Manual door handle position prompting method and device, vehicle and readable storage medium

Abstract

The invention relates to a manual door handle position prompting method and device, a vehicle and a readable storage medium. The method comprises the steps of obtaining vehicle operation data of a target vehicle under the condition that the target vehicle is in a power-on state; according to the vehicle operation data, the starting state of an intelligent door in the target vehicle is determined; and under the condition that the starting state of the intelligent door is abnormal, the position of the manual door handle in the target vehicle is prompted. By adopting the method, the position of the manual door handle can be prompted in time under the condition that the starting state of the intelligent door is abnormal, so that the riding user can leave the target vehicle conveniently.

Description

Technical Field

[0001] The present application relates to the field of intelligent automobile technology, and in particular to a manual door handle position prompt method, device, vehicle and readable storage medium. Background Art

[0002] With the rapid development of intelligent automobile technology, smart doors (i.e. electric doors) are gradually becoming popular in various models. Vehicles equipped with smart doors (i.e. target vehicles) realize automatic opening and closing of smart doors through data transmission between various sensors and controllers.

[0003] However, in extreme cases, the smart door may be out of control, resulting in the inability to open the smart door when the target vehicle needs to be opened. Therefore, an emergency door handle (i.e., a manual door handle) is also provided in the target vehicle to facilitate passengers to leave the target vehicle in extreme cases. However, in general, users other than the car owner do not know the location of the emergency door handle in the car, resulting in the inability of passengers to leave the target vehicle in time in extreme cases, which urgently needs to be solved. Summary of the invention

[0004] Based on this, it is necessary to provide a manual door handle position prompt method, device, vehicle and readable storage medium to address the above technical problems, which can promptly prompt the position of the manual door handle when the startup state of the smart door is abnormal, so as to facilitate passengers to leave the target vehicle.

[0005] In a first aspect, the present application provides a manual door handle position prompt method, comprising:

[0006] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0007] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0008] In case of abnormal start-up status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0009] In one of the embodiments, the vehicle operation data includes the system operation data of the vehicle electronic control system corresponding to the target vehicle in the current time period; accordingly, the startup status of the intelligent door in the target vehicle is determined based on the vehicle operation data, including: determining the startup failure rate corresponding to the intelligent door in the target vehicle based on the system operation data; determining the startup status of the intelligent door in the target vehicle based on the startup failure rate.

[0010] In one of the embodiments, the startup failure rate corresponding to the smart door in the target vehicle is determined based on the system operation data, including: when the system operation data exceeds a preset operation threshold, the startup failure rate corresponding to the smart door in the target vehicle is determined based on the system operation data.

[0011] In one of the embodiments, the vehicle operation data includes the key position information of the digital key corresponding to the target vehicle, and the vehicle position information of the target vehicle; accordingly, the start-up status of the smart door in the target vehicle is determined based on the vehicle operation data, including: determining the communication evaluation data of the target vehicle based on the key position information and the vehicle position information; determining the start-up status of the smart door based on the communication evaluation data.

[0012] In one of the embodiments, the vehicle operation data includes obstacle motion information corresponding to at least one obstacle in the area where the target vehicle is located, and vehicle motion information of the target vehicle; accordingly, the start-up state of the smart door in the target vehicle is determined based on the vehicle operation data, including: predicting the predicted collision points corresponding to the target vehicle and each obstacle based on the obstacle motion information and vehicle motion information corresponding to at least one obstacle; determining the start-up state of the smart door based on the distance between the current position of the target vehicle and each predicted collision point.

[0013] In one of the embodiments, when the target vehicle is powered on, vehicle operation data of the target vehicle is obtained, including: when the target vehicle is powered on and there are passengers in the target vehicle, the vehicle operation data of the target vehicle is obtained; correspondingly, when the startup state of the smart door is abnormal, the position of the manual door handle in the target vehicle is prompted, including: when the startup state of the smart door is abnormal, the position of the manual door handle that matches the position of the passenger is prompted.

[0014] In one of the embodiments, prompting the position of a manual door handle that matches the position of a passenger includes: controlling an indicator light corresponding to the manual door handle that matches the position of the passenger to light up to prompt the position of the corresponding manual door handle.

[0015] In a second aspect, the present application also provides a manual door handle position prompting device, comprising:

[0016] A data acquisition module, used to acquire vehicle operation data of the target vehicle when the target vehicle is in a powered-on state;

[0017] A state determination module, used to determine the start state of the smart door in the target vehicle according to the vehicle operation data;

[0018] The position prompt module is used to prompt the position of the manual door handle in the target vehicle when the start-up state of the smart door is abnormal.

[0019] In a third aspect, the present application further provides a vehicle, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0020] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0021] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0022] In case of abnormal start-up status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0023] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0024] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0025] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0026] In case of abnormal startup status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0027] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0028] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0029] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0030] In case of abnormal startup status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0031] The above-mentioned manual door handle position prompt method, device, vehicle and readable storage medium, when detecting that the target vehicle is in the power-on state, obtain the vehicle operation data of the target vehicle, and determine the start-up state of the smart door in the target vehicle according to the vehicle operation data. Further, in the case where the start-up state of the smart door is abnormal, the position of the manual door handle in the target vehicle is prompted. In the above process, the start-up state of the smart door in the target vehicle is determined based on the vehicle operation data of the target vehicle, which can improve the accuracy of the start-up state determination and avoid the problem of not prompting when the position of the manual door handle needs to be prompted. Further, in the case where the start-up state of the smart door indicates that the door of the target vehicle may not be opened or closed normally electrically, in order to avoid being unable to control the door of the target vehicle, the position of the manual door handle in the target vehicle is prompted to facilitate opening or closing the door of the target vehicle. In other words, the above process can prompt the position of the manual door handle in time when the start-up state of the smart door is abnormal, so as to facilitate the passenger to leave the target vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 A diagram showing an application environment of a manual door handle position prompting method in one embodiment;

[0034] Figure 2 A schematic diagram of a flow chart of a manual door handle position prompting method in one embodiment;

[0035] Figure 3 A schematic diagram of a process of determining a startup state in one embodiment;

[0036] Figure 4 A schematic flow chart of a startup state determination step in another embodiment;

[0037] Figure 5A A schematic flow chart of a startup state determination step in another embodiment;

[0038] Figure 5B An interactive schematic diagram of predicting a collision point in one embodiment;

[0039] Figure 5C A schematic diagram of a path for a target vehicle and an obstacle to reach a predicted collision point in one embodiment;

[0040] Figure 5D A schematic diagram of a path for a target vehicle and an obstacle to reach a predicted collision point in another embodiment;

[0041] Fig. 6A A schematic flow chart of vehicle operation data acquisition steps in one embodiment;

[0042] Figure 6B A schematic diagram of a manual door handle display mode in an embodiment;

[0043] Fig. 7A A schematic diagram of a flow chart of a manual door handle position prompting method in another embodiment;

[0044] Figure 7B A schematic flow chart of a startup state determination step in another embodiment;

[0045] Figure 7C A schematic flow chart of a startup state determination step in another embodiment;

[0046] Fig.7D A schematic flow chart of a startup state determination step in another embodiment;

[0047] Figure 8 is a structural block diagram of a manual door handle position prompting device in one embodiment;

[0048] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] Before introducing the manual door handle position prompt method provided by this application, it should be noted that at this stage, smart doors are slowly entering various models, but most people except car owners do not know that in addition to an electric switch, there is also an emergency manual door handle in the car. The manual door handle is relatively private, usually located in the storage box under the door. Smart doors usually refer to doors that are automatically opened and closed by ECU. The working principle of this door mainly depends on the coordinated work of components such as motors, sensors, ECUs and power systems. When the ECU detects that the user issues an instruction to open or close the door through a remote control, button or vehicle-mounted system, the ECU will control the operation of the motor and realize the opening and closing of the door by the forward and reverse rotation of the motor. At the same time, the sensor monitors the position of the door to ensure that the motor stops running when the door is fully opened or closed. However, in the event of a failure in a system or device working in collaboration, the ECU will not be able to receive the door control command, and thus the door cannot be opened or closed normally.

[0051] The present application is precisely to solve the above-mentioned problem. By predicting the occurrence of abnormal situations (including ECU communication, vehicle collision, circuit short circuit, power battery pack damage, etc.) in advance, when the smart door lock may fail to automatically unlock the vehicle, the passenger is prompted with the location of the manual door handle, so that the passenger can find the location of the manual door handle and manually open the door to avoid dangerous situations.

[0052] The manual door handle position prompt method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown in the figure, the electronic control unit (Engine Control Unit, ECU) 102 communicates with the body control module (Body Control Module, BCM) 104 through the network. Specifically, when the target vehicle is in the power-on state, the ECU obtains the vehicle operation data of the target vehicle, and determines the start state of the smart door in the target vehicle according to the vehicle operation data. When the start state of the smart door is abnormal, the ECU controls the BCM to prompt the position of the manual door handle in the target vehicle.

[0053] In an exemplary embodiment, Figure 2 As shown, a manual door handle position prompt method is provided, and the method is applied to Figure 1 Taking the ECU 102 in the example as an example, the following steps are included:

[0054] S210, when the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle.

[0055] Among them, the target vehicle is a vehicle equipped with intelligent doors, that is, the doors of the target vehicle are controlled to open and close through the car side door electric opening system configured in the target vehicle.

[0056] The vehicle operation data can be used to characterize the operating parameters of the target vehicle at the current time or at the current time and in the historical period, and can reflect the working state and performance of the target vehicle. For example, the vehicle operation data can include at least one of vehicle state data, vehicle driving data, vehicle generator data, and vehicle electrical data.

[0057] It should be noted that the target vehicle is in a powered-on state, which indicates that the power system of the target vehicle has been connected and the battery starts to provide power to the vehicle. At this time, the target vehicle may be in a driving state or a non-driving state.

[0058] Specifically, in this embodiment, when it is detected that the target vehicle is in a powered-on state, the vehicle operation data of the target vehicle is obtained from the storage location corresponding to the vehicle operation data. Exemplarily, different types of vehicle operation data can be stored in different locations; accordingly, when the target vehicle is in a powered-on state, the vehicle operation data of the vehicle can be obtained from the storage location corresponding to the required data according to the vehicle operation data acquisition requirement.

[0059] S220: Determine the activation state of the intelligent door in the target vehicle according to the vehicle operation data.

[0060] The start-up state of the smart door is used to characterize whether the smart door in the target vehicle can be opened or closed electrically normally. It is understandable that when the start-up state of the smart door is normal, the door of the target vehicle can be opened or closed electrically; when the start-up state of the smart door is abnormal, the door of the target vehicle may not be opened or closed electrically.

[0061] In an optional implementation, the reference operating data of the reference vehicle and the start-up state of the smart door corresponding to the reference vehicle under different reference operating data can be acquired in advance, and then the corresponding relationship between the reference operating data and the reference start-up state is determined according to the acquired data. The reference start-up state corresponding to the vehicle operating data of the target vehicle in the corresponding relationship is used as the start-up state of the smart door in the target vehicle. The model of the reference vehicle is the same as that of the target vehicle.

[0062] In an optional embodiment, the vehicle operation data can be input into a pre-trained start-up state determination model to obtain the start-up state of the intelligent door in the target vehicle. Among them, the start-up state determination model can be built based on a common neural network, which will not be described in detail here. Furthermore, in the process of training the start-up state determination model, the reference operation data can be input into the start-up state determination model to be trained to obtain the predicted start-up state corresponding to the reference operation data, and then the model parameters of the start-up state determination model are adjusted according to the predicted start-up state and the reference start-up state corresponding to the corresponding reference operation data.

[0063] In an optional implementation, the safe operation state of the target vehicle can be determined based on the vehicle operation data, and the start-up state of the smart door in the target vehicle can be determined based on the safe operation state of the target vehicle. The safe operation state represents whether the target vehicle can operate normally. For example, when it is determined that the target vehicle can operate normally, the start-up state of the smart door in the target vehicle is determined to be normal; when it is determined that the target vehicle cannot operate normally, the start-up state of the smart door in the target vehicle is determined to be abnormal.

[0064] S230, when the start-up state of the intelligent door is abnormal, the position of the manual door handle in the target vehicle is prompted.

[0065] In an optional implementation, when it is determined that the startup state of the smart door is abnormal, the position information of the manual door handle in the target vehicle is output by voice to prompt the position of the manual door handle in the target vehicle.

[0066] In an optional implementation, when it is determined that the startup state of the smart door is abnormal, the position information of the manual door handle in the target vehicle is displayed on the vehicle-mounted terminal of the target vehicle to prompt the position of the manual door handle in the target vehicle.

[0067] In an optional embodiment, when it is determined that the startup state of the smart door is abnormal, the position information of the manual door handle in the target vehicle can be displayed on the on-board terminal of the target vehicle. At the same time, the position information of the manual door handle in the target vehicle can be output by voice to prompt the position of the manual door handle in the target vehicle.

[0068] In the above-mentioned manual door handle position prompt method, when it is detected that the target vehicle is in the power-on state, the vehicle operation data of the target vehicle is obtained, and the start-up state of the smart door in the target vehicle is determined according to the vehicle operation data. Furthermore, in the case that the start-up state of the smart door is abnormal, the position of the manual door handle in the target vehicle is prompted. In the above process, the start-up state of the smart door in the target vehicle is determined based on the vehicle operation data of the target vehicle, which can improve the accuracy of the start-up state determination and avoid the problem of not prompting when the position of the manual door handle needs to be prompted. Furthermore, in the case that the start-up state of the smart door indicates that the door of the target vehicle may not be opened or closed normally electrically, in order to avoid being unable to control the door of the target vehicle, the position of the manual door handle in the target vehicle is prompted to facilitate opening or closing the door of the target vehicle. In other words, the above process can prompt the position of the manual door handle in time when the start-up state of the smart door is abnormal, so as to facilitate the passenger to leave the target vehicle.

[0069] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the vehicle operation data includes the system operation data of the vehicle electronic control system corresponding to the target vehicle in the current time period. Under this limited condition, this optional embodiment refines the process of determining the start state of the smart door in the target vehicle based on the vehicle operation data.

[0070] The system operation data is used to characterize the parameters such as voltage, current, temperature, load and switch status in the vehicle electronic control system of the target vehicle. The system operation data can be collected through OBD.

[0071] See also Figure 3 The steps for determining the startup state shown include:

[0072] S310: Determine the starting failure rate corresponding to the intelligent door in the target vehicle according to the system operation data.

[0073] Among them, the starting failure rate is used to indicate the probability that the intelligent door in the target vehicle cannot be opened or closed normally electrically.

[0074] In an optional implementation, the reference system data of the reference vehicle and the startup failure rate of the smart door corresponding to the reference vehicle under different reference system data can be obtained in advance, and then the corresponding relationship between the reference system data and the reference startup failure rate is determined based on the acquired data. The reference startup failure rate corresponding to the system operation data of the target vehicle in the corresponding relationship is used as the startup failure rate corresponding to the smart door in the target vehicle. The model of the reference vehicle is the same as that of the target vehicle.

[0075] In an optional implementation, the system operation data can be input into a pre-trained fault prediction model to obtain the startup failure rate corresponding to the intelligent door in the target vehicle. Among them, the fault prediction model can be built based on a common neural network, which will not be described here. Furthermore, in the process of training the fault prediction model, the reference system data can be input into the fault prediction model to be trained to obtain the predicted startup failure rate corresponding to the reference system data, and then the model parameters of the fault prediction model can be adjusted according to the predicted startup failure rate and the reference startup failure rate corresponding to the corresponding reference operation data.

[0076] The model training process of the fault prediction model is further explained: the reference system data is standardized or normalized to obtain sample system data, the sample system data is input into the input layer of the fault prediction model, and the output result of the input layer is input into the hidden layer cascaded with the input layer; the output result of the hidden layer is input into the prediction layer cascaded with the hidden layer; the output result of the prediction layer is input into the output layer cascaded with the prediction layer to obtain the predicted startup failure rate; and according to the predicted startup failure rate and the actual startup failure rate corresponding to the corresponding sample system data, the model parameters of the fault prediction model are adjusted until the model performance of the fault prediction model reaches a preset level.

[0077] Specifically, the processing process corresponding to different network layers can be expressed by the following formula:

[0078] ;

[0079] Where O1 and O2 are the outputs of the prediction layer and the output layer respectively; f is the activation function used for fault prediction; W1 and W2 are the weights corresponding to the prediction layer and the output layer respectively, and the weight values ​​can be determined based on manual experience or through a large number of experiments; b1 and b2 are the bias items corresponding to the prediction layer and the output layer respectively; I is the sample system data input to the input layer.

[0080] Furthermore, the loss value is determined by a loss function, and the model accuracy of the fault prediction model is evaluated according to the loss value. For example, the loss function can be shown in the following formula:

[0081] ;

[0082] Where L is the loss value; n is the number of sample system data; is the predicted startup failure rate corresponding to the i-th sample system data; y i is the actual startup failure rate corresponding to the i-th sample system data.

[0083] Specifically, the gradient is calculated according to the loss value, and the weights and bias items corresponding to different network layers are updated, and the forward propagation and / or back propagation steps are repeated according to the updated weights and bias items until the model performance reaches a preset level. Exemplarily, the update formula of the weights and bias items can be as follows:

[0084] ;

[0085] Where L is the loss value; W is the weight corresponding to the target network layer; O2 is the output of the output layer; W2 is the weight corresponding to the output layer; α is the learning rate.

[0086] In an optional embodiment, in order to avoid wasting computing power caused by determining the startup failure rate, a preset operating threshold corresponding to the system operation data can be set in advance, and when the system operation data exceeds the preset operating threshold, the startup failure rate corresponding to the intelligent door in the target vehicle is determined based on the system operation data.

[0087] It is understandable that when the corresponding system operation data at the current moment does not exceed the preset operation threshold, or the difference between the corresponding system operation data at the current moment and other system operation data in the current time period does not exceed the preset difference threshold, it is determined that the start-up state of the intelligent door in the target vehicle must be normal. Otherwise, it is considered that the target vehicle has abnormal electronic control characteristics, such as sudden current changes caused by large load changes. Exemplarily, the system operation data can be processed to determine the abnormal electronic control characteristics corresponding to the target vehicle. For example, the data processing method can be Fourier transform and wavelet transform. Among them, the preset operation threshold and the preset difference threshold can be determined based on manual experience, or through a large number of experiments.

[0088] It should be noted that abnormal electronic control characteristics may include sudden current changes caused by battery aging, which may lead to motor failure; vibration, noise and instability during motor operation caused by abnormal motor temperature; motor failure caused by mechanical problems such as bearing wear and rotor imbalance due to untimely maintenance; and abnormal motor load caused by acceleration, deceleration, climbing, and abnormal use of electrical systems such as air conditioning, lighting and entertainment systems.

[0089] S320: Determine the start status of the intelligent door in the target vehicle according to the start failure rate.

[0090] Specifically, in this embodiment, when the startup failure rate exceeds the failure rate threshold, it is determined that the startup state of the smart door in the target vehicle is normal; when the startup failure rate does not exceed the failure rate threshold, it is determined that the startup state of the smart door in the target vehicle is abnormal. The failure rate threshold can be determined based on manual experience or through a large number of tests, and this application does not impose any limitation on this.

[0091] In the above embodiment, the process of determining the start-up state of the smart door in the target vehicle according to the vehicle operation data is refined. Specifically, the start-up failure rate corresponding to the smart door in the target vehicle is determined by considering the system operation data corresponding to the vehicle electronic control system corresponding to the target vehicle in the current time period, and the start-up state of the smart door is determined according to the start-up failure rate.

[0092] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the vehicle operation data includes the key position information of the digital key corresponding to the target vehicle, and the vehicle position information of the target vehicle. Under this limited condition, this optional embodiment details the process of determining the start status of the smart door in the target vehicle based on the vehicle operation data.

[0093] See also Figure 4 The steps for determining the startup state shown include:

[0094] S410, determining communication evaluation data of the target vehicle according to the key position information and the vehicle position information.

[0095] Among them, the key position information represents the position of the digital key bound to the target vehicle at the current moment; the vehicle position information represents the position of the target vehicle at the current moment. The communication evaluation data is used to evaluate the communication status between the target vehicle and the digital key at the current moment. It can be understood that the communication evaluation data can be qualitative data, that is, normal status or abnormal status; or quantitative data, that is, communication score; this application does not make any limitation on this.

[0096] In an optional implementation, the communication distance between the target vehicle and the digital key bound to it can be determined based on the key location information and the vehicle location information, and the communication evaluation data of the target vehicle can be determined based on the communication distance.

[0097] Optionally, when the communication distance exceeds a preset distance threshold, the communication status of the target vehicle is determined to be abnormal; when the communication distance does not exceed the preset distance threshold, the communication status of the target vehicle is determined to be normal.

[0098] Optionally, a communication evaluation data determination formula is pre-constructed with the communication distance as the independent variable and the communication evaluation data as the dependent variable, and the communication evaluation data of the target vehicle is determined based on the communication evaluation data determination formula and the communication distance. Exemplarily, the communication evaluation data determination formula may be as follows:

[0099] ;

[0100] Wherein, L is the communication evaluation data of the target vehicle; d is the communication distance between the target vehicle and the digital key; f is the signal frequency corresponding to the signal used for communication between the target vehicle and the digital key; C is the speed of light; K is a constant determined based on artificial experience and is used to reduce errors.

[0101] It should be noted that, in actual situations, it is rare that wireless signals are completely unaffected by obstacles, terrain, buildings, or weather conditions, so the corresponding communication evaluation data of the target vehicle in various scenarios can be measured through multiple tests, and a constant value K applicable to the general formula can be corrected by data training. For example, K can be adjusted in the following ways:

[0102] When the target vehicle is located in multiple different open areas, when entering the vehicle through the digital key, multiple communication evaluation data L will be measured and recorded, and these L will be normalized to obtain a unified communication evaluation data range L1~L2, and stored in the database. At the same time, these communication evaluation data are labeled "digital key is located in an open area" for subsequent identification and use. When the target vehicle is used next time, the system obtains the communication evaluation data L under the label again. If the L value falls within the range of L1~L2, it is determined that the current location of the target vehicle is an open area. Furthermore, based on an image acquisition device, such as a camera, the current standard position of the target vehicle is obtained to verify the current position of the target vehicle, thereby adjusting the K value in the above formula.

[0103] S420, determining the start-up status of the intelligent door according to the communication evaluation data.

[0104] Optionally, when the communication evaluation data is quantitative data, the startup state of the smart door is determined according to the communication evaluation data and a preset evaluation data threshold. Exemplarily, when the communication evaluation data exceeds the preset evaluation data threshold, it is determined that the startup state of the smart door is normal; when the communication evaluation data does not exceed the preset evaluation data threshold, it is determined that the startup state of the smart door is abnormal.

[0105] Optionally, when the communication evaluation data is qualitative data, if the communication evaluation data indicates that the communication is normal, it is determined that the startup state of the smart door is normal; if the communication evaluation data indicates that the communication is abnormal, it is determined that the startup state of the smart door is abnormal.

[0106] In the above embodiment, another specific method for determining the startup state of the smart door is provided. Specifically, since the communication evaluation data represents the current communication state of the target vehicle, and in the case of abnormal communication, the startup state of the smart door in the target vehicle is likely to be abnormal. Therefore, determining the startup state of the smart door based on the communication evaluation data of the target vehicle can improve the accuracy of the startup state determination and also improve the richness of the startup state determination.

[0107] Furthermore, the above S410 is only an exemplary method for determining the communication evaluation data in this embodiment. In an optional implementation, the communication evaluation data of the target vehicle can also be determined by determining the signal-to-noise ratio (i.e., the ratio of signal power to noise power), bit error rate and packet loss rate of the target vehicle.

[0108] Specifically, the signal-to-noise ratio can be determined by:

[0109] SNR=10*log10(signal power / noise power);

[0110] In the formula, SNR is the signal-to-noise ratio; signal power represents the energy carried or transmitted by the signal received by the target vehicle per unit time; and noise power represents the total energy corresponding to the noise signal generated by the signal received by the target vehicle within the specified frequency band.

[0111] The signal power is determined in the following way: the target vehicle samples the received wireless signal, discretizes it into a series of sampling points, squares the amplitude of each sampling point of the signal and sums them up to estimate the signal energy: that is, signal power = Σ(signal sampling point amplitude) 2 ), where N is the number of signal sampling points. The noise power is determined by converting the signal received from the target vehicle from the time domain to the frequency domain by Fourier transform, and then calculating the power spectral density of the signal to extract the power of the noise.

[0112] Furthermore, when the signal-to-noise ratio exceeds a preset signal-to-noise ratio threshold, it is determined that the communication evaluation data of the target vehicle represents communication abnormality of the target vehicle. The preset signal-to-noise ratio threshold may be determined based on manual experience or through a large number of experiments.

[0113] Specifically, the bit error rate can be determined by:

[0114] The bit error rate corresponding to the target vehicle is determined according to the number of erroneous data packets received by the target vehicle in a unit time period and the number of total data packets sent by the target vehicle in a unit time period. For example, the ratio of the number of erroneous data packets to the number of total data packets can be used as the bit error rate corresponding to the target vehicle.

[0115] Furthermore, when the bit error rate exceeds a preset bit error rate threshold, it is determined that the communication evaluation data of the target vehicle represents a communication abnormality of the target vehicle. The preset bit error rate threshold can be determined based on manual experience or through a large number of experiments.

[0116] Specifically, the packet loss rate can be determined by:

[0117] The packet loss rate corresponding to the target vehicle is determined according to the number of packets of data packets sent and the number of packets of data packets received by the target vehicle in a unit time period. For example, the difference between the number of packets of data packets sent and the number of packets of data packets received can be determined, and the ratio of the difference to the number of packets of data packets sent is used as the packet loss rate corresponding to the target vehicle.

[0118] Furthermore, when the packet loss rate exceeds a preset packet loss rate threshold, it is determined that the communication evaluation data of the target vehicle represents communication abnormality of the target vehicle. The preset packet loss rate threshold can be determined based on manual experience or through a large number of experiments.

[0119] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the vehicle operation data includes obstacle motion information corresponding to at least one obstacle in the area where the target vehicle is located, and vehicle motion information of the target vehicle. Under this limited condition, this optional embodiment introduces the process of determining the start-up state of the smart door in the target vehicle based on the vehicle operation data.

[0120] See also Figure 5A The steps for determining the startup state shown include:

[0121] S510: predicting a predicted collision point between the target vehicle and each obstacle according to obstacle motion information and vehicle motion information corresponding to at least one obstacle.

[0122] The obstacle may be a pedestrian, a vehicle or a tree or other object located in front of the target vehicle. Specifically, in this embodiment, when the target vehicle is in a driving state, the predicted collision point corresponding to the target vehicle and each obstacle is predicted.

[0123] Among them, obstacle operation information can be collected based on the vehicle-to-everything (V2X) information exchange system.

[0124] In an optional embodiment, the obstacle motion information and vehicle motion information corresponding to the obstacle can be input into the predicted collision point determination model to obtain the predicted collision points corresponding to the target vehicle and each obstacle. The predicted collision points can be built based on a common neural network. In the process of training the predicted collision point determination model, the first sample operation information and the second sample operation information can be input into the predicted collision point determination model to be trained to obtain the predicted collision points corresponding to the first sample and the second sample, and the model parameters of the predicted collision point determination model to be trained can be adjusted according to the predicted collision points and the corresponding collision point labels.

[0125] S520: Determine the start state of the intelligent door according to the distance between the current position of the target vehicle and each predicted collision point.

[0126] Specifically, the current position of the target vehicle is obtained, and when the distance between the current position of the target vehicle and any predicted collision point is less than the preset safety distance, it is determined that the startup status of the smart door is abnormal; when the distance between the current position of the target vehicle and all predicted collision points is not less than the preset safety distance, it is determined that the startup status of the smart door is normal.

[0127] In the above embodiment, another specific method for determining the activation state of the smart door is provided. Specifically, based on the collision risk of the target vehicle, the activation state of the smart door of the target vehicle is determined, so that the target vehicle can also prompt the position of the manual door handle in the event of a possible collision, so as to facilitate the passenger to leave the target vehicle and avoid being unable to open the door in the event of a collision of the target vehicle.

[0128] Furthermore, the above S510 is only an exemplary method for determining the predicted collision point in this embodiment. In an optional implementation, in order to reduce the waste of computing power of the ECU of the target vehicle in determining the predicted collision point, in this embodiment, the predicted collision point can be determined by other systems. For example, the ECU sends obstacle motion information and vehicle motion information corresponding to at least one obstacle to the collision point prediction system, and obtains the predicted collision point fed back by the collision point prediction system.

[0129] For example, Figure 5B As shown, the predicted collision point can be determined by:

[0130] (1) The V2X software module of the vehicle-road cooperative communication system (V-BOX) receives road information from the remote end, namely obstacle operation information (including real-time information of vehicles, people, lights, etc.), and publishes it through a network communication protocol, such as the SOMEIP service;

[0131] (2) The V2X software module of the analog to digital converter (ADC) system receives road information (including real-time information of vehicles and people) from the radar and publishes it through the SOMEIP service;

[0132] (3) The automatic adjustment and continuous damping control system (CDC) receives the obstacle movement information. The V2X software module classifies the received V2X information data, then identifies the remote information such as vehicles, people, and lights, and sends it to the information fusion software module through the speed and positioning information of the vehicles and people;

[0133] (4) The CDC system subscribes to the radar information of the ADC system through the SOMEIP service, and can obtain the near-end road information detected by the radar in real time (including real-time information of vehicles and people), and then send it to the radar information software module. The radar information software module processes and identifies the detection data obtained by the radar, obtains the early warning identification information of the near-end vehicles, people, road facilities, etc., and then sends it to the information fusion software module;

[0134] (5) The Controller Area Network (CAN) parsing software module obtains the vehicle CAN signal from the body control module (BCM) from the CAN software module's transceiver queue, parses the vehicle's current CAN message speed, acceleration, steering and other information, and sends the information to the information fusion software module;

[0135] (6) The information fusion software module calculates the predicted collision point based on V2X remote information, map information, and current vehicle speed, acceleration, steering and other information, and outputs the predicted collision point to the ECU.

[0136] Optionally, after the predicted collision point is determined, the coordinates of the predicted collision point can be output to the map display software module and displayed in the map information of the target vehicle. It should be noted that since the path of the target vehicle and the obstacle to the predicted collision point in the map information of the target vehicle is not a straight line (as shown below Figure 5C As shown in the figure), the information fusion software module can also transform the path length information of the map information into the following Figure 5D Display format shown.

[0137] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the process of obtaining the vehicle operation data of the target vehicle when the target vehicle is in a powered-on state is refined.

[0138] See also Fig. 6A The vehicle operation data acquisition steps shown include:

[0139] S610, when the target vehicle is in a powered-on state and there is a passenger in the target vehicle, obtain vehicle operation data of the target vehicle.

[0140] It should be noted that the manual door handle in the target vehicle is set inside the vehicle, and the purpose of this application is to be able to open the door inside the vehicle when the start-up state of the smart door in the target vehicle is abnormal. Therefore, if there is no passenger in the target vehicle, there is no need to execute the manual door handle prompt method provided by this application. Based on this, the premise for this application to obtain the vehicle operation data of the target vehicle is that the target vehicle is in a powered-on state and there is a passenger in the target vehicle.

[0141] Correspondingly, in the case where the startup state of the smart door is abnormal, prompting the position of the manual door handle in the target vehicle includes: in the case where the startup state of the smart door is abnormal, prompting the position of the manual door handle that matches the position of the passenger.

[0142] In an optional implementation, the position of the passenger in the target vehicle can be determined, and the position of the manual door handle corresponding to the position of the passenger can be prompted. Exemplarily, the position of the passenger in the target vehicle can be determined based on a seat sensor.

[0143] Furthermore, the present application also provides a method for indicating the position of a manual door handle: controlling the indicator light corresponding to the manual door handle that matches the position of the passenger to light up, so as to indicate the position of the corresponding manual door handle. Specifically, an indicator light is provided near each manual door handle, and the position of the manual door handle is indicated by controlling the indicator light to light up. For example, Figure 6B As shown, when the indicator light is on, a more conspicuous indicator arrow may be displayed, and the arrow points to the manual door handle.

[0144] In the above embodiment, the vehicle operation data of the target vehicle is obtained only when there is a passenger in the target vehicle, and the manual door handle position prompting method provided by the present application is executed, so as to avoid the waste of computing power caused by executing the solution when there is no passenger in the target vehicle. Furthermore, the specific method of prompting the position of the manual door handle in the present application is specifically disclosed.

[0145] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the manual door handle position prompt method provided by the present application is introduced in detail.

[0146] See also Fig. 7AThe manual door handle position prompting method shown includes:

[0147] S710A, when the target vehicle is powered on and there is a passenger in the target vehicle, determining the activation state of the intelligent door in the target vehicle;

[0148] S720A, when the start-up state of the intelligent door is abnormal, the indicator light corresponding to the manual door handle matching the position of the passenger is controlled to light up to indicate the position of the corresponding manual door handle.

[0149] Further, the above steps of S710A are described in detail. Figure 7B-7D The steps for determining the startup state shown include:

[0150] S710B, obtaining and determining the parking intention of the target vehicle;

[0151] S720B, when the target vehicle intends to park, the vehicle computer is controlled to send a distance measurement signal to the digital key matched with the target vehicle, and the degree of signal interference is determined according to the feedback distance information;

[0152] S730B, when the signal interference level is greater than a preset interference level threshold, it is determined that the start-up state of the intelligent door in the target vehicle is abnormal.

[0153] See also Figure 7C The steps for determining the startup state shown include:

[0154] S710C, determining at least one predicted collision point corresponding to the target vehicle;

[0155] S720C: When the distance between the target vehicle and any predicted collision point is less than a preset distance threshold, it is determined that the start-up state of the intelligent door in the target vehicle is abnormal.

[0156] See also Fig.7D The steps for determining the startup state shown include:

[0157] S710D, obtaining system operation data of a vehicle electronic control system in a target vehicle;

[0158] S720D, processing the system operation data to determine whether the target vehicle has abnormal electronic control characteristics;

[0159] S730D, when the target vehicle has abnormal electronic control characteristics, the system operation data is processed through the fault prediction model to obtain the predicted fault rate;

[0160] S740D, when the predicted failure rate is greater than a preset failure rate threshold, it is determined that the starting state of the intelligent door in the target vehicle is abnormal.

[0161] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0162] Based on the same inventive concept, the embodiment of the present application also provides a manual door handle position prompting device for implementing the manual door handle position prompting method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the manual door handle position prompting device provided below can refer to the limitations of the manual door handle position prompting method above, and will not be repeated here.

[0163] In an exemplary embodiment, Figure 8 As shown, a manual door handle position prompting device is provided, comprising: a data acquisition module 810, a state determination module 820 and a position prompting module 830, wherein:

[0164] The data acquisition module 810 is used to acquire vehicle operation data of the target vehicle when the target vehicle is in a powered-on state.

[0165] The state determination module 820 is used to determine the start state of the intelligent door in the target vehicle according to the vehicle operation data.

[0166] The position prompt module 830 is used to prompt the position of the manual door handle in the target vehicle when the startup state of the smart door is abnormal.

[0167] In one embodiment, the vehicle operation data includes the system operation data of the vehicle electronic control system corresponding to the target vehicle in the current time period; accordingly, the state determination module 820 includes a starting failure rate determination unit, which is used to determine the starting failure rate corresponding to the intelligent door in the target vehicle according to the system operation data; a first starting state determination unit is used to determine the starting state of the intelligent door in the target vehicle according to the starting failure rate.

[0168] In one embodiment, the startup failure rate determination unit is used to determine the startup failure rate corresponding to the intelligent door in the target vehicle according to the system operation data when the system operation data exceeds a preset operation threshold.

[0169] In one embodiment, the vehicle operation data includes the key position information of the digital key corresponding to the target vehicle and the vehicle position information of the target vehicle; accordingly, the status determination module 820 includes a communication evaluation data determination unit, which is used to determine the communication evaluation data of the target vehicle based on the key position information and the vehicle position information; and a second startup status determination unit, which is used to determine the startup status of the smart door based on the communication evaluation data.

[0170] In one embodiment, the vehicle operation data includes obstacle motion information corresponding to at least one obstacle in the area where the target vehicle is located, and vehicle motion information of the target vehicle; accordingly, the state determination module 820 includes a predicted collision point determination unit, which is used to predict the predicted collision point corresponding to the target vehicle and each obstacle based on the obstacle motion information and vehicle motion information corresponding to at least one obstacle; a third starting state determination unit, which is used to determine the starting state of the intelligent door according to the distance between the current position of the target vehicle and each predicted collision point.

[0171] In one embodiment, the data acquisition module 810 is used to acquire the vehicle operation data of the target vehicle when the target vehicle is in a powered-on state and there are passengers in the target vehicle; correspondingly, the position prompt module 830 is used to prompt the position of the manual door handle that matches the position of the passenger when the startup state of the smart door is abnormal.

[0172] In one embodiment, the position prompt module 830 is specifically used to control the indicator light corresponding to the manual door handle that matches the position of the passenger to light up, so as to prompt the position of the corresponding manual door handle.

[0173] Each module in the manual door handle position prompt device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0174] In an exemplary embodiment, a vehicle including a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Fig. 9As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a manual door handle position prompt method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0175] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0176] In an exemplary embodiment, a vehicle including a computer device is provided, wherein the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0177] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0178] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0179] In case of abnormal startup status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0180] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the starting failure rate corresponding to the intelligent door in the target vehicle based on the system operation data; and determining the starting status of the intelligent door in the target vehicle based on the starting failure rate.

[0181] In one embodiment, when the processor executes the computer program, the following steps are also implemented: when the system operation data exceeds a preset operation threshold, the starting failure rate corresponding to the intelligent door in the target vehicle is determined based on the system operation data.

[0182] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the communication evaluation data of the target vehicle based on the key position information and the vehicle position information; and determining the start-up status of the smart door based on the communication evaluation data.

[0183] In one embodiment, when the processor executes the computer program, the following steps are also implemented: predicting the predicted collision points corresponding to the target vehicle and each obstacle based on the obstacle motion information and vehicle motion information corresponding to at least one obstacle; determining the start-up state of the smart door based on the distance between the current position of the target vehicle and each predicted collision point.

[0184] In one embodiment, the processor also implements the following steps when executing the computer program: when the target vehicle is in a powered-on state and there are passengers in the target vehicle, the vehicle operation data of the target vehicle is obtained; correspondingly, when the startup state of the smart door is abnormal, the position of the manual door handle that matches the position of the passenger is prompted.

[0185] In one embodiment, when the processor executes the computer program, the following steps are also implemented: controlling the indicator light corresponding to the manual door handle matching the position of the passenger to light up, so as to indicate the position of the corresponding manual door handle.

[0186] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0187] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0188] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0189] In case of abnormal startup status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0190] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the system operation data, the starting failure rate corresponding to the intelligent door in the target vehicle is determined; based on the starting failure rate, the starting status of the intelligent door in the target vehicle is determined.

[0191] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the system operation data exceeds a preset operation threshold, the starting failure rate corresponding to the intelligent door in the target vehicle is determined based on the system operation data.

[0192] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the communication evaluation data of the target vehicle based on the key position information and the vehicle position information; and determining the start-up status of the smart door based on the communication evaluation data.

[0193] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: predicting the predicted collision points corresponding to the target vehicle and each obstacle based on the obstacle motion information and vehicle motion information corresponding to at least one obstacle; determining the start-up state of the smart door based on the distance between the current position of the target vehicle and each predicted collision point.

[0194] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the target vehicle is in a powered-on state and there are passengers in the target vehicle, the vehicle operation data of the target vehicle is obtained; correspondingly, when the startup state of the smart door is abnormal, the position of the manual door handle that matches the position of the passenger is prompted.

[0195] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: controlling the indicator light corresponding to the manual door handle matching the position of the passenger to light up, so as to indicate the position of the corresponding manual door handle.

[0196] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0197] When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle;

[0198] Determine the activation status of the smart door in the target vehicle based on the vehicle operation data;

[0199] In case of abnormal start-up status of the smart door, the location of the manual door handle in the target vehicle is prompted.

[0200] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the system operation data, the starting failure rate corresponding to the intelligent door in the target vehicle is determined; based on the starting failure rate, the starting status of the intelligent door in the target vehicle is determined.

[0201] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the system operation data exceeds a preset operation threshold, the starting failure rate corresponding to the intelligent door in the target vehicle is determined based on the system operation data.

[0202] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the communication evaluation data of the target vehicle based on the key position information and the vehicle position information; and determining the start-up status of the smart door based on the communication evaluation data.

[0203] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: predicting the predicted collision points corresponding to the target vehicle and each obstacle based on the obstacle motion information and vehicle motion information corresponding to at least one obstacle; determining the start-up state of the smart door based on the distance between the current position of the target vehicle and each predicted collision point.

[0204] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the target vehicle is in a powered-on state and there are passengers in the target vehicle, the vehicle operation data of the target vehicle is obtained; correspondingly, when the startup state of the smart door is abnormal, the position of the manual door handle that matches the position of the passenger is prompted.

[0205] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: controlling the indicator light corresponding to the manual door handle matching the position of the passenger to light up, so as to indicate the position of the corresponding manual door handle.

[0206] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0207] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0208] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for prompting the position of a manual door handle, characterized in that: The method comprises: When the target vehicle is in a powered-on state, obtaining vehicle operation data of the target vehicle; Determining the activation state of the intelligent door in the target vehicle according to the vehicle operation data; When the startup state of the smart door is abnormal, the position of the manual door handle in the target vehicle is prompted.

2. The method according to claim 1, characterized in that The vehicle operation data includes system operation data of the vehicle electronic control system corresponding to the target vehicle in the current time period; accordingly, determining the start state of the intelligent door in the target vehicle according to the vehicle operation data includes: Determine the startup failure rate corresponding to the intelligent door in the target vehicle according to the system operation data; According to the startup failure rate, the startup status of the intelligent door in the target vehicle is determined.

3. The method according to claim 2, characterized in that Determining the startup failure rate corresponding to the intelligent door in the target vehicle according to the system operation data includes: When the system operation data exceeds a preset operation threshold, the starting failure rate corresponding to the intelligent door in the target vehicle is determined according to the system operation data.

4. The method according to claim 1, characterized in that: The vehicle operation data includes key position information of a digital key corresponding to the target vehicle and vehicle position information of the target vehicle; correspondingly, determining the start state of the smart door in the target vehicle according to the vehicle operation data includes: determining communication evaluation data of the target vehicle according to the key position information and the vehicle position information; The startup status of the intelligent door is determined based on the communication evaluation data.

5. The method according to claim 1, characterized in that The vehicle operation data includes obstacle motion information corresponding to at least one obstacle in the area where the target vehicle is located, and vehicle motion information of the target vehicle; accordingly, determining the activation state of the intelligent door in the target vehicle according to the vehicle operation data includes: Predicting a predicted collision point between the target vehicle and each obstacle according to the obstacle motion information corresponding to the at least one obstacle and the vehicle motion information; The start-up state of the intelligent door is determined according to the distance between the current position of the target vehicle and each of the predicted collision points.

6. The method according to any one of claims 1 to 5, characterized in that The step of obtaining the vehicle operation data of the target vehicle when the target vehicle is in a powered-on state includes: When the target vehicle is powered on and there is a passenger in the target vehicle, obtaining vehicle operation data of the target vehicle; Accordingly, in the case where the start state of the smart door is abnormal, prompting the position of the manual door handle in the target vehicle includes: When the startup state of the smart door is abnormal, the position of the manual door handle matching the position of the passenger is prompted.

7. The method according to claim 6, characterized in that The prompting of the position of the manual door handle matching the position of the passenger comprises: The indicator light corresponding to the manual door handle matching the position of the passenger is controlled to light up to indicate the position of the corresponding manual door handle.

8. A manual door handle position prompting device, characterized in that: The device comprises: A data acquisition module, used for acquiring vehicle operation data of the target vehicle when the target vehicle is in a powered-on state; A state determination module, used to determine the start state of the intelligent door in the target vehicle according to the vehicle operation data; The position prompt module is used to prompt the position of the manual door handle in the target vehicle when the startup state of the smart door is abnormal.

9. A vehicle, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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