JP2006046149A - Operation support device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an operation support device capable of reducing cost and mounting a vehicle without selecting it by eliminating the necessity for preparing a fuel consumption map beforehand. <P>SOLUTION: A running condition detection means 10a-1 detects a running condition of the vehicle. A fuel consumption detection means 10a-2 detects fuel consumption information of the vehicle. A learning means 10a-3 performs learning for setting the detected running condition information to be input and the detected fuel consumption information to be output. A deducing means 10a-4 deduces fuel consumption information with respect to the inputted running condition information by using the result of learning performed by the learning means 10a-3. An input means 10a-5 inputs the running condition information to the deducing means 10a-4. A support means 10a-6 supports fuel saving operation based on comparison of the current fuel consumption information detected by the fuel consumption detection means 10a-2 with the fuel consumption information deduced by the deducing means 10a-4. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a driving support device that supports fuel-saving driving.

  As the driving support apparatus described above, for example, a vehicle driving state evaluation system described in Patent Document 1 has been proposed. According to this vehicle operating state evaluation system, the current engine fuel efficiency is calculated from the current engine speed and load with reference to the fuel efficiency map that defines the relationship between the engine speed, load, and fuel efficiency. .

  Further, the engine rotational speed and load at the time of upshifting are obtained, and the fuel efficiency ratio of the engine at the time of upshifting is calculated with reference to the fuel efficiency ratio map described above. Then, the shift-up is promoted when the fuel consumption rate is smaller than the calculated current fuel consumption rate.

In addition, it is described that the above-described fuel consumption rate map is created based on data obtained at the time of engine development, or created based on a test result of a vehicle running test. In any case, the fuel consumption rate map is created in advance before being mounted on the vehicle.
JP 2004-60548 A

  However, in the above-described conventional vehicle driving state evaluation system, it is necessary to create a fuel consumption rate map in advance. This fuel consumption rate map is different for each mounted engine. Therefore, it is necessary to create it for each mounted engine, which causes a problem in terms of cost. There is also a problem that it cannot be used for a vehicle equipped with an engine for which a fuel consumption map is not created. Furthermore, since the fuel efficiency rate map may differ slightly depending on the mounted vehicle as well as the difference between the mounted engines, the conventional system cannot provide accurate fuel efficiency driving support.

  In addition, even if the fuel consumption rate map changes due to changes in the vehicle over time, accurate fuel consumption driving support cannot be performed. Furthermore, the driving instruction is only for upshifting, and no specific accelerator opening instruction is given.

  In view of the above, the present invention provides a driving support device that can be mounted without selecting a vehicle while reducing costs by eliminating the need to create a fuel efficiency map in advance by paying attention to the above problems. The task is to do.

  According to the first aspect of the present invention, according to the basic configuration diagram shown in FIG. 1, the driving state detection means 10a-1 for detecting the driving state information of the vehicle and the fuel consumption detection means 10a-2 for detecting the fuel consumption information of the vehicle. Learning means 10a-3 that performs learning using the detected traveling state information as input and the detected fuel consumption information as output, and the input traveling state using the learning result performed by the learning means Inference means 10a-4 for inferring fuel consumption information for information, input means 10a-5 for inputting driving state information to the inference means, current fuel consumption information detected by the fuel consumption detection means, and inference means by the inference means The driving support apparatus is characterized by comprising support means 10a-6 for supporting fuel-saving driving based on comparison with the fuel efficiency information.

  According to the first aspect of the present invention, the traveling state detection means 10a-1 detects the traveling state of the vehicle. The fuel consumption detection means 10a-2 detects vehicle fuel consumption information. The learning unit 10a-3 performs learning using the detected traveling state information as an input and the detected fuel consumption information as an output. The inference means 10a-4 infers the fuel consumption information for the input driving state information using the learning result obtained by the learning means. The input means 10a-5 inputs the running state information to the inference means. The support unit 10a-6 supports fuel-saving driving based on a comparison between the current fuel consumption information detected by the fuel consumption detection unit 10a-2 and the fuel consumption information inferred by the inference unit 10a-4.

  Therefore, using the detection results of the driving state detection unit 10a-1 and the fuel consumption detection unit 10a-2, learning is performed using the driving state information as input and outputting the fuel consumption information, and driving assistance is performed using the learning result. Is called. That is, the relationship between the driving state information and the fuel consumption information can be obtained by learning performed during traveling, and it is not necessary to create a map indicating the relationship between the driving state information and the fuel consumption information in advance.

  According to a second aspect of the present invention, there is provided the driving support apparatus according to the first aspect, wherein the fuel consumption detection means detects a fuel consumption per unit time as the fuel consumption information. Exist.

  According to the second aspect of the present invention, accurate fuel consumption information can be obtained by detecting the fuel consumption per unit time as the fuel consumption information.

  A third aspect of the present invention is the driving support device according to the first aspect, wherein the fuel consumption detection means detects an efficiency coefficient obtained from a vehicle speed and an accelerator opening as the fuel consumption information. It exists in the driving assistance device.

  According to the third aspect of the invention, by detecting the efficiency coefficient obtained from the vehicle speed and the accelerator opening as the fuel consumption information, the fuel consumption information can be obtained without using a fuel meter that measures the fuel consumption. Can do.

  A fourth aspect of the present invention is the driving support apparatus according to any one of the first to third aspects, wherein the input means inputs the current travel state information detected by the travel state detection means to the inference means. It exists in the driving assistance device characterized by doing.

  According to the invention described in claim 4, the input means inputs the current running state information detected by the running state detecting means to the inference means. Therefore, it can be determined whether or not the current fuel consumption information for the current running state information is in a state with good fuel consumption.

  The invention according to claim 5 is the driving support device according to claim 4, wherein the support means infers from the current running state information by the current fuel consumption information detected by the fuel consumption detection means and the inference means. The present invention resides in a driving support device that detects a current fuel consumption state of a vehicle based on a comparison with the fuel consumption information and notifies the driver.

  According to the fifth aspect of the present invention, the support means is configured to compare the current fuel consumption information detected by the fuel consumption detection means with the fuel consumption information inferred from the current running state information by the inference means. The state is detected and the driver is notified. Therefore, the driver can grasp whether the current fuel consumption state is good or bad.

  A sixth aspect of the present invention is the driving support apparatus according to any one of the first to fifth aspects, wherein the travel information detecting means includes input travel state information serving as an input of the learning means, and the learning means. Detecting the output travel state information to be output, the learning means performs the learning using the detected input travel state information as an input, the detected fuel consumption information and the output travel state information as an output, and The input means inputs the current input travel state information detected by the travel state detection means to the inference means, and the inference means uses the learning result performed by the learning means to input the input current input travel state. The fuel consumption information and the output travel state information are inferred with respect to the state information, and the support means determines that the vehicle travels when the current fuel consumption information detected by the fuel consumption detection means is worse than the fuel consumption information inferred by the inference means. State resides in the driving support apparatus characterized by prompted to output running state information inferred by the inference means.

  According to the sixth aspect of the present invention, the travel information detecting means detects the input travel state information that becomes the input of the learning means and the output travel state information that becomes the output of the learning means. The learning means performs learning using the detected input travel state information as an input and the detected fuel consumption information and output travel state information as an output. The input means inputs the current input travel state information detected by the travel state detection means to the inference means. The inference means infers the fuel consumption information and the output travel state information for the input current input travel state information using the learning result performed by the learning unit. When the current fuel consumption information detected by the fuel consumption detection means is worse than the fuel consumption information inferred by the inference means, the support means prompts the driving state of the vehicle to be the output travel state information inferred by the inference means. Therefore, it is possible to advise the driver about the output travel state information that can save fuel.

  A seventh aspect of the present invention is the driving support apparatus according to the sixth aspect, wherein the accelerator opening of the vehicle is used as the output travel state information, and the support means has the current fuel consumption information detected by the fuel consumption detection means. When the fuel consumption information inferred by the inference means is worse, the driving assistance device is urged to open the accelerator opening inferred by the inference means.

  According to the invention of claim 7, the accelerator opening of the vehicle is used as the output travel state information. The support means urges the accelerator opening estimated by the inference means when the current fuel efficiency information detected by the fuel efficiency detection means is worse than the fuel efficiency information inferred by the inference means. Therefore, it is possible to advise the driver about the accelerator opening that can save fuel.

  The invention according to claim 8 is the driving support apparatus according to any one of claims 1 to 7, wherein the input means inputs a plurality of patterns of driving state information to the inference means, and the support means includes: When the current fuel consumption information detected by the fuel consumption detection means is worse than the best fuel efficiency information inferred by the inference means with respect to the input of the plurality of patterns of travel state information, The driving support apparatus is characterized by prompting to make the driving state information input at the time of inferring the best fuel efficiency information.

  According to the invention described in claim 8, the input means inputs a plurality of patterns of running state information to the inference means. When the current fuel efficiency information detected by the fuel efficiency detection means is worse than the best fuel efficiency information inferred by the inference means for the input of the driving state information of a plurality of patterns, the support means Prompt to use the driving state information that was input when inferring the best fuel economy information. Therefore, it is possible to advise the driver about the driving state information that can save fuel.

  A ninth aspect of the present invention is the driving support apparatus according to the eighth aspect, wherein the traveling state detecting unit detects traveling state information including a gear ratio of the vehicle, and the input unit includes a plurality of patterns of gears. The combination of the ratio and the current running state information detected by the running state detection unit, excluding the gear ratio, is input to the inference unit, and the support unit is configured to input the gear ratios of the plurality of patterns. When the current fuel consumption information detected by the fuel consumption detection means is worse than the best fuel efficiency information inferred by the inference means, the gear ratio input at the time of inference of the best fuel information is urged. It exists in the driving assistance device characterized by this.

  According to the ninth aspect of the present invention, the traveling state detection means detects traveling state information including the gear ratio of the vehicle. The input means inputs a combination of a plurality of patterns of gear ratios and the current travel state information detected by the travel state detection means, excluding the gear ratio, to the inference means. The assisting means determines when the best fuel information is inferred when the current fuel efficiency information detected by the fuel efficiency detecting means is worse than the best fuel efficiency information inferred by the inference means for the input of gear ratios of a plurality of patterns. Prompt to use the input gear ratio. Therefore, it is possible to advise the driver about a gear ratio that can save fuel.

  A tenth aspect of the present invention is the driving support apparatus according to any one of the sixth to ninth aspects, wherein the traveling state detecting means detects the speed of the vehicle as the traveling state information, and the learning means is the vehicle. The driving support apparatus is characterized in that learning is performed with the speed of the input as an input, and the input means inputs the current speed of the vehicle to the inference means.

  According to the tenth aspect of the present invention, the traveling state detecting means detects the vehicle speed as the traveling state information. Learning means learns with the speed of the vehicle as an input. The input means inputs the current speed of the vehicle to the inference means. Therefore, by setting the vehicle speed as the driving state information input to the learning means, it is possible to advise the driver about the driving state information that saves fuel while keeping the speed constant.

  The invention according to claim 11 is the driving support apparatus according to any one of claims 1 to 10, wherein the traveling state detecting means is configured to determine a vehicle speed, vehicle engine load information, and a vehicle gear ratio. It exists in the driving assistance device characterized by detecting as information.

  According to the eleventh aspect of the present invention, the traveling state detection means detects the vehicle speed, the vehicle engine load information, and the vehicle gear ratio as the traveling state information. Therefore, the relationship between the speed, load information and gear ratio and fuel consumption information can be obtained by learning performed while the vehicle is running, and a map showing the relationship between the speed, load information and gear ratio and fuel consumption information needs to be created. There is no.

  A twelfth aspect of the invention is the driving support apparatus according to the eleventh aspect, wherein the traveling state detecting means detects accelerator opening / engine speed as load information. .

  According to the twelfth aspect of the present invention, the traveling state detecting means detects the accelerator opening / engine speed as load information. Therefore, load information can be easily obtained based on the accelerator opening / engine speed.

  A thirteenth aspect of the present invention is the driving support apparatus according to the twelfth aspect of the present invention, wherein the traveling state detecting means detects a vehicle speed / engine speed as a gear ratio. .

  According to a thirteenth aspect of the present invention, the traveling state detection means detects the vehicle speed / engine speed as a gear ratio. Therefore, the gear ratio can be obtained by using the vehicle speed of the running state information and the engine speed for obtaining the load information.

  As described above, according to the first aspect of the present invention, learning is performed by using the detection results obtained by the driving state detection unit and the fuel consumption detection unit, using the driving state information as input, and outputting the fuel consumption information. Driving assistance is performed using. In other words, the relationship between the driving state information and the fuel consumption information can be obtained by learning performed while the vehicle is traveling, and it is not necessary to create a map showing the relationship between the driving state information and the fuel consumption information in advance. In addition, it is possible to obtain a driving support device that can be mounted without selecting a vehicle.

  According to the invention described in claim 2, by detecting the fuel consumption per unit time as the fuel consumption information, it is possible to obtain a driving support device capable of obtaining accurate fuel consumption information.

  According to the third aspect of the present invention, fuel efficiency information can be obtained without using a fuel gauge by detecting an efficiency coefficient obtained from vehicle speed / accelerator opening as fuel efficiency information. It is possible to obtain a driving support device that can be used even in a vehicle not equipped with a vehicle.

  According to the fourth aspect of the present invention, it is possible to obtain a driving support device that can determine whether or not the current fuel consumption information corresponding to the current running state information is in a state with good fuel consumption.

  According to the fifth aspect of the present invention, since the driver can grasp whether the current fuel consumption state is good or bad, it is possible to obtain a driving assistance device capable of performing appropriate driving assistance.

  According to the sixth aspect of the present invention, the driver can be advised with respect to output travel state information that can save fuel, and thus a driving support device that can perform appropriate driving support can be obtained.

  According to the seventh aspect of the present invention, the driver can be advised about the accelerator opening that can save fuel, and thus a driving support device that can perform appropriate driving support can be obtained.

  According to the eighth aspect of the invention, since it is possible to advise the driver about driving state information that can save fuel, a driving support device that can perform appropriate driving support can be obtained.

  According to the ninth aspect of the invention, since it is possible to advise the driver about a gear ratio that can save fuel, it is possible to obtain a driving support device that can perform appropriate driving support.

  According to the invention described in claim 10, by providing the vehicle speed as the driving state information input to the learning means, the driver is advised about the driving state information that can save fuel while keeping the speed constant. Therefore, it is possible to obtain a driving support device that can perform appropriate driving support.

  According to the eleventh aspect of the present invention, the relationship between the speed, load information, gear ratio, and fuel consumption information can be obtained by learning performed during traveling, and the relationship between the speed, load information, gear ratio, and fuel consumption information is obtained. Since it is not necessary to create a map to be shown, it is possible to obtain a driving support device that can be mounted without selecting a vehicle while reducing costs.

  According to the twelfth aspect of the present invention, it is possible to obtain a driving support device that can easily obtain load information based on the accelerator opening / engine speed.

  According to the thirteenth aspect of the invention, it is possible to obtain a driving support device that can obtain the gear ratio by using the vehicle speed of the driving state information and the engine speed for obtaining the load information.

  Hereinafter, the driving support device of the present invention is explained based on a drawing. FIG. 2 is a block diagram showing an embodiment of the driving support apparatus of the present invention. As shown in the figure, a microcomputer (hereinafter referred to as μCOM) 10 provided in the driving support apparatus of the present invention has a vehicle speed pulse P1 output every time the vehicle travels a unit distance via an input I / F 11. A rotation speed pulse P2 output according to the rotation of the crankshaft and a fuel pulse P3 output every time 1 cc of fuel is consumed are supplied.

  The μCOM 10 described above is also supplied with a voltage value from an angle sensor attached to an accelerator pedal as an accelerator opening signal S1 via an input interface (I / F) 11. The μCOM 10 includes a central processing unit (CPU) 10a that performs various processes according to programs, a ROM 10b that is a read-only memory that stores programs for processes performed by the CPU 10a, a work area that is used in various processes in the CPU 10a, various types A RAM 10c, which is a readable / writable memory having a data storage area for storing data, and the like are incorporated.

  The above-described μCOM 10 is connected to the liquid crystal display 13. As shown in FIG. 3, for example, the liquid crystal display 13 includes a fuel consumption state display unit 13a, a shift operation display unit 13b, an ideal accelerator opening degree instruction unit 13c, a current accelerator opening degree instruction unit 13d, and a multi display unit 13e. ing. The fuel consumption state display unit 13a is for displaying the current fuel consumption state of the vehicle. For example, the fuel consumption state display unit 13a includes a belt-like display unit that changes from red to green as it goes from the thicker (downward) to the thinner (upward). Has been. In this fuel consumption state display section 13a, the fuel consumption is improved as it goes from the thicker (red) to the thinner (green).

  The shift operation display unit 13b is for instructing a shift operation. “UP” is lit when a shift up is instructed, and “DOWN” is lit when a downshift is instructed. The ideal accelerator opening degree instruction unit 13c instructs an ideal accelerator opening degree that saves fuel, and includes, for example, a band-shaped display unit. The ideal accelerator opening degree instruction unit 13c indicates a state in which the ideal accelerator opening degree increases as the distance from the narrower side to the thicker side increases.

  The current accelerator opening degree instruction unit 13d is for instructing the current accelerator opening degree. Accordingly, when an instruction to step on the accelerator is given, the ideal accelerator opening is displayed below the current accelerator opening instruction unit 13d, and when an instruction to loosen the accelerator is given, from the current accelerator opening instruction unit 13d. The ideal accelerator opening is displayed on the upper side.

  The multi-display unit 13e displays average fuel consumption, instantaneous fuel consumption, speed, fuel consumption, fuel saving score, vehicle maintenance information, and the like. Further, the above-described μCOM 10 is connected to a switch SW (see FIG. 2) that is turned on when the setting button 14 (see FIG. 3) is pressed, and a display item or the like on the multi-display unit 13e is set by operating the setting button 14. It can be done. Further, the above-described μCOM 10 can write various traveling state information such as the speed of the vehicle to the compact flash card (CF card) 16 via the output I / F 15.

  The operation of the driving support apparatus having the above-described configuration will be described below with reference to flowcharts showing processing procedures of the CPU 10a in FIGS. First, the CPU 10a functions as a traveling state detection unit and a fuel consumption detection unit, and performs the detection process shown in FIG. 4 every second, for example. In this detection process, the CPU 10a first determines the current vehicle speed vp (km / h), engine speed Np (rpm), vehicle speed pulse P1, engine speed pulse P2, fuel pulse P3, and accelerator opening signal S1. The fuel consumption amount αp (cc) per second and the accelerator opening βp (%) as fuel consumption information are detected (step S1).

  Next, the CPU 10a detects the gear ratio Gp (= vp / Np) from the speed vp and the engine speed Np (step S2). Further, the CPU 10a detects a load coefficient γp (= βp / Np) as load information from the obtained accelerator opening βp and engine speed Np (step S3). Here, in the no-load state, it is considered that the engine speed can be determined almost uniquely according to the fuel consumption (≈ accelerator opening). However, in reality, energy loss occurs due to various loads (road resistance, gradient, load load, etc.), and the relationship between the accelerator opening and the engine speed changes according to the load.

From this, it is considered that the magnitude of the load can be expressed by calculating “driving force per engine (≈fuel consumption≈accelerator opening) (≈engine speed)”. It can be said that the larger this value is, the smaller the loss is, that is, the smaller the load is. However, since it is more intuitive that “the size of the coefficient = the size of the load”, the reciprocal is taken. Defined.
Load coefficient = accelerator opening / rotation speed

  Further, the CPU 10a performs an inference process for inferring the speed v, the load coefficient γ, and the gear ratio G as input data and the fuel consumption α and the accelerator opening β as output data according to a fuzzy neuro network as shown in FIG. It can be carried out. Further, the relationship between the input data and the output data is learned based on the detection result of the detection process. These inference and learning will be described in detail later.

Further, every time the detection process is performed, the CPU 10a functions as an inference unit, an input unit, and a support unit, and performs a support process for supporting the fuel-saving driving shown in FIG. First, the CPU 10a creates input data to the network as shown in FIG. 6 (step S5). Input data includes the current gear ratio Gp detected by the detection process, the gear ratio Gu that is one higher than the current gear ratio, and the gear ratio Gd that is one lower than the current gear ratio. Three patterns I1 to I3 are generated by combining the current speed vp and the current load coefficient γp.
I1 = [Gu, vp, γp], I2 = [Gd, vp, γp], I3 = [Gp, vp, γp]

  Next, the CPU 10a inputs I1 to I3 to a network as shown in FIG. 6 and performs an inference process for inferring fuel consumptions α1 to α3 and accelerator pedal openings β1 to β3 with respect to I1 to I3 (step S6). ). Next, the CPU 10a compares the smallest fuel consumption amount αmin among the inferred fuel consumption amounts α1 to α3 with the current fuel consumption amount αp detected by the detection process (step S7).

  If the fuel consumption amount αmin = α1 and the current fuel consumption amount αp> the estimated fuel consumption amount α1 = αmin (Y in step S7), the input data I1 when the fuel consumption amount αmin is inferred The middle gear ratio Gu is determined to be a gear ratio that is one higher than the current gear ratio Gp (N in step S8), and the shift instruction unit 13 gives a shift instruction to light “UP” (step S9). Encourage drivers to shift up. Thereafter, the accelerator opening degree β1 inferred with respect to the input data I1 is instructed to the ideal accelerator opening degree instruction unit 13c, and the current accelerator opening degree βp detected by the detection processing is instructed by the current accelerator opening degree instruction unit 13d. After giving the instruction (step S10), the process proceeds to step S11.

  If the fuel consumption amount αmin = α2 and the current fuel consumption amount αp> the estimated fuel consumption amount α2 = αmin (Y in step S7), the input data I2 when the fuel consumption amount α2 is inferred The middle gear ratio Gd is determined to be one gear ratio lower than the current gear ratio Gp (N in step S8), and a shift instruction to turn on “DOWN” is given in the shift instruction unit 13 (step S9). Encourage the driver to shift down. Thereafter, the accelerator opening degree β2 inferred with respect to the input data I2 is instructed to the ideal accelerator opening degree instruction unit 13c, and the current accelerator opening degree βp detected by the detection process is instructed by the current accelerator opening degree instruction unit 13d. After the accelerator instruction is given (step S10), the process proceeds to step S11.

  If the fuel consumption amount αmin = α3 and the current fuel consumption amount αp> the inferred fuel consumption amount α3 = αmin (Y in step S7), the input data I3 when the fuel consumption amount α3 is inferred The intermediate gear ratio Gp is determined to be the same as the current gear ratio Gp (Y in step S8), and the process immediately proceeds to step S10 without performing the shift instruction in step S9. In step S10, the CPU 10a instructs the accelerator opening degree β3 inferred with respect to the input data I3 to the ideal accelerator opening degree instruction unit 13c, and uses the current accelerator opening degree βp detected by the detection process as the current accelerator opening degree. After the accelerator instruction to be instructed by the instruction unit 13d is performed, the process proceeds to step S11.

  On the other hand, if the current fuel consumption amount αp ≦ αmin (N in step S7), it is determined that the fuel-saving driving can be performed in the current traveling state, and the step is immediately performed without performing the shift instruction or the accelerator instruction. Proceed to S11. In step S11, a process for displaying the current fuel consumption state is performed. Specifically, for example, when the current fuel consumption amount αp is smaller than the fuel consumption amount αmin (N in step S7), it is displayed that the current fuel consumption state is the best. On the other hand, when the current fuel consumption amount αp is larger than the fuel consumption amount αmin (Y in step S7), the fuel consumption state is displayed so that the difference between the current fuel consumption amount αp and the fuel consumption amount αmin increases. As is clear from the above, the speed, load coefficient, and gear ratio correspond to the input travel state information, and the accelerator opening corresponds to the output travel state information.

  The learning / inference in the present embodiment uses fuzzy neuro. The fuzzy neuro is a combination of the advantages of a conventional neural network and fuzzy reasoning. The fuzzy neuro is basically composed of a filter function called a trapezoidal membership function (hereinafter referred to as MF) generally used in fuzzy inference and an element having a weight w. This MF is expressed by approximating the frequency distribution of the input data to a normal distribution as shown in FIG.

  FIG. 6 shows the network configuration of the fuzzy neuro. The basic network configuration includes an input unit composed of normalization tables NT1 to NT3, a pre-stage unit composed of a three-layer structure of pattern sets PS1 to PS3, pattern tables PT1 and PT3, pattern sets PS4 and PS5, and a normalization table NT3. And it consists of a two-layer structure of NT4, and consists of a rear-stage part that is an inversion of the front-stage part. In the input unit, the input data is converted into normalized data in the normalization tables NT1 to NT3, respectively. Each normalized input data is input to the MF, where it is converted into a matching degree.

  The pattern sets PS1 to PS3 in the next stage are composed of MF aggregates, and the outputs obtained by combining the matching degrees obtained by the MFs using weights are output. In the pattern tables PT1 and PT2 of the output unit, the highest one of the matching degrees output from the plurality of pattern sets PS1 to PT3 is output to the subsequent stage unit. In the latter part, in the pattern sets PS4 and PS5, the outputs from the pattern tables PT1 and PT2 that exceed the threshold value are output, and the MF on the link is transformed according to the degree of coincidence, and the latter normalization table NT3 and Transmit to NT4. In the normalization tables NT3 and NT4, the center of the transmitted MF shape is synthesized and de-fuzzified, for example, to convert it into a continuous value having a dimension equivalent to the taught output data.

  In the learning process that works as a learning means, the speed, load coefficient, and gear ratio detected by the detection process are used as input data, the accelerator opening, and the fuel consumption are used as teacher signals to change the shape of the membership function and the pattern set. Although automatic generation is performed, in this fuzzy neuro, learning is not performed for each teacher signal, but is performed after a certain number of accumulations, so that high-speed learning is possible.

  When learning is performed, the speed, fuel consumption, and accelerator opening are filtered under the following conditions. Regarding the speed, 5 km / h or less is regarded as a stop, and is set to 0 km / h. Regarding the fuel consumption, 1 cc or less is regarded as being unable to be further improved, and is set to 0 cc. Regarding the accelerator opening, 5% or less is regarded as noise due to voltage fluctuation and is set to 0%.

  According to the driving support device having the above-described configuration, learning using the detection result of the detection process as an input of the speed, load coefficient, and gear ratio, and the accelerator opening and the fuel consumption as an output is performed. Driving assistance is performed using. That is, by learning performed during traveling, it is possible to obtain the relationship between the speed, load coefficient, and gear ratio corresponding to the vehicle, the accelerator opening, and the fuel consumption, and the speed, load coefficient, and gear ratio are determined in advance. There is no need to create a map showing the relationship between the accelerator opening and the fuel consumption. For this reason, the cost can be reduced and the vehicle can be mounted without selecting it.

  Further, according to the driving support device having the above-described configuration, the fuel consumption amount is inferred by inputting the running state information including the current speed and the current load coefficient detected by the detection process, and the current fuel consumption detected by the detection process is estimated. Based on the comparison between the amount and the estimated fuel consumption, the driver is notified of the current fuel consumption state of the vehicle. For this reason, it can be determined whether the current fuel consumption with respect to the current speed and the current load coefficient is in a state of good fuel consumption, and appropriate driving support can be performed.

  In addition, according to the driving support device having the above-described configuration, the speed, load coefficient, and gear ratio corresponding to the input travel state information are input, and the accelerator opening corresponding to the output travel state information is output as an output for detection. Using the input running state information including the current speed and current load coefficient detected by the process as input, the accelerator opening and fuel consumption are inferred, and inferred when the inferred fuel consumption is less than the current fuel consumption Assisted the accelerator opening. As a result, the driver can be advised about the accelerator opening at which the fuel consumption is smaller than the current speed while maintaining the current speed, and appropriate driving assistance can be performed.

  Further, according to the driving support apparatus having the above-described configuration, the three patterns of input data I1 to I3 are formed by combining the current speed, the current load coefficient, and the three patterns of gear ratios. Fuel consumptions α1 to α3 are inferred using I3 as an input, and among the fuel consumptions α1 to α3 inferred for the three input data I1 to I3, the current fuel consumption αp is smaller than the smallest fuel consumption αmin. When the fuel consumption amount is large, the gear ratio input when the fuel consumption amount αmin is inferred is urged. As a result, the driver can be advised on the gear ratio at which the fuel consumption is smaller than the current speed while maintaining the current speed, and appropriate driving assistance can be performed.

  In the above-described embodiment, the fuel consumption per unit time is used as the fuel consumption information. However, for example, an efficiency coefficient obtained from the vehicle speed / accelerator opening may be used as the fuel consumption information. In this case, since fuel efficiency information can be obtained without using a fuel gauge that measures fuel consumption, it can also be used in vehicles that are not equipped with a fuel gauge.

  In the above-described embodiment, the vehicle speed / engine speed is obtained as the gear ratio. Thus, the gear ratio is obtained by using the vehicle speed as the running state information and the engine speed for obtaining the load coefficient. However, if the vehicle is equipped with a sensor that outputs a signal corresponding to the gear position, for example, it is conceivable to determine the gear ratio based on the signal from the sensor.

  In the above-described embodiment, learning / inference is performed using fuzzy neurology. However, the learning / inference is not limited to this, and a known method such as a general neuronetwork may be used.

  In the above-described embodiment, the speed, load coefficient, and gear ratio are input travel state information. However, the present embodiment is not limited to this embodiment as long as the travel state information can infer the fuel consumption state of the vehicle. .

  In the above-described embodiment, the accelerator opening is used as the output travel state information. However, for example, when it is desired to advise the speed with the best fuel efficiency using the current load coefficient, the vehicle speed may be used as the output travel state information. It is done.

  In the above-described embodiment, the three patterns of input data I1 to I3 are generated by combining the current load coefficient and the three patterns of gear ratios and input to the neuron network. It is conceivable to input a driving pattern information of a simple pattern. Also, without entering multiple patterns of driving status information, simply enter the current speed, current load coefficient, and current gear ratio to infer the fuel consumption and accelerator opening, and this inferred fuel consumption And the current fuel consumption amount may be compared, and the current fuel consumption state and the accelerator opening may only be notified to the driver. It is also conceivable that only the gear ratio is instructed without inferring the accelerator opening.

  Furthermore, in the above-described embodiment, driving assistance is performed using the liquid crystal display 13 as shown in FIG. 3. For example, driving assistance is performed using a display using LEDs as shown in FIG. 7. Also good. In FIG. 7, the fuel consumption state display unit 13a is composed of a plurality of LEDs arranged in stages from red to green as they go from the bottom to the top, and the fuel consumption increases toward the top (green) from the bottom (red). Indicates a good condition.

  The ideal accelerator opening degree instruction unit 13c is composed of a plurality of LEDs arranged vertically. When the current situation is good, the central part (green) is lit, and when the accelerator is stepped on, the lower side is lit. When loosening the accelerator, the top side should be lit.

  Further, the shift operation instructing unit 13b is composed of an arrow that indicates the up and down direction with the fuel consumption state display unit 13a and the ideal accelerator opening degree instructing unit 13c interposed therebetween. When instructing, the down arrow is even lit.

It is a basic lineblock diagram of the driving support device of the present invention. It is a block diagram which shows one Embodiment of the driving assistance device of this invention. It is the figure which showed the example of a display of the liquid crystal display which comprises the driving assistance apparatus shown in FIG. It is a flowchart which shows the process sequence in the detection process of CPU10a which comprises the driving assistance apparatus shown in FIG. It is a flowchart which shows the process sequence in the assistance process of CPU10a which comprises the driving assistance apparatus shown in FIG. It is an example of a fuzzy neuro network used in learning / inference of this embodiment. It is the figure which showed the other example of a display of driving assistance.

Explanation of symbols

10a-1 Traveling state detection means (CPU)
10a-2 Fuel consumption detection means (CPU)
10a-3 Learning means (CPU)
10a-4 Inference means (CPU)
10a-5 Input means (CPU)
10a-6 Support means (CPU)

Claims (13)

Traveling state detecting means for detecting traveling state information of the vehicle;
Fuel consumption detection means for detecting fuel consumption information of the vehicle;
Learning means for performing learning using the detected running state information as an input and the detected fuel consumption information as an output;
An inference means for inferring fuel efficiency information for the input driving state information using a learning result performed by the learning means;
Input means for inputting driving state information to the inference means;
A driving support apparatus comprising: a support unit that supports fuel-saving driving based on a comparison between the current fuel consumption information detected by the fuel consumption detection unit and the fuel consumption information inferred by the inference unit. The driving support device according to claim 1,
The fuel consumption detection means detects a fuel consumption per unit time as the fuel consumption information. The driving support device according to claim 1,
The fuel efficiency detection means detects an efficiency coefficient obtained from a vehicle speed and an accelerator opening as the fuel efficiency information. The driving support device according to any one of claims 1 to 3,
The driving support apparatus according to claim 1, wherein the input means inputs the current running state information detected by the running state detection means to the inference means. The driving support device according to claim 4,
The support means detects the current fuel consumption state of the vehicle based on a comparison between the current fuel consumption information detected by the fuel consumption detection means and the fuel consumption information inferred from the current running state information by the inference means, and driving A driving support device that informs a person. The driving support device according to any one of claims 1 to 5,
The travel information detection means detects input travel state information as an input of the learning means and output travel state information as an output of the learning means,
The learning means uses the detected input running state information as input, performs learning using the detected fuel consumption information and the output running state information as outputs,
The input means inputs the current input travel state information detected by the travel state detection means to the inference means,
The inference means infers fuel consumption information and output travel state information with respect to the input current input travel state information using a learning result performed by the learning unit,
When the current fuel consumption information detected by the fuel consumption detection means is worse than the fuel consumption information inferred by the inference means, the support means changes the vehicle travel state to output travel state information inferred by the inference means. A driving assistance device characterized by prompting The driving support device according to claim 6,
The accelerator opening of the vehicle is used as the output travel state information,
The assist means urges the accelerator opening estimated by the inference means when the current fuel efficiency information detected by the fuel efficiency detection means is worse than the fuel efficiency information inferred by the inference means. apparatus. The driving support device according to any one of claims 1 to 7,
The input means inputs a plurality of patterns of driving state information to the inference means,
The support means is configured such that when the current fuel consumption information detected by the fuel consumption detection means is worse than the best fuel efficiency information inferred by the inference means for the input of the plurality of patterns of driving state information, A driving support device that urges the driving state to be the driving state information input when the best fuel consumption information is inferred. The driving support device according to claim 8,
The traveling state detection means detects traveling state information including a gear ratio of the vehicle,
The input means inputs a combination of a plurality of patterns of gear ratios and the current running state information detected by the running state detection means to the inference means, excluding the gear ratio,
The support means is best when the current fuel consumption information detected by the fuel consumption detection means is worse than the best fuel efficiency information inferred by the inference means with respect to the input of gear ratios of the plurality of patterns. A driving support device that urges to use a gear ratio inputted at the time of inference of fuel information. The driving support device according to claim 6, wherein
The traveling state detection means detects the speed of the vehicle as the traveling state information;
The learning means learns with the speed of the vehicle as an input,
The driving support device, wherein the input means inputs the current speed of the vehicle to the inference means. The driving support device according to any one of claims 1 to 10,
The driving state detecting means detects a vehicle speed, vehicle engine load information, and a vehicle gear ratio as driving state information. The driving support device according to claim 11,
The driving state detecting means detects the accelerator opening / engine speed as load information. The driving support device according to claim 12, wherein
The driving state detecting means detects a vehicle speed / engine speed as a gear ratio.

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