CN109249933B - Driver acceleration intention identification method and device - Google Patents
Driver acceleration intention identification method and device Download PDFInfo
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- CN109249933B CN109249933B CN201710575605.7A CN201710575605A CN109249933B CN 109249933 B CN109249933 B CN 109249933B CN 201710575605 A CN201710575605 A CN 201710575605A CN 109249933 B CN109249933 B CN 109249933B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W40/09—Driving style or behaviour
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/10—Accelerator pedal position
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/10—Accelerator pedal position
- B60W2540/106—Rate of change
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Abstract
The invention relates to a method and a device for identifying the acceleration intention of a driver. Therefore, the problem that the accuracy of the intention identification of the driver is low in the aspects of actual working conditions and vehicle conditions is solved.
Description
Technical Field
The invention relates to a method and a device for identifying the acceleration intention of a driver, belonging to the technical field of driving intention identification.
Background
Most of the current methods for identifying the intention of the driver are on a pure software level, and the intention of the driver is mainly identified by using intelligent algorithms such as fuzzy control, Mapedif, neural network and other intelligent control schemes.
Chinese patent document CN 103318181 a discloses a driver intention identification method, which identifies the behavior and intention of a driver based on a multidimensional discrete hidden markov model.
Firstly, the scheme does not consider the real-time condition of actual vehicle operation, for example, when a vehicle fault cannot respond to complex road conditions such as normal output torque, vehicle heavy load, climbing and the like, even different drivers, a preset vehicle acceleration model and a threshold value for identifying driving intention cannot meet the accurate identification of the intention of the driver, and under the condition, the adjusted corresponding control parameters are wrong.
Secondly, the intelligent algorithms for intention recognition including the markov models are often large in calculation amount and high in requirements on a single chip microcomputer, and for mass-produced vehicles, the cost is increased. Meanwhile, the complex operation means a complex program, which brings about a high program error rate and a long program execution time, which are disadvantageous for safe driving.
Disclosure of Invention
The invention aims to provide a method and a device for identifying the acceleration intention of a driver, which are used for solving the problem that the driving intention is not accurately identified due to the fact that the actual running condition of a vehicle is not considered in the prior art. Furthermore, the problems of high hardware cost, program execution time and error rate caused by excessively large and complex intelligent algorithm adopted in the prior art can be solved.
In order to achieve the above object, the scheme of the invention comprises:
the invention discloses a driver acceleration intention recognition method, which comprises the following steps:
an off-line development calibration step: the method comprises the steps of calculating characteristic parameters through a first method, dividing at least two threshold value ranges according to the obtained characteristic parameter values, wherein each threshold value range corresponds to a corresponding acceleration control strategy;
and (3) real-time operation correction: and the characteristic parameter value correction module is used for calculating the characteristic parameter according to the first method in the actual vehicle running stage, calculating or acquiring the characteristic parameter through the second method, comparing the characteristic parameter value calculated through the first method with the characteristic parameter value obtained through the second method, and correcting the threshold range by using the characteristic parameter value obtained through the second method if the characteristic parameter value is different from the characteristic parameter value obtained through the first method.
Further, the characteristic parameter is an acceleration a; the first method comprises the following steps: and calculating the acceleration a through the collected accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd.
Further, the second method is to measure the real-time acceleration a _ real by the acceleration measuring device.
Further, the acceleration measuring device is a gyroscope.
Further, the threshold ranges are (0, d 1), (d1, d2), (d2, and + ∞), and the acceleration strategy is when 0
D1 is slowly accelerated when a is less than or equal to a; when d1 is more than a and less than or equal to d2, the acceleration is general; when a > d2 is emergency acceleration.
Further, the formula adopted by the first method is as follows:
k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd; wherein k1, k2 and k3 are constant values.
Further, in the real-time operation correction step, the characteristic parameter value comparison method is that if a _ real is not equal to a and the confirmation is repeated for 2 times or more than 2 times, the ratio of the a _ real average value a _ real _ avg to a for 2 times or more than 2 times is used as the correction coefficient mdf _ fac of the threshold value for correcting the recognition result of the driver's intention.
The invention relates to a driver acceleration intention recognition device, which comprises a processor and a memory, wherein the processor is used for executing instructions stored in the memory to realize the following method:
and in the actual vehicle running stage, calculating the characteristic parameters according to a first method, calculating or acquiring the characteristic parameters through a second method, comparing the characteristic parameter values calculated through the first method with the characteristic parameter values obtained through the second method, and correcting a threshold range by using the characteristic parameter values obtained through the second method if the characteristic parameter values are different from the characteristic parameter values obtained through the first method, wherein the threshold range corresponds to different acceleration control strategies.
Further, in the method, the characteristic parameter is an acceleration a; the first method comprises the following steps: and calculating the acceleration a through the collected accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd.
Further, in the method, the second method is to measure the real-time acceleration a _ real by an acceleration measuring device.
Further, the acceleration measuring device is a gyroscope.
Further, the threshold ranges in the method are (0, d1], (d1, d2], (d2, + ∞). The acceleration strategy is slow acceleration when 0 < a ≦ d1, general acceleration when d1 < a ≦ d2, and emergency acceleration when a > d 2.
Further, the formula adopted by the first method is as follows:
k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd; wherein k1, k2 and k3 are constant values.
Further, in the real-time operation correction step, the characteristic parameter value comparison method is that if a _ real is not equal to a and the confirmation is repeated for 2 times or more than 2 times, the ratio of the a _ real average value a _ real _ avg to a for 2 times or more than 2 times is used as the correction coefficient mdf _ fac of the threshold value for correcting the recognition result of the driver's intention.
The invention has the beneficial effects that:
the method for identifying the driver acceleration intention takes the real-time running condition of the vehicle into consideration, and feeds back the real-time running condition of the vehicle to adjust the intention identification threshold value, so that the driver intention and the actual acceleration condition form closed-loop control, and the accuracy of the identification of the driver intention is greatly improved.
In addition, the parameter acquisition related by the invention is easy, the calculated amount is small, and the program is simple and reliable. The requirement on a control chip of the vehicle is low, and the cost and the development difficulty can be effectively reduced for mass production of vehicle types; for practical use, the control system is not easy to make mistakes, and is safe and reliable.
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Fig. 1 is a flowchart of a driver acceleration intention recognition method.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
FIG. 1 shows a flowchart of a driver acceleration intention recognition method, which is divided into an off-line development calibration stage and a system real-time operation stage; the off-line development calibration stage specifically comprises the following steps:
1) based on a vehicle with a fixed load, a large amount of working condition data are collected, and the influence of three factors, namely accelerator opening AccPed _ Norm, accelerator change Rate AccPed _ Rate and vehicle speed V _ Spd, on vehicle acceleration a is found out through combing and analyzing the data. The action rule of the operation intention of the driver can be found out according to the rule, and the sequence of the output signals in the whole process is shown as follows: the accelerator opening AccPed _ Norm is changed, then the accelerator change Rate AccPed _ Rate is changed, and finally the change of the vehicle acceleration a and the vehicle speed V _ Spd is reflected. It can be seen from the sampling data that within 0.1 second after the accelerator opening degree is changed, the accelerator change rate reaches a peak value (maximum value or minimum value), then the acceleration a reaches the peak value after delaying for about 1.2 seconds, and the vehicle acceleration change trend is mainly related to the accelerator opening degree, but has a certain relation with the accelerator change rate and the vehicle speed.
2) Through matlabbcftool fitting toolbox, three influencing factors are input, and the fitting acceleration function is as follows: and a, k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd (after the function is confirmed, k1, k2 and k3 are fixed values), obtaining a vehicle acceleration model, quantifying or classifying the intention of the driver according to the acceleration value of the vehicle, and selecting a control related parameter set or different control modes according to the identified intention of the driver, so that the optimal control is achieved.
3) The obtained acceleration a is divided into three classes according to the driving intention according to experience, and the corresponding threshold value sets are (0, d1, d2), (1) emergency acceleration when a is larger than d2, (2) normal acceleration when a is between d1 and d2, and (3) slow acceleration when a is between 0 and d 1.
The real-time operation stage of the system specifically comprises the following steps:
1) in the real-time running process of the vehicle, the vehicle control unit collects the accelerator opening AccPed _ Norm _ real, the accelerator change Rate AccPed _ Rate _ real, the vehicle speed V _ Spd _ real and the actual acceleration a _ real of the vehicle read by the gyroscope in real time, judges that if the accelerator opening, the accelerator change Rate and the vehicle speed are the same, if the a _ real is not equal to a and the confirmation is repeated for 10 times, the ratio of the average value a _ real _ avg of the a _ real to a for 10 times is used as the correction coefficient mdf _ fac of the threshold value, and accordingly corrects the intention recognition result of the driver.
The basic scheme embodied in the above examples is:
when the calibration is developed off line, calculating characteristic parameters by a first method, dividing at least two threshold value ranges according to the obtained characteristic parameter values, wherein each threshold value range corresponds to a corresponding acceleration control strategy; when the vehicle runs in real time, the characteristic parameters are calculated according to the first method, meanwhile, the characteristic parameters are calculated or collected through the second method, the characteristic parameter values calculated through the first method are compared with the characteristic parameter values obtained through the second method, and if the characteristic parameter values are different, the threshold value range is corrected through the characteristic parameter values obtained through the second method.
In this embodiment, the first method is to fit the accelerator opening, the accelerator change rate, and the speed to a function of the acceleration a by using a computer: a is k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd, and the acceleration a is the characteristic parameter; the second method is that a gyroscope is utilized to collect the actual acceleration a _ real when the vehicle runs in real time; the modified threshold range is to modify the threshold by using the ratio of the average value a _ real _ avg of a _ real to a as a modification coefficient mdf _ fac; the correction condition is that a _ real is not equal to a for ten consecutive times.
However, the invention is not limited to the specific content and mode of the first method, the second method, the threshold correction method and the correction condition, and the key point of the invention is the feedback correction of the threshold in the real-time running stage of the vehicle; as another embodiment, the first method may be another algorithm as long as the corresponding characteristic parameter can be calculated, the threshold corresponding to different control parameters is divided by the corresponding characteristic parameter, and the characteristic parameter can be obtained again by the second algorithm when the algorithm is running in real time.
Claims (8)
1. A driver acceleration intention recognition method characterized by comprising:
an off-line development calibration step: collecting a large amount of working condition data based on a constant-load vehicle; fitting the accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd into a function of the acceleration a by using a computer: k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd, where k1, k2, and k3 are fixed values, the acceleration a is a characteristic parameter, at least two threshold value ranges are divided according to the obtained characteristic parameter value, and each threshold value range corresponds to a corresponding acceleration control strategy;
and (3) real-time operation correction: the method is used for calculating the acceleration a by acquiring the accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd in the actual vehicle running stage, and the calculation formula is as follows: k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd; wherein k1, k2 and k3 are constant values; and meanwhile, measuring the real-time acceleration a _ real by an acceleration measuring device, comparing the value of the acceleration a calculated by the calculation formula with the value of the real-time acceleration a _ real, and correcting the threshold range by using the value of the real-time acceleration a _ real if the two values are different.
2. The method for identifying the acceleration intention of the driver as recited in claim 1, wherein the acceleration measuring device is a gyroscope.
3. The method as claimed in claim 1, wherein the threshold ranges are (0, d1], (d1, d2], (d2, + ∞), the acceleration strategy is slow acceleration when 0 < a ≦ d1, general acceleration when d1 < a ≦ d2, and emergency acceleration when a > d 2.
4. The method as claimed in claim 1, wherein in the step of real-time running correction, the comparison of the characteristic parameter value is performed by using the ratio of the average value a _ real _ avg of a _ real to a of 2 or more times as the correction coefficient mdf _ fac of the threshold value for correcting the recognition result of the driver's intention if a _ real is not equal to a and the confirmation is repeated 2 or more times.
5. A driver acceleration intention recognition apparatus comprising a processor, a memory, wherein the processor is configured to execute instructions stored in the memory to implement a method comprising:
in the actual vehicle running stage, the acceleration a is calculated by acquiring the accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd, and the calculation formula is as follows: k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd; wherein k1, k2 and k3 are constant values; simultaneously, measuring real-time acceleration a _ real by an acceleration measuring device, comparing the value of the acceleration a calculated by the calculation formula with the value of the real-time acceleration a _ real, and correcting a threshold range by using the value of the real-time acceleration a _ real if the two values are different, wherein the threshold range corresponds to different acceleration control strategies;
the calculation formula and the threshold value range are obtained by an off-line development and calibration step: collecting a large amount of working condition data based on a constant-load vehicle; fitting the accelerator opening AccPed _ Norm, the accelerator change Rate AccPed _ Rate and the vehicle speed V _ Spd into a function of the acceleration a by using a computer: k1 × AccPed _ Norm + k2 × AccPed _ Rate + k3 × V _ Spd, where k1, k2, and k3 are fixed values, the acceleration a is a characteristic parameter, at least two threshold value ranges are divided according to the obtained characteristic parameter value, and each threshold value range corresponds to a corresponding acceleration control strategy.
6. The apparatus for recognizing the acceleration intention of a driver as claimed in claim 5, wherein said acceleration measuring means is a gyroscope.
7. The apparatus for recognizing an acceleration intention of a driver as claimed in claim 5, wherein the threshold range is (0, d1], (d1, d2], (d2, + ∞) in the method, the acceleration strategy is slow acceleration when 0 < a ≦ d1, general acceleration when d1 < a ≦ d2, and urgent acceleration when a > d 2.
8. The apparatus according to claim 5, wherein in the real-time running correction step, the characteristic parameter value is compared by using a ratio of an a _ real average a _ real _ avg to a of 2 or more times as the correction coefficient mdf _ fac of the threshold value for correcting the recognition result of the driver's intention if a _ real is not equal to a and the confirmation is repeated 2 or more times.
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| CN113492868B (en) * | 2020-04-02 | 2024-09-20 | 广州汽车集团股份有限公司 | Method and device for identifying acceleration intention of automobile, automobile and computer readable storage medium |
| CN113147734B (en) * | 2021-05-21 | 2022-09-16 | 吉林大学 | Closed-loop control method based on longitudinal acceleration intention of driver |
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| CN102494125A (en) * | 2011-11-22 | 2012-06-13 | 广西柳工机械股份有限公司 | Driver's intention recognition system for automatic transmission control of loader and recognition method |
| CN106740864A (en) * | 2017-01-12 | 2017-05-31 | 北京交通大学 | A kind of driving behavior is intended to judge and Forecasting Methodology |
| CN107539305A (en) * | 2017-08-25 | 2018-01-05 | 吉林大学 | A kind of dynamic torque control method for coordinating of planetary parallel-serial hybrid power system |
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| DE102009033760A1 (en) * | 2009-07-17 | 2011-01-27 | Continental Automotive Gmbh | Method for roll detection |
| US8258934B2 (en) * | 2009-10-30 | 2012-09-04 | Ford Global Technologies, Llc | Vehicle and method of advising a driver therein |
| CN102673569B (en) * | 2012-05-25 | 2015-10-28 | 同济大学 | Vehicle-state is calculated device, method and is used the vehicle of this device |
| JP6233727B2 (en) * | 2013-12-05 | 2017-11-22 | ▲華▼▲為▼▲終▼端有限公司 | Method and apparatus for determining vehicle acceleration |
| CN106168542B (en) * | 2016-07-06 | 2019-01-25 | 广州汽车集团股份有限公司 | A kind of online recognition method, system and the vehicle of vehicle working condition |
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| CN102494125A (en) * | 2011-11-22 | 2012-06-13 | 广西柳工机械股份有限公司 | Driver's intention recognition system for automatic transmission control of loader and recognition method |
| CN106740864A (en) * | 2017-01-12 | 2017-05-31 | 北京交通大学 | A kind of driving behavior is intended to judge and Forecasting Methodology |
| CN107539305A (en) * | 2017-08-25 | 2018-01-05 | 吉林大学 | A kind of dynamic torque control method for coordinating of planetary parallel-serial hybrid power system |
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