travels in the target section, and sequentially sends the calculated vehicle speed V and the target section driving data to the cloud CL1. It should be noted that hereinafter, the vehicle speed V when the vehicle 10 travels in the target section is called the "target section vehicle speed V". In this example, the ECU 30 calculates the target section vehicle speed V of the vehicle 10 based on the time change of the position of the vehicle 10 obtained from the position information acquisition device 35. It should be noted that the ECU 30 can also use the average value of the vehicle speed of the vehicle 10 detected by the vehicle state quantity sensor 34 in the target section as the target section vehicle speed V.

[0074] The cloud CL1 includes a server 41 and a storage device 42. The server 41 includes a microcomputer. It should be noted that the server 41 can also be composed of multiple servers. The storage device 42 can also be composed of multiple storage devices. For convenience, the "server 41" is also called the "information processing device". The server 41 retrieves and reads the data stored in the storage device 42, and writes the data into the storage device 42.

[0075] Moreover, the server 41 performs data processing on the data received from the wireless communication device 36. More specifically, the server 41 sequentially receives from the wireless communication device 36 via the communication line IN1 (Internet line) the target section driving data including the target section sensing data and the target section vehicle speed V. The server 41 generates the time series data of the unsprung displacement z1 (hereinafter, called the "target section unsprung displacement data".) by performing data processing on the target section sensing data.

[0076] More specifically, the server 41 performs data processing on the target section sensing data in an offline processing manner. Examples of data processing include filtering processing, integration processing, and / or subtraction processing, etc. In this example, the target section sensing data is the time series data of the vertical acceleration above the spring (hereinafter, called the "target section vertical acceleration data above the spring".) and the time series data of the vertical stroke (hereinafter, called the "target section vertical stroke data".).

[0077] The server 41 generates the under-spring displacement data of the object interval by performing a subtraction process of subtracting the up-and-down stroke data of the object interval after performing a second-order time integration process on the up-and-down acceleration data of the object interval spring.

[0078] It should be noted that the server 41 can also perform a band-pass filtering process (hereinafter referred to as "BPF process") that allows only the components of a specific frequency band to pass through these object interval sensing data. In this case, the server 41 uses the object interval sensing data after the BPF process to generate the under-spring displacement data of the object interval.

[0079] The specific frequency band is set as a frequency band selected in such a way as to at least include the resonance frequency of the spring mass. More specifically, the specific frequency band is a frequency band above the first cut-off frequency and below the second cut-off frequency. The first cut-off frequency is set to a frequency smaller than the resonance frequency of the spring mass. The second cut-off frequency is set to a frequency smaller than the resonance frequency of the under-spring and larger than the resonance frequency of the spring mass.

[0080] The storage device 42 is configured to be able to perform writing and reading of data. The storage device 42 has a road surface information map. The road surface information map 42a is set for each object interval ARj as shown Figure 3A below. Figure 3B FIG. shows the road surface information map 42a set corresponding to one object interval ARj (AR1). The road surface information map is an aggregate of such road surface information maps 42a. The virtual area DRj corresponding to one object interval ARj is divided by a line Lx parallel to the X direction and a line Ly parallel to the Y direction into a plurality of square partitions Gd (also referred to as "grids") having equal sizes to each other. A position (latitude and longitude) is set in the virtual area DRj in a manner corresponding to the position (latitude and longitude) of the object interval ARj. The road surface information map 42a is configured to store data in a storage area set for each partition Gd of the road surface information map 42a. In this example, the distance d0 of one side of the partition Gd is a fixed value of 50 mm or more and 150 mm or less (typically 100 mm). It should be noted that the shape of each partition Gd is not limited to a square, and can also be determined according to the size and shape of the contact area of the tire of the wheel 11 and the ease of control. In the case where the shape of the partition Gd is a rectangle, the distance d0 of one side of the partition Gd is defined as the maximum distance among the distances of the sides of the partition Gd.

[0081] The X direction of the road surface information map 42a is, for example, the direction of north in terms of azimuth, and the Y direction is the direction perpendicular to the X direction. It should be noted that the X direction of the road surface information map 42a can also be the azimuth along the traveling direction of the road (the direction in which the vehicle travels) (for example, if it is a straight road extending east-west, it is east). The positions of the X direction and Y direction of each partition Gd are respectively represented by the index Xm (m = 1, 2, 3,...) and the index Yn (n = 1, 2, 3,...). That is to say, the partition Gd corresponding to a certain road section of a certain object section ARj is determined by the index Aj(Xm, Yn). Here, Aj is the identification number of the road surface information map 42a (area DRj) corresponding to each object section ARj, and j is a positive integer. If Aj(Xm, Yn) is determined, the road surface information map 42a corresponding to the object section ARj and the partition Gd corresponding to Aj(Xm, Yn) (the position of the partition Gd (for example, the latitude and longitude of the centroid position of the partition Gd)) are determined.

[0082] In the storage area corresponding to each partition Gd of the road surface information map 42a, a partition road surface displacement correlation value that is correlated with the up-and-down displacement of the road surface of the road section corresponding to each partition Gd is stored.

[0083] In this example, the partition road surface displacement correlation value is the partition unsprung displacement Z1 calculated based on the unsprung displacement z1 generated by the road section corresponding to each partition Gd.

[0084] That is, the road surface information map 42a stores the partition unsprung displacement Z1 in association with each partition Gd (the position of each partition Gd) of the road surface information map 42a.

[0085] Moreover, in the storage area corresponding to each partition Gd, a count Nnew indicating the number of unsprung displacements z1 used in the calculation of the partition unsprung displacement Z1 is stored.

[0086] It should be noted that the partition unsprung displacement Z1 and the count Nnew will be described later.

[0087] In the initial state of the road surface information map 42a, an initial value (for example, "0") is stored in the storage area corresponding to each partition Gd as the partition unsprung displacement Z1 (that is, the partition unsprung displacement Z1 is not stored), and an initial value ("0") is stored as the count Nnew. The road surface information map 42a is used to obtain the predictive reference data for the predictive damping control described later. The predictive reference data is data including the position (position information) of the partition Gd obtained based on the road surface information map 42a and the partition unsprung displacement Z1 associated with this position.

[0088] Refer again Figure 1, the ECU 30 is connected to each of the left front wheel active actuator 17FL, the right front wheel active actuator 17FR, the left rear wheel active actuator 17RL, and the right rear wheel active actuator 17RR via a drive circuit (not shown).

[0089] The ECU 30 calculates a target control force Fct for reducing the vibration of the sprung mass of each wheel 11 based on the unsprung displacement z1 at the predicted passing position of each wheel 11 described below. The ECU 30 controls the wheel actuator 17 such that the control force Fc generated by the wheel actuator 17 becomes the target control force Fct when each wheel 11 passes through the predicted passing position.

[0090] <Summary of predictive damping control>

[0091] In the following description, the sprung mass is set to m2, the unsprung displacement (i.e., the up-and-down displacement of the unsprung part) is set to z1, and the sprung displacement (i.e., the up-and-down displacement of the sprung part at the position of each wheel 11) is set to z2. Further, the spring constant (equivalent spring constant) of the spring of the suspension 13 (e.g., the suspension spring 16) is set to K, the damping coefficient (equivalent damping coefficient) of the damper of the suspension 13 (e.g., the shock absorber 15) is set to C, and the control force generated by the wheel actuator 17 is set to Fc.

[0092] Moreover, the time derivatives of z1 and z2 are respectively set to dz1 and dz2, and the second-order time derivatives of z1 and z2 are respectively set to ddz1 and ddz2. It should be noted that for z1 and z2, the displacement upward is defined as positive, and for the forces generated by the spring, the damper, and the wheel actuator 17, etc., the upward direction is defined as positive.

[0093] The equation of motion for the up-and-down movement of the sprung mass of the vehicle 10 is represented by the following equation (1).

[0094] m2ddz2 = C(dz1 - dz2) + K(z1 - z2) - Fc... (1)

[0095] It is assumed that the damping coefficient C in Equation (1) is constant. However, the actual damping coefficient varies according to the stroke speed of the suspension 13. Therefore, for example, the damping coefficient C can be variably set according to the time derivative of the up-and-down stroke.

[0096] Moreover, when the vibration of the sprung mass is completely eliminated by the control force Fc (i.e., when the sprung acceleration ddz2, the sprung velocity dz2, and the sprung displacement z2 are respectively zero), the control force Fc is represented by Equation (2).

[0097] Fc = Cdz1 + Kz1... (2)

[0098] Therefore, when the control gain is set to α, the control force Fc for reducing the vibration above the spring can be expressed by Equation (3). It should be noted that the control gain α is an arbitrary constant greater than 0 and less than or equal to 1.

[0099] Fc = α(Cdz1 + Kz1)……(3)

[0100] Moreover, if Equation (3) is applied to Equation (1), Equation (1) can be expressed by Equation (4).

[0101] m2ddz2 = C(dz1 - dz2) + K(z1 - z2) - α(Cdz1 + Kz1)……(4)

[0102] If Laplace transform is performed on Equation (4) and it is rearranged, Equation (4) is expressed by Equation (5). That is, the transfer function from the displacement z1 below the spring to the displacement z2 above the spring is expressed by Equation (5). It should be noted that "s" in Equation (5) is the Laplace operator.

[0103]

[0104] According to Equation (5), the value of the transfer function changes according to α, and when α is 1, the value of the transfer function becomes the minimum. Therefore, the target control force Fct can be expressed by the following Equation (6) corresponding to Equation (3). It should be noted that the gain β1 in Equation (6) corresponds to αCs, and the gain β2 corresponds to αK.

[0105] Fct = β1×dz1 + β2×z1……(6)

[0106] Thus, the ECU 30 obtains the predictive reference data of the area predicted to be passed by the wheel 11 from the cloud CL1 through communication. It should be noted that the predictive reference data is sometimes referred to as "control data". The ECU 30 pre-obtains (pre-reads) the displacement z1 below the spring at the position (predicted passing position) that the wheel 11 will pass through later based on the predictive reference data, and calculates the target control force Fct by applying the displacement z1 below the spring to Equation (6). And the ECU 30 makes the wheel actuator 17 generate a control force Fc corresponding to the target control force Fct at the timing when the wheel 11 passes through the predicted passing position (that is, at the timing when the displacement z1 below the spring applied to Equation (6) is generated). If this is done, the vibration above the spring can be reduced when the wheel 11 passes through the predicted passing position (that is, when the displacement z1 below the spring applied to Equation (6) is generated).

[0107] The above is the vibration damping control above the spring. The vibration damping control above the spring based on the pre-obtained displacement z1 below the spring is the predictive vibration damping control in the present embodiment.

[0108] It should be noted that in the above description, the unsprung mass and the elastic deformation of the tire are ignored, and it is assumed that the road surface displacement z0 and the unsprung displacement z1 are the same. Therefore, the road surface displacement z0 can also be used instead of the unsprung displacement z1 to perform the same predictive vibration damping control.

[0109] The following formula (7) is a formula for simply calculating the target control force Fct by omitting the differential term (β1×dz1) in the above formula (6). When the target control force Fct is calculated according to formula (7), a control force Fc (=β2×z1) that reduces the vibration of the sprung mass is also generated by the wheel actuator 17. Therefore, compared with the case where this control force Fc is not generated, the vibration of the sprung mass can be reduced.

[0110] Fct=β2×z1……(7)

[0111] <Outline of operation>

[0112] The server 41 obtains the "partition unsprung displacement Z1" for the partition Gd (the partition Gd corresponding to Aj(Xm, Yn)) of the region DRj based on the object interval travel data of the object interval ARj (that is, the object interval sensing data and the object interval position information data).

[0113] The server 41 stores the obtained "partition unsprung displacement Z1" in the storage area corresponding to the partition Gd. That is, when the server 41 obtains a plurality of unsprung displacements z1 for a certain partition Gd, it calculates the average value of the plurality of unsprung displacements z1 and stores the calculated average value in the "storage area corresponding to the partition Gd" of the road surface information map 42a as the "partition unsprung displacement Z1".

[0114] More specifically, as described above, the server 41 generates object interval unsprung displacement data by performing data processing on the object interval sensing data. The server 41 attempts to associate data (unsprung displacement z1 and position information) with each other whose corresponding times are the same, that is, the time corresponding to each unsprung displacement z1 included in the object interval unsprung displacement data and the time corresponding to each position information included in the object interval position information data. Thereby, the server 41 can distinguish which partition Gd the sensor value (unsprung displacement z1) included in the object interval unsprung displacement data belongs to.

[0115] However, in this example, the sampling time interval ΔTP of the object interval position information data is longer than the sampling time interval ΔTB of the object interval unsprung displacement data (ΔTP > ΔTB). Therefore, due to the lack of position information of the object interval position information data corresponding to each sampling moment of the object interval unsprung displacement data, not all of the object interval unsprung displacement data can be used as data for generating the road surface information map 42a. As a result, there is a situation where it is impossible to efficiently produce a road surface information map 42a with good accuracy.

[0116] Therefore, the server 41 first obtains the position (position information) corresponding to each of the unsprung displacements z1 included in the object interval unsprung displacement data by performing data interpolation processing on the object interval position information data (for example, one of the well-known linear interpolation and spline interpolation). That is, the server 41 obtains the detection object position at the moment corresponding to each of the unsprung displacements z1 based on the object interval position information data through data interpolation processing based on time. In other words, for the data in the object interval unsprung displacement data where the corresponding position (position information) is missing, the position (position information) is obtained by interpolation. As a result, the position (position information) corresponding to each of the unsprung displacements z1 included in the object interval unsprung displacement data is determined. It should be noted that hereinafter, the set of the object interval unsprung displacement data and the interpolated object interval position information data is referred to as "data for map production". Through the above interpolation, in the data for map production, there is a set of the unsprung displacement z1 and the position (position information) corresponding to the unsprung displacement z1 at every sampling time interval ΔTB of the object interval unsprung displacement data.

[0117] Furthermore, as Figure 4 shown, assume that the set of the unsprung displacement z1 and the position corresponding to the unsprung displacement z1 at the first moment ta of the data for map production is the unsprung displacement z1a and the set of the position represented by the first sample point P1a. Also, assume that the set of the unsprung displacement z1 and the position corresponding to the unsprung displacement z1 at the second moment tb of the data for map production is the unsprung displacement z1b and the set of the position represented by the first sample point P1b. It should be noted that the second moment tb is a moment that is "sampling time interval ΔTB" later than the first moment ta. The first sample point P1a and the first sample point P1b are points that represent that both the unsprung displacement z1 and its position are determined (exist) at the positions represented by each of them through the above data interpolation processing of the object interval position information data.

[0118] In this example, the first sample point P1a corresponds to the partition Gd determined by Aj(X5, Y5). The first sample point P1b corresponds to the partition Gd determined by Aj(X7, Y6). That is, only one unsprung displacement z1a is obtained in the partition Gd determined by Aj(X5, Y5), and only one unsprung displacement z1b is obtained in the partition Gd determined by Aj(X7, Y6). Thus, the unsprung displacement z1a can be stored as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X5, Y5), and the unsprung displacement z1b can be stored as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X7, Y6). However, compared with the average value of multiple unsprung displacements z1, one unsprung displacement z1 may contain a large error relative to the true value.

[0119] In addition, for each of the partition Gd determined by Aj(X6, Y5) and the partition Gd determined by Aj(X6, Y6), although it is located on the straight line Tr1 corresponding to the passing trajectory of the wheel 11, there is no data (a set of the unsprung displacement z1 and the position (position information) corresponding to the unsprung displacement z1). Therefore, the data corresponding to these partitions Gd in the road surface information map 42a cannot be created. That is, the server 41 cannot efficiently create the road surface information map 42a.

[0120] Therefore, the server 41 calculates the first sampling distance d1 to determine whether further data processing (the "resampling" described later) is required. More specifically, the server 41 obtains the first sampling distance d1 by multiplying the vehicle speed V in the target section by the "sampling time interval ΔTB". The first sampling distance d1 is the distance "between the positions (sampling positions) represented by the adjacent first sample points P1a and the position (sampling position) represented by the first sample point P1b".

[0121] Next, the server 41 determines whether the first sampling distance d1 is longer than a specified first threshold distance dth1. The first threshold distance dth1 is set to be shorter than the distance d0 of one side of the partition Gd. In this example, the first threshold distance dth1 is 1 / 10 of the distance d0 of one side of the partition Gd. Then, when the first sampling distance d1 is longer than the first threshold distance dth1, the server 41 performs resampling on the data for map creation (the unsprung displacement data in the target section and the interpolated position information data in the target section).

[0122] More specifically, the server 41 uses the unsprung displacement z1 and the position (position information) of each of the "adjacent first sample points P1a and P1b" to obtain the "unsprung displacement z1 and the position (position information)" of the position (sampling position) represented by each of the plurality of second sample points P2 through data interpolation. Each of the plurality of second sample points P2 is a point between the position represented by the first sample point P1a and the position represented by the first sample point P1b. That is, the server 41 performs data interpolation processing on the map production data (object interval unsprung displacement data and interpolated object interval position information data), increasing the number of data (groups of unsprung displacement z1 and position information) that can be used for the road surface information map 42a. In this example, each of the distances between the positions (sampling positions) represented by the plurality of adjacent second sample points P2 is set to a certain second sampling distance d2.

[0123] The second sampling distance d2 is set to a distance equal to or less than the first threshold distance dth1 (the same distance as the first threshold distance dth1 in this example). The data interpolation processing for resampling is performed according to a well-known processing method (e.g., linear interpolation or spline interpolation). It should be noted that it is sufficient that each of the distances between the positions (sampling positions) represented by two adjacent second sample points P2 is set to a distance equal to or less than the first threshold distance, and it is not necessary to be set to a certain second sampling distance d2.

[0124] Then, the server 41 uses the groups of the plurality of unsprung displacements z1 and sampling positions (position information) obtained from the resampled data to determine the unsprung displacement z1 belonging to each partition Gd. The server 41 calculates the average value of the unsprung displacements z1 determined to belong to a certain partition as the partition unsprung displacement Z1, and stores the partition unsprung displacement Z1 in the storage area of the road surface information map 42a corresponding to the corresponding partition Gd.

[0125] That is, in Figure 4 the example shown, the server 41 stores the average value of the unsprung displacements z1 corresponding to the plurality of second sample points P2 within the dotted line Gr1 in the corresponding storage area as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X5, Y5).

[0126] Similarly, the server 41 stores the average value of the unsprung displacements z1 corresponding to the plurality of second sample points P2 within the dotted line Gr2 in the corresponding storage area as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X6, Y5).

[0127] The server 41 stores the average value of the unsprung displacements z1 corresponding to the plurality of second sample points P2 within the dotted line Gr3 in the corresponding storage area as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X6, Y6).

[0128] Moreover, the server 41 stores the average value of the unsprung displacement z1 corresponding to a plurality of second sample points P2 within the dotted line Gr4 in the corresponding storage area as the partition unsprung displacement Z1 of the partition Gd determined by Aj(X7, Y6).

[0129] It should be noted that when the partition unsprung displacement Z1 has already been stored in the storage area corresponding to the partition Gd at the time point when the partition unsprung displacement Z1 is newly calculated for the partition Gd, the server 41 updates the partition unsprung displacement Z1 for the partition Gd based on both the stored partition unsprung displacement Z1 and the newly obtained partition unsprung displacement Z1 (or unsprung displacement z1) for the partition Gd.

[0130] In this way, the server 41 can reduce the number of partitions Gd for which the unsprung displacement z1 is not obtained. Moreover, the server 41 can increase the number of "unsprung displacements z1 that can be used for the generation of data for the road surface information map 42a" for one partition Gd. Therefore, the server 41 can efficiently create a highly accurate road surface information map 42a.

[0131] <Specific operations>

[0132] Whenever a specified time has elapsed (i.e., whenever the travel data for the target section is sent), the CPU of the server 41 executes the routine shown in the flowchart of Figure 5 Therefore, when a specified timing is reached, the CPU starts processing from step 500 of Figure 5 and sequentially executes the processes of steps 505 to 515 described below, and then proceeds to step 520.

[0133] Step 505: The CPU acquires the travel data for the target section (the target section sensed data and the target section position information data) and the target section vehicle speed V from the in-vehicle device 20 (vehicle 10). The target section sensed data includes the target section sprung up-and-down acceleration data and the target section up-and-down stroke data.

[0134] Step 510: The CPU generates the target section unsprung displacement data based on the target section sensed data.

[0135] Step 515: The CPU obtains the positions corresponding to the unsprung displacements z1 of the target section unsprung displacement data by performing data interpolation processing on the target section position information data. Then, the CPU groups the "unsprung displacement z1 of the target section unsprung displacement data and the position of the target section position information data" at the same time (i.e., synchronizes these data in time). In other words, the CPU acquires the unsprung displacement z1 included in the target section unsprung displacement data and the position (position information) at which the unsprung displacement z1 is obtained (i.e., the group of multiple unsprung displacements z1 and the sampling positions of the unsprung displacement z1).

[0136] Note that, different from this example, when the sampling time interval ΔTB of the under-spring displacement data in the target section is longer than the sampling time interval ΔTP of the position information data in the target section, the CPU obtains the under-spring displacement z1 corresponding to each position of the position information data in the target section by performing data interpolation processing on the under-spring displacement data in the target section in step 515.

[0137] When entering step 520, the CPU determines whether the sampling time interval ΔTP of the position information data in the target section is equal to or less than a specified time.

[0138] When the sampling time interval ΔTP of the position information data in the target section is longer than the specified time, there is a high possibility that the interpolated position information in step 515 is incorrect. Therefore, in this case, the CPU determines "No" in step 520 and enters step 595 to temporarily end this routine.

[0139] When the sampling time interval ΔTP of the position information data in the target section is equal to or less than the specified time, the CPU determines "Yes" in step 520, executes the processing of step 525 described below, and then enters step 530.

[0140] Step 525: The CPU obtains the first sampling distance d1 by multiplying the vehicle speed V in the target section by the sampling time interval ΔTB of the under-spring displacement data in the target section.

[0141] Note that, different from this example, when the sampling time interval ΔTB of the under-spring displacement data in the target section is longer than the sampling time interval ΔTP of the position information data in the target section, the CPU obtains the first sampling distance d1 by multiplying the vehicle speed V in the target section by the sampling time interval ΔTP of the position information data in the target section in step 525.

[0142] When entering step 530, the CPU determines whether the first sampling distance d1 is longer than the first threshold distance dth1.

[0143] When the first sampling distance d1 is longer than the first threshold distance dth1, the CPU determines "Yes" in step 530, executes the processing of step 535 described below, and then enters step 540.

[0144] Step 535: The CPU resamples the object interval unsprung displacement data and the interpolated object interval position information data. That is, the CPU calculates the unsprung displacement z1 and the position (resampled sampling position) for each of the above-mentioned second sampling distances d2 (i.e., the sampling positions after resampling). Specifically, the CPU resamples in such a way that the sampling positions for each second sampling distance d2 are present in the resampled interpolated object interval position information data, and each corresponding unsprung displacement z1 for the sampling positions of each second sampling distance d2 is present in the resampled object interval unsprung displacement data. Then, the CPU obtains (determines) a group of multiple unsprung displacements z1 and the sampling positions of the unsprung displacements z1 from the resampled data.

[0145] When the first sampling distance d1 is less than or equal to the first threshold distance dth1, the necessity of resampling is low. Therefore, in this case, the CPU determines "No" in step 530 and directly proceeds to step 540. It should be noted that in this case, the group of multiple unsprung displacements z1 and the sampling positions of the unsprung displacements z1 obtained in step 515 are used for the map update processing routine in step 540.

[0146] When entering step 540, the CPU performs Figure 6 the map update processing routine shown. More specifically, when entering step 540, the CPU enters step 605 via Figure 6 step 600. When entering step 605, the CPU selects an arbitrary unselected sampling position from the sampling positions obtained for the object interval ARj (i.e., the sampling positions obtained in step 515 or step 535). After that, the CPU executes the processing of steps 610 to 630 described below, and then proceeds to step 635.

[0147] Step 610: The CPU determines the partition Gd corresponding to the selected sampling position based on the selected sampling position.

[0148] Step 615: The CPU sets the unsprung displacement z1 of the selected sampling position as "variable Znow", and sets the value of "count Nnew" at the current time point of the partition Gd determined in step 610 as "count Nold". Moreover, the CPU sets the partition unsprung displacement Znew at the current time point corresponding to the partition Gd determined in step 610 as "variable Zold". It should be noted that as described above, when the storage area corresponding to the determined partition Gd is in the initial state, the initial value of the partition unsprung displacement Z1 is stored in this storage area, and "0" is stored as the value of "count Nnew".

[0149] Step 620: The CPU calculates the value of "variable Znew" by the following formula (8).

[0150] Znew = {Znow + (Zold × Nold)} ÷ (Nold + 1)……(8)

[0151] That is, the sum of the CPU-computed variable Znow (the unsprung displacement z1 at the selected sampling position) and the value obtained by multiplying the variable Zold by the "count Nold". Here, the variable Znow is equal to the unsprung displacement z1 at the selected sampling position. Here, the variable Zold is equal to the unsprung displacement Z1 at the current time point of the determined partition Gd. Here, the value of the "count Nold" is equal to the value of the "count Nnew" at the current time point stored in the storage area corresponding to the determined partition Gd. Moreover, the CPU calculates the value of the "variable Znew" by dividing the calculated sum by the value obtained by incrementing the value of the "count Nold" (the value of the "count Nnew" at the current time point stored in the storage area corresponding to the determined partition Gd) by 1. Thus, the CPU calculates the average value (the value of the "variable Znew") of the unsprung displacement z1 used in the setting (calculation) of the unsprung displacement Z1 at the current time point and the unsprung displacement z1 at the selected sampling position.

[0152] Step 625: The CPU stores the calculated value of the "variable Znew" in the storage area corresponding to the partition Gd determined in Step 610 as the unsprung displacement Z1 of the partition.

[0153] Step 630: The CPU increments the value of the "count Nnew" stored in the storage area corresponding to the partition Gd determined in Step 610 by "1".

[0154] When entering Step 635, the CPU determines whether all the sampling positions obtained for the object interval ARj in the current operation have been selected.

[0155] In the case where not all the sampling positions obtained for the object interval ARj have been selected, the CPU determines "No" in Step 635 and returns to Step 605 to select the unselected sampling position. In contrast, in the case where all the sampling positions for the object interval ARj have been selected, the CPU determines "Yes" in Step 635 and enters Figure 5 Step 595, temporarily ending Figure 5 the routine.

[0156] As described above, the cloud CL1 can efficiently create a highly accurate road surface information map 42a.

[0157] <<Second Embodiment>>

[0158] The predictive damping control system of the road surface information production device (Cloud CL1) including the second embodiment of the present invention differs from the predictive damping control system of the first embodiment only in the following points.

[0159] · The road surface information production device calculates a first sampling distance d1 based on the longer sampling time interval among the sampling time interval ΔTP of the object section position information data and the sampling time interval ΔTB of the object section unsprung displacement data and the vehicle speed.

[0160] · The road surface information production device obtains a plurality of sets of sampling positions of each second sampling distance d2 and the unsprung displacement z1 of the sampling positions by resampling each of the object section position information data and the object section unsprung displacement data.

[0161] The following will be described centering on these differences.

[0162] <Specific operations>

[0163] Whenever a specified time has elapsed, the CPU executes routines in place of Figure 5 and Figure 7 shown in Figure 6 shown in. Figure 7 The routine of Figure 5 differs from the routine of

[0164] only in the following points.

[0165] · Step 515 is replaced by step 705, step 525 is replaced by step 710, and step 535 is replaced by step 715.

[0166] The following will be described centering on these differences. It should be noted that Figure 6 the routine shown in

[0167] has already been described, so its description will be omitted.

[0168] When entering step 705, the CPU synchronizes the object section position information data and the object section unsprung displacement data in terms of time.When entering step 710, the CPU calculates the first sampling distance d1 using the longer sampling time interval between the sampling time interval ΔTP of the object interval position information data and the sampling time interval ΔTB of the object interval unsprung displacement data. It should be noted that in this example, the sampling time interval ΔTP is longer than the sampling time interval ΔTB. Therefore, the CPU obtains the first sampling distance d1 by multiplying the vehicle speed V of the object interval by the sampling time interval ΔTP of the object interval position information data. Different from this example, when the sampling time interval ΔTB is longer than the sampling time interval ΔTP, the CPU obtains the first sampling distance d1 by multiplying the vehicle speed V of the object interval by the sampling time interval ΔTB of the object interval unsprung displacement data.

[0169] At the time point of executing the process of step 530, when the first sampling distance d1 is longer than the first threshold distance dth1, the CPU determines "yes" in step 530 and enters step 715.

[0170] When entering step 715, the CPU resamples each of the object interval unsprung displacement data and the object interval position information data. Specifically, the CPU resamples in such a way that the sampling position of each second sampling distance d2 exists in the resampled object interval position information data, and the unsprung displacement z1 corresponding to each sampling position of each second sampling distance d2 exists in the resampled object interval unsprung displacement data. Then, the CPU obtains (determines) a group of multiple unsprung displacements z1 and the sampling positions of the unsprung displacements z1 from the resampled data.

[0171] At the time point of executing the process of step 530, when the first sampling distance d1 is less than or equal to the first threshold distance dth1, the CPU determines "no" in step 530 and enters step 720.

[0172] When entering step 720, the CPU performs data interpolation processing on the object interval position information data in such a way that the detection object position (position information) exists at the sampling moment of the object interval unsprung displacement data. Then, the CPU obtains (determines) a group of multiple unsprung displacements z1 and the sampling positions (position information) of the unsprung displacements z1 from the object interval unsprung displacement data and the object interval position information data after the interpolation processing. It should be noted that different from this example, when the sampling time interval ΔTB is longer than the sampling time interval ΔTP, the CPU performs the following processing in step 720. The CPU performs data interpolation processing on the object interval unsprung displacement data in such a way that the unsprung displacement z1 exists at the sampling moment of the object interval position information data. Then, the CPU obtains (determines) a group of multiple unsprung displacements z1 and the sampling positions (position information) of the unsprung displacements z1 from the object interval unsprung displacement data after the interpolation processing and the object interval position information data.

[0173] It should be noted that it is also possible to set it so as not to perform data interpolation processing, and obtain (determine) a group of multiple unsprung displacements z1 and the sampling positions (position information) of the unsprung displacement z1 from the unsprung displacement data and the position information data in the target section.

[0174] The present invention is not limited to the above-described embodiments, and various modifications can be adopted within the scope of the present invention.

[0175] In the above first embodiment, the CPU may also execute Figure 8 the routine shown to replace Figure 5 the routine. Figure 8 The routine shown only differs from Figure 5 the routine in that step 530 of Figure 5 is replaced by step 810 described below.

[0176] Step 810: The CPU determines whether the first sampling distance d1 is longer than the first threshold distance dth1 or is less than or equal to the second threshold distance dth2. It should be noted that the second threshold distance dth2 is set to a distance shorter than the second sampling distance d2.

[0177] When the first sampling distance d1 is longer than the first threshold distance dth1 or is less than or equal to the second threshold distance dth2, the CPU determines "yes" in step 810 and proceeds to step 535 to perform the data processing (resampling) of step 535 already described. After that, the CPU proceeds to step 540. When the first sampling distance d1 is longer than the second threshold distance dth2 and less than or equal to the first threshold distance dth1, the CPU determines "no" in step 810 and directly proceeds to step 540.

[0178] When the first sampling distance d1 becomes less than or equal to the second threshold distance dth2 due to the decrease in the vehicle speed V in the target section, the number of unsprung displacements z1 obtained for one partition Gd will increase considerably. In this case, the partition unsprung displacement Z1 of the partition Gd becomes a value that reflects the unsprung displacement z1 obtained when the vehicle speed V in the target section is slow to an excessive degree. Such a partition unsprung displacement Z1 becomes a value corresponding to a vehicle speed region that is considerably deviated from the typical vehicle speed region for predictive vibration damping control, and thus is not preferred.

[0179] In contrast, when using Figure 8In a modified example of the routine, when the first sampling distance d1 is equal to or less than the second threshold distance dth2, the sprung displacement data in the target section and the position information data in the target section are also resampled. That is, in the sprung displacement data in the target section and the position information data in the target section, resampling is performed in such a way that the sprung displacement z1 and the sampling positions exist at each second sampling distance d2. The second sampling distance d2 in this case is longer than the first sampling distance d1. Therefore, the number of the sprung displacements z1 obtained for one partition Gd is reduced. As a result, this modified example can reduce the possibility that the sprung displacement z1 obtained when the vehicle speed V in the target section is slow is greatly reflected in the partition sprung displacement Z1 stored in the storage area corresponding to the partition Gd.

[0180] In the above first embodiment, the CPU may also execute a routine (not shown) that is different only in that step 530 is omitted Figure 5 instead of the Figure 5 routine. In this case, after the processing in step 525, the CPU proceeds to step 535, and thus resampling is always performed regardless of the first sampling distance d1.

[0181] In the above second embodiment, the CPU may also execute a routine (not shown) that is different only in that step 530 is replaced by the already described step 810 Figure 7 instead of the Figure 7 routine. In the above second embodiment, the CPU may also execute a routine (not shown) that is different only in that step 530 and step 720 are omitted Figure 7 instead of the Figure 7 routine.

[0182] In the above embodiments, the road surface displacement correlation value is the sprung displacement z1, but the road surface displacement correlation value may also be the road surface displacement z0. In this case, the partition road surface displacement correlation value is the partition road surface displacement Z0 calculated based on the road surface displacement z0 of the road portion corresponding to each partition Gd. In this case, the target section sensing data is time series data of the up-and-down displacement of the road surface (i.e., the road surface displacement z0) acquired by the foresight sensor 33 when the vehicle 10 travels in the target section. After performing data processing (BPF processing) on the target section sensing data as needed, the server 41 acquires the target section sensing data as time series data of the road surface displacement z0.

[0183] Moreover, when the road surface displacement correlation value is the road surface displacement z0, it can also be assumed that the in-vehicle device 20 includes a laser displacement sensor (not shown) provided at a specified position of the vehicle 10. The laser displacement sensor detects the vertical distance of the road surface between the vehicle body 10a (laser displacement sensor) of the vehicle 10 and the road surface (hereinafter referred to as "the vertical relative displacement between the vehicle body 10a and the road surface"), and generates a signal representing the vertical relative displacement between the vehicle body 10a and the road surface. The ECU 30 acquires, from the laser displacement sensor, a signal representing the vertical relative displacement between the vehicle body 10a and the road surface every time a certain sampling time elapses.

[0184] In this case, the target section sensing data is time-series data of the vertical relative displacement between the vehicle body 10a and the road surface and time-series data of the vertical acceleration above the spring acquired by the laser displacement sensor when the vehicle 10 travels in the target section. The server 41 generates time-series data of the road surface displacement z0 by performing data processing on the target section sensing data using offline processing.

[0185] In each of the above-described embodiments, it can also be assumed that the in-vehicle device 20 includes a sub-spring acceleration sensor (not shown). In this case, it can also be assumed that the cloud CL1 generates time-series data of the sub-spring displacement z1 by performing data processing (performing second-order time integration processing and BPF processing) on the time-series data of the sub-spring acceleration detected by the sub-spring acceleration sensor in an offline processing manner.

[0186] In each of the above-described embodiments, it can also be assumed that the cloud CL1 performs processing for generating (estimating) time-series data of the road surface displacement z0 or the sub-spring displacement z1 using an observer based on at least one of the time-series data of the sensor values acquired by the road surface correlation information sensor RS1.

[0187] In each of the above-described embodiments, it can also be assumed that a road surface information creation device having the same function as the cloud CL1 is mounted on the vehicle 10, and the road surface information map 42a is created by this road surface information creation device.

[0188] In each of the above-described embodiments, the position information acquisition device 35 can also determine the current position of the vehicle 10 as follows. That is, the position information acquisition device 35 includes a LiDAR (laser radar), a camera sensor, etc., and uses at least one of them to detect a point group of feature points such as the road shape and structures around the vehicle 10. The position information acquisition device 35 determines the current position of the vehicle 10 based on the detected point group of feature points and a three-dimensional map (see Japanese Patent Laid-Open No. 2016-192028 and Japanese Patent Laid-Open No. 2020-16541, etc.).

Claims

1. A road surface information production device, comprising: A storage device having a road surface information map, in which a virtual area corresponding to a specified section of a road is divided into a plurality of partitions, and partition road surface displacement correlation values related to the up-and-down displacement of the road surface corresponding to each of the plurality of partitions are stored in each storage area set to correspond to each of the partitions; and An information processing device that stores the partition road surface displacement correlation values in the storage areas of the road surface information map, The information processing device is configured to: Obtain first data from a vehicle through communication, the first data including: When the vehicle travels in the specified section, the sensor values detected by a road surface related information sensor provided in the vehicle and required to obtain the partition road surface displacement correlation values, and the time when the sensor values are detected; and when the vehicle travels in the specified section, the position information related to the position of the vehicle obtained by a position information acquisition device provided in the vehicle and the time when the position information is obtained, Based on the first data, second data is obtained, the second data including time series data for obtaining a data set, the data set including a set of a plurality of road surface displacement correlation values associated with the up-and-down displacement of the road surface and sampling positions that are the detection positions of the road surface displacement correlation values, The data set is obtained from the second data, A first sampling distance corresponding to the distance between two adjacent sampling positions in the data set is calculated, When the first sampling distance is longer than a first threshold distance, the data set is re-obtained from the data obtained by resampling the second data. In this resampling, interpolation processing is performed such that the distance between each of a plurality of adjacent two sampling positions becomes equal to or less than the first threshold distance and there is a road surface displacement correlation value corresponding to each of the sampling positions, Using the data set, for each partition determined to be the partition to which the sampling position belongs among the plurality of partitions, a first average value representing the average of the road surface displacement correlation values of the sampling positions included in the determined partition is calculated, and the calculated first average value is stored in the storage area corresponding to the determined partition as the partition road surface displacement correlation value.

2. The road surface information production device according to claim 1, wherein The information processing device is configured to: Also obtain the vehicle speed of the vehicle when the vehicle travels in the specified section from the vehicle through the communication, The time series data of the road surface displacement correlation values and the time series data of the detection target positions of the road surface related information sensor are obtained from the first data as the second data, The first sampling distance is calculated by multiplying the vehicle speed by the longer sampling time interval among the sampling time intervals of the time series data of the road surface displacement correlation values and the sampling time intervals of the time series data of the detection target positions of the road surface related information sensor.

3. The road surface information production device according to claim 1, wherein The information processing device is configured to: The vehicle speed of the vehicle when traveling in the specified section is also obtained from the vehicle through the communication. Time series data of the road surface displacement correlation value and time series data of the detection object position of the road surface correlation information sensor are obtained from the first data. Interpolate one of the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor at the sampling time of the time series data with a shorter sampling time interval among the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor, so that the road surface displacement correlation value and the detection object position exist, and obtain data including the interpolated data as the interpolated time series data of the one party and the time series data of the other party of the time series data of the road surface displacement correlation value and the time series data of the detection object position of the road surface correlation information sensor as the second data. The first sampling distance is calculated by multiplying the vehicle speed by the sampling time interval of the time series data with a shorter sampling time interval.

4. The road surface information production device according to any one of claims 1 to 3, wherein The information processing device is configured to perform the resampling such that each of the distances between the plurality of adjacent two sampling positions becomes a certain second sampling distance that is equal to or less than the first threshold distance.

5. The road surface information production device according to claim 4, wherein The information processing device is configured to perform the resampling even when the first sampling distance is equal to or less than a second threshold distance that is set to be shorter than the second sampling distance.

6. The road surface information production device according to any one of claims 1 to 3, wherein The information processing device is configured to, when the storage area corresponding to the determined section already stores the section road surface displacement related value, newly store a second average value in the storage area corresponding to the determined section as the section road surface displacement related value, and the second average value represents the average of the road surface displacement correlation value of the sampling positions included in the determined section and the already stored section road surface displacement related value.

7. The road surface information production device according to any one of claims 1 to 3, wherein The road surface displacement correlation value is the unsprung vertical displacement representing the vertical displacement of the vehicle under the spring. The sensor value is the vertical acceleration of the vehicle above the spring and the vertical relative displacement between the above-spring and the below-spring, or the sensor value is the unsprung acceleration.

8. A vehicle control system includes a road surface information production device, a first vehicle, and a second vehicle that are configured to communicate with each other, wherein The road surface information production device includes: A storage device having a road surface information map in which a virtual area corresponding to a specified section of a road is divided into a plurality of sections, and section road surface displacement correlation values correlated with the vertical displacement of the road surface corresponding to each of the plurality of sections are stored in respective storage areas set corresponding to the respective sections; and an information processing device that stores the section road surface displacement correlation values in the storage areas of the road surface information map, wherein the information processing device is configured to: acquire first data from the first vehicle through communication, the first data including: sensor values detected by a road surface related information sensor of the first vehicle when the first vehicle travels in the specified section and required for obtaining the section road surface displacement correlation values, and the time when the sensor values are detected; and position information correlated with the position of the first vehicle acquired by a position information acquisition device of the first vehicle when the first vehicle travels in the specified section, and the time when the position information is acquired, acquire second data based on the first data, the second data including time series data for acquiring a data set, the data set including a group of a plurality of road surface displacement correlation values associated with the vertical displacement of the road surface and sampling positions as the detection positions of the road surface displacement correlation values, acquire the data set from the second data, calculate a first sampling distance corresponding to the distance between two adjacent sampling positions of the data set, in a case where the first sampling distance is longer than a first threshold distance, re-acquire the data set from data obtained by resampling the second data, in the resampling, interpolation processing is performed such that the distance between each of a plurality of adjacent two sampling positions becomes equal to or less than the first threshold distance and there is a road surface displacement correlation value corresponding to each of the sampling positions, use the data set to calculate, for each of the plurality of sections determined to be the sections to which the sampling positions belong, a first average value representing the average of the road surface displacement correlation values of the sampling positions included in the determined sections, and store the calculated first average value in the storage area corresponding to the determined section as the section road surface displacement correlation value, at least one of the first vehicle and the second vehicle is configured to: receive control data for vehicle control from the road surface information production device, the control data including position information of the sections based on the road surface information map and the section road surface displacement correlation values associated with the position information.

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