Method of determining a short-term driving tendency and system of shift control which uses the method

Abstract

A method for determining a short-term driving tendency index, comprising: Detecting (S100) input variables, Determine (S110) whether an investigative condition of the tendency to travel short-term is met, Calculate (S120, S130, S140) trends and output membership function values ​​according to a plurality of fuzzy rules based on the input variables when the short-term driving trend determination condition is satisfied, and Determine (S150) a short-term trip tendency index based on the tendencies and output membership function values ​​according to the majority of fuzzy rules, where the determination condition of short-term journey tendency is met if a distance to a vehicle ahead is greater than or equal to a predetermined distance, a radius of curvature of a road ahead is greater than or equal to a predetermined curve radius, a gradient of a road is less than or equal to a predetermined gradient, or a road condition is not a slippery road, not an icy road, not an uneven road, or not an unpaved road.

Description

Background of the invention; Field of the invention

[0001] The present invention relates to a method for determining a short-term driving tendency and a system for shift control (or shift process control) which uses the method. In particular, the present invention relates to a method for determining a short-term driving tendency and a system for shift control which uses the method, which, by further accurately determining a short-term driving tendency, precisely reflects the driver's intention regarding the shift process (or the shift process corresponds to the driver's wish). Description of the related technology

[0002] Consumer satisfaction related to a vehicle's driving performance depends on how closely the vehicle behaves in accordance with the consumer's (or driver's) tendency (or intention). While consumer tendencies vary, a vehicle's performance characteristic within the same vehicle model is fixed to a single characteristic. Therefore, a vehicle's response (or behavior) may not always align with the consumer's tendency. Consequently, consumers often complain about the vehicle's driving performance. This means that if the consumer's driving tendency is captured and the vehicle's shifting is controlled to match that tendency, consumer satisfaction with the vehicle's driving performance can be maximized.

[0003] Therefore, many methods have been developed for learning the consumer's long-term driving tendency and controlling gear changes according to this learned tendency. The method of controlling gear changes / shifting according to the learned driving tendency is based on the assumption that the consumer's driving tendency is constant. However, the driver's driving tendency is not constant and changes according to temporary shifts in driver perception or intent, road conditions, and so on. Therefore, the learned driving tendency can deviate significantly from the driver's actual driving tendency at any given time. If the gear changes (or shifting) are controlled according to the learned driving tendency, the driver's current driving intent cannot be reflected in the gear change (i.e., the gear change does not correspond to the driver's wishes), and the driver may be dissatisfied with the driving performance.

[0004] For example, if the driver presses the accelerator pedal far (or applies it forcefully), a conventional shift control system cannot distinguish between the driver pressing the accelerator pedal far to drive uphill and / or to increase vehicle speed. Therefore, an incorrect shift (or gear selection) may be controlled, and the driver may be dissatisfied with the vehicle's performance.

[0005] The information disclosed in this section “Background of the Invention” is provided solely for a better understanding of the general background of the invention and should not be construed as an admission or any form of suggestion that this information constitutes the prior art known to the person skilled in the art.

[0006] For example, from each of DE 10 2012 223 381 A1, DE 10 2012 209 518 A1 and DE 10 2010 060 839 A1, a method for determining a short-term driving tendency index is known, wherein input variables are detected, the determination condition for a short-term driving tendency is determined, driving tendencies and output membership function values ​​are calculated, and a short-term driving tendency index is determined based on the tendencies and the output membership function values. Explanation of the invention

[0007] The present invention was undertaken in an effort to provide a method for determining a short-term driving tendency and a system for controlling the shifting which uses the method, which have the advantages of further accurate (or more precise) reflection of the driver's intention on the shifting process (or the shifting) by accurately determining a short-term driving tendency index of the driver, that is, a driving tendency for a short time (e.g. for current driving or for a predetermined time during current driving).

[0008] According to the invention, a method for determining a short-term driving tendency index with the features of claim 1 and a system for controlling switching with the features of claim 11 are provided. Further embodiments of the method and the system are described in the respective dependent claims. That is, a method for determining a short-term driving tendency index comprises: detecting input variables, determining whether a determination condition of the short-term driving tendency is met, calculating trends and output membership function values ​​according to a plurality of fuzzy rules.Fuzzy logic rules) based on the input variables, if the short-term travel tendency determination condition is met, and determining a short-term travel tendency index based on the tendencies and the output membership function values ​​according to the majority of fuzzy rules, wherein the short-term travel tendency determination condition is met if a distance to a preceding (or preceding) vehicle is greater than or equal to a predetermined distance, a radius of curvature of a preceding road is greater than or equal to a predetermined curve radius, a gradient of a road is less than or equal to a predetermined gradient, or a road condition is not a slippery road, (not) an icy road, (not) a bumpy road, or (not) an unpaved road.The input variables can include an accelerator pedal position, a rate of change of the accelerator pedal position, a vehicle speed, and a road incline.

[0009] Calculating the trends and output membership function values ​​according to the multiple fuzzy rules based on the input variables can involve calculating one trend and one output membership function value according to each of the multiple fuzzy rules. Calculating the trend and output membership function value according to each fuzzy rule can involve: determining whether the input variables satisfy the respective fuzzy rule; selecting a trend and an output membership function according to the respective fuzzy rule if the respective fuzzy rule is satisfied; calculating input membership function values ​​according to the input variables included in the respective fuzzy rule; calculating a minimum value of the input membership function values; and setting the minimum value as the output membership function value according to the respective fuzzy rule.The calculation of the tendency and output membership function value according to each fuzzy rule may further include setting a predetermined tendency and predetermined value as the respective tendency and output membership function value according to the respective fuzzy rule if the input variables do not satisfy the respective fuzzy rule.

[0010] Determining the short-term trip tendency index can involve: overlapping the majority of output membership functions in a short-term trip tendency index graph, calculating a midpoint of an area / region occupied by the majority of output membership function values ​​in the short-term trip tendency index graph, and setting the midpoint as the short-term trip tendency index.

[0011] Four fuzzy rules, three tendencies (gentle, normal, and sporty), and output membership functions according to each tendency can be preset. A first fuzzy rule could be that if the vehicle speed is low, the accelerator pedal position is medium, and the rate of change of the accelerator pedal position is medium, the tendency is normal. A second fuzzy rule could be that if the vehicle speed is low, the accelerator pedal position is medium, and the rate of change of the accelerator pedal position is high, the tendency is sporty. A third fuzzy rule could be that if the vehicle speed is high, the accelerator pedal position is high, and the rate of change of the accelerator pedal position is high, the tendency is sporty. A fourth fuzzy rule could be that if the accelerator pedal position is medium and the road camber is high, the tendency is normal.

[0012] Furthermore, a shift control system according to numerous aspects of the present invention comprises: an accelerator pedal position sensor which detects an accelerator pedal position, a vehicle speed sensor which detects a vehicle speed, a navigation device which is configured to provide road information including the inclination of a road, a control device which receives information about input variables from the accelerator pedal position sensor, the vehicle speed sensor and the navigation device, which include the accelerator pedal position, the vehicle speed and the inclination of the road, which determines a short-term driving tendency of a driver based on the information and which controls an engine (e.g. an internal combustion engine) or a transmission (e.g. a gearbox).an automatic transmission) according to the short-term trip tendency index, wherein the control device computes tendencies and output membership function values ​​according to a plurality of fuzzy rules (or fuzzy logic rules) based on the input variables and determines the short-term trip tendency index based on the tendencies and output membership function values ​​according to the plurality of fuzzy rules, wherein. The control device determines the short-term driving tendency index when the distance to a vehicle ahead is greater than or equal to a predetermined distance, the radius of curvature of a road ahead is greater than or equal to a predetermined curve radius, the gradient of the road is less than or equal to a predetermined gradient, or the road condition is not a slippery road, (not) an icy road, (not) an uneven road, or (not) an unpaved road.

[0013] The control device can calculate the trends and output membership function values ​​according to the majority of fuzzy rules based on the input variables by calculating the trend and output membership function value according to each fuzzy rule. The control device can calculate the trend and output membership function value according to each fuzzy rule by selecting the trend and output membership function according to the respective fuzzy rule, can calculate input membership function values ​​according to the input variables contained in the respective fuzzy rule, and can calculate a minimum value of the input membership function values ​​as the output membership function value according to the respective fuzzy rule.

[0014] The control device can determine whether the input variables satisfy the respective fuzzy rule, can select the tendency and output membership function according to the respective fuzzy rule if the respective fuzzy rule is satisfied, and can set a predetermined tendency and a predetermined value as the respective tendency and output membership function value according to the respective fuzzy rule if the respective fuzzy rule is not satisfied.

[0015] The control device can determine the short-term trip tendency index by overlapping the majority of output membership functions in a short-term trip tendency representation and can calculate a midpoint of an area occupied by the majority of output membership function values ​​in the short-term trip tendency index diagram.

[0016] The methods and devices of the present invention have other features and advantages, which will become clear from the accompanying drawings included herein and the following detailed description, which together serve to explain certain principles of the present invention, or which are explained in more detail therein. Brief description of the drawings Fig. Figure 1 is a block diagram of an exemplary switching control system according to the present invention. Fig. Figure 2 is a flowchart of an exemplary method for determining a short-term driving tendency index according to the present invention. Fig. Figure 3 is a flowchart of calculating an i-th tendency and an i-th output membership function value according to an i-th fuzzy rule in an exemplary method of determining a short-term driving tendency according to the present invention. Fig. Figure 4 is a flowchart of determining a short-term trend index in an exemplary method of determining a short-term driving trend according to the present invention. Fig. Table 5 shows exemplary fuzzy rules. Fig. Figure 6 is a diagram showing example input membership functions. Fig. Figure 7 is a diagram showing example output membership functions. Fig. Figure 8 is a diagram illustrating the determination of a short-term driving tendency index in an exemplary method of determining a short-term driving tendency index according to the present invention. Detailed description

[0017] Reference will now be made in detail to various embodiments of the present invention, examples of which are illustrated in the accompanying drawings and described below. Although the invention is described in connection with the exemplary embodiments, it is clear that the present description is not intended to limit the invention to these exemplary embodiments.

[0018] The Fig. Figure 1 is a block diagram of a switching control system according to numerous embodiments of the present invention. As in the Fig. Figure 1 shows a switching control system comprising a data detector 10, a control device 20, a transmission 30 and a motor (e.g. an internal combustion engine) 40.

[0019] The data detector 10 detects data to determine a short-term driving tendency index of a driver, and the data detected by the data detector 10 are transmitted to the control device 20. The data detector 10 includes an accelerator pedal position sensor 11, a vehicle speed sensor 12, a navigation device 13, and a global positioning system (GPS) 14.

[0020] The accelerator pedal position sensor 11 detects the degree to which a driver presses (i.e., operates) the accelerator pedal. In other words, the accelerator pedal position sensor 11 detects data relating to the driver's intention to accelerate.

[0021] The vehicle speed sensor 12 detects the vehicle speed and is attached to (e.g., in) a wheel of the vehicle. In some cases, the vehicle speed can be calculated based on a GPS signal received via GPS 14.

[0022] A target gear shift stage can be calculated using a gear shift pattern based on the signal from the accelerator pedal position sensor 11 and the signal from the vehicle speed sensor 12, and the shifting process / shifting to the target gear shift stage is controlled. This means that hydraulic pressure, which is supplied to or released from a plurality of friction elements, is controlled in an automatic transmission equipped with a plurality of planetary gear sets and a plurality of friction elements. Additionally, an (electrical) current applied to a plurality of synchronizers and actuators is controlled in a dual-clutch transmission.

[0023] The navigation device 13 is a device that informs the driver about a route to a destination. The navigation device (or navigation system) 13 comprises an input / output section that inputs or outputs information for route guidance, an instantaneous position detection section that detects information about the vehicle's current position, a memory unit in which map data for route calculation and route guidance data are stored, and a control section for searching for the route and executing route guidance. However, in an exemplary embodiment of the present invention, it is sufficient that the navigation device 13 can provide information about a road's geometry, such as a road's gradient or radius of curvature, to the control device 20.Therefore, it is clear that the navigation device 13 in this description and the claims includes (or may include) any device which can provide information about the road characteristics to the control device 20.

[0024] The GPS 14 receives a signal emitted by a GPS satellite and transmits a corresponding signal to the navigation device 13.

[0025] The control device 20 determines the driver's short-term driving tendency, that is, a driving tendency for a relatively short period of time, based on the data detected by the data detector 10. In other words, the control device 20 determines the driver's driving tendency, for example, during current driving or for a predetermined time during (or while driving). The driver's short-term driving tendency can be determined based on how well one or more assumptions regarding the driver's driving tendency are fulfilled, and fuzzy control theory can be used to determine the driver's short-term driving tendency.For these purposes, the control device 20 can be implemented by means of one or more processors, which is / are activated by means of a predetermined program, and the predetermined program can be programmed to execute each step of a method of determining a short-term driving tendency according to an exemplary embodiment of the present invention.

[0026] Furthermore, the control device 20 controls the transmission 30 or the engine 40 according to the short-term driving tendency index. That is, the control device 20 can change a gear shift pattern, a shift feel to (or an engagement feel of) the target gear stage, an engine torque map and / or an engine torque filter according to the short-term driving tendency index.

[0027] With regard to the Fig. Sections 2 to 4 below describe in detail a method for determining a short-term driving tendency according to numerous exemplary embodiments of the present invention. Fig. Figure 2 is a flowchart of a procedure for determining a short-term travel tendency, which Fig. Figure 3 is a flowchart of calculating an i-th tendency and an i-th output membership function value according to an i-th fuzzy rule in a procedure for determining a short-term driving tendency, and the Fig. Figure 4 is a flowchart of determining a short-term driving tendency in a method of determining a short-term driving tendency according to numerous embodiments of the present invention.

[0028] As in the Fig. Figure 2 shows a method for determining a short-term driving tendency according to numerous embodiments of the present invention, beginning with the detection of input variables at step S100. When the data detector 10 detects the data and transmits it to the control device 20, the control device 20 determines at step S110 whether the determination condition for the short-term driving tendency index is met. For example, the determination condition for the short-term driving tendency may be met (but is not limited to this) if a distance to a preceding (or(preceding) vehicle is greater than or equal to a predetermined distance, a radius of curvature of a road ahead is greater than or equal to a predetermined radius of curvature, a gradient of a road is less than or equal to a predetermined gradient, or a road condition is not a slippery road, not an icy road, not an uneven road, or not an unpaved road.

[0029] If the short-term travel tendency determination condition is not met at step S110, the control device 20 terminates the short-term travel tendency determination process according to numerous embodiments of the present invention. If the short-term travel tendency determination condition is met at step S110, the control device 20 calculates a first tendency and a first output membership function value according to a first fuzzy rule at step S120, and calculates a second tendency and a second output membership function value according to a second fuzzy rule at step S130. The calculation of the tendency and the output membership function value is repeated using the predetermined number (e.g., L) of fuzzy rules.

[0030] If, at step S140, the control device 20 calculates an I-th (L-th) tendency and an I-th (L-th) output membership function value according to an I-th (L-th) fuzzy rule, at step S150 the control device 20 determines a short-term driving tendency index based on the calculated tendencies and the output membership function values. Thereafter, the control device 20 terminates the process of determining the short-term driving tendency according to the exemplary embodiment of the present invention and controls the transmission 30 or the motor 40 based on the short-term driving tendency index.

[0031] The following describes in detail the calculation of an i-th tendency and an i-th output membership function value according to an i-th fuzzy rule. First, as in the Fig. As shown in Figure 3, the control device 20 determines at step S210 whether the input variables satisfy the i-th fuzzy rule. The i-th fuzzy rule can be an assumption suitable for determining the driver's short-term driving tendency index and can be predefined.

[0032] If, at step S210, the input variables do not satisfy the i-th fuzzy rule, the control device, at step S260, sets a predetermined value and a predetermined tendency as the (respective) i-th output membership function value and the (respective) i-th tendency and exits the calculation of the i-th tendency and the i-th output membership function value according to the i-th fuzzy rule.

[0033] If, at step S210, the input variables satisfy the i-th fuzzy rule, the control device 20 selects the i-th tendency and the i-th output membership function at step S220. The i-th output membership function can be defined according to the i-th tendency. Then, at step S230, the control device 20 calculates input membership function values ​​according to the input variables included in the i-th fuzzy rule. If, at step S230, the input membership function values ​​have been calculated according to a plurality of input variables, the control device 20 calculates a minimum value of the input membership function values ​​at step S240. The control device 20 then sets this minimum value as the i-th output membership function value and exits the calculation of the i-th tendency and the i-th output membership function value according to the i-th fuzzy rule.

[0034] The following section describes in detail how to determine a short-term trend index. As in the Fig. As shown in Figure 4, the control device 20 overlaps the predetermined number n of output membership functions in the short-term driving tendency index diagram at step S310. In numerous exemplary embodiments, the number of output membership functions can be three, as shown in the Fig. Figure 7 shows that the number of output membership functions is not limited to three. Then, at step S320, the control device 20 calculates a center point (e.g., geometric, weighted, or a center of mass) of an area / region occupied (or bounded) by the number L of output membership function values ​​and, at step S330, sets the center point as the short-term travel tendency index.

[0035] The following refers to the Fig. Sections 5 to 8 describe in detail a method for determining the short-term driving tendency index according to an exemplary embodiment of the present invention. It is clear that the description illustrates only one example and that the scope of the present invention is not limited by this description.

[0036] The Fig. Table 5 shows exemplary fuzzy rules that Fig. Figure 6 is a diagram showing exemplary input membership functions that Fig. Figure 7 is a diagram showing example output membership functions, and the Fig. Figure 8 is a diagram illustrating the determination of a short-term driving tendency index according to an exemplary embodiment of the present invention.

[0037] As in the Fig. Figure 5 shows an example to explain the procedure for determining the short-term driving tendency index. Four fuzzy rules are used, and the input variables included in the four fuzzy rules are the accelerator pedal position, the rate of change of the accelerator pedal position, the vehicle speed, and the slope of the road.

[0038] Furthermore, as in the Fig. As shown in Figure 6, at least one input membership function is predetermined for each input variable. For example, two input membership functions are predetermined for the vehicle speed: input membership function (MF1-L) for a low vehicle speed and input membership function (MF1-H) for a high vehicle speed. Here, a state (or property or value) of the input variable is designated by a "low" state, a "medium" state, and a "high" state, but they are not limited to these.

[0039] Furthermore, as in the Fig. Figure 7 shows that the output membership functions are also predetermined. Three output membership functions (e.g., an output membership function for "gentle," an output membership function for "normal," and an output membership function for "sporty") are used in an example to illustrate the procedure for determining the short-term driving tendency index, but they are not limited to this. The output membership functions are determined according to the tendencies. That is, if any fuzzy rule is satisfied and the tendency to be "gentle" is determined, the output membership function for "gentle" is used.

[0040] Referring again to the Fig. Rule 5 specifies a first fuzzy rule stating that the vehicle speed is "low," the accelerator pedal position is "medium," the rate of change of the accelerator pedal position is "medium," and the tendency is "normal." A second fuzzy rule specifies that the vehicle speed is "low," the accelerator pedal position is "medium," the rate of change of the accelerator pedal position is "high," and the tendency is "sporty." A third fuzzy rule specifies that the vehicle speed is "high," the accelerator pedal position is "high," and the tendency is "sporty." A fourth fuzzy rule specifies that the accelerator pedal position is "medium," the road gradient is "high," and the tendency is "normal."

[0041] A case in which the vehicle speed is 20 km / h, the accelerator pedal position is 50% (the accelerator pedal position is 0% when the accelerator pedal is not pressed, and the accelerator pedal position is 100% when the accelerator pedal is fully pressed) and the rate of change of the accelerator pedal position is 50% / s is explained.

[0042] If the vehicle speed is 20 km / h, the control device 20 can determine whether the vehicle speed is "low" or "medium". If the accelerator pedal position is 50%, the control device 20 can determine whether the accelerator pedal position is "low", "medium", or "high". Furthermore, if the rate of change of the accelerator pedal position is 50% / s, the control device 20 can determine whether the rate of change of the accelerator pedal position is "low", "medium", or "high".

[0043] The control device 20 determines the fuzzy rules that are satisfied by the input variables. Based on the results determined above for the input variables, control device 20 determines that the input variables satisfy the first fuzzy rule and the second fuzzy rule, but do not satisfy the third and fourth fuzzy rules.

[0044] As described above, if the input variables do not satisfy the i-th fuzzy rule, the control device 20 can set the predetermined value and predetermined tendency as the respective i-th output membership function value and the respective i-th tendency. In an example to illustrate the procedure for determining the short-term driving tendency index, the predetermined tendency can be "soft" and the predetermined value can be 1.

[0045] As a result, the control device 20 determines that the tendency according to the first fuzzy rule is “normal”, the tendency according to the second fuzzy rule is “sporty”, the tendency according to the third fuzzy rule is “gentle”, and the tendency according to the fourth fuzzy rule is “gentle”.

[0046] Referring again to the Fig. 6. If the vehicle speed is 20 km / h, the input membership function value in the input membership function (MF1-L) for low vehicle speed is 0.6. If the accelerator pedal position is 50%, the input membership function value in the input membership function (MF2-M) for a medium accelerator pedal position is 1 (one). If the rate of change of the accelerator pedal position is 50% / s, the input membership function value in the input membership function (MF3-M) for a medium rate of change of the accelerator pedal position is 1 (one). If the rate of change of the accelerator pedal position is 50% / s, the input membership function value in the input membership function (MF3-M) for a high rate of change of the accelerator pedal position is 0.1.

[0047] When the control device 20 calculates the input membership function values ​​according to the input variables contained in the first fuzzy rule and the input membership function values ​​according to the input variables contained in the second fuzzy rule as described above, the control device 20 calculates the minimum value of the input membership function values ​​according to the corresponding fuzzy rule as the output membership function value according to the corresponding fuzzy rule.

[0048] As a result, the control device 20 calculates that the output membership function value according to the first fuzzy rule is 0.6, that the output membership function value according to the second fuzzy rule is 0.1, that the output membership function value according to the third fuzzy rule is 1, and that the output membership function value according to the fourth fuzzy rule is 1.

[0049] After that, the control device 20 overlaps the output membership functions, which are in the Fig. 7 are shown in a short-term trip tendency index diagram (see Fig. 8). In the Fig. 8 represents the y-axis as the output membership function value and the x-axis as the short-term trip tendency index.

[0050] The control device 20 then marks (or determines) the output membership function value according to each fuzzy rule on the corresponding output membership function. That is, 0.6, which is the output membership function value according to the first fuzzy rule, is marked on the output membership function for the "normal" tendency; 0.1, which is the output membership function value according to the second fuzzy rule, is marked on the output membership function for the "sporty" tendency; 1, which is the output membership function value according to the third fuzzy rule, is marked on the output membership function for the "gentle" tendency; and 1, which is the output membership function value according to the fourth fuzzy rule, is marked on the output membership function for the "gentle" tendency (referring to a hatched area in the Fig. 8).

[0051] The control device 20 then calculates the center point (e.g., geometric, weighted, or the center of mass) of the area / region occupied by the four output membership function values ​​(since one x-value represents the short-term driving tendency index in the Fig. 8 represents, the x-value of the midpoint is calculated), and defines the midpoint as the short-term trip tendency index. That is, in the Fig. 8 is set to 35 as the short-term driving tendency index. When the short-term driving tendency index is set, the control device 20 controls the shifting process (or the gear shift stage) according to the short-term driving tendency index.

[0052] As described above, the driver's tendency to drive short distances can be precisely determined according to an exemplary embodiment of the present invention. Therefore, the driver's intention to drive (or desire to drive) can be accurately reflected in the shifting / shifting process (e.g., the gear selection). Furthermore, it is understandable that the values ​​used here (e.g., 20 km / h; 50%; 0.1; 0.6 or 35) are easily adjustable.

Claims

[1] A method for determining a short-term driving tendency index, comprising: Detecting (S100) input variables, Determine (S110) whether an investigative condition of the tendency to travel short-term is met, Calculate (S120, S130, S140) trends and output membership function values ​​according to a plurality of fuzzy rules based on the input variables when the short-term driving trend determination condition is met, and Determine (S150) a short-term trip tendency index based on the tendencies and output membership function values ​​according to the majority of fuzzy rules, where the determination condition of short-term journey tendency is met if a distance to a vehicle ahead is greater than or equal to a predetermined distance, a radius of curvature of a road ahead is greater than or equal to a predetermined curve radius, a gradient of a road is less than or equal to a predetermined gradient, or a road condition is not a slippery road, not an icy road, not an uneven road, or not an unpaved road. [2] The method according to claim 1, wherein the input variables are an accelerator pedal position, a rate of change of the accelerator pedal position, a vehicle speed and a gradient of a road. [3] The method according to claim 1 or 2, wherein the calculation of the tendencies and the output membership function values ​​according to the plurality of fuzzy rules based on the input variables comprises calculating a tendency and an output membership function value according to each fuzzy rule of the plurality of fuzzy rules, and wherein the calculation of the tendency and the output membership function value according to each fuzzy rule comprises: Determine (S210) whether the input variables satisfy the respective fuzzy rule, Selecting (S220) a tendency and an output membership function according to the respective fuzzy rule, if the respective fuzzy rule is satisfied, Calculating (S230) input membership function values ​​according to the input variables contained in the respective fuzzy rule, Calculate (S240) a minimum value of the input membership function values, and Setting (S250) the minimum value as the output membership function value according to the respective fuzzy rule. [4] The method according to any one of claims 1 to 3, further comprising the calculation of the tendency and the output membership function value according to each fuzzy rule: Setting (S260) a predetermined tendency and a predetermined value as the respective tendency and output membership function value according to the respective fuzzy rule when the input variables do not satisfy the respective fuzzy rule. [5] The method according to claim 1, wherein the determination of the short-term driving tendency index comprises: Overlap (S310) of the majority of output membership functions in a short-term trip tendency index diagram, Calculate (S320) a midpoint of a range occupied by the majority of output membership function values ​​in the short-term trip tendency index diagram, and Defining (S330) the midpoint as the short-term travel tendency index. [6] The method according to any of the preceding claims, wherein four fuzzy rules, three tendencies, which have gentle, normal and sporty, and output membership functions according to each tendency are preset. [7] The method according to any one of claims 1 to 6, wherein a first fuzzy rule provides that when the vehicle speed is low, the accelerator pedal position is medium and the rate of change of the accelerator pedal position is medium, the tendency is normal. [8] The method according to any one of claims 1 to 6, wherein a second fuzzy rule provides that when the vehicle speed is low, the accelerator pedal position is medium, and the rate of change of the accelerator pedal position is high, the tendency is sporty. [9] The method according to any one of claims 1 to 6, wherein a third fuzzy rule provides that if the vehicle speed is high, the accelerator pedal position is high and the rate of change of the accelerator pedal position is high, the tendency is sporty. [10] The method according to any one of claims 1 to 6, wherein a fourth fuzzy rule provides that when the accelerator pedal position is medium and the incline of the road is high, the tendency is normal. [11] A system for controlling switching, comprising: an accelerator pedal position sensor (11) which detects an accelerator pedal position, a vehicle speed sensor (12) which detects a vehicle speed, a navigation device (13) which is configured to provide road information which includes a gradient of a road, a control device (20) which receives information about input variables from the accelerator pedal position sensor (11), the vehicle speed sensor (12) and the navigation device (13), which includes the accelerator pedal position, the vehicle speed and the inclination of the road, which determines a short-term driving tendency of a driver based on the information and which controls an engine (40) or a transmission (30) according to the short-term driving tendency index, wherein the control device (20) calculates tendencies and output membership function values ​​according to a plurality of fuzzy rules based on the input variables and determines the short-term driving tendency index based on the tendencies and output membership function values ​​according to the plurality of fuzzy rules, and wherein the control device (20) determines the short-term driving tendency index when a distance to a vehicle ahead is greater than or equal to a predetermined distance, a radius of curvature of a road ahead is greater than or equal to a predetermined curve radius, the gradient of the road is less than or equal to a predetermined gradient, or a road condition is not a slippery road, not an icy road, not an uneven road or not an unpaved road. [12] The system according to claim 11, wherein the control device (20) calculates the tendencies and the output membership function values ​​according to the plurality of fuzzy rules based on the input variables by calculating the tendency and the output membership function value according to each fuzzy rule. [13] The system according to claim 11 or 12, wherein the control device (20) calculates the tendency and output membership function value according to each fuzzy rule by selecting the tendency and output membership function according to the respective fuzzy rule, calculates input membership function values ​​according to the input variables which are included in the respective fuzzy rule, and calculates a minimum value of the input membership function values ​​as the output membership function value according to the respective fuzzy rule. [14] The system according to any one of claims 11 to 13, wherein the control device (20) determines whether the input variables satisfy the respective fuzzy rule, selects the tendency and the output membership function according to the respective fuzzy rule if the respective fuzzy rule is satisfied, and sets a predetermined tendency and a predetermined value as the respective tendency and the respective output membership function value according to the respective fuzzy rule if the respective fuzzy rule is not satisfied. [15] The system according to any one of claims 11 to 14, wherein the control device determines the short-term driving tendency index by overlapping the plurality of output membership functions in a short-term driving tendency representation and calculates a midpoint of a region occupied by the plurality of output membership function values ​​in the short-term driving tendency index diagram.

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