JPH0460482A - Vehicle collision alarm system - Google Patents

Abstract

PURPOSE:To raise a proper alarm of a vehicle collision by changing an alarm range of an alarm algorithm according to a deviation value from a reference value of a driver's driving-sense inclination in each class, classifying the running state of the vehicle by the relative difficulty of the running. CONSTITUTION:A space headway measuring part 1 is the so-called range finder by a laser method, generates a laser diode 102 at a given period, radiates to a target 4, receives reflected-rays from the target 4 and operates the distance between the self vehicle and the target 4. A running speed signal transmitting part 2 transmits signals necessary for measurement of the running speed and the running distance to a signal processing part 3. The processing part 3 is equipped with a CPU 303 which processes the distance signals from the measuring part 1 according to a fixed algorithm and operates whether there is any need of the alarm, a fuzzy inference IC 305 inferring the running state, etc. By this constitution, the vehicle running state is classified on the relative difficulty of the running, and the alarm algorithm is set up according to a deviation value of a driver's driving-sensory inclination from a reference value, using the running speed and the space of the front running vehicle as parameters, at each class, of the running state classified, to which the state belongs.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention provides a system that issues a warning when the distance between the own vehicle and a vehicle traveling in front falls within a warning range determined according to the vehicle speed of the own vehicle. The present invention relates to a vehicle collision warning system, and more particularly to a vehicle collision warning system in which the warning range is made variable based on vehicle driving conditions and individual differences between drivers, thereby making it possible to more appropriately issue a warning.

[Prior art] The distance between the host vehicle and the vehicle in front is measured based on the time it takes for a signal such as light or radio waves emitted from the vehicle to be reflected by the vehicle in front and received, and the distance is determined by the warning signal. Vehicle collision warning systems have been put into practical use that issue an alarm when the vehicle falls within the range. When issuing a vehicle collision warning, the above-mentioned warning range cannot be fixedly determined due to individual differences among drivers. A system is adopted in which the driver himself/herself selects the alarm range that suits his/her own driving sense using the above switch.

Further, as a more advanced warning method, a method of estimating the driver's driving sensation from the driver's tendency to step on the brake and variably controlling the above-mentioned warning range based on this estimation is disclosed in Japanese Patent Application No. 57-215977, for example. No. (Special Publication No. 2-10912
(No.).

[Problems to be Solved by the Invention] According to the above-mentioned conventional technology, the switching of the warning range is performed subjectively by the driver himself, and the warning range is not necessarily selected appropriately. Operating the switch while driving is extremely dangerous.

Furthermore, in the method proposed in the above-mentioned Japanese Patent Application No. 57-215978, accidents that do not correspond to normal driving sensations may occur, for example, when sudden braking is applied due to an emergency brake of a vehicle traveling ahead or a person jumping out. However, there is a problem in that the setting of the warning range is not appropriate except when the above-mentioned accidental factors are small, such as when driving on a highway.

The present invention is proposed to solve the above problems.
The object of the present invention is to obtain a vehicle collision warning system that automatically determines the surrounding conditions during driving and the driver's changing driving sense tendency, and automatically and variably sets a more appropriate warning range. shall be.

[Means for solving the problem] Above I! In order to solve this problem, the present invention classifies vehicle driving situations according to the degree of difficulty of driving, defines the driver's driving sensation tendency using vehicle speed and distance from the vehicle running ahead as parameters, and also uses the above-mentioned categorization. A standard value for the driving sense propensity is set for each type of driving situation in which the driver's driving sense propensity is determined based on the standard value for the driving sense propensity set for the class of driving situation to which the own vehicle is traveling. The deviation is determined, and the warning range determined by the distance between the host vehicle and the vehicle traveling ahead and the vehicle speed of the host vehicle is changed in accordance with the deviation value of the driving sensation tendency.

In addition, as a method of categorizing the above-mentioned driving conditions, the present invention provides (1) a method of categorizing the vehicle speed and the amount of change in the vehicle speed within a certain period of time, (2) a method of categorizing the vehicle speed and the amount of change in the vehicle speed within a certain period of time; A method of categorizing using a fuzzy space in which the amount of change in is used as a parameter, and the probability that the current run belongs to the class classified by the two parameters is added (
In this method, the reference value of the driving sense propensity is changed in accordance with the above-mentioned probability. ), (3) Based on the vehicle speed when driving at a constant speed extracted within a certain period of time and the time the vehicle traveled at that speed,
(4) A method of defining driving situation judgment values and categorizing them according to the range of the judgment values, or (4) defining driving situation judgment values using the distance traveled within a certain period of time, maximum vehicle speed, and minimum vehicle speed, and classifying them according to the range of the judgment values. The method of classification is adopted.

[Function] With the above configuration, in the present invention, the warning range is automatically variably controlled depending on the surrounding situation while driving, the psychological state of the driver while driving, etc. It is possible to issue an objective collision warning that is not arbitrary.

[Example] The drawings explain the present invention in detail, and Fig. 1 is a block diagram of a vehicle collision warning system, Fig. 2 is a flowchart showing signal processing, and Fig. 3 is a flowchart showing driving situation determination and vehicle speed. Figure 4 explains the concept when the driving situation is determined based on the relationship between the vehicle speed and the amount of change in vehicle speed. Figure 5 is a diagram explaining the concept of determining the driving situation based on the constant speed travel distance or the maximum and minimum vehicle speeds.
FIG. 6 is a diagram showing the driver's driving sense tendency characteristics, and FIG. 7 is a diagram showing the setting of the warning range in the warning algorithm.

As shown in FIG.
Based on the signals from the vehicle distance measuring section 1 and the vehicle speed signal transmitting section 2, The system is comprised of a signal processing unit 3 that executes a warning algorithm, determines whether a collision warning is necessary, and generates a warning if necessary.

The vehicle distance measuring unit 1 is a so-called radar one-type distance measuring device (distance measuring device). That is, in the case of the embodiment, light (laser light) is used as the distance measuring medium, and the driver 1
01 causes the laser diode 02 to emit light at a constant period to emit light toward a target object (vehicle traveling ahead) 4, and the photodiode 103 receives the reflected light of the emitted light from the target object 4. Repeatedly several times, the arithmetic unit 104 calculates the difference between the driving time of the driver 101 (i.e., the emitting time of the synchrotron radiation) and the reception time of the signal from the photodiode 103 that is manually input via the amplifier 105 (i.e., the reception time of the reflected light). The distance to the target object 4, that is, the distance between the host vehicle and the vehicle running ahead 4 is calculated from the average value of the time difference for the plurality of operations.

The vehicle speed signal sending unit 2 sends signals necessary for measuring the vehicle speed (ground speed of the vehicle) and the distance traveled to the signal processing unit 3. Note that since the signals sent to the speedometer and odometer of the car can be used as they are, there is no need to provide the vehicle speed signal sending section 2 independently of the alarm device.

The signal processing section 3 measures the vehicle speed by counting the signals output from the S/P converter 301, which converts the distance signal inputted in the form of a serial signal from the vehicle distance measurement section 1 into a form of parallel signal, and the signal outputted from the vehicle speed signal transmission section 2. and a counter 302 and S/P converter 301 that output count values that are the basis for measuring mileage.
, a CPU that processes the signal output from the counter 302 according to a predetermined alarm algorithm and calculates whether or not an alarm is necessary.
(Microcomputer) 303, a memory 304 (consisting of ROM and RAM) for storing the program of the CPU 303 and a driving situation determination map described below, etc.
A fuzzy inference IC 305 for inferring the driving situation (unnecessary depending on the embodiment of the present invention), a buzzer 306 for audibly displaying a warning, and a display for visually displaying the warning and other information (for example, following distance information, etc.) 307 etc.

In the warning system of the present invention, the driving situation of the car is determined based on the difficulty of driving, such as (a) driving in traffic jams, (b) driving in urban areas,
and (c) highway driving.

The first method for classifying the driving situation is to use a table that maps the regions to which the above three categories belong, using the vehicle speed and the amount of change in the vehicle speed within a set time as parameters.

That is, for example, a map as shown in FIG. 3 is stored in the memory 3.
04, and calculate the vehicle speed at the time of the alarm judgment and the amount of change in the vehicle speed within a certain period of time (within a certain period of time set for the driving situation classification) from the time of the alarm judgment, from the count value output from the counter 302. The CPU 303 calculates the vehicle speed based on the calculated vehicle speed measurement [(determined from the count value during unit time), and refers to the above map to determine whether the vehicle is traveling at that time (a) or (b).
) (C). The amount of change in vehicle speed is determined by integrating the differences between adjacent local maximum values and minimum values within a certain range of vehicle speeds within the above-mentioned certain period of time.

In addition, the second classification method for driving conditions uses the vehicle speed and the amount of change in the vehicle speed within a certain period of time as parameters, as in the first classification method. This is a method in which the probability of belonging to any one of the first or second classes is used as the basis for judgment.

That is, for example, the 41st! A fuzzy inference IC 305 based on a fuzzy set as shown in FIG. Find the class that is estimated to be deaf and the probability of belonging to that class.

Unlike the first classification method, this second classification method does not fit the driving at that time into one category, but rather uses ambiguous driving situations that cannot be said to belong to any category. , it is possible to apply the results to multiple classes that take into account probabilities, making it possible to judge the driving situation more realistically.

If this second classification method were to be performed by the CPU 303 like other processes, the number of processing steps would be extremely large, a large memory space would be required, and a long processing time would be required, reducing the judgment speed. It is necessary to use a dedicated IC 305 designed for inference.

In addition, the third classification method for driving conditions is to extract the time when the vehicle was traveling at a constant speed and the vehicle speed at that time within a certain period of time dating back to the time when the alarm was determined, and to extract the time when the vehicle was traveling at a constant speed and the vehicle speed at that time. In this method, the added value of the product is defined as the driving situation determination value, and the driving conditions are classified into the above-mentioned categories (a), (b), and (c) according to the range of this driving situation determination value.

In this method as well, the vehicle speed can be obtained by calculating the signal from the counter 302.

To further explain this third classification method with reference to FIG. 5, time t is the alarm judgment time, T is a certain period of time before the alarm judgment time t, and T1, T2, T3, and T4 are the times when the vehicle indicates the time during which the vehicle is traveling at a constant speed, and the vehicle speeds during the constant speed traveling times T1, T2, T3, and T4 are respectively 1, v2, V3, and v4. The value S is 5=V1-TI + V2-T2 + V3-T3
+V4・T4−(1). Note that whether or not the vehicle is traveling at a constant speed is determined based on whether the amount of change in vehicle speed is maintained within a certain range of change for a certain period of time set for the constant speed determination. . This determination can also be made by arithmetic processing based on the output signal from the counter 302.

The driving condition determination value S indicates the distance traveled by constant speed driving within a certain period of time T, and the longer this distance, the faster the vehicle is traveling. In other words, the driving situation can be categorized into (a), (b), and (C) according to the value range of the driving situation determination 4Iis.

The above equation (1) can be generally expressed as follows.

S=ΣVi φTi (2) However, Vi is the vehicle speed sample during constant speed running extracted within a certain period of time, and Tj is the time the vehicle traveled at the vehicle speed V1.

In addition, the fourth classification method for driving conditions is to calculate the value obtained by dividing the distance traveled by the vehicle during a certain period of time dating back to the time of warning determination by the difference between the highest and lowest vehicle speeds during the specified period of time. As in the third classification method, the range of the driving situation determination value S determines the conditions (a), (b),
This is a method of categorizing into (c).

This fourth classification method is explained with reference to Fig. 5. If the distance traveled by the vehicle during a certain time T is the distance traveled by the vehicle, the maximum vehicle speed within the certain time T is vM, and the minimum vehicle speed is VN, then the driving situation judgment value S is defined by the following formula: S=L, / (VM-VN)
(3) The travel path ML in this equation (3) is obtained by simply integrating the signal output from the vehicle speed signal sending unit 2 using the counter 302, and the maximum vehicle speed VM
and the minimum vehicle speed VN are obtained by the CPU 303 comparing and analyzing the vehicle speeds obtained from the count value of the signal output from the vehicle speed signal sending section 2 in a unit time by the counter 302. When the vehicle is traveling smoothly on the expressway without congestion, the value of the traveling route ML is large and the value of the difference between the maximum and minimum vehicle speeds (VM-VN) is small. Therefore, the value of the driving situation determination value S shown by the above equation (3) becomes large. On the other hand, during traffic jams, the distance traveled is small, and since the vehicle repeats starting and stopping, the difference between the highest and lowest vehicle speeds (VM-VN) increases, so the above-mentioned driving situation judgment The value of the value S becomes smaller.

As is clear from the above, the driving situation can be adjusted according to the range of the driving situation judgment value S shown in the above equation (3).
, (b), and (c).

In addition, in the third classification method and the fourth classification method, the range of the driving situation determination value S determined as (a), (b), and (c) is determined by the setting of the value of the fixed time T. It is decided.

Types of driving situations categorized as above, (a), (
For each of b) and (c), as shown in FIG. 6, a driving sensation tendency characteristic is set using the vehicle speed and the distance from the vehicle running ahead as parameters.

In Figure 6, ao, bo and CO are each (a)
It is a reference value curve of each type of driving sensation tendency for driving in traffic jams, (b) city driving, and (C) expressway driving, &1, a2
, bl, b2 and cl, c2 are the above (a), respectively.
In categories (b) and (c), the driving sensation tendency characteristics show characteristic curves in which they deviate from the reference values ao, bo, and co by ±α.

As shown in FIG. 7, the warning algorithm uses the sense of the vehicle traveling ahead and the vehicle speed as parameters, and is set to vary according to the amount of deviation ±α from the standards [ao, bo, co] of the driving sense tendency.

That is, the alarm range corresponding to the above reference values ao, bo, and co is the range below the song &IAo in FIG.
If the driver's driving sense tendency shifts in the direction of +α, the warning range expands as shown by curve A1, and if it shifts in the direction of -α, the warning range contracts as shown by curve A2.

Next, control processing in the CPU 303 of the signal processing section 3 will be explained with reference to FIG.

First, a case will be described in which the categorization of driving situations is performed using the first or second method.

When the alarm operation is started, the CPU 303 first reads the vehicle speed from the counter 302 in step (3). This vehicle speed reading is performed multiple times during a certain period of time, and each vehicle speed is stored in the RAM space of the memory 304 in preparation for the next step.

Next, in step (2), the vehicle speed stored in the memory 304 is analyzed to detect the amount of change in vehicle speed, and in step (2), the driving situation is determined. To determine this driving situation, the vehicle speed at the time closest to the time of warning determination is used to determine the amount of change in vehicle speed and the vehicle speed stored in the memory 304.
The driving situation determination map shown in FIG. 3 stored in the ROM space of FIG. 3 or the driving situation determination fuzzy set shown in FIG. 4 using the fuzzy reasoning IC 305 is used.

Next, in step (2), the measured value of the leap distance between the host vehicle and the vehicle running ahead 4 is read from the vehicle distance measurement unit 1 and stored in the memory 30.
4, and the vehicle speed is analyzed again in step (2) to determine whether or not the own vehicle is traveling at a constant speed. The determination in step (2) is made based on whether or not the vehicle speed remains within a certain range for a certain period of time or longer. If the judgment in step (■) is "YES', the distance between the preceding vehicles and the vehicle speed at that time read in step (2) are compared with the driving sensation tendency characteristics shown in the sixth step, and the driving situation determined in step (2) is The criterion corresponding to [a
The deviation value of the driver's driving sense tendency from o, bo, or co is calculated in step (3).

When determining the driving situation using the map shown in No. 39, the above-mentioned driving sensation propensity characteristics are classified into the respective class (a).
, (b), (c) are fixed, but when the driving situation is judged by the fuzzy set shown in FIG. 4, the reference values [ao, bO
lCO varies depending on the difference in the probability of belonging to each class.

For example, for a driving situation in which the probability of belonging to the class of city driving and the probability of belonging to the class of expressway driving are determined to be 50%, the reference value curve is moves to an intermediate point between the reference value bo for city driving and the reference value WicO for expressway driving.

Further, if the determination in step (2) is ``No'', step (2) holds the deviation value of the driving sensation tendency at the time of the previous warning determination so that it can be used as it is in the next step. That is, when the vehicle is not traveling at a constant speed, the deviation value of the driving sensation tendency changes frequently in short cycles due to the unstable vehicle speed, so the deviation amount is not determined within one cycle of processing. This is because it becomes impossible to set the alarm range in the next step. In addition, when the process moves to the step (2) in the first processing cycle after the start and the step (2) occurs in the first process cycle, the driving sense propensity is at the reference value ao, b.

Or use CO (zero deviation amount).

Once the driver's driving sensation tendency deviation value is determined as described above, the next step is step (2), in which the alarm algorithm is calculated. That is, in the warning algorithm shown in FIG. 7, a warning range is set corresponding to the above deviation value, and the relationship between the vehicle speed at that time and the distance between vehicles traveling in front is compared with the warning algorithm after setting the warning range. Then, in step (2), it is determined whether the relationship is within the alarm range.

If the judgment in step ■ is YES', in step [phase] the buzzer 306 is sounded to display the alarm audibly, and the alarm is visually displayed on the display 307, and then the process from step ■ is repeated again. , If the determination in step (2) is 'NO', the process from step (2) is repeated without displaying the alarm.

Next, a case will be described in which the categorization of driving situations is performed using the third or fourth method.

In the second case, the 21st! ! In step (2) of the processing flow shown in I, the vehicle speed stored in the memory 304 is analyzed, and the driving situation determination MS is calculated using the above equation (2) or (3), and the driving situation is determined in step (2). Then, the driving situation determination value S corresponds to each of the driving situation categories (a) and (b).
) and (c), it is determined which predetermined range it belongs to.

Other processing is the same as in the case of the first or second categorization method.

As can be understood from the above description of the embodiments, in the present invention, all differences in the surrounding environment when the vehicle is running, such as the difference between doubt and nighttime, or the difference between sunny and rainy days, are automatically added to the warning algorithm. In addition, differences in the driver's own driving technique or changes in psychological state are all automatically added to the warning algorithm.In other words, most of the factors that affect driving are the vehicle speed, the amount of change in vehicle speed, and the forward movement. This will manifest itself as a change in the vehicle distance of either l or more than 1, so various judgments made based on the characteristics shown in Figures 3 to 6 using these as parameters are the factors that affect the above-mentioned driving. (In the categorization of driving conditions in the example, each category was classified as ``driving in traffic jams,'' ``driving in the city,'' and ``driving at high speeds.'' ,(b),
and (C) are representative driving modes in each category. ).

[Effects of the Invention] As explained above, the present invention classifies the driving situation of a vehicle into a plurality of categories depending on the difficulty of driving, and sets a standard value of driving sensation tendency for each category, thereby improving the driver's driving sensation. The deviation value of the tendency from the above reference value is calculated, and the warning range of the alarm algorithm is changed according to the above deviation value, and the difference in the surrounding environment when the vehicle is running and the difference in the driver's driving sense tendency is calculated. Since all of these are automatically added to the warning algorithm, the effect is that extremely appropriate and natural vehicle collision warning can be provided.

[Brief explanation of drawings]

The drawings all explain the present invention in detail. Fig. 1 is a block diagram of a vehicle collision warning system, Fig. 2 is a flowchart showing signal processing, and Fig. 3 is a flowchart showing driving situation determination based on vehicle speed and the amount of change in vehicle speed. Figure 4 is a diagram explaining the concept of determining the driving situation using a fuzzy set that adds probability to the relationship between vehicle speed and vehicle speed change. Figure 5 is a diagram explaining the concept of determining the driving situation based on the relationship between A diagram explaining the concept when determining the situation based on the constant speed driving distance or the maximum and minimum vehicle speeds. Figure 6 is a diagram showing the driver's driving sense tendency characteristics. Figure 7 is the warning range in the warning algorithm. FIG. (Main symbols) 1 Vehicle distance measurement section 2 Vehicle speed signal transmission section 3 Signal processing section

Claims (1)

[Claims] 1. A warning is issued when the distance between the host vehicle and the vehicle traveling ahead, as measured by the vehicle distance measurement unit, falls within a warning range determined according to the vehicle speed of the host vehicle. In a vehicle collision warning system having a warning algorithm, the driving situation of the vehicle is classified according to the degree of difficulty of driving, and the driver's driving sense tendency is defined using the vehicle speed and the distance from the vehicle traveling in front as parameters. A standard value of the driving sense tendency is set for each of the above classified driving situations, and the driver's driving sense tendency is calculated from the standard value of the driving sense tendency set for the above driving situation class to which the own vehicle is traveling. A vehicle collision warning system that calculates a deviation value of a driving sense tendency and changes the warning range of the above-mentioned warning algorithm in accordance with the deviation value of the driving sense tendency. 2. The vehicle collision warning system according to claim 1, wherein the classification of driving situations is performed using vehicle speed and the amount of change in the vehicle speed within a set time as parameters. 3. In the vehicle collision warning system according to claim 2, the class of driving situation to which the own vehicle belongs is determined based on a fuzzy set including the probability that the current driving will belong to the class. A vehicle collision warning system in which the reference value of the driving sensation tendency is changed according to the above probability. 4. The vehicle collision warning system according to claim 1, wherein the classification of the driving situation is performed based on the range of the driving situation judgment value S defined by the following equation. S=ΣVi・Ti However, Vi is the vehicle speed sample during constant speed driving extracted within a certain period of time, and Ti is the time the vehicle traveled at the vehicle speed Vi. 5. The vehicle collision warning system according to claim 4, wherein the driving situation determination value S is changed as shown in the following equation. S=L/(VM-VN) However, L, VM, and VN are the distance traveled within a certain period of time, the maximum vehicle speed, and the minimum vehicle speed, respectively.