Evaluation Method, Device, Equipment and Storage Medium for Driving Somatosensory Comfort

Abstract

The present invention relates to the field of intelligent driving technology, and provides a method, device, equipment and storage medium for evaluating the driving somatic comfort, so as to improve the generalization of the evaluation of the somatic comfort of autonomous driving. The method for evaluating the driving somatic comfort includes: obtaining the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration; obtaining the target parameter factor corresponding to the driving longitudinal acceleration, and calculating the somatic comfort in the acceleration scenario or the deceleration scenario based on the driving longitudinal acceleration and the target parameter factor to obtain the longitudinal acceleration intensity somatic comfort; obtaining the lateral comfort, and determining the target somatic comfort based on the longitudinal acceleration intensity somatic comfort, the longitudinal acceleration change rate and the lateral comfort.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent driving, and particularly to a method, device, equipment and storage medium for evaluating the driving somatic comfort. Background Art

[0002] The somatic comfort of autonomous driving is one of the factors to be considered in the improvement of autonomous driving technology. Among them, braking is one of the scenarios that need to be concerned in the evaluation of the somatic comfort of autonomous driving. At present, the absolute value of the acceleration intensity, the change rate of the acceleration with time, and the change rate of the centrifugal force during steering are used to reflect the force condition of the passengers in the autonomous driving vehicle, and the force condition is associated with the somatic comfort of the passengers, and finally the evaluation of the somatic comfort is obtained.

[0003] However, the above method depends on the absolute value of the acceleration intensity, because it is impossible to distinguish the somatic comfort of braking and accelerating. However, due to the existence of the seat back, the somatic sensations of accelerating and braking under the same acceleration are different. Therefore, the evaluation system obtained for braking cannot be generalized to the accelerating situation, resulting in low generalization of the evaluation of the somatic comfort of autonomous driving. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for evaluating the driving somatic comfort, which is used to improve the generalization of the evaluation of the somatic comfort of autonomous driving.

[0005] In the first aspect of the present invention, a method for evaluating the driving somatic comfort is provided, including:

[0006] Obtain the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration;

[0007] Obtain the target parameter factor corresponding to the driving longitudinal acceleration, and based on the driving longitudinal acceleration and the target parameter factor, calculate the somatic comfort in the acceleration scenario or the deceleration scenario to obtain the somatic comfort of the longitudinal acceleration intensity;

[0008] Obtain the lateral comfort, and determine the target somatic comfort based on the somatic comfort of the longitudinal acceleration intensity, the longitudinal acceleration change rate and the lateral comfort.

[0009] Optionally, in the first implementation manner of the first aspect of the present invention, the obtaining the target parameter factor corresponding to the driving longitudinal acceleration, and based on the driving longitudinal acceleration and the target parameter factor, calculating the somatic comfort in the acceleration scenario or the deceleration scenario to obtain the somatic comfort of the longitudinal acceleration intensity includes:

[0010] Judge whether the driving longitudinal acceleration is greater than a preset target value;

[0011] If the driving longitudinal acceleration is greater than a preset target value, obtain a target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is an acceleration parameter factor, and the acceleration parameter factor is a parameter factor generated based on road test data in an acceleration scenario;

[0012] Calculate the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level;

[0013] If the driving longitudinal acceleration is less than or equal to the preset target value, obtain a target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is a deceleration parameter factor, and the deceleration parameter factor is a parameter factor generated based on road test data in a deceleration scenario;

[0014] Calculate the somatic comfort level in the deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

[0015] Optionally, in the second implementation manner of the first aspect of the present invention, the calculating the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level includes:

[0016] Calculate the absolute value of the driving longitudinal acceleration, and determine whether the absolute value of the driving longitudinal acceleration is less than a preset threshold;

[0017] If the absolute value of the driving longitudinal acceleration is less than the preset threshold, determine the longitudinal acceleration intensity somatic comfort level in the acceleration scenario as the preset comfort threshold to obtain the longitudinal acceleration intensity somatic comfort level;

[0018] If the absolute value of the driving longitudinal acceleration is greater than or equal to the preset threshold, calculate the somatic comfort level in the acceleration scenario based on a preset first asymmetric saturation function, the acceleration parameter factor, and the absolute value of the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

[0019] Optionally, in the third implementation manner of the first aspect of the present invention, the calculating the somatic comfort level in the deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level includes:

[0020] Calculate the absolute value of the driving longitudinal acceleration;

[0021] Calculate the somatic comfort level in the deceleration scenario based on a preset second asymmetric saturation function, the deceleration parameter factor, and the absolute value of the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

[0022] Optionally, in the fourth implementation manner of the first aspect of the present invention, before obtaining the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration, it further includes:

[0023] Obtain road test data in an acceleration scenario and road test data in a deceleration scenario. The road test data includes longitudinal acceleration intensity, longitudinal acceleration change rate, and somatosensory comfort data in the case of each combination of longitudinal acceleration intensity and longitudinal acceleration change rate;

[0024] Perform parameter fitting on the road test data in the acceleration scenario to obtain an acceleration parameter factor, and perform parameter fitting on the road test data in the deceleration scenario to obtain a deceleration parameter factor. The acceleration parameter factor is used to indicate the parameters for comfort evaluation in the acceleration scenario, and the deceleration parameter factor is used to indicate the parameters for comfort evaluation in the deceleration scenario;

[0025] Determine the acceleration parameter factor or the deceleration parameter factor as the target parameter factor.

[0026] Optionally, in the fifth implementation manner of the first aspect of the present invention, the obtaining of the lateral comfort, and determining the target somatosensory comfort based on the longitudinal acceleration intensity somatosensory comfort, the longitudinal acceleration change rate, and the lateral comfort includes:

[0027] Perform weighted summation on the longitudinal acceleration intensity somatosensory comfort and the longitudinal acceleration change rate to obtain longitudinal comfort;

[0028] Obtain the lateral comfort, and perform weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort.

[0029] Optionally, in the sixth implementation manner of the first aspect of the present invention, the obtaining of the lateral comfort, and performing weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort includes:

[0030] Obtain acceleration data in the vertical vehicle body direction in an acceleration scenario or a deceleration scenario, and calculate the variance of the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario to obtain the lateral acceleration variance;

[0031] Perform normalization processing on the lateral acceleration variance to obtain the lateral comfort;

[0032] Perform weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort.

[0033] The second aspect of the present invention provides an evaluation device for driving somatosensory comfort, including:

[0034] A first acquisition module, configured to acquire the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration;

[0035] A calculation module, configured to acquire a target parameter factor corresponding to the driving longitudinal acceleration, and calculate the somatic comfort level in an acceleration scenario or a deceleration scenario based on the driving longitudinal acceleration and the target parameter factor, so as to obtain the longitudinal acceleration intensity somatic comfort level;

[0036] A first determination module, configured to acquire the lateral comfort level, and determine the target somatic comfort level based on the longitudinal acceleration intensity somatic comfort level, the longitudinal acceleration change rate, and the lateral comfort level.

[0037] Optionally, in the first implementation manner of the second aspect of the present invention, the calculation module includes:

[0038] A judgment unit, configured to judge whether the driving longitudinal acceleration is greater than a preset target value;

[0039] A first acquisition unit, configured to, if the driving longitudinal acceleration is greater than the preset target value, acquire a target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is an acceleration parameter factor, and the acceleration parameter factor is a parameter factor generated based on road test data in an acceleration scenario;

[0040] A first calculation unit, configured to calculate the somatic comfort level in an acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatic comfort level;

[0041] A second acquisition unit, configured to, if the driving longitudinal acceleration is less than or equal to the preset target value, acquire a target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is a deceleration parameter factor, and the deceleration parameter factor is a parameter factor generated based on road test data in a deceleration scenario;

[0042] A second calculation unit, configured to calculate the somatic comfort level in a deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatic comfort level.

[0043] Optionally, in the second implementation manner of the second aspect of the present invention, the first calculation unit is specifically configured to:

[0044] Calculate the absolute value of the driving longitudinal acceleration, and judge whether the absolute value of the driving longitudinal acceleration is less than a preset threshold;

[0045] If the absolute value of the driving longitudinal acceleration is less than the preset threshold, determine the longitudinal acceleration intensity somatic comfort level in an acceleration scenario as a preset comfort threshold, so as to obtain the longitudinal acceleration intensity somatic comfort level;

[0046] If the absolute value of the driving longitudinal acceleration is greater than or equal to a preset threshold, calculate the perceived comfort level in the acceleration scenario based on a preset first asymmetric saturation function, the acceleration parameter factor, and the absolute value of the driving longitudinal acceleration, to obtain the perceived comfort level of the longitudinal acceleration intensity.

[0047] Optionally, in the third implementation manner of the second aspect of the present invention, the second calculation unit is specifically configured to:

[0048] Calculate the absolute value of the driving longitudinal acceleration;

[0049] Calculate the perceived comfort level in the deceleration scenario based on a preset second asymmetric saturation function, the deceleration parameter factor, and the absolute value of the driving longitudinal acceleration, to obtain the perceived comfort level of the longitudinal acceleration intensity.

[0050] Optionally, in the fourth implementation manner of the second aspect of the present invention, the driving perceived comfort evaluation device further includes:

[0051] A second acquisition module, configured to acquire road test data in the acceleration scenario and road test data in the deceleration scenario, where the road test data includes longitudinal acceleration intensity, longitudinal acceleration change rate, and perceived comfort data in the case of each combination of longitudinal acceleration intensity and longitudinal acceleration change rate;

[0052] A fitting module, configured to perform parameter fitting on the road test data in the acceleration scenario to obtain an acceleration parameter factor, and perform parameter fitting on the road test data in the deceleration scenario to obtain a deceleration parameter factor, where the acceleration parameter factor is used to indicate a parameter for comfort evaluation in the acceleration scenario, and the deceleration parameter factor is used to indicate a parameter for comfort evaluation in the deceleration scenario;

[0053] A second determination module, configured to determine the acceleration parameter factor or the deceleration parameter factor as the target parameter factor.

[0054] Optionally, in the fifth implementation manner of the second aspect of the present invention, the first determination module includes:

[0055] A first summation unit, configured to perform weighted summation on the perceived comfort level of the longitudinal acceleration intensity and the longitudinal acceleration change rate to obtain a longitudinal comfort level;

[0056] A second summation unit, configured to obtain a lateral comfort level, and perform weighted summation on the longitudinal comfort level and the lateral comfort level to obtain a target perceived comfort level.

[0057] Optionally, in the sixth implementation manner of the second aspect of the present invention, the second summation unit is specifically configured to:

[0058] Obtain the acceleration data in the vertical body direction in the acceleration scenario or the deceleration scenario, and calculate the variance of the acceleration data in the vertical body direction in the acceleration scenario or the deceleration scenario to obtain the lateral acceleration variance;

[0059] Perform normalization processing on the lateral acceleration variance to obtain the lateral comfort level;

[0060] Perform weighted summation on the longitudinal comfort level and the lateral comfort level to obtain the target somatic comfort level.

[0061] The third aspect of the present invention provides a computer device, including: a memory and at least one processor, wherein a computer program is stored in the memory; the at least one processor calls the computer program in the memory so that the computer device executes the above-mentioned method for evaluating the driving somatic comfort level.

[0062] The fourth aspect of the present invention provides a computer-readable storage medium, in which a computer program is stored. When it runs on a computer, it enables the computer to execute the above-mentioned method for evaluating the driving somatic comfort level.

[0063] In the technical solution provided by the present invention, by fusing the evaluation of somatic comfort in the acceleration scenario and the evaluation of somatic comfort in the deceleration scenario, and combining the acceleration intensity that causes a large difference in somatic comfort between the braking and acceleration scenarios, it is possible to distinguish the somatic comfort levels in the two situations of braking and acceleration, and it is possible to generalize the evaluation system obtained for braking to the acceleration situation, thereby improving the generalization of the evaluation of autonomous driving somatic comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic diagram of an embodiment showing the relationship between the acceleration intensity and the corresponding somatic comfort level in the deceleration scenario and the acceleration scenario in the embodiment of the present invention;

[0065] Figure 2 It is a schematic diagram of an embodiment of the method for evaluating the driving somatic comfort level in the embodiment of the present invention;

[0066] Figure 3 It is a schematic diagram of another embodiment of the method for evaluating the driving somatic comfort level in the embodiment of the present invention;

[0067] Figure 4 It is a schematic diagram of an embodiment of the device for evaluating the driving somatic comfort level in the embodiment of the present invention;

[0068] Figure 5 It is a schematic diagram of another embodiment of the device for evaluating the driving somatic comfort level in the embodiment of the present invention;

[0069] Figure 6 This is a schematic diagram of an embodiment of the computer device in the embodiments of the present invention. Detailed implementation manners

[0070] The embodiments of the present invention provide a method, device, equipment and storage medium for evaluating the driving somatic comfort, which improves the generalization of the evaluation of the somatic comfort of autonomous driving.

[0071] Terms such as "first", "second", "third", "fourth", etc. (if any) in the specification, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "comprising" or "having" and any deformation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or equipment comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or equipment.

[0072] Through road tests (road tests refer to experimental tests of the corresponding vehicle movements of the test items on the actual road), the somatic comfort data (acceleration somatic comfort data) under different acceleration intensities and different acceleration change rates in the acceleration scenario are collected, as well as the somatic comfort data (deceleration somatic comfort data) under different acceleration intensities and different acceleration change rates in the deceleration scenario. By comparing the acceleration somatic comfort data with the deceleration somatic comfort data, it can be obtained that the somatic difference in comfort caused by the acceleration intensity in the braking (deceleration scenario) and acceleration scenarios is very large. And in the acceleration scenario, the main source of somatic discomfort is the acceleration intensity. The greater the acceleration intensity, the more obvious the corresponding vehicle speed change. Excessive speed change will lead to an increase in the concern about driving safety, and then lead to somatic discomfort. Therefore, the method for evaluating the driving somatic comfort in the embodiments of the present invention obtains parameter factors by fitting experimental data to quantify the somatic comfort in the acceleration scenario, and gives an improved scheme considering the differences between the acceleration and deceleration scenarios on the basis of the general autonomous driving comfort evaluation framework to improve the generalization of the evaluation of the somatic comfort of autonomous driving. As Figure 1 shown Figure 2 What is shown is the relationship between the acceleration intensity and the corresponding somatic comfort in the deceleration scenario (curve 1), and the relationship between the acceleration intensity and the corresponding somatic comfort in the acceleration scenario (curve 2). The acceleration with a "-" sign represents the acceleration in the deceleration scenario, and the positive acceleration value represents the acceleration in the acceleration scenario.

[0073] For ease of understanding, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 2 , an embodiment of the method for evaluating the driving somatic comfort in the embodiments of the present invention includes:

[0074] 201. Obtain the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration.

[0075] It can be understood that the execution subject of the present invention can be an evaluation device for driving somatic comfort, or a terminal or a server. Specifically, it is not limited here. The embodiments of the present invention will be described by taking the server as the execution subject as an example.

[0076] Among them, the driving acceleration and the acceleration change rate of the driving acceleration can be the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration in an acceleration scenario, or the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration in a deceleration scenario. Among them, the motion states in the deceleration scenario include a variable deceleration motion state and a uniform deceleration motion state.

[0077] The server obtains the driving longitudinal acceleration by obtaining the driving acceleration along the vehicle body direction in an acceleration scenario or a deceleration scenario during the somatic comfort evaluation period of the autonomous vehicle, and calculates the change rate of the driving longitudinal acceleration, so as to obtain the longitudinal acceleration change rate of the driving longitudinal acceleration.

[0078] 202. Obtain the target parameter factor corresponding to the driving longitudinal acceleration, and calculate the somatic comfort in the acceleration scenario or the deceleration scenario based on the driving longitudinal acceleration and the target parameter factor to obtain the longitudinal acceleration intensity somatic comfort.

[0079] The server determines the corresponding scenario based on the longitudinal driving acceleration, that is, whether the longitudinal driving acceleration is the longitudinal acceleration in the acceleration scenario or the longitudinal acceleration in the deceleration scenario. If the longitudinal driving acceleration is the longitudinal acceleration in the acceleration scenario, the parameterization factor corresponding to the acceleration scenario, that is, the target parameter factor, is obtained, and the perceived comfort in the acceleration scenario is calculated through the longitudinal driving acceleration and the parameterization factor corresponding to the acceleration scenario, so as to obtain the perceived comfort of the longitudinal acceleration intensity. If the longitudinal driving acceleration is the longitudinal acceleration in the deceleration scenario, the parameterization factor corresponding to the deceleration scenario, that is, the target parameter factor, is obtained, and the perceived comfort in the deceleration scenario is calculated through the longitudinal driving acceleration and the parameterization factor corresponding to the deceleration scenario, so as to obtain the perceived comfort of the longitudinal acceleration intensity. Among them, the target parameter factor is a parameter factor fitted based on the road test data in the acceleration scenario or a parameter factor fitted based on the road test data in the deceleration scenario. The road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the perceived comfort data under the combination of each longitudinal acceleration intensity and each longitudinal acceleration change rate. The longitudinal acceleration intensity is the absolute value of the longitudinal acceleration.

[0080] In a feasible implementation manner, the target parameter factor is used to indicate the calculation metrics in the acceleration scenario and the deceleration scenario, that is, the calculation methods of the perceived comfort in the acceleration scenario and the deceleration scenario are both in accordance with the calculation metrics, for example, absolute value calculation, variance calculation, and normalization processing, etc.; the absolute value of the longitudinal driving acceleration in the acceleration scenario is calculated to obtain the longitudinal driving acceleration intensity, the variance of the longitudinal driving acceleration intensity is calculated and normalized to obtain the perceived comfort of the longitudinal acceleration intensity, so as to realize the calculation of the perceived comfort in the acceleration scenario; the absolute value of the longitudinal driving acceleration in the deceleration scenario is calculated to obtain the longitudinal driving acceleration intensity, the variance of the longitudinal driving acceleration intensity is calculated and normalized to obtain the normalized value, and the normalized value is given a negative value to obtain the perceived comfort of the longitudinal acceleration intensity, so as to realize the calculation of the perceived comfort in the deceleration scenario.

[0081] Alternatively, the target parameter factor is used to indicate the metrics for calculations in an acceleration scenario or a deceleration scenario, that is, the calculation methods for the perceived comfort in both the acceleration scenario and the deceleration scenario are based on the calculation metrics. The calculation method for the perceived comfort in the other scenario is calculated according to the parameter factor obtained by fitting the road test data in the acceleration scenario or the parameter factor obtained by fitting the road test data in the deceleration scenario as described above. By way of example and not limitation, taking the target parameter factor as an example for indicating the metrics for calculations in the deceleration scenario, when the driving longitudinal acceleration is the longitudinal acceleration in the acceleration scenario, obtain the parameterized factor corresponding to the acceleration scenario, that is, the target parameter factor, and calculate the perceived comfort in the acceleration scenario through the driving longitudinal acceleration and the parameterized factor corresponding to the acceleration scenario to obtain the perceived comfort of the longitudinal acceleration intensity; when the driving longitudinal acceleration is the acceleration in the deceleration scenario, calculate the absolute value of the driving longitudinal acceleration in the deceleration scenario to obtain the driving longitudinal acceleration intensity, calculate the variance of the driving longitudinal acceleration intensity and perform normalization processing to obtain a normalized value, and assign a negative value to the normalized value to obtain the perceived comfort of the longitudinal acceleration intensity.

[0082] 203. Obtain the lateral comfort, and determine the target perceived comfort based on the perceived comfort of the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the lateral comfort.

[0083] The server obtains the driving acceleration perpendicular to the vehicle body in the acceleration scenario or the deceleration scenario during the perceived comfort evaluation period of the autonomous vehicle to obtain the driving lateral acceleration, calculates the variance of the driving lateral acceleration and performs normalization processing to obtain the lateral comfort. Fuse the perceived comfort of the longitudinal acceleration intensity and the longitudinal acceleration change rate to obtain the longitudinal comfort, and fuse the longitudinal comfort and the lateral comfort to obtain the target perceived comfort, where the implementation method of the fusion depends on the actual situation and is not limited herein. By way of example and not limitation, the implementation method of the fusion can be simple addition, that is, adding the longitudinal comfort and the lateral comfort, and the implementation method of the fusion can also be weighted summation, that is, performing weighted summation on the longitudinal comfort and the lateral comfort.

[0084] In the embodiments of the present invention, by fusing the perceived comfort evaluation in the acceleration scenario and the perceived comfort evaluation in the deceleration scenario, and combining the acceleration intensity that causes a large difference in the perceived comfort between the braking and acceleration scenarios, it is possible to distinguish the perceived comfort in the two situations of braking and acceleration, and it is possible to generalize the evaluation system obtained for braking to the acceleration situation, thereby improving the generalization of the perceived comfort evaluation of autonomous driving.

[0085] Please refer to Figure 3 , another embodiment of the method for evaluating the driving perceived comfort in the embodiments of the present invention includes:

[0086] Through road tests (road tests refer to experimental tests of corresponding vehicle movements for test items on actual roads), different acceleration intensities and different acceleration change rates in acceleration scenarios, as well as different acceleration intensities and different acceleration change rates in deceleration scenarios are collected. The different acceleration intensities and different acceleration change rates in the acceleration scenario are respectively fitted to obtain the fitting data in the acceleration scenario, and the different acceleration intensities and different acceleration change rates in the deceleration scenario are respectively fitted to obtain the fitting data in the deceleration scenario. The fitting data in the acceleration scenario or the fitting data in the deceleration scenario is the target parameter factor. A parameterized model for comfort evaluation in the acceleration scenario is constructed based on the fitting data in the acceleration scenario to obtain an acceleration parameterized model, and a parameterized model for comfort evaluation in the deceleration scenario is constructed based on the fitting data in the deceleration scenario to obtain a deceleration parameterized model. The perceived comfort in the acceleration scenario is calculated through the acceleration parameterized model, and the perceived comfort in the deceleration scenario is calculated through the deceleration parameterized model, so as to introduce the acceleration-deceleration difference into the perceived comfort evaluation system.

[0087] In the embodiment of the present invention, the evaluation method of driving perceived comfort obtains a parameterized model (acceleration parameterized model) by fitting experimental data (i.e., road test data) to quantify the perceived comfort in the acceleration scenario, and gives an improved scheme considering the acceleration-deceleration scenario difference on the basis of the general autonomous driving comfort evaluation framework.

[0088] 301. Obtain the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration.

[0089] Among them, the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration may be the driving longitudinal acceleration and the acceleration change rate of the driving longitudinal acceleration in the acceleration scenario, or the driving longitudinal acceleration and the acceleration change rate of the driving longitudinal acceleration in the deceleration scenario. Among them, the motion states in the deceleration scenario include a variable deceleration motion state and a uniform deceleration motion state.

[0090] The server obtains the driving acceleration along the vehicle body direction in the acceleration scenario or the deceleration scenario during the perceived comfort evaluation period of the autonomous driving vehicle to obtain the driving longitudinal acceleration, and calculates the change rate of the driving acceleration along the vehicle body direction in the acceleration scenario or the deceleration scenario during the perceived comfort evaluation period, so as to obtain the longitudinal acceleration change rate of the driving longitudinal acceleration.

[0091] Specifically, before the server obtains the driving longitudinal acceleration and the acceleration change rate of the driving longitudinal acceleration, it obtains the road test data in the acceleration scenario and the road test data in the deceleration scenario. The road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the somatosensory comfort data in the case of each combination of the longitudinal acceleration intensity and the longitudinal acceleration change rate. Perform parameter fitting on the road test data in the acceleration scenario to obtain an acceleration parameter factor, and perform parameter fitting on the road test data in the deceleration scenario to obtain a deceleration parameter factor. The acceleration parameter factor is used to indicate the parameters for comfort evaluation in the acceleration scenario, and the deceleration parameter factor is used to indicate the parameters for comfort evaluation in the deceleration scenario. Determine the acceleration parameter factor or the deceleration parameter factor as the target parameter factor.

[0092] Among them, by way of example and not limitation, the implementation manner of parameter fitting can be a preset fitting function. The fitting function is a regression function, and the implementation manner of parameter fitting can be curve fitting. The parameters in the parameter fitting of the road test data in the acceleration scenario are the parameters required to construct a parameterized model for comfort evaluation in the acceleration scenario based on the fitting data in the acceleration scenario. The parameters in the parameter fitting of the road test data in the deceleration scenario are the parameters required to construct a parameterized model for comfort evaluation in the acceleration scenario based on the fitting data in the deceleration scenario.

[0093] Construct the target parameter factor through fitting to facilitate the calculation difference between the acceleration scenario and the deceleration scenario of the constructed parameterized model and improve its calculation accuracy.

[0094] 302. Determine whether the driving longitudinal acceleration is greater than a preset target value.

[0095] Among them, the preset target value is used to indicate whether the driving longitudinal acceleration is the longitudinal acceleration in the acceleration scenario or the longitudinal acceleration in the deceleration scenario. Preferably, the target value in the embodiments of the present invention is 0. The server determines whether the driving longitudinal acceleration is greater than 0 to determine whether the driving longitudinal acceleration is the longitudinal acceleration in the acceleration scenario.

[0096] 303. If the driving longitudinal acceleration is greater than the preset target value, obtain the target parameter factor corresponding to the driving longitudinal acceleration. The target parameter factor is the acceleration parameter factor, and the acceleration parameter factor is a parameter factor generated based on the road test data in the acceleration scenario.

[0097] If the driving longitudinal acceleration is greater than a preset target value, i.e., greater than 0, it indicates that the driving longitudinal acceleration is the longitudinal acceleration in an acceleration scenario. Obtain the target parameter factor corresponding to the acceleration scenario, i.e., the acceleration parameter factor. The acceleration parameter factor is the data obtained by fitting the road test data in the acceleration scenario according to the parameter terms in the parameterized model (which can be a function or an algorithm) of the preset acceleration scenario. Preferably, in the embodiment of the present invention, the acceleration parameter factor is the data obtained by fitting the road test data in the acceleration scenario according to the parameter terms in the preset asymmetric saturation function.

[0098] 304. Calculate the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

[0099] Specifically, the server calculates the absolute value of the driving longitudinal acceleration and determines whether the absolute value of the driving longitudinal acceleration is less than a preset threshold; if the absolute value of the driving longitudinal acceleration is less than the preset threshold, determine the longitudinal acceleration intensity somatic comfort level in the acceleration scenario as the preset comfort threshold to obtain the longitudinal acceleration intensity somatic comfort level; if the absolute value of the driving longitudinal acceleration is greater than or equal to the preset threshold, calculate the somatic comfort level in the acceleration scenario based on the preset first asymmetric saturation function, the acceleration parameter factor, and the absolute value of the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

[0100] When the driving longitudinal acceleration is the acceleration in the acceleration scenario, calculate the absolute value of the driving longitudinal acceleration, denoted as |acc1|; determine whether |acc1| is less than the preset threshold. The preset threshold is used to indicate the cut-off value, that is, through this cut-off value, it is determined whether the longitudinal acceleration intensity somatic comfort level in the acceleration scenario is a constant value. Preferably, the preset threshold in the embodiment of the present invention is 0; if so, determine the longitudinal acceleration intensity somatic comfort level in the acceleration scenario as the preset comfort threshold. The preset comfort threshold is a constant value. Preferably, the preset comfort threshold in the embodiment of the present invention is 1, that is, if |acc1| < the preset threshold, then f1(|acc1|) = 1, where f1(|acc1|) represents the longitudinal acceleration intensity somatic comfort level in the acceleration scenario, that is, the acceleration parameterization model; if not, calculate the somatic comfort level in the acceleration scenario based on the preset first asymmetric saturation function, the acceleration parameter factor, and the absolute value of the driving longitudinal acceleration. The specific form of the first asymmetric saturation function is as follows: Where f1 represents the somatic comfort level in the acceleration scenario, that is, the longitudinal acceleration intensity somatic comfort level in the acceleration scenario. θ1, θ2, and θ3 all represent the acceleration parameter factor, and ξ1 represents the absolute value of the driving longitudinal acceleration, that is, |acc1|.

[0101] Through the implementation method of the somatic comfort in the above-mentioned calculation acceleration scenario, the accuracy of the longitudinal somatic comfort in the acceleration scenario is improved.

[0102] 305. If the driving longitudinal acceleration is less than or equal to a preset target value, obtain the target parameter factor corresponding to the driving longitudinal acceleration. The target parameter factor is a deceleration parameter factor, and the deceleration parameter factor is a parameter factor generated based on the road test data in the deceleration scenario.

[0103] If the driving longitudinal acceleration is less than or equal to the preset target value, that is, less than or equal to 0, it means that the driving longitudinal acceleration is the longitudinal acceleration in the deceleration scenario. Obtain the target parameter factor corresponding to the deceleration scenario, that is, the deceleration parameter factor. The deceleration parameter factor is the data obtained by fitting the road test data in the deceleration scenario according to the parameter items in the parameterized model (which can be a function or an algorithm) of the preset deceleration scenario. Preferably, the deceleration parameter factor in the embodiment of the present invention is the data obtained by fitting the road test data in the deceleration scenario according to the parameter items in the preset asymmetric saturation function.

[0104] 306. Calculate the somatic comfort in the deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort.

[0105] Specifically, the server calculates the absolute value of the driving longitudinal acceleration; based on the preset second asymmetric saturation function, the deceleration parameter factor and the absolute value of the driving longitudinal acceleration, calculate the somatic comfort in the deceleration scenario to obtain the longitudinal acceleration intensity somatic comfort.

[0106] When the driving longitudinal acceleration is the longitudinal acceleration in the deceleration scenario, calculate the absolute value of the driving longitudinal acceleration, denoted as |acc2|; based on the preset second asymmetric saturation function, the deceleration parameter factor and the absolute value of the driving longitudinal acceleration, calculate the somatic comfort in the deceleration scenario. Among them, the second asymmetric saturation function (acceleration parameterization model, that is, f2) is specifically as follows: Among them, f2 represents the somatic comfort in the deceleration scenario, that is, the longitudinal acceleration intensity somatic comfort. θ4, θ5 and θ6 all represent the deceleration parameter factor, and ξ2 represents the absolute value of the driving longitudinal acceleration, that is, |acc2|.

[0107] Through the above implementation method of calculating the somatic comfort in the deceleration scenario, the accuracy of the longitudinal somatic comfort in the deceleration scenario is improved.

[0108] 307. Obtain the lateral comfort, and determine the target somatic comfort based on the longitudinal acceleration intensity somatic comfort, the longitudinal acceleration change rate and the lateral comfort.

[0109] Specifically, the server performs weighted summation on the longitudinal acceleration intensity somatosensory comfort and the longitudinal acceleration change rate to obtain the longitudinal comfort; obtains the lateral comfort, and performs weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort.

[0110] Specifically, the server obtains the lateral comfort, and performs weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort, including: obtaining the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario, and calculating the variance of the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario to obtain the lateral acceleration variance; performing normalization processing on the lateral acceleration variance to obtain the lateral comfort; performing weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort.

[0111] The server obtains the driving acceleration perpendicular to the vehicle body direction in the acceleration scenario or the deceleration scenario during the somatosensory comfort evaluation period of the autonomous driving vehicle to obtain the driving lateral acceleration, calculates the variance of the driving lateral acceleration and performs normalization processing, thereby obtaining the lateral comfort. The server performs weighted summation on the longitudinal acceleration intensity somatosensory comfort and the longitudinal acceleration change rate to obtain the longitudinal comfort, and performs weighted summation on the longitudinal comfort and the lateral comfort to obtain the target somatosensory comfort. By combining the longitudinal comfort and the lateral comfort in the acceleration scenario or the deceleration scenario to determine the target somatosensory comfort, the generalization of the autonomous driving somatosensory comfort evaluation is improved.

[0112] In the embodiment of the present invention, by fusing the somatosensory comfort evaluation in the acceleration scenario and the somatosensory comfort evaluation in the deceleration scenario, and combining the acceleration intensity with a large somatosensory difference in the braking and acceleration scenarios resulting in the somatosensory comfort, it is possible to distinguish the somatosensory comfort in the two situations of braking and acceleration, and it is possible to generalize the evaluation system obtained for braking to the acceleration situation, thereby improving the generalization of the autonomous driving somatosensory comfort evaluation.

[0113] The evaluation method of the driving somatosensory comfort in the embodiment of the present invention has been described above. Next, the evaluation device of the driving somatosensory comfort in the embodiment of the present invention will be described. Please refer to Figure 4 In an embodiment, the evaluation device of the driving somatosensory comfort in the embodiment of the present invention includes:

[0114] The first acquisition module 401 is used to acquire the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration;

[0115] The calculation module 402 is used to acquire the target parameter factor corresponding to the driving longitudinal acceleration, and based on the driving longitudinal acceleration and the target parameter factor, calculate the somatosensory comfort in the acceleration scenario or the deceleration scenario to obtain the longitudinal acceleration intensity somatosensory comfort;

[0116] The first determination module 403 is configured to obtain the lateral comfort level, and determine the target somatic comfort level based on the longitudinal acceleration intensity somatic comfort level, the longitudinal acceleration change rate, and the lateral comfort level.

[0117] The functions of the various modules in the above-mentioned driving somatic comfort evaluation device correspond to the steps in the embodiments of the above-mentioned driving somatic comfort evaluation method, and their functions and implementation processes will not be elaborated here one by one.

[0118] In the embodiments of the present invention, by fusing the somatic comfort evaluation in the acceleration scenario and the somatic comfort evaluation in the deceleration scenario, and combining the acceleration intensity with a large difference in somatic comfort between the braking and acceleration scenarios, it is possible to distinguish the somatic comfort levels in the two situations of braking and acceleration, and it is possible to generalize the evaluation system obtained for braking to the acceleration situation, thereby improving the generalization of the autonomous driving somatic comfort evaluation.

[0119] Please refer to Figure 5 , another embodiment of the driving somatic comfort evaluation device in the embodiments of the present invention includes:

[0120] The first acquisition module 401 is configured to acquire the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration;

[0121] The calculation module 402 is configured to obtain the target parameter factor corresponding to the driving longitudinal acceleration, and calculate the somatic comfort level in the acceleration scenario or the deceleration scenario based on the driving longitudinal acceleration and the target parameter factor, so as to obtain the longitudinal acceleration intensity somatic comfort level;

[0122] Wherein, the calculation module 402 specifically includes:

[0123] The judgment unit 4021 is configured to judge whether the driving longitudinal acceleration is greater than a preset target value;

[0124] The first acquisition unit 4022 is configured to, if the driving longitudinal acceleration is greater than the preset target value, acquire the target parameter factor corresponding to the driving longitudinal acceleration, and the target parameter factor is an acceleration parameter factor, and the acceleration parameter factor is a parameter factor generated based on the road test data in the acceleration scenario;

[0125] The first calculation unit 4023 is configured to calculate the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatic comfort level;

[0126] The second acquisition unit 4024 is configured to, if the driving longitudinal acceleration is less than or equal to the preset target value, acquire the target parameter factor corresponding to the driving longitudinal acceleration, and the target parameter factor is a deceleration parameter factor, and the deceleration parameter factor is a parameter factor generated based on the road test data in the deceleration scenario;

[0127] A second calculation unit 4025 is configured to calculate the somatosensory comfort level in a deceleration scenario based on a deceleration parameter factor and the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatosensory comfort level.

[0128] A first determination module 403 is configured to obtain the lateral comfort level, and determine the target somatosensory comfort level based on the longitudinal acceleration intensity somatosensory comfort level, the longitudinal acceleration change rate, and the lateral comfort level.

[0129] Optionally, the first calculation unit 4023 may further be specifically configured to:

[0130] Calculate the absolute value of the driving longitudinal acceleration, and determine whether the absolute value of the driving longitudinal acceleration is less than a preset threshold;

[0131] If the absolute value of the driving longitudinal acceleration is less than the preset threshold, determine the longitudinal acceleration intensity somatosensory comfort level in the acceleration scenario as the preset comfort threshold to obtain the longitudinal acceleration intensity somatosensory comfort level;

[0132] If the absolute value of the driving longitudinal acceleration is greater than or equal to the preset threshold, calculate the somatosensory comfort level in the acceleration scenario based on a preset first asymmetric saturation function, an acceleration parameter factor, and the absolute value of the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatosensory comfort level.

[0133] Optionally, the second calculation unit 4025 may further be specifically configured to:

[0134] Calculate the absolute value of the driving longitudinal acceleration;

[0135] Calculate the somatosensory comfort level in the deceleration scenario based on a preset second asymmetric saturation function, a deceleration parameter factor, and the absolute value of the driving longitudinal acceleration, so as to obtain the longitudinal acceleration intensity somatosensory comfort level.

[0136] Optionally, the driving somatosensory comfort level evaluation device further includes:

[0137] A second acquisition module 404 is configured to acquire the road test data in the acceleration scenario and the road test data in the deceleration scenario. The road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the somatosensory comfort level data in the case of each combination of the longitudinal acceleration intensity and the longitudinal acceleration change rate;

[0138] A fitting module 405 is configured to perform parameter fitting on the road test data in the acceleration scenario to obtain an acceleration parameter factor, and perform parameter fitting on the road test data in the deceleration scenario to obtain a deceleration parameter factor. The acceleration parameter factor is used to indicate the parameters for comfort level evaluation in the acceleration scenario, and the deceleration parameter factor is used to indicate the parameters for comfort level evaluation in the deceleration scenario;

[0139] The second determination module 406 is configured to determine an acceleration parameter factor or a deceleration parameter factor as a target parameter factor.

[0140] Optionally, the first determination module 403 includes:

[0141] A first summation unit 4031, configured to perform weighted summation on the longitudinal acceleration intensity body feeling comfort and the longitudinal acceleration change rate to obtain longitudinal comfort;

[0142] A second summation unit 4032, configured to obtain lateral comfort, and perform weighted summation on the longitudinal comfort and the lateral comfort to obtain the target body feeling comfort.

[0143] Optionally, the second summation unit 4032 may specifically be configured to:

[0144] Obtain acceleration data in the vertical vehicle body direction in an acceleration scenario or a deceleration scenario, and calculate the variance of the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario to obtain a lateral acceleration variance;

[0145] Perform normalization processing on the lateral acceleration variance to obtain lateral comfort;

[0146] Perform weighted summation on the longitudinal comfort and the lateral comfort to obtain the target body feeling comfort.

[0147] The functions of each module and each unit in the above driving body feeling comfort evaluation device correspond to the steps in the above driving body feeling comfort evaluation method embodiment, and their functions and implementation processes will not be elaborated here one by one.

[0148] In the embodiment of the present invention, by fusing the body feeling comfort evaluation in the acceleration scenario and the body feeling comfort evaluation in the deceleration scenario, and combining the acceleration intensity with a large difference in body feeling comfort between the braking and acceleration scenarios, it is possible to distinguish the body feeling comfort in the two situations of braking and acceleration, and to generalize the evaluation system obtained for braking to the acceleration situation, thereby improving the generalization of the automatic driving body feeling comfort evaluation.

[0149] Above Figure 4 And Figure 5 The evaluation device for driving body feeling comfort in the embodiment of the present invention is described in detail from the perspective of modular functional entities. Below, the computer device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0150] Figure 6FIG. 0 is a schematic structural diagram of a computer device provided by an embodiment of the present invention. The computer device 600 may vary greatly due to different configurations or performances, and may include one or more central processing units (CPUs) 610 (for example, one or more processors) and a memory 620, and one or more storage media 630 (for example, one or more mass storage devices) for storing application programs 633 or data 632. Among them, the memory 620 and the storage media 630 may be transient storage or persistent storage. The programs stored in the storage media 630 may include one or more modules (not shown in the figure), and each module may include a series of computer program operations on the computer device 600. Further, the processor 610 may be configured to communicate with the storage media 630 and execute a series of computer program operations in the storage media 630 on the computer device 600.

[0151] The computer device 600 may further include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input / output interfaces 660, and / or one or more operating systems 631, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 6 the computer device structure shown does not constitute a limitation on the computer device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0152] The present invention also provides a computer device, including: a memory and at least one processor, where a computer program is stored in the memory, and the memory and the at least one processor are interconnected by a line; the at least one processor invokes the computer program in the memory to enable the computer device to execute the steps in the above-mentioned method for evaluating the driving body feeling comfort. The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. A computer program is stored in the computer-readable storage medium. When the computer program runs on a computer, the computer is enabled to execute the steps of the method for evaluating the driving body feeling comfort.

[0153] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described systems, devices, and units may refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0154] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several computer programs to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0155] In the above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A method for evaluating the driving body feeling comfort, characterized in that The method for evaluating the driving somatic comfort level includes: Obtaining the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration; Obtaining the target parameter factor corresponding to the driving longitudinal acceleration, and calculating the somatic comfort level in the acceleration scenario or the deceleration scenario based on the driving longitudinal acceleration and the target parameter factor to obtain the longitudinal acceleration intensity somatic comfort level; wherein, the target parameter factor is a parameter factor fitted based on the road test data in the acceleration scenario or a parameter factor fitted based on the road test data in the deceleration scenario, and the road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the somatic comfort level data in the case of each combination of the longitudinal acceleration intensity and the longitudinal acceleration change rate; Obtaining the lateral comfort level, and determining the target somatic comfort level based on the longitudinal acceleration intensity somatic comfort level, the longitudinal acceleration change rate, and the lateral comfort level.

2. The evaluation method of driving body feeling comfort according to claim 1, characterized in that, The step of obtaining the target parameter factor corresponding to the driving longitudinal acceleration, and calculating the somatic comfort level in the acceleration scenario or the deceleration scenario based on the driving longitudinal acceleration and the target parameter factor to obtain the longitudinal acceleration intensity somatic comfort level includes: Judging whether the driving longitudinal acceleration is greater than a preset target value; If the driving longitudinal acceleration is greater than the preset target value, obtaining the target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is an acceleration parameter factor, and the acceleration parameter factor is a parameter factor generated based on the road test data in the acceleration scenario; Calculating the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level; If the driving longitudinal acceleration is less than or equal to the preset target value, obtaining the target parameter factor corresponding to the driving longitudinal acceleration, where the target parameter factor is a deceleration parameter factor, and the deceleration parameter factor is a parameter factor generated based on the road test data in the deceleration scenario; Calculating the somatic comfort level in the deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

3. The evaluation method of driving body feeling comfort according to claim 2, characterized in that The step of calculating the somatic comfort level in the acceleration scenario through the acceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level includes: Calculating the absolute value of the driving longitudinal acceleration, and judging whether the absolute value of the driving longitudinal acceleration is less than a preset threshold; If the absolute value of the driving longitudinal acceleration is less than the preset threshold, determining the longitudinal acceleration intensity somatic comfort level in the acceleration scenario as the preset comfort threshold to obtain the longitudinal acceleration intensity somatic comfort level; If the absolute value of the driving longitudinal acceleration is greater than or equal to the preset threshold, calculating the somatic comfort level in the acceleration scenario based on a preset first asymmetric saturation function, the acceleration parameter factor, and the absolute value of the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level.

4. The evaluation method for driving somatic comfort according to claim 2, characterized in that, The step of calculating the somatic comfort level in the deceleration scenario through the deceleration parameter factor and the driving longitudinal acceleration to obtain the longitudinal acceleration intensity somatic comfort level includes: Calculate the absolute value of the driving longitudinal acceleration; Based on a preset second asymmetric saturation function, the deceleration parameter factor, and the absolute value of the driving longitudinal acceleration, calculate the somatosensory comfort level in the deceleration scenario to obtain the longitudinal acceleration intensity somatosensory comfort level.

5. The evaluation method for driving body sensation comfort according to claim 1, wherein Before obtaining the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration, it further includes: Obtain the road test data in the acceleration scenario and the road test data in the deceleration scenario. The road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the somatosensory comfort level data in the case of each combination of the longitudinal acceleration intensity and the longitudinal acceleration change rate; Perform parameter fitting on the road test data in the acceleration scenario to obtain an acceleration parameter factor, and perform parameter fitting on the road test data in the deceleration scenario to obtain a deceleration parameter factor. The acceleration parameter factor is used to indicate the parameter for comfort evaluation in the acceleration scenario, and the deceleration parameter factor is used to indicate the parameter for comfort evaluation in the deceleration scenario; Determine the acceleration parameter factor or the deceleration parameter factor as the target parameter factor.

6. The evaluation method for driving body feeling comfort according to any one of claims 1-5, characterized in that, The obtaining of the lateral comfort level, and determining the target somatosensory comfort level based on the longitudinal acceleration intensity somatosensory comfort level, the longitudinal acceleration change rate, and the lateral comfort level, includes: Perform weighted summation on the longitudinal acceleration intensity somatosensory comfort level and the longitudinal acceleration change rate to obtain the longitudinal comfort level; Obtain the lateral comfort level, and perform weighted summation on the longitudinal comfort level and the lateral comfort level to obtain the target somatosensory comfort level.

7. The evaluation method for driving body feeling comfort according to claim 6, characterized in that, The obtaining of the lateral comfort level, and performing weighted summation on the longitudinal comfort level and the lateral comfort level to obtain the target somatosensory comfort level, includes: Obtain the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario, and calculate the variance of the acceleration data in the vertical vehicle body direction in the acceleration scenario or the deceleration scenario to obtain the lateral acceleration variance; Perform normalization processing on the lateral acceleration variance to obtain the lateral comfort level; Perform weighted summation on the longitudinal comfort level and the lateral comfort level to obtain the target somatosensory comfort level.

8. An evaluation device for the comfort of driving experience, characterized in that, The device for evaluating the driving somatosensory comfort level includes: A first obtaining module, configured to obtain the driving longitudinal acceleration and the longitudinal acceleration change rate of the driving longitudinal acceleration; A calculation module, configured to obtain the target parameter factor corresponding to the driving longitudinal acceleration, and based on the driving longitudinal acceleration and the target parameter factor, calculate the somatosensory comfort level in the acceleration scenario or the deceleration scenario to obtain the longitudinal acceleration intensity somatosensory comfort level; the target parameter factor is a parameter factor obtained by fitting the road test data in the acceleration scenario or a parameter factor obtained by fitting the road test data in the deceleration scenario. The road test data includes the longitudinal acceleration intensity, the longitudinal acceleration change rate, and the somatosensory comfort level data in the case of each combination of the longitudinal acceleration intensity and the longitudinal acceleration change rate; A first determination module, configured to obtain the lateral comfort level, and determine the target somatosensory comfort level based on the longitudinal acceleration intensity somatosensory comfort level, the longitudinal acceleration change rate, and the lateral comfort level.

9. A computer device, characterized in that, The computer device includes: a memory and at least one processor, and a computer program is stored in the memory; The at least one processor calls the computer program in the memory to cause the computer device to execute the method for evaluating driving body feeling comfort as described in any one of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by the processor, it implements the method for evaluating driving body feeling comfort as described in any one of claims 1-7.

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