JP6817768B2 - Steering assist ratio calculation device for power steering system and steering assist ratio calculation method for power steering system - Google Patents

Description

The present invention relates to a steering assist ratio calculation device for a power steering system and a steering assist ratio calculation method for a power steering system.

Conventionally, for example, in Patent Document 1 below, a myoelectric potential is detected from a deltoid muscle electrode, an integrated myoelectric potential is obtained, and whether it is an active state or a passive state is determined based on the integrated myoelectric potential, and in the active state or the passive state. It is described that the information from the pressure sensor, the vehicle steering state detection unit, and the sensory evaluation input unit is collected and stored together with the information on the presence, and the factor of the steering feeling is evaluated using these information. ..

Japanese Unexamined Patent Publication No. 2003-177079

When the driver drives the vehicle, steering is one of the main parts of the driving operation, and the driving feeling can be enhanced by improving the steering feeling. However, the technique described in the above patent document evaluates the factors of the steering feeling, and it is not expected to improve the steering feeling at all.

Therefore, the present invention has been made in view of the above problems, and an object of the present invention is that it is possible to improve the steering feeling of the driver by optimally setting the steering assist ratio. It is an object of the present invention to provide a new and improved steering assist ratio calculation device and a steering assist ratio calculation device method.

In order to solve the above problem, according to a certain viewpoint of the present invention, the difference between the average vehicle speed and the average yaw rate when driving on a curve is obtained for each of a plurality of set values of the steering assist ratio set by the power steering system. For each driving state classified according to the above, a biological information acquisition unit that acquires the acceleration of the arm and the amount of muscle activity of the arm related to the steering of the driver from an individual driver who drives the vehicle, and the driving state. Each time, the assist ratio calculation unit that calculates the peak value of the assist ratio at which the acceleration of the arm and the degree of dispersion of the muscle activity of the arm become low are associated with the peak value of the assist ratio and the driving state. driving a storage unit for storing the database, and the assist ratio deviation calculating unit for determining the standard deviation of the peak value of the assist ratio based on the average value of the peak value of the assist ratio, the driver actually vehicle Te As the assist ratio set by the power steering system, the average value of the peak values of the assist ratio and the driving state according to the driving path are applied to the database based on the standard deviation corresponding to the driver. The assist ratio selection unit for selecting either the obtained assist ratio, the assist ratio obtained by applying the future driving state to the database, or the assist ratio obtained by applying the current driving state to the database is provided. , A steering assist ratio determining device for a power steering system is provided.

Further, the assist ratio calculation unit may calculate the peak value of the assist ratio at which the degree of discreteness of the Z score of the acceleration of the arm and the muscle activity of the arm becomes low.

Further, the assist ratio calculation unit calculates the peak values of a plurality of the assist ratio and the assist ratio discrete degree decreases the Z score based relationship approximate curve that approximates a discrete degree of the Z score It may be a thing.

Further, by acquiring the vehicle speed and the yaw rate for each curve section obtained from the map information and averaging the vehicle speed and the yaw rate in all the curve sections, the average vehicle speed and the average yaw rate according to the driving route can be obtained according to the driving route. It may be acquired as an operating state.

Further, the future operating state may be predicted based on the image information obtained from the image pickup apparatus.

Further, as the current driving state, the sensor values of the vehicle speed and the yaw rate may be acquired.

Further, in order to solve the above-mentioned problems, according to another viewpoint of the present invention, the average vehicle speed and the average when driving on a curve are obtained for each of a plurality of set values of the steering assist ratio set by the power steering system. For each driving state classified according to the difference in yaw rate, a step of acquiring arm acceleration and arm muscle activity related to the steering of the driver from an individual driver who drives the vehicle, and the driving state. For each step, the step of calculating the peak value of the assist ratio at which the acceleration of the arm and the degree of dispersion of the muscle activity of the arm become low, the peak value of the assist ratio, and the driving state are associated with each other in the database. A step to record, a step to obtain a standard deviation of the peak value of the assist ratio based on the average value of the peak values of the assist ratio, and a step set by the power steering system when the driver actually drives the vehicle. As the assist ratio, the average value of the peak values of the assist ratio, the assist ratio obtained by applying the driving state according to the driving route to the database, and the future driving state based on the standard deviation corresponding to the driver. Provided is a method for determining the steering assist ratio of the power steering system, which comprises a step of selecting either an assist ratio obtained by applying the above database or an assist ratio obtained by applying the current driving state to the database. Will be done.

As described above, according to the present invention, the steering feeling of the driver can be improved by optimally setting the steering assist ratio.

It is a schematic diagram which shows the structure of the assist ratio calculation system 1000 of steering steering which concerns on one Embodiment of this invention. It is a schematic diagram which shows the outline of the processing performed by the assist ratio arithmetic unit 100. It is a flowchart which shows the detail of the process performed by the assist ratio arithmetic unit 100. It is a flowchart which shows the detail of the process performed by the assist ratio arithmetic unit 100. It is a schematic diagram which shows the example of a label table. It is a characteristic diagram which shows the example which plotted the Z score (ZA _ijk ) of the acceleration of an arm and the Z score (ZM _ijk ) of the muscle load of an arm on a two-dimensional plane. It is a characteristic figure which shows the relationship between the discretenesses D ₁₁₁ , D ₂₁₁ , and D _{311 of} i = 1, 2, 3 and the assist ratio in the case of j = 1, k = 1. It is a schematic diagram which shows the approximate curve calculated from the formula (2). It is a flowchart which shows the process of the automatic change mode of the assist ratio which concerns on this embodiment. It is a schematic diagram which shows the state that the optimum C _xjk is stored in the database according to the traveling state. It is a schematic diagram which shows the route from the present place to the destination. It is a schematic diagram which shows the information stored in a database. It is a flowchart for demonstrating the automatic change mode 2 of the assist ratio which concerns on this embodiment. It is a flowchart which shows the process which estimates the traveling vehicle speed of a steady circular section, and changes the control. 10 is a schematic diagram showing a state in which a vehicle travels on a straight line → a transition curve → a steady circular section → a transition curve → a straight line in the processes of FIGS. 10 and 11. It is a flowchart which shows the process of the automatic change mode of the assist ratio which concerns on this embodiment. It is a flowchart which shows the process of automatic selection which concerns on this Embodiment. It is a characteristic diagram for _{demonstrating} how the peak value C _xjk of the assist ratio is different for each of different drivers A, B, and C. It is a characteristic diagram for _{demonstrating} how the peak value C _xjk of the assist ratio is different for each of different drivers A, B, and C. It is a characteristic diagram for _{demonstrating} how the peak value C _xjk of the assist ratio is different for each of different drivers A, B, and C.

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

FIG. 1 is a schematic view showing the configuration of the steering assist ratio calculation system 1000 according to the embodiment of the present invention. The system 1000 shown in FIG. 1 can be mounted on a vehicle. In the present embodiment, body information related to steering is acquired from each driver (driver), and the optimum steering assist ratio for each driver is calculated based on the acquired body information. Steering As body information related to steering, arm acceleration A and arm muscle activity M (myoelectricity (also referred to as muscle load)) are used.

When the driver drives the vehicle, steering is one of the main parts of the driving operation, and the driving feeling can be enhanced by improving the steering feeling. In the present embodiment, the steering feeling is improved by setting the optimum steering control according to the individual characteristics by measuring the operation of the occupant during steering. Specifically, the acceleration A and the muscle activity amount M of the hand during steering are measured by biometric measurement. These measurements are performed with three or more different control settings. The control setting is changed by changing the assist ratio C of the electric power steering system (EPS). Acceleration A and muscle activity M acquired with different control settings are scored as Z, and the average of the degree of discreteness D as a steering feeling index is calculated for each control setting on the two-axis phase plane of acceleration A and muscle activity M. calculate. Then, an approximate curve is obtained so that the obtained discrete degree D and the assist ratio C are non-linear (D = f (C)), and the assist ratio at which the discrete degree D is the optimum value (vertex that becomes convex downward) is obtained. .. As the acceleration A, the average value of the three-axis composite vector may be used.

In the present embodiment, the acceleration A of the arm and the muscle activity amount M of the arm are exemplified as the biological information, but the biological information may be other information. Further, although two pieces of information, the acceleration A of the arm and the muscle activity amount M of the arm, are used as the biological information, one or three or more biological information may be used.

As shown in FIG. 1, the assist ratio calculation system 1000 includes a control device (assist ratio calculation device) 100, a biological sensor 200 (accelerometer 210, muscle load sensor 220 for measuring muscle load), a vehicle sensor 400, and a mode switching SW500. , Communication unit 510, and electric power steering system (EPS) 600. The vehicle sensor 400 includes a vehicle speed sensor 402, a steering angle sensor 404, a yaw rate sensor 406, a steering torque sensor 408, an outside sensor 410, and a position sensor (GPS) 412. The vehicle exterior sensor 410 detects the road shape, the white line shape of the road surface, and the like by image processing of an image obtained from a stereo camera or the like. Instead of the stereo camera, another imaging device such as a monocular camera may be used. Further, as the vehicle exterior sensor 410, a device that detects the situation outside the vehicle by using a millimeter wave radar, an infrared laser, or the like may be used. The position sensor 412 acquires the current position. The communication unit 510 communicates with the outside by wireless communication and acquires the traveling history of another vehicle and the like.

The acceleration of the arm is measured by attaching the acceleration sensor 210 to the driver's arm. Further, the acceleration of the arm may be calculated from the locus of the hand by analyzing the image captured by the camera and measuring the locus of the hand. In the case of image analysis, marker measurement by motion capture and markerless measurement by a stereo camera, an infrared camera, or the like can be used. The method of acquiring the acceleration of the arm is not limited to these, and other methods may be used.

The muscle burden sensor 220 includes an electromyogram (electrode), and measures the electromyography by, for example, attaching the electromyogram to the deltoid muscle of the driver. Specifically, the value obtained by calculating% MVC from the myoelectric data can be used from the following formula. The RMS value represents the effective value of myoelectricity. The RMS value at the time of maximum voluntary contraction is measured in advance in a stopped state or the like.
% MVC = RMS value at the analysis site ÷ RMS value at the time of maximum voluntary contraction Note that the muscle load may be measured by a substitute measurement using a load sensor instead of the electromyogram. In this case, a load sensor is attached to the steering wheel or the seat, the load is measured as the point of action when the driver applies force, and the muscle load is estimated from the load. In addition, the muscle load may be estimated using a musculoskeletal model or the like.

The assist ratio arithmetic unit 100 includes a first control unit 110, a second control unit 120, a motor control unit 130, and databases 140 and 150. The first control unit 110 obtains a control value for controlling the motor included in the electric power steering system (EPS) 600 based on the vehicle speed and steering torque, and sends the control value to the motor control unit 130. The motor control unit 130 controls the motor included in the electric power steering system (EPS) 600 based on the control value.

The second control unit 120 calculates the assist ratio of the electric power steering system (EPS) 600 based on the information of the biosensor 200. The motor control unit 130 controls the motor included in the electric power steering system (EPS) 600 based on the assist ratio calculated by the second control unit 120.

In a normal driving state, the motor included in the electric power steering system (EPS) 600 is controlled based on the vehicle speed and steering torque. At this time, the electric power steering system (EPS) 600 controls the electric power steering system (EPS) 600 with a predetermined assist ratio. On the other hand, when the driver performs a predetermined operation by the mode switching SW500, the assist ratio by the electric power steering system (EPS) 600 is changed to the assist ratio calculated by the second control unit 120, and the electric power is changed by the changed assist ratio. The motor included in the steering system (EPS) 600 is controlled.

The database 140 stores map information of the navigation system, travel history information of the own vehicle or another company, and the like. Further, the assist ratio C _xjk, which will be described later, is stored in the database 150.

The second control unit 120 includes a biological information acquisition unit 122 that acquires biological information detected by the biological sensor 200, an assist ratio calculation unit 124 that calculates an assist ratio based on the biological information, a route search unit 125, and a vehicle operating state. The driving state acquisition unit 126 for acquiring the assist ratio, the assist ratio acquisition unit 127 for acquiring the assist ratio stored in the database 150 based on the driving state of the vehicle, the assist ratio deviation calculation unit 128 for obtaining the deviation of the assist ratio, and the assist ratio It is configured to include an assist ratio selection unit 129, which selects an assist ratio based on a deviation.

More specifically, the biometric information acquisition unit 122 acquires biometric information related to steering steering according to a plurality of driving states for each of the plurality of assist ratios of steering steering set by the power steering system 600. In addition, the assist ratio calculation unit 124 calculates the assist ratio at which the degree of dispersal of biological information becomes low in a plurality of operating states. Further, the assist ratio acquisition unit 127 determines the steering assist ratio used in the power steering system 600 based on the assist ratio calculated by the assist ratio calculation unit 124 in a plurality of driving states.

The driving state acquisition unit 126 acquires the driving state according to the driving route based on the information of the current location and the destination of the vehicle. In addition, the operating state acquisition unit 126 acquires (predicts) the current or future operating state. The assist ratio acquisition unit 127 acquires the assist ratio according to the driving state from the database 150 in which the assist ratio at which the degree of dispersal of biological information related to steering is reduced is defined for each driving state.

Further, the assist ratio deviation calculation unit 128 obtains the deviation of the assist ratio calculated by the assist ratio calculation unit 124. The assist ratio selection unit 129 applies the average value Cx of the assist ratio, the operation state according to the operation route to the database 150 based on the deviation calculated by the assist ratio deviation calculation unit 128, the assist ratio obtained, and the future operation state. Is applied to the database 150 to obtain an assist ratio, and the current operating state is applied to the database 150 to obtain an assist ratio.

Each component of the assist ratio arithmetic unit 100 of FIG. 1 can be composed of a central processing unit such as a circuit (hardware) or a CPU and a program (software) for functioning the central arithmetic unit. Further, the program can be stored in a recording medium such as a memory.

FIG. 2 is a schematic diagram showing an outline of processing performed by the assist ratio arithmetic unit 100. First, the vehicle is driven with the acceleration sensor 210 and the muscle load sensor 220 attached to the driver (step S10). Then, the acceleration and myoelectricity of the hand are measured during driving (steps S12 and S14).

Next, the measured acceleration and the degree of discreteness of myoelectricity are calculated (step S16). Next, the discreteness data is accumulated, and the optimum value of the steering assist ratio is calculated based on the discreteness (step S18). Next, the steering assist ratio in the electric power steering system (EPS) 600 is changed (step S18), the process returns to step S10, and the processes of steps S10 to S20 are repeated. Then, after repeating the process three or more times, the process proceeds from step S16 to step S22 to determine the optimum value and finally determine the assist ratio (step S24). The control condition is determined by the assist ratio determined in step S24, and the vehicle is driven (step S26). Various vehicle information such as vehicle speed and steering angle are appropriately used to determine the control conditions.

3 and 4 are flowcharts showing the details of the processing performed by the assist ratio arithmetic unit 100. The process of FIG. 3 is mainly performed by the biological information acquisition unit 122. Further, the processing of FIG. 4 is mainly performed by the assist ratio calculation unit 124 and the assist ratio determination unit 127. First, in step S100, the mode switching SW500 is operated to turn on the initial setting mode. The initial setting mode is premised on driving the vehicle, but various information may be acquired in the simulation setting mode in which the vehicle is steered while the vehicle is stationary. In the next step S102, the assist ratio Ci of the electric power steering system (EPS) 600 at each control setting is set. i is set to 3 or more, and 3 or more assist ratios are set. As an example, i = 1, 2, and 3, and C1 = 1, C2 = 2, and C3 = 0.4. In addition, the assist ratio is set in a straight section or while the vehicle is stopped. The straight line section can be estimated by using the map information of the navigation system, the information obtained from the external sensor 410, and the like.

In the next step S104, recording of various data is started. The data recorded here are various data such as vehicle speed Vi, steering angle αi, yaw rate γi, actual steering torque Tsi, steering torque Thi, arm acceleration Ai, arm muscle load Mi, and the like.

In the next step S106, it is estimated whether or not the vehicle is traveling in the steady circle section, and the average value of each of the above data is calculated for each travel in the steady circle section. As an example, the moving average peak value of the yaw rate is calculated, and 4 seconds before and 2 seconds after the peak value are estimated as the steady circle running section, and each data is calculated.

In the next step S108, each data is labeled with j and k according to the average value of the vehicle speed and the yaw rate for each steady circle section according to the label table. FIG. 5 is a schematic diagram showing an example of a label table. When i = 1, the average vehicle speed V1 in a certain steady circle section is 0 to 10 [km / s], and when the average yaw rate γ1 is 0.1 to 0.2 [rad / s], after labeling. The acceleration of the arm is A ₁₁₅ .

In the next step S110, the operation is continued until N data in which j and k are combined are recorded. In the next step S112, 1 is added to the value of i, in the next step S114, it is determined whether or not the value of i is 3 or less, and if the value of i is 3 or less, the processing after step S102 is repeated. Do.

If the value of i exceeds 3 in step S114, the process proceeds to step S116 of FIG. In step S116, j and k are changed from 1, and the calculation is started with each combination. The value of j is from 1 to J (j = 1: J), and the value of k is from 1 to K (k = 1: K). In the next step S118, the data (arm acceleration, arm muscle load) with matching labels j and k are converted into Z scores, respectively. As a result, (ZA _ijk , ZM _ijk ) is obtained. The Z score is expressed by replacing the position of a certain value pi of the element i constituting the population in the distribution with a standard normal distribution having a mean value of 0 and a standard deviation of 1 (Z). Score = (pi-μ) / σ, where μ is the population mean, σ is the standard deviation), and if pi is equal to the mean, the Z score is 0, if it is higher than the mean, the Z score is positive, if it is lower It will be a negative value. The above equation for obtaining the Z score is obtained by replacing the distribution of the standard deviation of an arbitrary value with the standard normal distribution of the standard deviation 1.

FIG. 6 is a characteristic diagram showing an example in which the Z score (ZA _ijk ) of the acceleration of the arm and the Z score (ZM _ijk ) of the muscle load of the arm are plotted on a two-dimensional plane. In FIG. 6, the horizontal axis shows the value of the Z score (ZA _ijk ) of the acceleration of the arm, and the vertical axis shows the value of the Z score (ZM _ijk ) of the muscle burden of the arm. The characteristics of the plot shown in FIG. 6 are obtained for each specific combination of j and k. In a specific combination of i and j, plotting is performed for each case where i indicating the assist ratio is 1, 2, or 3. As an example, for convenience of explanation, the characteristics shown in FIG. 6 are assumed to be j = 1 and k = 1. In FIG. 6, the plot when i = 1 (assist ratio C1 = 1, steering torque “intermediate”) is shown by ◇, and the plot when i = 2 (assist ratio C2 = 2, steering torque “light”) is shown. It is shown by □, and the plot when i = 3 (assist ratio C3 = 0.4, steering torque “heavy”) is shown by Δ.

In the next step S120, the degree of discreteness _Dijk for each control setting of each assist ratio is obtained from the Z-score data. The degree of discreteness _Dijk is calculated from the following equation (1). The degree of discreteness D _ijk is an index created based on the experimental result that the movement during steering (acceleration A, muscle activity amount M) is highly reproducible in the control setting that is easy to drive. If the steering torque is too heavy or too light, the variation in muscle activity and acceleration tends to be large, and the degree of discreteness tends to be high, and the degree of discreteness has a high correlation with the steering feeling. When an appropriate steering torque with a good steering feeling is set, muscle activity and acceleration do not increase or decrease excessively with respect to a setting where the steering torque is heavy or light, variation is reduced, and the degree of discreteness is reduced.

As described above, for example, when j = 1 and k = 1, the degree of discreteness _{Di 11} can be obtained. FIG. 7 is a characteristic diagram showing the relationship between the discretenesses D ₁₁₁ , D ₂₁₁ , and D _{311 of} i = 1, 2, and 3 and the assist ratio when j = 1 and k = 1. As shown in FIG. 7, it can be seen that the degree of discreteness D changes according to the assist ratio.

In the next step S122, it is determined whether or not the conditions of D _1jk <D _2jk and D _1jk <D _3jk are satisfied, and if this condition is satisfied, the process proceeds to step S124. On the other hand, if this condition is not satisfied, the process returns to step S116 and recalculation is performed. Here, when the assist ratio is C3, the steering torque is heavy, when the assist ratio is C2, the steering torque is light, and C3 and C2 are set to control settings in which the assist ratios are extremely removed. On the other hand, in the case of the assist ratio C1, the steering torque is intermediate, the design neutral value, and the control setting is assumed to be close to an appropriate value. Therefore, by performing the determination in step S122, only the condition that the degree of discreteness at the assist ratio C1 becomes the minimum value smaller than the degree of discreteness at the time of the assist ratio C2 and the assist ratio C3 is extracted.

In step S124, a non-linear approximation curve showing the relationship between the degree of discreteness D and the assist ratio C in FIG. 7 is calculated. The approximate curve can be calculated from the following equation (2), for example. However, in equation (2), e is a constant term.
D _jk = (C-C _xjk ) + e ... (2)

FIG. 8 is a schematic diagram showing an approximate curve calculated from the equation (2). In step S124, the peak value C _xjk is calculated based on the approximate curve. In the examples of FIGS. 7 and 8, Ci ₁₁ which is the minimum value is calculated.

For example, in FIG. 8, D _jk in each case of the assist ratios C1 = 1, C2 = 2, C3 = 0.4 is substituted into the equation (2), and C _{x 11 is performed} by the following calculation based on the equation (2). = 0.81. Specifically, the degree of discreteness D ₁₁₁ = 0.9 when C1 = 1, the degree of discreteness D ₂₁₁ = 2.6 when C2 = 2, and the degree of discreteness D ₃₁₁ = 1 when C3 = 0.4. Substitute 4 into equation (2) to obtain C _x11 = 0.81. Therefore, in this case, the assist ratio having the lowest degree of discreteness is 0.81.
D _i11 = 3.93c ² -6.36c + 3.29
= 3.93 (c-0.81) ² + 0.71

In the next step S126, it is determined whether or not the processing of steps S116 to S124 is completed for all the combinations of j and k, and if the processing is completed for all the combinations of j and k, the process proceeds to step S128. Set the initial setting mode to OFF. On the other hand, if the processing is not completed for all the combinations of j and k, the process returns to step S116. In step S130, the average value Cx of all Cxjk is obtained. In the next step S134, all C _xjk are stored in the database 150. In the next step S136, the standard deviation σx is obtained from all of C _xjk .

FIG. 10 is a schematic view showing how the optimum C _xjk according to the traveling state is stored in the database 150. As shown in FIG. 10, the database stores the optimum assist ratio C _xjk for any combination of the average speed vj and the average yaw rate γl.

18A to 18C are characteristic diagrams showing how the peak value C _xjk of the assist ratio is different for each of the different drivers A, B, and C. In the characteristics of the driver A shown in FIG. 18A, the degree of discreteness peaks when the steering torque is in the middle (assist ratio ≈ 1). Further, in the characteristics of the driver B shown in FIG. 18B, the degree of discreteness peaks when the steering torque is heavy (assist ratio 1.0 or less). Further, in the characteristics of the driver C shown in FIG. 18C, the degree of discreteness peaks when the steering torque is light (assist ratio 1.0 or more). As described above, the optimum assist ratio differs for each driver, but in the present embodiment, the peak value C _{xjk at} which the degree of discreteness D is the smallest is obtained for each of the labels j and k according to the driving state, and all of _them are obtained. _Since the average value Cx of C _xjk is set as the steering assist ratio Cx in the electric power steering system (EPS) 600, it is possible to set the optimum assist ratio Cx for each driver.

Next, the automatic change mode 1 of the assist ratio according to the present embodiment will be described with reference to FIG. The processing of FIG. 9 is mainly performed by the operating state acquisition unit 126, the assist ratio acquisition unit 127, and the route search unit 125. First, in step S200, the driver turns on (ON) the automatic change mode 1. In the next step S202, the route search is started. Specifically, the route search unit 125 starts searching for a route from the current location to the destination based on the navigation map information stored in the database 140.

In the next step S204, the average vehicle speed vr when traveling on the curve section on the travel route is acquired for each curve section. Here, l is the number of curves. In the next step S206, the average yaw rate value γl or the average radius of curvature ρl when traveling on the curve section on the travel route is acquired for each curve section.

FIG. 11 is a schematic diagram showing a route from the current location to the destination. In the example of FIG. 11, the number of curves is 2 (l = 2), and in the section from the current location Q1 to the intermediate location Q2, the average vehicle speed is v1, the yaw rate average value is γ1, and the average radius of curvature is ρl. Further, in the section from the intermediate place Q2 to the destination Q3, the average vehicle speed is v2, the yaw rate average value is γ2, and the average radius of curvature is ρ2.

The average vehicle speed lv, the mean yaw rate rl, or the average radius of curvature ρl is acquired from the navigation map information data stored in the database 140. In addition, the travel history information of the own vehicle or another vehicle may be acquired and acquired from the travel history information. FIG. 12 is a schematic diagram showing information stored in the database 140. As shown in FIG. 12, the database 140 stores information such as the average vehicle speed vr, the average yaw rate value γl, and the average radius of curvature ρl in each section in association with the map information. In addition, the database 140 and the database 140 store information on the traveling history of the own vehicle and other vehicles, and when the curve section in the map information and the vehicle or other vehicle travel on the curved section. The average vehicle speed lv, the average yaw rate rl, or the average radius of curvature ρl are recorded in association with each other.

If the data acquired in step S206 is ρl, the process proceeds to step S208, and the average yaw rate γl is calculated from the following formula. When the yaw rate average value rl is directly acquired in step S206, the process proceeds to step S210 without going through step S208.
γl = vl / ρl

In step S210, the average vehicle speed vy of the traveling route to the destination is obtained by averaging the average vehicle speed vr acquired in all the curve sections. Further, the average yaw rate γy of the traveling route to the destination is obtained by averaging the average yaw rate γl acquired in all the curve sections. As described above, the driving state acquisition unit 126 acquires the average vehicle speed by and the average yaw rate γy as the driving state according to the driving route. In the next step S212, the assist ratio acquisition unit 127 selects the combination of the vehicle speed vj and the yaw rate γk that is the closest value to the combination of the average vehicle speed by and the average yaw rate γy from the database 150 storing the C _xjk shown in FIG. The search is performed, and the control condition C _xjk corresponding to the combination of the searched vehicle speed vj and the yaw rate γk is selected.

In the next step S214, the control condition (assist ratio is C _xjk ) is set. When the vehicle reaches the destination in the next step S216, the automatic change mode 1 is turned off (OFF) in the next step S218.

Next, the automatic change mode 2 of the assist ratio according to the present embodiment will be described with reference to FIG. The process shown in FIG. 13 is mainly performed by the operating state acquisition (prediction) unit 126. First, in step S300, the automatic change mode 2 is turned on. In the next step S301, acquisition of the road curvature radius ρ ahead, the vehicle speed v of the own vehicle, and the front-rear acceleration information is started while the vehicle is traveling. The radius of curvature ρ of the road ahead is acquired from the image information of the stereo camera included in the external sensor 410. In the next step S302, the radius of curvature ρl at the F [m] destination is acquired and the data is stored. In addition, l is a value from 1 to infinity (∞). Further, F represents the maximum forward distance that can be detected by the external sensor 410, and ∞ indicates that the process is continued until the end determination of the loop calculation is obtained. When acquiring the radius of curvature ρ of the road, more specifically, lane detection is performed from the image information, and when the displacement of a point in the lane ahead of F0 m (in the lateral direction of the vehicle) exceeds a certain threshold, 3 on the white line The arc passing through the points (F0, F1, F2) is calculated, and the radius of curvature is obtained from the arc. When detecting a lane, the image information is binarized, and points continuously detected in the front-rear direction are determined to be lanes. F0, F1 and F2 can be set arbitrarily (F0 = F may be set), and they are set at equal intervals as much as possible. Further, the number of measurement points may be increased to four or more by adding a measurement point F3 to improve the accuracy. As a calculation example in that case, the average of the arc passing through F0, F1 and F2 and the arc passing through F1, F2 and F3 is used for calculating the radius of curvature. In the case of a stereo camera, the position of the white line can be accurately detected from the position of the own vehicle by using the parallax image created from the acquired image.

In the next step S304, it is determined whether or not l ≧ 2, and if l ≧ 2, the process proceeds to step S306. The change in the radius of curvature is calculated to estimate the starting point of the transition curve, but since it is necessary to acquire two or more data for that purpose, it is determined in step S304 whether or not l ≧ 2. .. In addition, in order to improve the accuracy, it may be set to acquire three or more data.

In step S306, it is determined whether or not ρl <ρ _l-1, in the case of ρl <ρ _l-1 proceeds to step S308. In step S306, when the radius of curvature ρ decreases, it is determined that the transition curve has been entered. For example, the number of determinations may be increased to improve the accuracy by determining whether or not ρ _l <ρ _l-1 <ρ _l-2 is satisfied. In step S310, the coordinates of the F [m] destination are recorded, and these coordinates are set as the start position P1 of the transition curve.

On the other hand, if l <2 in step S304, or if ρl ≧ ρ _{l-1 in} step S306, the process proceeds to step S310, 1 is added to the value of l (l = l + 1), and the processes after step S302 are repeated. Do.

After step S310, the process proceeds to step S312 to acquire the radius of curvature ρm at the F [m] destination and store it in the database. In addition, m is a value from 1 to infinity (∞). In the next step S314, it is determined whether or not m ≧ 2, and if m ≧ 2, the process proceeds to step S316. The change in the radius of curvature is calculated to estimate the start point of the stationary circle section, but in order to acquire two or more data, it is determined in step S314 whether or not m ≧ 2. In addition, in order to further improve the accuracy, three or more data may be acquired.

In step S316, it is determined whether or not _{ρ m -ρ m-1 <ρx1} , in the case of ρ _m -ρ _m-1 <ρx1 proceeds to step S318. When the radius of curvature ρ does not change in this way, it is estimated to be a steady circular interval, and in step S318, the radius of curvature at that time is recorded as ρy. At that time, if the threshold value is less than ρx1, it is determined as an error or a transition curve. The number of judgments may be increased to improve the accuracy. For example, when m ≧ 3, ρ _m −ρ _m-1 <ρx1 and ρ _m-1 −ρ _m-2 <ρx1 may proceed to step S318.

On the other hand, if m <2 in step S314, or if ρ _m −ρ _m-1 ≧ ρx1 in step S316, the process proceeds to step S320, 1 is added to the value of m (m = m + 1), and after step S312. Perform the process again.

After step S318, the process proceeds to step S320. In step S320, the coordinates of the F [m] destination are recorded and set as the start position P2 of the steady circle section. As described above, the operating state acquisition (prediction) unit 126 predicts that the steady-state circular section starts from F [m].

FIG. 14 is a flowchart showing a process of estimating the traveling vehicle speed in the steady circular section and changing the control. The processing shown in FIG. 14 is mainly performed by the operating state acquisition (prediction) unit 126 and the assist ratio acquisition unit 127. First, in step S400, when the start position P2 of the steady circular section is reached, the vehicle speed by when traveling in the steady circular section is estimated. The vehicle speed by is estimated based on the information stored in the database 140 (speed limit, running history of own vehicle or other vehicle), or the speed of a vehicle in front, if any. In the next step S402, the yaw rate γy when traveling in the steady circular section is calculated. The yaw rate γy can be calculated from the following formula. As described above, the operating state acquisition (prediction) unit 126 predicts that the steady-state circular section starts from F [m], and predicts the vehicle speed by and the yaw rate γy in the steady-state circular section.
γy = vy / ρy

As shown in FIG. 14, the database 140 stores information such as the average vehicle speed vr, the average yaw rate value γl, and the average radius of curvature ρl in each section in association with the map information. In addition, the database 140 stores information on the travel history of the own vehicle and other vehicles, and includes the curve section in the map information, the average vehicle speed vr when the vehicle and other vehicles travel on the curve section, and the average yaw rate. It is recorded in association with rl or the average radius of curvature ρl. The average vehicle speed lv, mean yaw rate value γl, or average radius of curvature ρl in each section shown in FIG. 14 is obtained by averaging the vehicle speed, yaw rate, and radius of curvature when traveling in the estimated stationary circular section. For example, it can be obtained by starting to accumulate each data when it is determined to be the beginning of the stationary circle interval, and calculating the average value of each data when determining the end of the stationary circle interval.

In the next step S404, the assist ratio acquisition unit 127 _searches the database 150 storing the C _xjk shown in FIG. 9 for the combination of vehicle speed vj and yaw rate γk that is the closest value to the combination of vehicle speed by and yaw rate γy. , Select the C _xjk corresponding to the searched combination. In the next step S406, the assist ratio is set to C _xjk selected in step S404.

In the next step S408, the radius of curvature ρn at the F [m] destination is acquired and stored in the database. In the next step S410, it is determined whether or not n ≧ 2, and if n ≧ 2, the process proceeds to step S412. The change in the radius of curvature is calculated to estimate the start point of the straight section, but in order to acquire two or more data, it is determined in step S410 whether or not n ≧ 2. In addition, in order to further improve the accuracy, three or more data may be acquired.

In step S412, it is determined whether the ρ _n -ρ _n-1 = 0 and ρ _n> ρ _x2, if this condition is satisfied, the process proceeds to step S414. Specifically, in step S412, it is determined that the change in the radius of curvature is larger than the condition of step S316 in FIG. 10 and the start of the transition curve is determined when the radius of curvature ρ _n is equal to or greater than the threshold value ρx2. In step S414, the coordinates of the F [m] destination are recorded and set as the start position P3 of the transition curve.

On the other hand, if n <2 in step S410, or if ρ _n −ρ _n-1 ≠ 0 or ρ _n ≦ ρ _x2 in step S412, the process proceeds to step S416, and 1 is added to the value of n (n = n + 1). ), The processing after step S408 is performed again.

After step S414, the process proceeds to step S418, and when the own vehicle reaches P3, the control setting (assist ratio) is changed to the initial value. In the next step S420, the automatic change mode 2 is turned off (OFF). After step S420, the process ends (END).

FIG. 15 is a schematic view showing how the vehicle travels in a straight line → a transition curve → a steady circular section → a straight line in the processing of FIGS. 10 and 11. As shown in FIG. 15, a transition curve is usually provided between a straight line and a stationary circular section. If the condition of step S306 is satisfied while the vehicle is traveling on a straight line, it is determined that the transition curve starts from the start position P1 ahead of F [m], and the process proceeds to the determination process of the steady circle section after step S312. After that, when the condition of step S316 is satisfied, the assist ratio C _xjk when traveling in the steady circular section is set. After that, when the condition of step S412 is satisfied, the assist ratio is changed to the initial value when the vehicle reaches the start position P3 of the transition curve in step S418.

Next, the automatic change mode 3 of the assist ratio according to the present embodiment will be described with reference to FIG. First, in step S500, the automatic change mode 3 is turned on. In the next step S502, acquisition of the steering angle αl, the vehicle speed lv, and the yaw rate γl is started. The steering angle αl is detected by the steering angle sensor 404, the vehicle speed lv is detected by the vehicle speed sensor 402, and the yaw rate γl is detected by the yaw rate sensor 406. The value of l is set from 1 to ∞ (l = 1: ∞), and the calculation is continued until the automatic change mode 3 is turned off (OFF).

In the next step S504, it is determined whether or not αl ≠ 0, and if αl ≠ 0, the process proceeds to step S506. On the other hand, when αl = 0, proceeds to step S508, 1 is added to the value of l (l = l + 1), and the processing after step S502 is performed again. By determining whether or not αl ≠ 0, if the steering angle is 0, control change or the like is not performed. In step S504, the process may proceed to step S508 when the absolute value of the steering angle αl exceeds the threshold value αt and the vehicle speed vr exceeds the threshold value vt. That is, in step S504, the same determination may be made based on the threshold values αt and vt by determining whether or not | αl |> αt and | vr |> vt. Further, in this case, the steering angle αl may be replaced with the steering angular velocity or the steering angular acceleration. The vehicle speed vt may be replaced with the vehicle front-rear acceleration. The threshold values αt and vt can be changed arbitrarily. As described above, basically, when the steering wheel is operated, the assist ratio is automatically changed, so that the steering feeling can be improved in real time.

In step _S506, vl from a database which stores _{C xjk,} vj as the value closest to Ganmaeru, searching .gamma.k, selects the _{C xjk} at that time. In the next step S510, the assist ratio is set to C _xjk selected in step S506. In the next step S512, it is determined whether or not the automatic mode 3 is set to OFF (OFF), and if the dynamic mode 3 is set to OFF (OFF), the process ends (END). On the other hand, if the automatic mode 3 is not set to OFF, the process proceeds to step S508, 1 is added to the value of l (l = l + 1), and the processes after step S502 are performed again.

Next, the automatic selection process according to the present embodiment will be described with reference to FIG. First, in step S600, automatic determination is performed based on the value of the standard deviation σx obtained in step S136 of FIG. Here, the value of the standard deviation σx is determined based on the threshold values σ1, σ2, σ3, and the assist ratio is set to a fixed value based on the determination, or the above-mentioned automatic change mode 1 and automatic change mode 2 are performed. Alternatively, the assist ratio is changed in any of the automatic change modes 3.

Here, σ1 <σ2 <σ3. First, when σx <σ1, the process proceeds to step S602, and all C _xjk are averaged to obtain Cx. In the next step S604, the assist ratio is set to Cx. After step S604, the process ends.

If σ1 ≦ σx <σ2, the process proceeds to step S606, and the assist ratio is changed in the automatic change mode 1.

If σ2 ≦ σx <σ3, the process proceeds to step S608, and the assist ratio is changed in the automatic change mode 2.

If σ3 ≦ σx, the process proceeds to step S610, and the assist ratio is changed in the automatic change mode 3.

When the standard deviation σx is sufficiently small, the change in the degree of discreteness for each operating state is small, so that the Cx obtained by averaging all the _Cxjk can be uniformly used as the assist ratio of the electric power steering system 600, and the steering feeling is good. Can be obtained. On the other hand, as the standard deviation σx increases, the variation of the assist ratio C _xjk for each operating state increases, so it is desirable to set the assist ratio more accurately according to the operating state. Therefore, in the present embodiment, as the standard deviation σx increases, the operating state used when extracting the assist ratio from the database 150, such as the operating state based on the driving path → the future operating state → the current operating state, is used. Change and change the mode as in the order of automatic change mode 1 (FIG. 9) → automatic change mode 2 (FIG. 13) → automatic change mode 3 (FIG. 16). This makes it possible to select the optimum assist ratio according to the standard deviation σx of the assist ratio obtained by the calculation.

Although the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person having ordinary knowledge in the field of technology to which the present invention belongs can come up with various modifications or modifications within the scope of the technical ideas described in the claims. , These are also naturally understood to belong to the technical scope of the present invention.

100 Assist ratio calculation device 124 Assist ratio calculation unit 128 Assist ratio deviation calculation unit 129 Assist ratio selection unit

Claims (7)

For each of the multiple settings of the steering assist ratio set by the power steering system, the individual driving the vehicle is classified according to the difference in the average vehicle speed and the average yaw rate when driving on a curve . A biometric information acquisition unit that acquires the acceleration of the arm and the amount of muscle activity of the arm related to the steering of the driver from the driver.
An assist ratio calculation unit that calculates the peak value of the assist ratio at which the acceleration of the arm and the degree of discreteness of the muscle activity of the arm are reduced for each driving state.
A storage unit for storing in the database in association with the peak value of the assist ratio, and the driving state,
An assist ratio deviation calculation unit that obtains the standard deviation of the peak value of the assist ratio based on the average value of the peak values of the assist ratio, and
As the assist ratio set by the power steering system when the driver actually drives the vehicle, the average value of the peak values of the assist ratio and the driving path are based on the standard deviation corresponding to the driver. Select either the assist ratio obtained by applying the operating state to the database, the assist ratio obtained by applying the future operating state to the database, or the assist ratio obtained by applying the current operating state to the database. Assist ratio selection unit and
A steering assist ratio determining device for a power steering system, which comprises. The steering assist ratio of the power steering system according to claim 1, wherein the assist ratio calculation unit calculates a peak value of the assist ratio at which the degree of discreteness of the Z score of the acceleration of the arm and the muscle activity of the arm becomes low. Decision device. The assist ratio calculation unit calculates the peak value of the assist ratio at which the degree of dispersal of the Z score becomes low based on an approximate curve that approximates the relationship between the plurality of the assist ratios and the degree of dispersal of the Z score. The steering assist ratio determining device for the power steering system according to claim 2 , which is characterized. By acquiring the vehicle speed and yaw rate for each curve section obtained from the map information and averaging the vehicle speed and yaw rate in all the curve sections, the average vehicle speed and average yaw rate according to the driving route can be obtained as the driving state according to the driving route. The steering assist ratio determining device for the power steering system according to any one of claims 1 to 3 , wherein the power steering system is obtained as a vehicle. The steering assist ratio determining device for a power steering system according to any one of claims 1 to 3 , wherein the future driving state is predicted based on the image information obtained from the image pickup device. The steering assist ratio determining device for a power steering system according to any one of claims 1 to 3 , wherein the sensor values of the vehicle speed and the yaw rate are acquired as the current driving state. For each of the multiple settings of the steering assist ratio set by the power steering system, the individual driving the vehicle is classified according to the difference in the average vehicle speed and the average yaw rate when driving on a curve . A step of acquiring the acceleration of the arm and the amount of muscle activity of the arm related to the steering of the driver from the driver.
A step of calculating the peak value of the assist ratio at which the degree of dispersion of the acceleration of the arm and the muscle activity of the arm becomes low for each of the driving states, and
A step of associating the peak value of the assist ratio with the operating state and recording it in a database.
A step of obtaining the standard deviation of the peak value of the assist ratio based on the average value of the peak value of the assist ratio, and
As the assist ratio set by the power steering system when the driver actually drives the vehicle, the average value of the peak values of the assist ratio and the driving path are based on the standard deviation corresponding to the driver. Select either the assist ratio obtained by applying the operating state to the database, the assist ratio obtained by applying the future operating state to the database, or the assist ratio obtained by applying the current operating state to the database. Steps to do and
A method for determining the steering assist ratio of a power steering system, which comprises the above.

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