A steering intention decision method that can adapt to weather changes

Abstract

The present invention belongs to the field of automobile technology, and in particular, is a steering intention decision method that can adapt to weather changes. The steering intention decision method is composed of a steering style recognition module, a steering intention analysis module, a ground adhesion coefficient calculation module, a visibility calculation module, and a comprehensive adaptive adjustment module. The steering style recognition module is composed of an established steering style recognition model. On the basis of constructing different styles of steering intention analysis models, the present invention considers the influence of weather conditions on the road adhesion coefficient and the driver's visibility on the driver, and obtains correction parameters after comprehensively considering the two aspects of influence, and adjusts the steering intention analysis model based on this, which can provide the driver with a higher quality steering operation experience.

Description

Technical Field

[0001] The present invention relates to the field of automobile technology, and in particular to a steering intention decision method capable of adaptively adapting to weather changes. Background Art

[0002] With the rapid development of the automotive industry, consumers pay more and more attention to the operational experience during vehicle driving, among which steering operation is an important part of the driving experience. How to obtain the steering movement intensity expected by the driver, that is, the driver's steering intention, is the key to improving the steering operation experience and thus improving driving satisfaction.

[0003] Invention patent CN118358650A discloses a personalized steering feel design method for application in a wire-controlled steering system, which can be used to customize personalized steering feel and wire-controlled steering wheel compensation torque. It first establishes a tire and mechanical steering dynamics model, and calculates the tire self-aligning torque and the torque on the steering rod based on the vehicle parameters and state parameters. Then, a driver's road feel style information library is constructed and feature quantities for identifying styles are selected to establish a road feel style recognition model. The recognition results are integrated with the vehicle state parameters to finally obtain a personalized feedback torque. However, this method does not take into account the influence of weather. In rainy and snowy weather, the adhesion coefficient and visibility of the road surface will change. At this time, the personalized feedback torque under normal conditions may cause the driver to have an uncomfortable driving experience.

[0004] When driving in different weather conditions, the driver's expected steering intensity is different. The impact of weather on drivers is mainly in the following aspects: First, rain and snow will cause the adhesion coefficient of the road to decrease. When driving in such weather, the driver's expected steering intensity will be lower than that in normal weather conditions. In addition, rain, snow, fog and other weather will reduce the driver's visibility. At this time, for safety reasons, the driver's driving style tends to be cautious, and the preferred steering torque at the same steering intensity will also be greater.

[0005] Therefore, we propose a turning intention decision method that can adapt to weather changes to solve the above problems. Summary of the invention

[0006] 1. Technical issues to be resolved

[0007] In view of the deficiencies of the prior art, the present invention provides a turning intention decision method that can adapt to weather changes, solving the problems raised in the above-mentioned background technology.

[0008] (II) Technical solution

[0009] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0010] A steering intention decision method capable of adapting to weather changes, the steering intention decision method comprising a steering style recognition module, a steering intention analysis module, a ground adhesion coefficient calculation module, a visibility calculation module and a comprehensive adaptive adjustment module, the steering style recognition module being composed of an established steering style recognition model, and the steering style recognition model construction method comprising the following steps:

[0011] S1: First, build a driver steering style information database and design relevant feature parameters;

[0012] S2: clustering the driver steering feature parameters in the style information database into three categories, namely, radical, normal, and conservative;

[0013] S3: Then, a steering style recognition model is established based on the steering data information in the steering style information database. The model can output the driver's steering style through relevant vehicle state information during the steering process;

[0014] The turning intention decision method comprises the following steps:

[0015] Step 1: Steering style model recognition identifies the steering style based on the corresponding feature parameters;

[0016] Step 2: Calculate the ground adhesion coefficient and visibility in the current environment;

[0017] Step 3: Combine the ground adhesion coefficient and visibility information to obtain correction parameters;

[0018] Step 3: Based on the identified steering style and correction parameters, the final steering intention model is adjusted to obtain the steering intention at this time, that is, the expected steering movement intensity, according to the vehicle speed and the driver's steering input;

[0019] The driver's steering intention is the expected steering movement intensity. When the vehicle speed is low, the vehicle's steering dynamic response is not obvious, and the steering wheel angle can better represent the vehicle's steering movement intensity; when the vehicle speed is high, the vehicle's dynamic response is obvious, and the lateral acceleration can better represent the vehicle's steering movement intensity. Therefore, the steering intention relationship established by the present invention is as follows: when the vehicle speed is lower than 20 km / h, the relationship between the driver's steering input (steering wheel torque) and the steering wheel angle; when the vehicle speed is higher than 20 km / h, the relationship between the driver's steering input and the vehicle's lateral acceleration, using Stevens psychophysics law to construct the following relationship:

[0020] ;

[0021] ;

[0022] in is the desired steering wheel angle, is the desired lateral acceleration, represents the effect of speed on the strength coefficient, are the strength coefficients of steering wheel angle and lateral acceleration, are the power exponents corresponding to the steering wheel angle and lateral acceleration respectively;

[0023] Relevant experiments were conducted on aggressive, ordinary and conservative drivers and steering-related data were collected. The parameters of the above model were identified based on the collected data to obtain the basic steering intention analysis model corresponding to the three types of drivers.

[0024] The road adhesion coefficient calculation module is used to measure the road adhesion coefficient. It is based on the road adhesion coefficient identification method of the vehicle longitudinal response and slip rate-utilization adhesion coefficient curve. First, the longitudinal force of the wheel is estimated, and then the instantaneous utilization adhesion coefficient and slip rate of the wheel are calculated; on this basis, the slip rate is judged. If the slip rate is low, the road adhesion coefficient is distinguished according to the slope of the curve; if the slip rate is high, the similarity between the sampling points of the utilization coefficient and slip rate and the typical road surface within a certain time interval is calculated to estimate the road adhesion coefficient;

[0025] The visibility calculation module is used to measure the visibility in the current environment. The vehicle's camera system can be used to capture images of the road ahead in real time, analyze the clarity of the road ahead and the environment through image processing technology, and calculate visibility by comparing the clarity and contrast of objects in the image.

[0026] The comprehensive adaptive adjustment module outputs the corresponding correction parameters to the intention model through the measurement and identification results of the above modules to achieve relevant parameter adjustment. Consider the following: For the adhesion coefficient, the adhesion coefficient of the normal road surface is selected as the benchmark, and the real-time measured ground adhesion coefficient is compared with it. , the lower the ground adhesion coefficient, The value is small; at the same time, due to the reduction of the ground adhesion coefficient, the driver will tend to have a relatively low steering movement intensity under the same steering input conditions, and the steering intention model will be relatively increased; based on this, a correction relationship between the ground adhesion coefficient and the steering intention model is established;

[0027] For visibility, the visibility in good weather is used as the benchmark, the visibility in the current environment is measured and the ratio between it and the benchmark is obtained. ; The lower the visibility, the corresponding ratio The smaller it is; as visibility decreases, the driver will tend to adopt a relatively more cautious driving style, that is, the degree of conservatism will increase; based on this, the revised relationship between visibility and steering intention model is obtained.

[0028] Furthermore, the steering style recognition module is used to recognize the driver's steering style and transmit the recognized style to the steering intention analysis module.

[0029] Furthermore, the steering intention analysis module is composed of a constructed steering intention model. It first determines the steering intention model of the corresponding style according to the identified steering style, and then corrects the steering intention analysis model based on the correction parameters transmitted by the comprehensive adaptive module, and comprehensively considers the vehicle speed and the driver's steering input at this time to obtain the driver's steering intention at this time, that is, the expected steering movement intensity.

[0030] Furthermore, the ground adhesion coefficient calculation module is used to calculate the adhesion coefficient of the ground at this time, so as to evaluate the impact of weather conditions on the road surface. After obtaining the ground adhesion coefficient under the current environment, it is compared with the adhesion coefficient under good road conditions and input into the comprehensive adaptive adjustment module.

[0031] Furthermore, the visibility calculation module is used to calculate the visibility under the current environment, compare the calculated visibility with the visibility under good weather conditions, and pass the result to the comprehensive adaptive adjustment module.

[0032] (III) Beneficial effects

[0033] Compared with the prior art, the present invention provides a turning intention decision method that can adapt to weather changes, which has the following beneficial effects:

[0034] The present invention, on the basis of constructing different styles of steering intention analysis models, takes into account the influence of weather conditions on the road adhesion coefficient and the driver's visibility on the driver. After comprehensively considering the two aspects, the correction parameters are obtained, and the steering intention analysis model is adjusted based on this, which can provide the driver with a higher quality steering operation experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the system principle of the present invention;

[0036] Figure 2 This is a schematic diagram of the correction of the turning intention analysis model of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Example

[0039] like Figure 1-2 As shown, an embodiment of the present invention proposes a steering intention decision method that can adapt to weather changes. The steering intention decision method is composed of a steering style recognition module, a steering intention analysis module, a ground adhesion coefficient calculation module, a visibility calculation module and a comprehensive adaptive adjustment module. The steering style recognition module is composed of an established steering style recognition model. The steering style recognition model construction method includes the following steps:

[0040] S1: First, build a driver steering style information database and design relevant feature parameters;

[0041] S2: clustering the driver steering feature parameters in the style information database into three categories, namely, radical, normal, and conservative;

[0042] S3: Then, a steering style recognition model is established based on the steering data information in the steering style information database. The model can output the driver's steering style through relevant vehicle state information during the steering process;

[0043] The turning intention decision method includes the following steps:

[0044] Step 1: Steering style model recognition identifies the steering style based on the corresponding feature parameters;

[0045] Step 2: Calculate the ground adhesion coefficient and visibility in the current environment;

[0046] Step 3: Combine the ground adhesion coefficient and visibility information to obtain correction parameters;

[0047] Step 3: Based on the identified steering style and correction parameters, the final steering intention model is adjusted to obtain the steering intention at this time, that is, the expected steering movement intensity, according to the vehicle speed and the driver's steering input;

[0048] The driver's steering intention is the expected steering movement intensity. When the vehicle speed is low, the vehicle's steering dynamic response is not obvious, and the steering wheel angle can better represent the vehicle's steering movement intensity; when the vehicle speed is high, the vehicle's dynamic response is obvious, and the lateral acceleration can better represent the vehicle's steering movement intensity. Therefore, the steering intention relationship established by the present invention is as follows: when the vehicle speed is lower than 20 km / h, the relationship between the driver's steering input (steering wheel torque) and the steering wheel angle; when the vehicle speed is higher than 20 km / h, the relationship between the driver's steering input and the vehicle's lateral acceleration, using Stevens psychophysics law to construct the following relationship:

[0049] ;

[0050] ;

[0051] in is the desired steering wheel angle, is the desired lateral acceleration, represents the effect of speed on the strength coefficient, are the strength coefficients of steering wheel angle and lateral acceleration, are the power exponents corresponding to the steering wheel angle and lateral acceleration respectively;

[0052] Relevant experiments were conducted on aggressive, ordinary and conservative drivers and steering-related data were collected. The parameters of the above model were identified based on the collected data to obtain the basic steering intention analysis model corresponding to the three types of drivers.

[0053] The road adhesion coefficient calculation module is used to measure the road adhesion coefficient. It is based on the road adhesion coefficient identification method of the vehicle longitudinal response and slip rate-utilization adhesion coefficient curve. First, the longitudinal force of the wheel is estimated, and then the instantaneous utilization adhesion coefficient and slip rate of the wheel are calculated; on this basis, the slip rate is judged. If the slip rate is low, the road adhesion coefficient is distinguished according to the slope of the curve; if the slip rate is high, the similarity between the sampling points of the utilization coefficient and slip rate and the typical road surface within a certain time interval is calculated to estimate the road adhesion coefficient;

[0054] The visibility calculation module is used to measure the visibility in the current environment. The vehicle's camera system can be used to capture images of the road ahead in real time, analyze the clarity of the road ahead and the environment through image processing technology, and calculate visibility by comparing the clarity and contrast of objects in the image.

[0055] The comprehensive adaptive adjustment module outputs the corresponding correction parameters to the intention model through the measurement and identification results of the above modules to achieve relevant parameter adjustment. Consider the following: For the adhesion coefficient, the adhesion coefficient of the normal road surface is selected as the benchmark, and the real-time measured ground adhesion coefficient is compared with it. , the lower the ground adhesion coefficient, The value is small; at the same time, due to the reduction of the ground adhesion coefficient, the driver will tend to have a relatively low steering movement intensity under the same steering input conditions, and the correction relationship between the ground adhesion coefficient and the steering intention model is established based on this;

[0056] For visibility, a similar approach is adopted. The visibility in good weather is used as a benchmark, and the visibility in the current environment is measured and the ratio between the visibility and the benchmark is obtained. ; The lower the visibility, the corresponding ratio The smaller it is; as visibility decreases, the driver will tend to adopt a relatively more cautious driving style, that is, the degree of conservatism will increase; based on this, the revised relationship between visibility and steering intention model is obtained.

[0057] In some embodiments, the steering style recognition module is used to recognize the driver's steering style and transmit the recognized style to the steering intention analysis module.

[0058] In some embodiments, the steering intention analysis module is composed of a constructed steering intention model. It first determines the steering intention model of the corresponding style according to the identified steering style, and then corrects the steering intention analysis model based on the correction parameters transmitted by the comprehensive adaptive module. It combines the vehicle speed and the driver's steering input at this time to obtain the driver's steering intention at this time, that is, the expected steering movement intensity.

[0059] In some embodiments, the ground adhesion coefficient calculation module is used to calculate the adhesion coefficient of the ground at this time to evaluate the impact of weather conditions on the road surface. After obtaining the ground adhesion coefficient under the current environment, it is compared with the adhesion coefficient under good road conditions and input into the comprehensive adaptive adjustment module.

[0060] In some embodiments, the visibility calculation module is used to calculate the visibility under the current environment, compare the calculated visibility with the visibility under good weather conditions, and pass the result to the comprehensive adaptive adjustment module.

[0061] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A turning intention decision method that can adapt to weather changes, characterized by: The steering intention decision method is composed of a steering style recognition module, a steering intention analysis module, a ground adhesion coefficient calculation module, a visibility calculation module and a comprehensive adaptive adjustment module. The steering style recognition module is composed of an established steering style recognition model. The steering style recognition model construction method includes the following steps: S1: First, build a driver steering style information database and design relevant feature parameters; S2: clustering the driver steering feature parameters in the style information database into three categories, namely, radical, normal, and conservative; S3: Then, a steering style recognition model is established based on the steering data information in the steering style information database. The model can output the driver's steering style through relevant vehicle state information during the steering process; The turning intention decision method comprises the following steps: Step 1: Steering style model recognition identifies the steering style based on the corresponding feature parameters; Step 2: Calculate the ground adhesion coefficient and visibility in the current environment; Step 3: Combine the ground adhesion coefficient and visibility information to obtain correction parameters; Step 3: Based on the identified steering style and correction parameters, the final steering intention model is adjusted to obtain the steering intention at this time, that is, the expected steering movement intensity, according to the vehicle speed and the driver's steering input; The driver's steering intention is the expected steering movement intensity. When the vehicle speed is low, the vehicle's steering dynamic response is not obvious, and the steering wheel angle can better represent the vehicle's steering movement intensity; when the vehicle speed is high, the vehicle's dynamic response is obvious, and the lateral acceleration can better represent the vehicle's steering movement intensity. Therefore, the steering intention relationship established by the present invention is as follows: when the vehicle speed is lower than 20 km / h, the relationship between the driver's steering input and the steering wheel angle; when the vehicle speed is higher than 20 km / h, the relationship between the driver's steering input and the vehicle's lateral acceleration, using Stevens psychophysics law to construct the following relationship: in is the desired steering wheel angle, is the expected lateral acceleration, k, m represent the influence of speed on the strength coefficient, α1, α2 are the strength coefficients of the steering wheel angle and lateral acceleration, n1, n2 are the power exponents corresponding to the steering wheel angle and lateral acceleration, respectively; Relevant experiments were conducted on aggressive, ordinary and conservative drivers and steering-related data were collected. The parameters of the above model were identified based on the collected data to obtain the basic steering intention analysis model corresponding to the three types of drivers. The road adhesion coefficient calculation module is used to measure the road adhesion coefficient. It is based on the road adhesion coefficient identification method of the vehicle longitudinal response and slip rate-utilization adhesion coefficient curve. First, the longitudinal force of the wheel is estimated, and then the instantaneous utilization adhesion coefficient and slip rate of the wheel are calculated; on this basis, the slip rate is judged. If the slip rate is low, the road adhesion coefficient is distinguished according to the slope of the curve; If the slip ratio is high, the road adhesion coefficient is estimated by calculating the similarity between the sampling points of the coefficient and slip ratio and the typical road surface within a certain time interval; The visibility calculation module is used to measure the visibility in the current environment. The vehicle's camera system can be used to capture images of the road ahead in real time, analyze the clarity of the road ahead and the environment through image processing technology, and calculate visibility by comparing the clarity and contrast of objects in the image. The comprehensive adaptive adjustment module outputs the corresponding correction parameters to the intention model through the measurement and identification results of the above modules to achieve the adjustment of relevant parameters. The following considerations are taken: for the adhesion coefficient, the adhesion coefficient of the normal road surface is selected as the benchmark, and the real-time measured ground adhesion coefficient is used as the ratio m. The lower the ground adhesion coefficient, the smaller the m value. At the same time, due to the reduction of the ground adhesion coefficient, the driver will tend to increase the steering movement intensity relatively under the same steering input conditions. Based on this, the correction relationship between the ground adhesion coefficient and the steering intention model is established. For visibility, taking visibility in good weather as a benchmark, the visibility in the current environment is measured and its ratio n to the benchmark is obtained; the lower the visibility, the smaller the corresponding ratio n; as the visibility decreases, the driver will tend to adopt a relatively more cautious driving style, that is, the degree of conservatism will increase; based on this, a revised relationship between visibility and steering intention model is obtained.

2. The method for making a decision on turning intention that can adapt to weather changes according to claim 1, characterized in that: The steering style recognition module is used to recognize the driver's steering style and transmit the recognized style to the steering intention analysis module.

3. The method for making a decision on turning intention that can adapt to weather changes according to claim 1, characterized in that: The steering intention analysis module is composed of a constructed steering intention model. It first determines the steering intention model of the corresponding style according to the identified steering style, and then corrects the steering intention analysis model based on the correction parameters transmitted by the comprehensive adaptive module. It combines the vehicle speed and the driver's steering input at this time to obtain the driver's steering intention at this time, that is, the expected steering movement intensity.

4. The method for making a decision on turning intention that can adapt to weather changes according to claim 1, characterized in that: The ground adhesion coefficient calculation module is used to calculate the ground adhesion coefficient at this time to evaluate the impact of weather conditions on the road surface. After obtaining the ground adhesion coefficient under the current environment, it is compared with the adhesion coefficient under good road conditions and input into the comprehensive adaptive adjustment module.

5. The method for making a decision on turning intention that can adapt to weather changes according to claim 1, characterized in that: The visibility calculation module is used to calculate the visibility under the current environment, compare the calculated visibility with the visibility under good weather conditions, and pass the result to the comprehensive adaptive adjustment module.

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