Wind data estimating apparatus

A wind data estimating apparatus includes one or more processors configured to collect vehicle information including a first acceleration, an amount of driving operation performed by a driver of a vehicle, and position information, which are obtained by sensors installed in the vehicle; classify the collected vehicle information by an area of a plurality of areas according to the position information; and estimate a wind velocity and a wind direction for the area and for a time range when the vehicle information is obtained, on the basis of an acceleration obtained from subtracting a second acceleration caused by the amount of driving operation from the first acceleration included in the vehicle information classified by the area.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a wind data estimating apparatus.

2. Description of the Related Art

According to a related art, a wind detecting apparatus device that detects presence or absence of wind received by a mobile body includes a unit calculating the absolute value of a yaw rate, the absolute value of a roll angle, the absolute value of a vertical acceleration, and the absolute value of a lateral acceleration; and a unit determining that a crosswind is present when all of the calculated absolute values exceed corresponding predetermined threshold values (for example, see Japanese Laid-Open Patent Application No. 2015-093618).

SUMMARY OF THE INVENTION

According to an embodiment, a wind data estimating apparatus includes one or more processors configured to collect vehicle information including a first acceleration, an amount of driving operation performed by a driver of a vehicle, and position information, which are detected by sensors installed in the vehicle; classify the collected vehicle information by an area of a plurality of areas according to the position information; and estimate a wind velocity and a wind direction for the area and for a time range when the vehicle information is obtained, on the basis of an acceleration obtained from subtracting a second acceleration caused by the amount of driving operation from the first acceleration included in the vehicle information classified by the area.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The wind detecting apparatus according to the related art uses the absolute value of a yaw rate, the absolute value of a roll angle, the absolute value of a vertical acceleration, and the absolute value of a lateral acceleration calculated from detection values of the wind detecting apparatus installed in a vehicle to determine presence of a crosswind. However, the wind detecting apparatus cannot quantify a wind velocity and a wind direction. Data of a wind velocity and a wind direction can be used for an analysis for an influence of the wind on the vehicle in more detail.

An object of an embodiment is to provide a wind data estimating apparatus capable of estimating data concerning wind received by a vehicle.

A wind data estimating apparatus according to the embodiment of the present invention includes one or more processors configured to collect vehicle intonation including a first acceleration, an amount of driving operation performed by a driver of a vehicle, and position information, which are obtained by sensors installed in the vehicle; classify the collected vehicle information by an area of a plurality of areas according to the position information; and estimate a wind velocity and a wind direction for the area and for a time range when the vehicle information is obtained, on the basis of an acceleration obtained from subtracting a second acceleration caused by the amount of driving operation from the first acceleration included in the vehicle information classified by the area.

Thus, a wind velocity and a wind direction can be estimated on the basis of an acceleration obtained by subtracting an acceleration (a second acceleration) caused by a driving operation from an acceleration (a first acceleration) of a vehicle detected by a sensor.

Thus, it is possible to provide a wind data estimating apparatus100capable of estimating data concerning wind received by a vehicle.

In the wind data estimating apparatus according to the embodiment of the present invention, the amount of driving operation performed by the driver of the vehicle may be an accelerator position, a brake operation amount (an amount of brake operation), a vehicle velocity, or a steering angle detected by a corresponding sensor of the sensors installed in the vehicle.

Thus, it is possible to eliminate an influence of a second acceleration occurring in a vehicle due to an accelerator position, a brake operation amount, a vehicle velocity, or a steering angle.

Thus, it is possible to provide a wind data estimating apparatus capable of estimating wind received by a vehicle taking into account of a second acceleration occurring in a vehicle due to an accelerator position, a brake operation amount, a vehicle velocity, or a steering angle.

In the above-mentioned wind data estimating apparatus according to the embodiment of the present invention, the one or more processors may be configured to estimate the wind velocity and the wind direction of the area and the time range on the basis of an acceleration obtained from subtracting, from the first acceleration, the second acceleration and a third acceleration of the vehicle caused by a cross-grade or a grade of a road corresponding to the position information.

Thus, it is possible to eliminate an influence of a third acceleration occurring in a vehicle due the cross-grade or the grade of a road.

Thus, it is possible to provide a wind data estimating apparatus capable of estimating data concerning wind received by a vehicle taking into account of a third acceleration that occurs in the vehicle due to the cross-grade or the grade of a road.

In the wind data estimation apparatus according to the embodiment of the present invention, the one or more processors may be configured to collect respective sets of vehicle information from a plurality of vehicles; classify the collected sets of vehicle information by respective areas from among the plurality of areas in accordance with corresponding sets of position information; and estimate the wind velocity and the wind direction of the area on the basis of a plurality of wind velocities and a plurality of wind directions estimated from corresponding sets of vehicle information obtained during the same time range from among a plurality of sets of vehicle information classified by the same area.

Thus, a wind velocity and a wind direction can be estimated on the basis of vehicle information of a plurality of vehicles, allowing for more accurate estimation.

Thus, by estimating a wind velocity and a wind direction on the basis of vehicle information of a plurality of vehicles, a wind data estimating apparatus100can be provided that can estimate data concerning wind received by a vehicle with higher accuracy.

In the wind data estimating apparatus according to the embodiment of the present invention, the one or more processors may be configured to estimate the plurality of wind velocities and the plurality of wind directions from the corresponding sets of vehicle information of the same area and the same time range, on the basis of accelerations obtained from subtracting, from first accelerations, second accelerations and third accelerations that occur in the vehicles due to cross-grades or grades of roads associated with corresponding sets of position information, respectively.

Thus, wind velocities and wind directions can be estimated on the basis of vehicle information of a plurality of vehicles, taking into account of third accelerations that occur in the vehicles due to the cross-grades or grades of roads.

Thus, it is possible to provide a wind data estimating apparatus that can estimate wind velocities and wind directions on the basis of vehicle information of a plurality of vehicles taking into account of third accelerations that occur in the vehicle due to the cross-grades or the grades of roads, thereby estimating data concerning wind received by a vehicle more accurately.

In the wind data estimating apparatus according to the embodiment of the present invention, the one or more processors may be configured to obtain, from the estimated wind velocity and wind direction and a vehicle velocity of the vehicle, a wind velocity and a wind direction in a ground coordinate system with respect to a traveling direction of the vehicle.

Thus, it is possible to obtain estimates of a wind velocity and a wind direction expressed as a wind velocity and a wind direction in a ground coordinate system.

Thus, it is possible to provide a wind data estimating apparatus that can estimate data concerning wind received by a vehicle with higher accuracy by using estimates of a wind velocity and a wind direction in a ground coordinate system.

Thus, a wind data estimating apparatus capable of estimating data concerning wind received by a vehicle can be provided.

Hereinafter, an embodiment of a wind data estimating apparatus according to the present invention will be described.

EMBODIMENT

FIG. 1illustrates an example of a configuration of a wind data estimating system1including a wind data estimating apparatus100according to an embodiment.

The wind data estimating system1includes a wind data estimating apparatus100of a center10and an in-vehicle network system200installed in a vehicle20. The center10stores data indicating an identifier of the vehicle20.

The in-vehicle network system200and the center10can perform communication together through a predetermined communication network NW1that may be a mobile communication network or the Internet, i.e., a wireless communication network connected to a plurality of base stations at respective ends. InFIG. 1, for convenience, the single in-vehicle network system200is illustrated. However, it is possible that in-vehicle network systems200of a plurality of vehicles20perform communication with the center10through the network NW1.

The vehicle20is, for example, a HV (Hybrid Vehicle), a PHV (Plug-in Hybrid Vehicle), an EV (Electric Vehicle), a gasoline vehicle, a diesel vehicle, or the like, and includes the in-vehicle network system200.

The in-vehicle network system200has an information processing function and a communication function. The in-vehicle network system200transmits vehicle information of the vehicle20to the center10. Vehicle information includes data indicating at least an accelerator position, a vehicle velocity, accelerations, a steering angle, a yaw rate, a brake operation amount, and a position of a vehicle20.

Data indicating a position is data indicating the current position of a vehicle20at a certain point of time and is provided by a GPS (Global Positioning System). Time information indicating a time at which vehicle information is obtained is associated with the vehicle information.

Vehicle information is stored in a data area such as a frame of data that is transmitted between a DCM203(seeFIG. 3) and the center10.

The center10includes one or more computers (information processing apparatuses). The center10is a data center that receives vehicle information from respective in-vehicle network systems200of a plurality of vehicles20. Each vehicle20is assigned a unique ID (a vehicle ID) and vehicle information transmitted from each vehicle20to the center10is associated with the corresponding vehicle ID.

The center10includes a wind data estimating apparatus100. Below, a configuration where the wind data estimating apparatus100corresponds to some of functions of the center10will be described. In addition to the functions of the wind data estimating apparatus100, the center10has functions to provide traffic information and route guidance or to provide services through various applications to the in-vehicle network system200of the vehicles20, for example.

The wind data estimating apparatus100estimates wind data such as a wind direction and a wind velocity of a predetermined time range for an area where a plurality of vehicles20travel, on the basis of vehicle information transmitted from the in-vehicle network systems200of the plurality of vehicles20and received by the center10.

The configuration where the wind data estimating apparatus100corresponds to some of the functions of the center10will now be described. However, such a configuration need not be applied, and, for example, the wind data estimating apparatus100may be provided as a dedicated center for estimating wind data.

FIG. 2illustrates an example of a hardware configuration of the center10according to the embodiment. The center10ofFIG. 2includes a drive device11A, an auxiliary storage device11C, a memory device11D, a CPU11E, and an interface device11F, each of these devices being interconnected by a bus B.

A program that implements processing of the center10is provided by a recording medium11B, such as a CD-ROM. After the recording medium11B storing the program is set in the drive device11A, the program is installed from the recording medium11B to the auxiliary storage device11C via the drive device11A. However, it is not necessary to install the program from the recording medium11B; the program may be downloaded from another computer via the network. The auxiliary storage device11C stores the installed program and stores necessary files, data, and so forth.

The memory device11D reads the program from the auxiliary storage device11C and stores the program, in response to receiving a program startup instruction. The CPU11E executes the functions of the center10according to the program stored in the memory device11D. The interface device11F is used to connect to a network.

A recording medium that stores a wind data estimation program may be any one of the recording medium11B, the auxiliary storage device11C, and the memory device11D. The recording medium11B, the auxiliary storage device11C, and the memory device11D are each non-transitory recording media.

As the plurality of ECUs204,FIG. 3illustrates an engine ECU204A, a VSC (Vehicle Stability Control)-ECU204B, a brake ECU204C, and a navigation ECU204D from among various ECUs installed in the vehicle20.

The in-vehicle network system200also includes other ECUs (not illustrated) in addition to the engine ECU204A, the VSC-ECU204B, the brake ECU204C, and the navigation ECU204D. When the engine ECU204A, the VSC-ECU204B, the brake ECU204C, and the navigation ECU204D are not particularly specifically distinguished thereamong, they will be simply referred to as ECUs204.

The engine ECU204A is connected with a throttle sensor205A and a vehicle velocity sensor205B, the VSC-ECU204B is connected with an acceleration sensor205C and a steering-angle sensor205D, and the brake ECU204C is connected with an oil-pressure sensor205E. The GPS sensor205F is connected to the navigation ECU204D.

A vehicle20includes various sensors (not illustrated) in addition to the throttle sensor205A, the vehicle velocity sensor205B, the acceleration sensor205C, the steering-angle sensor205D, the oil-pressure sensor205E, and the GPS sensor205F; the various sensors are each connected to any one of the ECUs204or directly connected to a bus (any one of the buses202A,202B, and202C).

The above-described connection relationships where, as illustrated inFIG. 3, the throttle sensor205A and the vehicle velocity sensor205B are connected to the engine ECU204A, the acceleration sensor205C and the steering-angle sensor205D are connected to the VSC-ECU204B, the oil-pressure sensor205E is connected to the brake ECU204C, and the GPS sensor205F is connected to the navigation ECU204D, need not be applied as they are. Here, the case having the connection relationships illustrated inFIG. 3will be described.

Each of the CGW-ECU201and the plurality of ECUs204is implemented by a computer including, for example, a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read-Only Memory), a clock generator, an I/O interface, a communication interface, a transmitting and receiving unit, an internal bus, and so forth.

The in-vehicle network system200is installed in the vehicle20, where the ECUs204perform communication thereamong. The in-vehicle network system200obtains vehicle information, transmitted through buses202A,202B, and202C at a predetermined sampling rate, and transmits the vehicle information to the center10via the DCM203every predetermined time interval (e.g., every 8 minutes). The predetermined sampling rate is, for example, 100 ms (milliseconds).

The CGW-ECU201relays vehicle information among the buses202A,202B, and202C.

The buses202A,202B, and202C are used for data communication according to an Ethernet (registered trademark) protocol. The buses202A,202B, and202C may also be buses for data communication according to a CAN (controller area network) protocol.

The DCM203is connected to the bus202A. The bus202B is connected to the engine ECU204A, the VSC-ECU204B, and the brake ECU204C. The bus202C is connected with the navigation ECU204D. The buses202A,202B, and202C may be connected with other ECUs and sensors (not illustrated) in addition to the DCM203, the engine ECU204A, the VSC-ECU204B, the brake ECU204C, and the navigation ECU204D.

The DCM203is an example of an in-vehicle wireless communication device. For example, the DCM203performs wireless communication via a communication line such as a communication line of 3G (Third Generation), 4G (Fourth Generation), LTE (Long Term Evolution), or 5G (Fifth Generation). The DCM203includes a communication terminal and a dedicated ECU. Accordingly, the DCM203may be also treated as a type of ECU.

An ID (identification) is allocated to each ECU204. Which one of the ECUs204is a destination of data transmitted is determined from an ID included in the data.

The engine ECU204A controls the output of an engine on the basis of the accelerator position and the vehicle velocity detected by the throttle sensor205A and the vehicle velocity sensor205B, respectively. In a case of a HV (Hybrid Vehicle) or a case of an EV (Electric Vehicle), a HV-ECU controlling the output of the engine and controlling the output of the driving motor, or an EV-ECU controlling the output of the driving motor may be used instead of the engine ECU204A. In this regard, the accelerator position may be detected by an accelerator position sensor.

The VSC-ECU204B performs control to stabilize the behavior of a vehicle20on the basis of the accelerations (the forward/backward acceleration and the lateral acceleration) and the yaw rate of the vehicle20detected by the acceleration sensor205C and the steering angle detected by the steering-angle sensor205D. The acceleration sensor205C is a three-axis sensor that detects the forward/backward acceleration, the lateral acceleration, and the yaw rate.

The brake ECU204C performs control to implement an ABS (Anti-lock Brake System) function and a VSC (Vehicle Stability Control) function on the basis of, for example, the oil pressure detected by the oil-pressure sensor205E provided in the master cylinder. The oil pressure detected by the oil-pressure sensor205E indicates the amount of brake operation.

The navigation ECU204D controls a navigation device installed in the interior of a vehicle20. The navigation ECU204D uses position information detected by the GPS sensor205F to detect the current position of the vehicle20, to search for a route to a destination, to provide route guidance, and so forth. A route search may be implemented also by the center10. In such a case, the center10may search for a route; thus obtained route information may be then transmitted to the in-vehicle network device200; and the navigation ECU204D may perform route guidance using the transmitted route information.

The navigation device has one or more display panels; the navigation ECU204D controls displays of the one or more display panels. The navigation ECU204D thus displays the position of the vehicle20, the route to the destination, and so forth, on the one or more display panels.

Data indicating the accelerator position, the vehicle velocity, the accelerations and the yaw rate, the steering angle, the oil pressure (i.e., the brake operation amount), and the position detected by the throttle sensor205A, the vehicle velocity sensor205B, the acceleration sensor205C, the steering-angle sensor205D, the oil-pressure sensor205E, and the GPS sensor205F, respectively, are used by the engine ECU204A, the VSC-ECU204B, the brake ECU204C, and the navigation ECU204D, and also are transmitted to various ECUs through the buses202A,202B,202C.

The data thus detected by the sensors is also used to estimate wind data in the wind data estimating apparatus100. Details will be described later.

The DCM203transmits vehicle information including data indicating the accelerator position, the vehicle velocity, the accelerations, the steering angle, the yaw rate, the brake operation amount, and the position from among the data transmitted by the bus202A to the center10every predetermined time interval (e.g., every 8 minutes).

FIG. 4illustrates a configuration of the wind data estimating apparatus100.FIGS. 5A and 5Billustrate a data structure of a vehicle information database.

The wind data estimating apparatus100includes a main control unit110, an information collecting unit120, an information classifying unit130, an estimating unit140, a communication unit150, and a memory160. The main control unit110, the information collecting unit120, the information classifying unit130, the estimating unit140, and the communication unit150are illustrated as functional blocks of programs (functions) executed by the wind data estimating apparatus100. Also the memory160is functionally illustrated inFIG. 4.

The main control unit110performs overall control of processing performed by the wind data estimating apparatus100. The main control unit110performs processing other than processing performed by the information collecting unit120, the information classifying unit130, the estimating unit140, and the communication unit150.

The information collecting unit120obtains vehicle information including data indicating the accelerator position, the vehicle velocity, the accelerations, the steering angle, the yaw rate, the brake operation amount, and the position from the in-vehicle network systems200of vehicles20via the communication unit150every predetermined time interval (e.g., every 8 minutes). Vehicle information is obtained at a predetermined sampling rate (e.g., at 100 ms) in each of the vehicles20.

The information classifying unit130classifies the vehicle information of the vehicles20obtained through the information collecting unit120by predetermined areas and manages the vehicle information by classifying the vehicle information by time ranges. The predetermined areas are mesh-like areas each having a size of 100 m by 100 m, obtained from segmenting the whole area included in mapping data along the east-west direction and along the north-south direction. The whole area included in the mapping data is segmented and classified by the mesh-like areas each having the size of 100 m by 100 m; the respective areas are provided with unique identifiers.

The same time range means a time range that is the same among vehicles20; during the same time range, respective sets of vehicle information are obtained by the vehicles20. For example, the time axis is segmented from a standard time into one-minute time ranges; time points at which respective sets of vehicle information are obtained by the vehicles20are classified by corresponding time ranges, whereby it is possible to determine whether the respective sets of vehicle information have been obtained during the same time range.

The information classifying unit130identifies an area on the basis of data indicating a position included in vehicle information obtained by the information collecting unit120, and identifies a time range on the basis of time information indicating a time when the data indicating the position is obtained, thereby classifying the vehicle information by the area and by the time range and managing the vehicle information. Each set of vehicle information is associated with an area identifier and is stored in a vehicle information database (seeFIGS. 5A and 5B) of the memory160for each time range.

For example, as illustrated inFIGS. 5A and 5B, in the vehicle information database, sets of vehicle information obtained from a plurality of vehicles20are stored in association with areas and with time ranges for each vehicle ID. InFIGS. 5A and 5B, by a vehicle20having a vehicle ID 001, sets of vehicle information 001, 002, . . . , obtained during time ranges 1, 2, . . . , are obtained at an area 1. Vehicle information codes are assigned in an order starting from 001 for each time range. Similarly, sets of vehicle information are obtained by a vehicle20of a vehicle ID 002 and stored in association with areas and with time ranges. This is also applied to other vehicles20.

The estimating unit140estimates a wind velocity and a wind direction for a time range and an area on the basis of the accelerations, the yaw rates, the accelerator positions, the vehicle velocities, the steering angles, the brake operation amounts, and the data indicating the positions included in the plurality of sets of vehicle information concerning the time range and the area from among the plurality of sets of vehicle information classified by a plurality of areas and by a plurality of time ranges by the information classifying unit130. An actual method for estimating a wind velocity and a wind direction will be described later.

The communication unit150is a modem or the like that performs data communication with the DCMs203of in-vehicle network systems200. The communication unit150receives vehicle information from in-vehicle network systems200of a plurality of vehicles20, and transmits the received information to the information collecting unit120.

The memory160stores data and programs used for a wind velocity and wind direction estimation process, and stores data generated by the estimating unit140when the estimation process is performed. Data generated during such an estimation process is stored in a vehicle information database described above.

An estimation method for estimating a wind velocity and a wind direction will now be described. An estimation process for a wind velocity and a wind direction that will now be described is performed by the estimating unit140. Below, a method of estimating a wind velocity and a wind direction for a time range and an area on the basis of a plurality of sets of vehicle information concerning the time range and the area included in a vehicle information database by the estimating unit140will be described.

The estimating unit140estimates wind velocities and wind directions from data indicating the accelerations, the yaw rates, the accelerator positions, the vehicle velocities, the steering angles, the brake operation amounts, and the positions included in vehicle information, and estimates a wind velocity and a wind direction for a time range and an area by obtaining the averages of the estimated wind velocities and wind directions. The estimating unit140performs such a process using many sets of vehicle information.

For example, one area is a square of 100 meters by 100 meters, and one time range is a one-minute period out of every minute of every hour of a standard time. A wind velocity and a wind direction are estimated from each sample of 30 or more samples of vehicle information concerning one time range and one area; then a wind velocity and a wind direction for the one time range and the one area are estimated by calculating the average values of the estimated wind velocities and wind directions.

FIG. 6illustrates an acceleration a and a yaw rate ω of a vehicle20.FIG. 6illustrates a traveling direction of the vehicle20with an arrow. The vehicle20is indicated in a plan view; a coordinate system (a vehicle coordinate system) based on the vehicle20is indicated by a lowercase xy coordinate system. The x-axis corresponds to the forward and backward directions of the vehicle20; the backward direction of the vehicle20corresponds to the positive direction of the x-axis. Therefore, in the example ofFIG. 6, the traveling direction of the vehicle20is in the x-axis negative direction. The y-axis corresponds to the width directions of the vehicle20; the rightward direction with respect to the traveling direction of the vehicle corresponds to the positive direction of the y-axis.

ForFIG. 6, physical quantities and so forth will now be defined. GCdenotes the center of gravity of the vehicle20; GAdenotes the center of aerodynamic force (the yaw center) of the vehicle20. Below, VVdenotes the vehicle velocity of the vehicle20and therefore denotes a vector.

The vector a denotes the acceleration of the vehicle20. axdenotes the forward/backward component of the vector a; the backward direction corresponding to the positive direction. aydenotes the lateral component of the vector a; the right direction corresponds to the positive direction. The forward/backward acceleration axand the lateral acceleration ayare two axial accelerations detected by the acceleration sensor205C. ω denotes the yaw rate of the vehicle20detected by the acceleration sensor205C; the clockwise direction in a plan view of the vehicle20corresponds to the positive direction. The forward/backward acceleration axand the lateral acceleration ayare one example of a first acceleration.

Although not illustrated inFIG. 6, FVxdenotes a vector indicating the force exerted in a forward/backward direction of the vehicle20; the positive direction corresponds to the backward direction. FVydenotes a vector indicating the force exerted in a lateral direction of the vehicle20; the positive direction corresponds to the right direction. MVdenotes the moment (a vector quantity) generated in the vehicle20: the counterclockwise direction corresponds to the positive direction.

m denotes the mass of the vehicle20. I denotes the moment of inertia (a vector quantity) around the center of gravity GCof the vehicle20.

Although not illustrated inFIG. 6, Fuxdenotes a vector indicating the force exerted in a forward/backward direction of the vehicle20due to a driving operation; the backward direction correspond to the positive direction. Fuydenotes a vector indicating the force exerted in a lateral direction of the vehicle20due to a driving operation; the right direction corresponds to the positive direction. Mudenotes the moment (a vector quantity) exerted on the vehicle20due to a driving operation.

Although not illustrated inFIG. 6, FRxdenotes a vector indicating the force exerted in the forward/backward direction of the vehicle20due to the cant angle (the cross-grade) and the grade of the road surface on which the vehicle20runs; the backward direction corresponds to the positive direction. FRydenotes a vector indicating the force exerted in the lateral direction of the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs; right direction corresponds to the positive direction. MRdenotes the moment (a vector quantity) exerted on the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs.

Data of the cant angle and the grade of a road surface may be obtained as follows. For example, map data where cant angles and grades of road surfaces are associated with data of links (roads) may be used: the data of the cant angle and the grade corresponding to a desired link may be read to be used.

A vector and a moment (a vector quantity) indicating the force exerted on the vehicle20due to wind will now be expressed as follows. Fxdenotes a vector indicating the force exerted in the forward/backward direction as a result of the vehicle20receiving wind; the positive direction corresponds to the backward direction. Fydenotes a vector indicating the force exerted in the lateral direction as a result of the vehicle20receiving wind; the positive direction corresponds to the right direction. M denotes the moment (a vector quantity) exerted on the vehicle20as a result of the vehicle20receiving wind; the counterclockwise rotation direction corresponds to the positive direction.

Fx, Fy, and M can be expressed by the following equations (4) through (6), respectively.
Fx=FVx−Fux−FRx(4)
Fy=FVy−Fuy−FRy(5)
M=MV−Mu−MR(6)

The equations (4) through (6) can be used to obtain the force Fxexerted in the forward/backward direction as a result of the vehicle20receiving wind, the force Fyexerted in the lateral direction as a result of the vehicle20receiving wind, and the moment M exerted as a result of the vehicle20receiving wind.

Fxand Fycan be used to estimate a wind velocity and a wind direction of wind received by the vehicle20. An actual method for estimating a wind velocity and a wind direction from Fxand Fywill be described later. The moment M is used to remove vehicle information including an abnormality for a case where the abnormality such as an error is included in an acceleration a detected by the acceleration sensor205C. Details will be described below.

FIG. 7is a view where a motion of a vehicle20is assumed as a planar motion of a rigid body and a vehicle20is simplified as a front-and-rear-two-wheel model. α denotes the steering angle of the front wheel21F. lfdenotes the distance from the center of gravity GCof the vehicle20to the front wheel21F. lrdenotes the distance from the center of gravity GCof the vehicle20to the rear wheel21R.

From the planar kinetic equations of motion, the balance of the centrifugal force, and the balance of the yaw moments in the vehicle20, the force Fuyexerted in the lateral direction of the vehicle20due to a driving operation and the moment Muexerted on the vehicle20due to a driving operation can be expressed by the equations (7) and (8), respectively.
Fuy=m·a(VV,α)=m·VV·{A(VV)+δB(VV)/δt}·α(7)
Mu=I·δA(VV)/δt·α(8)

There, the lateral acceleration a(VV, α) of the vehicle20is expressed by
a(VV,α)=VV·{A(VV)+δB(VV)/δt}·α
as a function of the vehicle velocity VVand the steering angle α, where the vehicle velocity VVis a vector.

The functions A(VV) and B(VV) of the vehicle velocity VVare expressed by:
A(VV)=VV/{l−m·VV2·(lf·CPf−lr·CPr)/2·L·CPf·CPr}
B(VV)=(lr·Cpr−m·lf·VV2/2·L)/{L·CPr−m·(lfCPf−lr·CPr)·VV/2·L·CPf}

There, CPfand CPrdenote the cornering power of the front wheel and the cornering power of the rear wheel, respectively; L=lf+lr.

The vehicle velocity VVis a vector of the direction at the vehicle side slip angle β. Because the vehicle side slip angle β can be regarded as zero, the vehicle velocity VVcan be treated as a velocity (a scalar quantity) in the traveling direction of the vehicle20.

Where PAdenotes the accelerator position (the accelerator pedal operation amount) and PBdenotes the brake operation amount (brake pedal operation amount), the force Fuxexerted in the forward/backward direction of the vehicle20due to a driving operation of the vehicle20can be expressed as a function of the following equation (9).
Fux=C(PA,PB,VV,G)  (9)

The function C(PA, PB, VV, G) is a function that derives the force Fuxfrom the accelerator position PA, the brake operation amount PB, the vehicle velocity VV, and the total gear ratio of transmission G. Such a function may be determined as a function expressing the average response of the vehicle20with respect to an accelerator position PAand a brake operation amount PB. The average response may be obtained, for example, by using data obtained during development of vehicles20or by using a result obtained from an analysis of big data of vehicle information collected from a plurality of vehicles20by the center10.

The acceleration obtained from dividing C(PA, PB, VV, G) of the equation (9) by the mass m of the vehicle20(the acceleration of the vehicle20in the forward/backward direction due to a driving operation) and the acceleration a(VV, α) included in the equations (7) (the acceleration of the vehicle20in the lateral direction due to a driving operation) are one example of a second acceleration.

FIGS. 8A and 8Billustrate a vehicle20traveling on a road ST.

Concerning a road surface grade angle θG, the positive direction corresponds to the counterclockwise direction (a direction in which a vehicle20climbs) in view of the vehicle20from the right side. That is, as illustrated inFIG. 8A, when the vehicle20is viewed from the right side, a road surface grade angle θGdenotes the angle between the vertical direction and the z-axis and denotes the angle between the horizontal direction and the x-axis. Concerning a road surface cant angle θC, the counterclockwise direction when the vehicle20is viewed from the rear side corresponds to the positive direction. That is, as illustrated inFIG. 8B, a road surface cant angle θCdenotes the angle between the vertical direction and the z-axis when the vehicle20is viewed from the rear side and denotes the angle between the horizontal direction and the y-axis. The xyz coordinate system including the z-axis based on the vehicle20is a right-handed coordinate system.

By using a road surface grade angle θGand a road surface cant angle θ0, the forces FRxand FRyexerted in the forward/backward direction and the lateral direction of the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs and the moment MRexerted on the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs are expressed by the following equations (10) through (12).

In the equation (12), FRf(seeFIG. 7) denotes the lateral force exerted on the front tire21F due to the road surface cant; FRr(seeFIG. 7) denotes the lateral force exerted on the rear tire21R due to the road surface cant.
FRx=m·g·sin θG(10)
FRy=m·g·sin θC(11)
MR=I·δω/δt=lf·FRf−lr·FRr(12)

The accelerations g·sin θGand g·sin θCincluded in the equations (10) and (11) denote accelerations of the vehicle20due to the road surface grade and the road surface cant and are one example of a third acceleration.

FIG. 9illustrates a vector of wind received by a vehicle20. The ground coordinate system including the road surface on which the vehicle20runs is indicated by an uppercase XY coordinate system. The X-axis corresponds to the east-west direction; the east direction corresponds to the positive direction. The Y-axis corresponds to the north-south direction; the north direction corresponds to the positive direction.

VWGdenotes the ground-basis wind velocity (a vector) and has the wind velocity (a scalar quantity) indicated according to the ground coordinate system (the XY coordinate system of uppercase letters). A wind direction is indicated by the angle θ of the clockwise direction with respect to the Y-axis positive direction (the north direction). VWVdenotes the vehicle-basis wind velocity (a vector) and has the wind velocity (a scalar quantity) indicated according to the coordinate system (the xy coordinate system) of the vehicle20. VWVxdenotes the x-axis component of the vehicle-basis wind velocity; VWVydenotes the y-axis component of the vehicle-basis wind velocity.

It will now be assumed that the air density is ρ (kg/m3), the front projected area of a vehicle20is SF(m2), the side projected area of the vehicle20is SS(m2), the front air resistance coefficient of the vehicle20is CDF, the side air resistance coefficient of the vehicle20is CDS, and the distance from the center of the lateral force received by the vehicle20due to the wind from the lateral direction to the center of gravity of the vehicle20is l (m). In this regard, l≠lf+lrand l denotes the distance between the center of gravity Gc of the vehicle20and the aerodynamic yawing center GAin plan view (the distance along the centerline of the vehicle20).

For example, values of the vehicle specifications of the vehicle20may be used for the front projected area SF(m2), the side projected area SS(m2), the front air resistance coefficient CDF, the side air resistance coefficient CDS, and the distance l(m) from the center of the lateral force to the center of gravity of the vehicle20received by the vehicle20due to the wind from the lateral direction. As the air density ρ, the value in normal conditions may be used, for example, or a value obtained from correcting the value in normal conditions by the atmospheric temperature and/or the atmospheric pressure may be used, for example. The value of the atmospheric pressure may be obtained by converting the value of the altitude included in navigation map data.

Fx, Fy, and M included in the above-mentioned equations (4) through (6), respectively, can be expressed by the following equations (13) through (15) using the above-described vehicle specifications, or the like.
Fx=½·ρ·VWVx2·SF·CDF(13)
Fy=½·ρ·VWVy2·SS·CDS(14)
M=½·ρ·VWVy2·SS·CDs·l(15)

From the equations (13) and (14), the x-axis component VWVxand the y-axis component VWVyof the vehicle-basis wind velocity can be expressed by the equations (16) and (17).

That is, the force Fxexerted in the forward/backward direction as a result of the vehicle20receiving wind and the force Fyexerted in the lateral direction as a result of the vehicle20receiving wind can be converted to the x-axis component VWVxand the y-axis component VWVyof the vehicle-basis wind velocity.

Next, the ground-basis wind velocity VWGis calculated from the x-axis component VWVxand the y-axis component VWVyof a vehicle-basis wind velocity expressed by the equations (16) and (17). The vector of the ground-basis wind velocity VWGcan be expressed by the following equation (18) as the sum of the vector of the vehicle velocity VVand the vector of the vehicle-basis wind velocity VWV. VVXdenotes the x-axis component of a vehicle velocity VV; VVYdenotes the Y-axis component of a vehicle velocity VV.

From the equation (18), the ground-basis wind velocity VWGand the wind direction θ can be expressed by the equations (19) and (20), respectively.

The center10collects vehicle information from a plurality of vehicles20. For this purpose, the information collecting unit120of the wind data estimating apparatus100obtains vehicle information including data indicating accelerator positions, vehicle velocities, accelerations, steering angles, yaw rates, brake operation amounts, and positions from the vehicles20at a predetermined sampling rate. The information classifying unit130collects position information and time information indicating the positions and times at which the accelerations and the yaw rates are obtained. The estimating unit140performs the following processing.

The estimating unit140obtains the ground-basis wind velocities VWGiand the wind directions θiof the winds received by n vehicles running simultaneously in the same area where the vehicle20is running. n denotes the number of vehicles running simultaneously at the predetermined area for which the ground-basis wind velocities VWGand the wind directions θ are obtained; i is a number (an integer indicating an i-th vehicle) between 1 and n.

Average values VWGmand θmof the ground-basis wind velocities VWGiand wind directions θifor the n vehicles can be expressed by the following equations (21) and (22).

The sample standard deviations Sv and Sθ of the average values VWGmand θmof the ground-basis wind velocities and wind directions can be expressed by the following equations (23) and (24).

Thus, the estimating unit140can obtain the average values VWGmand θmof the ground-basis wind velocities and the wind directions as well as the sample standard deviations Sv and Sθ.

Thus, the vector of the vehicle-basis wind velocity V of the wind received by a single vehicle20can be obtained on the basis of the force FVxand FVyexerted in the forward/backward direction and the lateral direction of the vehicle20, the force Fuxand Fuyexerted in the forward/backward direction and the lateral direction of the vehicle20due to a driving operation, and the force FRxand FRyexerted in the forward/backward direction and the lateral direction of the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs. Further, by using the vehicle velocity VV, it is possible to obtain the ground-basis wind velocity VWGand the wind direction θ.

Then, the average values VWGmand θmof the ground-basis wind velocities VWGand the wind directions θ of a plurality of vehicles running in the same area during the same time range can be calculated as the wind velocity and the wind direction for the area and for the time range.

In order to eliminate vehicle information that includes an acceleration a including abnormality such as an error by using a moment M, the following procedure may be performed. For example, when the lateral acceleration of a vehicle20is zero and the absolute value of the yaw rate ω of the vehicle20not due to the driver's operation is greater than zero (|ω|>0), the corresponding data may be determined as vehicle data concerning an acceleration sensor failure and may be excluded from being used for statistical processing.

The moment MRexerted on a vehicle20due to the cant angle and the grade of the road surface can be determined as MR=0 in the equation (12) because f·FRf≈lr·FRrcan be considered to be true.

FIG. 10is a flowchart illustrating a process performed by the wind data estimating apparatus100.

After the process is started, the information collecting unit120obtains vehicle information from vehicles20(step S1).

In step S2, the information classifying unit130classifies the vehicle information of the vehicles20obtained by the information collecting unit120by predetermined areas, further classifies the vehicle information by time ranges, and stores the classified vehicle information in a vehicle information database. Thus, a vehicle information database such as the vehicle information database illustrated inFIGS. 5A and 5Bis obtained.

The wind data estimating apparatus100repeatedly performs steps S1and S2.

FIG. 11illustrates a flowchart illustrating a process performed by the wind data estimating apparatus100.

After the process is started, the estimating unit140selects one set of vehicle information classified by a predetermined area and a predetermined time range from the vehicle information database (step S11). For a predetermined area, the code of a corresponding area may be selected, one by one, in the ascending order from1. A predetermined time range may be selected in the order starting from the earliest for each of the thus selected areas.

Next, the estimating unit140executes steps S12A, S12B, and S12C in parallel and executes steps S13A, S13B, and S13C in parallel. Details are as follows.

In step S12A, the estimating unit140reads the forward/backward acceleration ax, the lateral acceleration ay, and the yaw rate ω from the selected set of vehicle information.

In step S12B, the estimating unit140reads the accelerator position, the steering angle, and the brake operation amount from the set of vehicle information.

In step S12C, the estimating unit140reads the position data included in the set of vehicle information and reads the cant angle and grade associated with the link corresponding to the read position data in the electronic map (i.e., the map data).

In step S13A, the estimating unit140calculates FVx, FVy, and MVusing the equations (1) through (3).

In step S13B, the estimating unit140calculates Fux, Fuy, and Muusing the equations (9), (7), and (8).

In step S13C, the estimating unit140calculates FRx, FRy, and MRusing the equation (10) through (12).

In step S14, the estimating unit140calculates Fx, Fy, and M using the equations (4) through (6).

In step S15, the estimating unit140obtains the vehicle-basis wind velocity VWVusing the equations (16) and (17), thereafter converts the vehicle-basis wind velocity VWVto the ground-basis wind velocity VWGusing the equations (18), (19), and (20), and thus calculates the ground-basis wind velocity VWGand the wind direction θ.

In step S16, the estimating unit140determines whether there remain unprocessed sets of vehicle information for which ground-basis wind velocities VWGand wind directions θ have not been calculated yet for the same time range and the same area. The process of step S16is performed by determining by the estimating unit140whether unprocessed sets of vehicle information remain in the vehicle information database for the same time and the same area.

When it is determined that there remain unprocessed sets of vehicle information (S16: YES), the estimating unit140returns to step S11and repeatedly executes steps S11through S16for the unprocessed sets of vehicle information.

When it is determined that there remain no unprocessed sets of vehicle information (S16: NO), the estimating unit140calculates, using the equations (21) and (22), the average values VWGmand θmof all of the ground-basis wind velocities VWG and wind directions θ calculated in step S15(step S17).

After the completion of step S17, the estimating unit140ends the process ofFIG. 11.

The wind data estimating apparatus100performs a process illustrated inFIG. 11for all of the time ranges and all of the areas included in the vehicle information database to calculate respective sets of average values VWGmand θmof ground-basis wind velocities VWGand wind directions θ.

In this regard, average values VWGmand θmfor which the sample standard deviations Sv and Sθ are equal to or less than a predetermined threshold value may be stored in a wind database, whereas, for average values VWGmand θmfor which the sample standard deviations Sv are greater than the predetermined threshold value, new average values VWGmand θmobtained after increasing the number of samples by increasing the size of the area until the sample standard deviations Sv and Sθ become equal to or less than the predetermined threshold value may be stored in the wind database; or the original average values VWGmand θmmay be stored in the wind database as they are leaving the size of the area unchanged together with flags indicating that the reliability of the estimated crosswind values is not high (or the variation is great).

FIG. 12illustrates vehicles20and wind directions in mesh-like areas 1 and 2. The areas 1 and 2 are areas adjacent to one another in the north and south directions, and there are roads ST extending in the north, east, west, and south directions. Within the area 1, 6 vehicles20run on roads ST; within area 2, 7 vehicles20run on roads ST. As indicated by arrows, southwest winds blow, and the vehicles20receive force in northeast directions accordingly.

The wind data estimating apparatus100can obtain average values VWGmand θmof ground-basis wind velocities and wind directions and obtain the sample standard deviations Sv and Sθ for each of the areas 1 and 2. The average values VWGmand θmof ground-basis wind velocities and wind directions are estimates.

FIG. 13illustrates a wind database calculated by the wind data estimating apparatus100. The wind database stores average values VWGmand θmof ground-basis wind velocities and wind directions calculated by the wind data estimating apparatus100. The wind database is associated with areas and time ranges and is stored in the memory160.

The data thus stored in the wind database may be, for example, distributed from the communication unit150to vehicles20and displayed on display panels of navigation systems of the vehicles, or used to display a message to alert to a strong wind, a gust, a tornado, or the like.

Settings of the VSC-ECUs204B of vehicles20may be adjusted according to crosswind velocities. When vehicles20include ECUs (steering assist ECUs) for assisting steering, the amounts of steering assist by the steering assist ECUs may be adjusted according to the crosswind velocities included in the wind database.

In addition, for example, for a case where vehicles20are self-driving cars, the data stored in the wind database may be used to correct amounts of driving operations, such as a steering operations, brake operations, accelerator operations, and so forth. Self-driving means self-driving of a predetermined level prescribed by the Ministry of Land, Infrastructure, Transport and Tourism, the Society of Automotive Engineers (SAE), or the like.

Furthermore, for example, by incorporating data of a wind database into a dynamic map, it is possible to provide a more accurate dynamic map including more information. For example, when the center10performs a route search, the center10may search for a route that bypasses a point where the wind velocity is greater than a predetermined velocity.

Thus, according to the embodiment, the wind data estimating apparatus100can be provided that can estimate data about wind received by a vehicle. Furthermore, by creating a dynamic map associated with a wind database, it is possible to use the dynamic map for various purposes such as alert display, control of a vehicle20, route search, and so forth.

Thus, the configuration where the wind data estimating apparatus100of the center10calculates a vehicle-basis wind velocity VWVhas been described. However, an ECU of a vehicle20may calculate and transmit a vehicle-basis wind velocity V to the wind data estimating apparatus100through the DCM203. In such a case, the wind data estimating apparatus100may obtain the average value of the vehicle-basis wind velocities VWVreceived from a plurality of vehicles20.

Furthermore, the configuration has been described where force FVxexerted in a forward/backward direction of a vehicle20due to a driving operation and force FRxexerted in a forward/backward direction of the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs are subtracted from force FVxexerted in a forward/backward direction of the vehicle20, whereby force Fxexerted in a forward/backward direction of the vehicle20as a result of the vehicle20receiving wind is obtained.

In addition, the configuration has been described where force FVyexerted in a lateral direction of a vehicle20due to a driving operation and force FRyexerted in a lateral direction of the vehicle20due to the cant angle and the grade of the road surface on which the vehicle20runs are subtracted from force FVyexerted in a lateral direction of the vehicle20, whereby force Fyexerted in a lateral direction of the vehicle20as a result of the vehicle20receiving wind is obtained.

However, force FVxexerted in a forward/backward direction of a vehicle and force FVyexerted in a lateral direction of the vehicle20may be obtained without subtraction of force FRxexerted in a forward/backward direction of the vehicle20and force FRyexerted in a lateral direction of the vehicle20due to the cant angle and grade of the road surface on which the vehicle20runs. Especially for a case where force FRxexerted in a forward/backward direction of a vehicle20and force FRyexerted in a lateral direction of the vehicle20due to the cant angle and grade of the road surface on which the vehicle20runs are small, the calculation amount can be reduced by omitting subtraction of the force FRxand FRyas mentioned above.

In addition, a wind velocity and a wind direction may be estimated taking into account of only one of the cant angle and the grade of a road surface.

In addition, the configuration where force Fuxand Fuyexerted in a forward/backward direction and a lateral direction of a vehicle20due to a driving operation is obtained using the accelerator position, the brake operation amount, the vehicle velocity, and the steering angle has been described. In this regard, accelerations of a vehicle20occurring due to a driving operation may be obtained using at least one of the accelerator position, the brake operation amount, the vehicle velocity, and the steering angle.

Thus, the wind data estimation apparatus of the exemplary embodiment of the present invention has been described. In this regard, the present invention is not limited to the specifically disclosed embodiment, and variations and modifications can be made without departing from the scope of the claims.

DESCRIPTION OF REFERENCE NUMERALS

The present application is based on and claims priority to Japanese patent application No. 2018-131837, filed on Jul. 11, 2018, the entire contents of which are hereby incorporated herein by reference.