Vehicle control method and vehicle

Abstract

The invention provides a vehicle control method and a vehicle, and relates to the technical field of intelligent driving. The vehicle control method comprises the steps that under the condition that a target vehicle is in a first state, the duration time when the target vehicle is in the first state is determined; under the condition that the duration time is smaller than a first time threshold value, the driving state of the driver is determined, and the driving state comprises a risk state and a non-risk state; and under the condition that the driver is in the risk state, the target vehicle is switched from the first state to the second state, so that the safety and the driving efficiency of the self-adaptive cruise control system are improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of intelligent driving, in particular to a vehicle control method and a vehicle. BACKGROUND

[0002] At present, adaptive cruise control (ACC) systems are widely used. The adaptive cruise control system obtains front road condition information based on sensors such as radars and cameras of a vehicle, and automatically adjusts the driving speed of the vehicle based on the front road condition information, so that the vehicle is kept within a set safe distance, effectively reduces the operation burden of the driver, significantly improves the driving comfort and road traffic efficiency, and has a high popularity rate in various vehicles.

[0003] However, in actual use, the adaptive cruise control system has safety hazards. When the driver turns on the adaptive cruise control system for a long time to follow and stop, the driver may not be able to take over the vehicle in time when needed due to fatigue or distraction, thereby increasing the risk of traffic accidents. SUMMARY

[0004] Therefore, the present disclosure provides a vehicle control method and a vehicle to improve the safety and driving efficiency of the adaptive cruise control system.

[0005] In a first aspect, a vehicle control method is provided, comprising: determining a duration that a target vehicle is in a first state, in a case that the target vehicle is in the first state; determining a driving state of a driver, the driving state comprising a risk state and a non-risk state, in a case that the duration is less than a first time threshold; and switching the target vehicle from the first state to a second state, in a case that the driver is in the risk state.

[0006] The vehicle control method described above detects the driving state of the driver in a case that the target vehicle is in the first state, and switches the system state of the adaptive cruise control system to the second state when the driver is in the risk state, so as to force the driver to actively participate in driving operation. The follow-and-stop holding time logic of the adaptive cruise control system after follow-and-stop is matched in real time according to the driving state of the driver, which effectively avoids the safety risks caused by the driver's excessive dependence on the adaptive cruise control system, and improves the driving efficiency of the adaptive cruise control system.

[0007] In combination with the first aspect, in some implementations of the first aspect, determining the driving state of the driver comprises: obtaining state detection information of the driver, the state detection information comprising at least one of eye movement tracking information, facial expression analysis information, and physiological signal information of the driver; and determining the driving state of the driver based on the state detection information.

[0008] The vehicle control method described above detects the multi-dimension of the driver's eye, face, and physiological signal, relies on a preset multi-dimension fusion algorithm, fuses the multi-dimension state detection information, analyzes various information according to the weight, reduces the misjudgment caused by a single signal abnormality (such as accidental lowering of the head), is more reliable than a single determination logic, and reduces the misjudgment probability. The state detection information covers the driver's behavior and physiological characteristics, adapts to various scenes, supports at least one type of information collection, can be flexibly selected according to the sensor configuration of the vehicle model, adapts to full-dimension detection of high-configuration vehicles, and also meets the core information collection needs of basic-configuration vehicles, provides accurate basis for subsequent vehicle control strategies, and ensures driving safety.

[0009] In combination with the first aspect, in some implementations of the first aspect, based on the state detection information, determining the driving state of the driver includes: if the number of eye closure and / or the single eye closure time of the driver based on the eye movement tracking information meets the first risk determination rule, determining that the driver is in a fatigue state; determining whether the driver is in a low attention state based on at least one of the eye movement tracking information, the facial expression analysis information, and the physiological signal information; and determining that the driving state is a risk state in the case that the driver is in a fatigue state and / or a low attention state.

[0010] The vehicle control method described above refines the risk state into a fatigue state and a low attention state, clearly defines the quantitative determination rules of the eye movement tracking information, the facial expression analysis information, and the physiological signal information, and improves the accuracy of determination. In addition, various determination rules are provided, which can be flexibly selected according to the scene, high-sensitivity rules are adapted to high-safety-demand scenes, and low-false-alarm-rate rules take into account the driving experience.

[0011] In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: in the case that the driver is in a non-risk state, switching the target vehicle from the first state to the third state.

[0012] The vehicle control method described above automatically switches the first state to the third state when it is detected that the driver is in a non-risk state, adapts to the scene of frequent start-stop of the preceding vehicle before the urban congestion section, and reduces the operation frequency of the driver. Moreover, the start of the target vehicle is based on the premise that the driver is in a non-risk state, ensures that the driver has the ability to take over in time, and improves the safety of the adaptive cruise control system as a whole.

[0013] In combination with the first aspect, in some implementations of the first aspect, switching the target vehicle from the first state to the third state includes: obtaining preceding vehicle dynamic information of the target vehicle, the preceding vehicle dynamic information representing the driving state of the vehicle in front of the target vehicle; and in the case that the vehicle in front starts based on the preceding vehicle dynamic information, controlling the target vehicle to switch to the third state.

[0014] The vehicle control method combines the dynamic information of the front vehicle and the driving state of the driver, so that the target vehicle quickly follows the front vehicle under the condition of ensuring driving safety, and avoids traffic congestion caused by delayed start.

[0015] In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: in a case where it is determined based on the dynamic information of the front vehicle that the front vehicle has not started, continuously detecting the driving state of the driver until the duration is equal to the first time threshold; in a case where the duration is equal to the first time threshold and the driver is in the non-risk state, keeping the target vehicle in the first state and continuously detecting the dynamic information of the front vehicle of the target vehicle; in a case where the duration of the target vehicle in the first state is less than a second time threshold and it is determined based on the dynamic information of the front vehicle that the front vehicle has started, switching the target vehicle from the first state to the third state, the second time threshold being greater than the first time threshold.

[0016] The vehicle control method appropriately prolongs the duration of the first state in a case where the driver is in the non-risk state, so as to realize quick response start of the target vehicle, thereby improving the safety of the adaptive cruise control system and taking into account the timeliness of subsequent start.

[0017] In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: in a case where the duration is greater than the first time threshold, switching the target vehicle from the first state to the second state.

[0018] The vehicle control method uses the duration of the first state as a condition for switching the state of the adaptive cruise control system, which cooperates with a scheme of using the driving state of the driver as a condition for switching the state of the adaptive cruise control system to form a double guarantee, effectively reduces the safety risk of the adaptive cruise control system in the first state, and significantly improves the overall operation safety.

[0019] In combination with the first aspect, in some implementations of the first aspect, switching the target vehicle from the first state to the second state in a case where the driver is in the risk state includes: in a case where the driver is in the risk state, determining whether the duration is greater than a third time threshold, the third time threshold being less than the first time threshold; in a case where the duration is greater than the third time threshold, switching the target vehicle from the first state to the second state.

[0020] The vehicle control method provided by the above-mentioned embodiment can regard the time period between the first time threshold and the third time threshold as a safety redundancy in the risk state of the driver, and if the risk state of the driver only appears for a short time, the adaptive cruise control system does not need to be switched to the second state immediately, thereby avoiding frequent switching of the adaptive cruise control system, reducing the operation burden of the driver, improving the driving efficiency of the adaptive cruise control system, and making the adaptive cruise control system more efficient in responding to scenes such as congested road sections, and balancing safety and driving fluency.

[0021] In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: generating a prompt information when the target vehicle is switched from the first state to the second state, the prompt information being used to prompt the driver to take over the target vehicle actively.

[0022] The vehicle control method provided by the above-mentioned embodiment can regard the time period between the first time threshold and the third time threshold as a safety redundancy in the risk state of the driver, and if the risk state of the driver only appears for a short time, the adaptive cruise control system does not need to be switched to the second state immediately, thereby avoiding frequent switching of the adaptive cruise control system, reducing the operation burden of the driver, improving the driving efficiency of the adaptive cruise control system, and making the adaptive cruise control system more efficient in responding to scenes such as congested road sections, and balancing safety and driving fluency.

[0023] In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: generating a prompt information when the target vehicle is switched from the first state to the second state, the prompt information being used to prompt the driver to take over the target vehicle actively. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present disclosure or the related art, the following will briefly introduce the drawings needed to be used in the embodiments or the related art description. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0025] Figure 1 Fig. 1 shows a system architecture topology diagram of a target vehicle provided by an embodiment of the present disclosure.

[0026] Figure 2 Fig. 2 shows a flowchart of a vehicle control method provided by an embodiment of the present disclosure.

[0027] Figure 3 Fig. 3 shows a flowchart of a step of determining the driving state of the driver provided by an embodiment of the present disclosure.

[0028] Figure 4 Fig. 4 shows a flowchart of a step of determining the driving state of the driver based on the state detection information provided by an embodiment of the present disclosure.

[0029] Figure 5Fig. 1 shows a flowchart of a vehicle control method according to an embodiment of the present disclosure.

[0030] Figure 6 Fig. 2 shows a flowchart of a step of switching a target vehicle from a first state to a third state according to an embodiment of the present disclosure.

[0031] Figure 7 Fig. 3 shows a flowchart of a vehicle control method according to another embodiment of the present disclosure.

[0032] Figure 8 Fig. 4 shows a flowchart of a vehicle control method according to yet another embodiment of the present disclosure.

[0033] Figure 9 Fig. 5 shows a flowchart of a step of switching a target vehicle from a first state to a second state in a case where a driver is in a risky state according to an embodiment of the present disclosure.

[0034] Figure 10 Fig. 6 shows a flowchart of a vehicle control method according to still another embodiment of the present disclosure.

[0035] Figure 11 Fig. 7 shows a structural diagram of a vehicle control device according to an embodiment of the present disclosure.

[0036] Figure 12 Fig. 8 shows a structural diagram of an electronic device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the scope of protection of the present disclosure.

[0038] At present, the intelligent degree of automobiles is gradually improved, from basic automatic parking to high-order lane keeping, and the auxiliary driving system has been deeply integrated into the driving scene, becoming one of the core indicators for measuring the technical level of vehicles and improving the user's purchase intention. Among them, the adaptive cruise control is a common function in the auxiliary driving system, which can automatically adjust the driving speed of the vehicle according to the speed of the preceding vehicle, realize following, deceleration, and even following and stopping, and greatly reduce the operation burden of the driver in long-distance driving and urban congested road sections.

[0039] The adaptive cruise control system is an intelligent driving assistance system that adds a vehicle distance control function to the traditional constant speed cruise control. The adaptive cruise control system monitors the front vehicle in real time through radar sensors, cameras and electronic control units, and automatically adjusts the vehicle speed to maintain a safe distance. The adaptive cruise control system is composed of sensors, controllers, engine management controllers, brake actuators and other components, and has the functions of constant speed cruise control, following vehicle control, automatic speed increase and decrease, etc.

[0040] When the adaptive cruise control system is turned on, when a front vehicle is decelerated or parked, the adaptive cruise control system can perform smooth braking until the vehicle is stationary, and automatically start after meeting certain conditions, thereby significantly reducing the operating intensity of the driver in the scenarios of highway and urban expressway, and improving the driving comfort and road traffic efficiency.

[0041] With the rapid popularization of the assisted driving system, users have higher requirements for the intelligent level and safety of its functions, especially in the urban road environment where traffic congestion and vehicle start-stop frequently occur. The use frequency and dependence of the adaptive cruise control system continue to increase. At the same time, excessive dependence on the adaptive cruise control system may lead to the driver's gradual reduction of active attention to the driving task, forming a dependence psychology. This excessive dependence psychology is prone to cause safety hazards in complex traffic scenarios, for example, when the adaptive cruise control system encounters a sudden pedestrian crossing the road, a non-motor vehicle, or a special situation such as an emergency lane change of a front vehicle, the driver needs to quickly take over the vehicle, but the driver who excessively depends on the adaptive cruise control system often cannot take over the vehicle in time, thereby causing safety risks.

[0042] To solve the above problems, the present disclosure provides a vehicle control method, comprising: in the case that the target vehicle is in a first state, determining the duration that the target vehicle is in the first state; in the case that the duration is less than a first time threshold, determining the driving state of the driver, the driving state including a risk state and a non-risk state; in the case that the driver is in the risk state, switching the target vehicle from the first state to a second state.

[0043] Figure 1 The system architecture topology diagram of the target vehicle provided by an embodiment of the present disclosure is shown. As shown in the figure, Figure 1 The system architecture of the target vehicle 100 includes a gateway 110, a driver monitoring system 120, a controller 130, an adaptive cruise control system 140 and a multimedia system 150. The driver monitoring system 120, the controller 130, the adaptive cruise control system 140 and the multimedia system 150 are respectively connected in communication with the gateway 110.

[0044] The gateway 110 is an information relay station of other systems.

[0045] The driver monitoring system 120 is configured to perceive the driving state of the driver and transmit the driving state to the controller 130 through the gateway 110. The controller 130 receives the driving state of the driver, combines the real-time state of the adaptive cruise control system, makes an analysis decision on the current scene based on the vehicle control method provided in the present disclosure, and generates a state switching instruction according to the analysis result. The state switching instruction is transmitted to the adaptive cruise control system 140 and the multimedia system 150 through the gateway 110, respectively.

[0046] The adaptive cruise control system 140 switches the system state according to the state switching instruction, or maintains the current system state unchanged. The multimedia system 150 can remind the driver to adjust his driving state through a pop-up window on the display screen, voice prompts, etc., to improve driving safety.

[0047] In addition, the target vehicle 100 can further include a radar module configured to monitor the environmental information in front of and around the target vehicle 100 in real time, to provide basic perception data for the adaptive cruise control system 140, and to assist in adjusting the following distance and speed.

[0048] The following will be described in detail Figures 2 to 10 The vehicle control method provided in the embodiments of the present disclosure will be described by way of example.

[0049] Figure 2 As shown in FIG. 1, the vehicle control method provided in the embodiments of the present disclosure includes the following steps. Figure 2 As shown in FIG. 1, the vehicle control method provided in the embodiments of the present disclosure includes the following steps.

[0050] S210, in the case where the target vehicle is in the first state, determining the duration of the target vehicle being in the first state.

[0051] The target vehicle is a vehicle configured with an adaptive cruise control system.

[0052] The target vehicle being in the first state can be understood as a follow-stop holding state, which means that the target vehicle stops due to the front vehicle of the target vehicle stopping under the action of the adaptive cruise control system, and the running state of the start-up instruction is not triggered. At this time, the braking system of the target vehicle is in a continuous locking or dynamic pressure holding state to prevent the vehicle from sliding.

[0053] The duration of the target vehicle being in the first state refers to the length of time experienced by the target vehicle from the time when the target vehicle enters the first state this time to the current time (i.e., the time when step S210 is started to be executed). The length of time can be determined by a clock module built in the controller of the target vehicle.

[0054] Specifically, when the controller monitors that the system state of the adaptive cruise control system is the first state, it is determined that the target vehicle enters the first state, and the built-in clock module is triggered to start timing.

[0055] S220, in the case where the duration is less than the first time threshold, determining the driving state of the driver.

[0056] When the next control strategy needs to be performed on the target vehicle (for example, when the front vehicle starts), the duration that the target vehicle is in the first state is determined based on the clock module.

[0057] The duration is compared with the first time threshold, wherein the first time threshold is pre-set. Exemplarily, the first time threshold can be set to 3 seconds, and can be adaptively adjusted according to the system performance of different vehicle models and road conditions.

[0058] If the duration is less than the first time threshold, real-time images of the driver are collected based on the sensor, and facial feature data and limb action data are extracted based on the real-time images, and the driving state of the driver is determined based on the facial feature data and the limb action data.

[0059] The driving state refers to the degree of attention and the operation preparation state of the driver of the target vehicle when the target vehicle is in the first state, and specifically includes a risk state and a non-risk state.

[0060] The risk state refers to the risk that the driver cannot take over the vehicle in time, for example, the driver's attention is distracted, the driver is fatigued, the driver's hands are off the steering wheel, etc.; the non-risk state refers to the driver does not have the risk of being unable to take over the vehicle in time, or such risk is extremely low, for example, the driver's attention is concentrated, the driver is not fatigued, the driver's hands are in a position that can operate the steering wheel, etc.

[0061] Further, the torque change of the driver's hands on the steering wheel can also be detected by a torque sensor of the steering wheel, the driver's sitting posture change can be monitored by a seat pressure sensor, and the driver's limb action can be detected by an in-vehicle radar.

[0062] Based on the above sensor data, a pre-trained driving state recognition algorithm is used for comprehensive analysis, and a determination result that the driver is currently in a risk state or a non-risk state is output.

[0063] Optionally, this step can also be performed once every certain period of time (such as 1 second) after the target vehicle enters the first state, to realize periodic monitoring; in this way, the strategy lag caused by single detection delay can be avoided, and this is especially suitable for scenarios in which the preceding vehicle frequently moves slightly in urban congested road sections, and the determination frequency of the driver state can be adjusted in time according to the duration; or, the driving state of the driver can also be monitored in real time after the target vehicle enters the first state, until the duration is equal to the first time threshold, to capture the instantaneous change of the driving state of the driver, and realize continuous, dynamic and instant attention to the driving state of the driver.

[0064] S230, switching the target vehicle from the first state to the second state in the case where the driver is in the risk state.

[0065] If the determination result is that the driver is in the risk state, it indicates that the driver has the risk of being unable to take over the vehicle in time at this time. In this case, even if the preceding vehicle starts and begins to move, the target vehicle should not continue to follow the preceding vehicle, so as to avoid the risk that the driver is unable to take over the vehicle in time and causes an accident. Therefore, when the controller determines that the driver is in the risk state, a state switching instruction is generated, and the state switching instruction is used to switch the target vehicle from the first state to the second state. The second state can be understood as a to-be-activated state.

[0066] When the adaptive cruise control system of the target vehicle is in the second state, the start of the preceding vehicle will not trigger the automatic start of the target vehicle, and the adaptive cruise control system function needs to be reactivated by the driver performing a preset operation (such as stepping on the accelerator pedal or pressing the adaptive cruise control activation button).

[0067] In the embodiments of the present disclosure, in the case where the target vehicle is in the first state, the driving state of the driver is detected, and when the driver is in the risk state, the system state of the adaptive cruise control system is switched to the second state, to force the driver to actively participate in the driving operation. The follow-stop holding time logic of the adaptive cruise control system after follow-stop is matched in real time according to the driving state of the driver, the safety risk caused by the driver's excessive dependence on the adaptive cruise control system is effectively avoided, and the driving efficiency of the adaptive cruise control system is improved.

[0068] In order to accurately identify the driving state of the driver, the present disclosure provides an optional embodiment, which can collect the state detection information of the driver in multiple dimensions and perform comprehensive analysis, and the specific implementation is as follows.

[0069] Figure 3 Fig. 1 shows a flowchart of the step of determining the driving state of the driver provided by an embodiment of the present disclosure. As shown in Fig. 1, the step of determining the driving state of the driver includes the following steps. Figure 3 As shown in Fig. 1, the step of determining the driving state of the driver includes the following steps.

[0070] S310, obtain state detection information of the driver.

[0071] The state detection information refers to a signal data set reflecting physiological and behavioral characteristics of the driver. The state detection information includes at least one of eye movement tracking information, facial expression analysis information, and physiological signal information of the driver.

[0072] The eye movement tracking information is related data of eye movement collected for the driver's eyes, including parameters such as the driver's line of sight, eye rotation speed, blink frequency, and eyelid closure degree.

[0073] The facial expression analysis information is information obtained after recognizing the activity state of the driver's facial muscles, such as whether there are yawns, frowns, and head-lowering actions and the duration of the actions.

[0074] The physiological signal information is a signal that can reflect the physiological state of the driver, including parameters such as heart rate, breathing rate, and driver posture.

[0075] The above state detection information can be synchronously collected by multiple types of sensors integrated in the vehicle. For example, it can be collected by a camera installed in front of the steering wheel or above the instrument panel. The eye movement tracking information can be captured by the camera in real time to track the eye movement trajectory and changes in eye features, generating eye movement tracking data. The facial expression analysis information is collected by the above-mentioned camera or an independent facial recognition camera, and after image preprocessing (such as noise reduction and face alignment), the motion parameters of key feature points (such as the positions of the corners of the mouth, the corners of the eyes, and the jaw) are extracted through a facial feature point detection algorithm to form facial expression analysis information. The physiological signal information can be collected by a biological sensor installed at the steering wheel grip, which can detect the bioelectric signals and pulse fluctuations of the driver's hands, and then convert them into physiological signal information such as heart rate. In addition, the biological sensor can also detect whether the driver's hands are holding the steering wheel to obtain the driver's posture.

[0076] S320, determine the driving state of the driver based on the state detection information.

[0077] After determining the state detection information, a pre-set multi-dimensional fusion algorithm is used to comprehensively analyze each type of information in the state detection information to determine the driving state.

[0078] Specifically, after obtaining the above-mentioned state detection information, a pre-set multi-dimensional fusion algorithm is used to comprehensively analyze the eye movement tracking, facial expression analysis, and physiological signal information. The algorithm sets different judgment conditions and weights according to each type of information, fuses and calculates the judgment results, and determines whether the driver is in a risk state or a non-risk state according to whether the comprehensive score exceeds a risk threshold, thereby reducing the probability of false judgment of a single signal and improving the accuracy of the determination.

[0079] Exemplarily, the risk probability is preliminarily determined based on the eye movement tracking information, the facial expression analysis information and the physiological signal information respectively. Then the driver monitoring system fuses and calculates the risk probability corresponding to each information according to preset weights (for example, the eye movement tracking information weight is 40%, the facial expression analysis information weight is 35%, and the physiological signal information weight is 25%) to obtain a comprehensive risk probability. When the comprehensive risk probability exceeds a risk threshold, it is determined that the driver is in a risk state; otherwise, it is determined that the driver is in a non-risk state.

[0080] In the embodiments of the present disclosure, the multi-dimensional detection of the eyes, face and physiological signals of the driver relies on a preset multi-dimensional fusion algorithm, and the multi-dimensional state detection information is fused, and each type of information is analyzed by weight to reduce the misjudgment caused by single signal anomaly (such as accidental lowering of the head). Compared with single determination logic, it is more reliable and reduces the probability of misjudgment. The state detection information covers the behavior and physiological characteristics of the driver, adapts to various scenes, supports at least one type of information collection, and can be flexibly selected according to the sensor configuration of the vehicle. It is suitable for full-dimensional detection of high-configuration vehicles and meets the core information collection needs of basic-configuration vehicles, provides accurate basis for subsequent vehicle control strategies, and ensures driving safety.

[0081] The above embodiments briefly introduce the risk state classification and the implementation method of determining the driving state of the driver based on the state detection information. The determination of the driving state based on the eye movement tracking, facial expression analysis and physiological signal information and the corresponding specific determination rules will be described in detail below, so as to improve the accuracy and executability of the driving state determination and provide a basis for subsequent differentiated safety strategy making. The specific implementation is as follows.

[0082] Figure 4 As shown in the figure, the steps of determining the driving state of the driver based on the state detection information include the following steps. Figure 4 As shown in the figure, the steps of determining the driving state of the driver based on the state detection information include the following steps.

[0083] S321, if the number of times of closing eyes and / or the single closing eye time of the driver meets the first risk determination rule based on the eye movement tracking information, it is determined that the driver is in a fatigue state.

[0084] The number of times of closing eyes of the driver refers to the number of times that the eyelid closure degree of the driver is greater than a preset closure degree (for example, eyelid closure degree ≥ 70%) within a preset statistical period through eye movement tracking information. The single driving eyelid closure degree of the driver is greater than the preset closure degree.

[0085] The first risk determination rule refers to a quantitative standard pre-stored in the driver monitoring system for determining whether the driver is in a fatigue state. The rule takes the number of eye closures and the single eye closure time as the core determination indexes, and the specific threshold is calibrated through a large number of real vehicle tests and ergonomics data. Exemplarily, the first risk determination rule can be set as: if the number of eye closures is greater than a first number, or the single eye closure time is greater than a first time, it is determined that the driver is in a fatigue state. Alternatively, the first risk determination rule can also be set as: if the number of eye closures is greater than a first number, and the single eye closure time is greater than a first time, it is determined that the driver is in a fatigue state.

[0086] Further, if the time interval between the multiple eye closure actions of the driver is less than a preset duration, it is determined that the multiple eye closure actions belong to continuous eye closure actions. The first risk determination rule can also be set as: the number of continuous eye closure actions of the driver is greater than a first number, and the single eye closure time is greater than a first time.

[0087] In the actual judgment process, the driver monitoring system first extracts eyelid closure degree data and performs time axis labeling; then counts the number of eye closures in the preset statistical period and records the duration of each eye closure; and then compares the statistical result with the first risk determination rule to determine whether the driver is in a fatigue state.

[0088] Exemplarily, the first risk determination rule can be set as: the number of eye closures is greater than three, and the single eye closure time is greater than 0.5 seconds. If the eye movement tracking information indicates that the number of eye closures of the driver is greater than three, and the single eye closure time is greater than 0.5 seconds, it is determined that the driver is in a fatigue state.

[0089] S322, determining whether the driver is in a low attention state based on at least one of the eye movement tracking information, the facial expression analysis information, and the physiological signal information.

[0090] The low attention state refers to a driving state in which the attention of the driver deviates from the driving task (such as checking the mobile phone or talking with the passenger) and the road condition perception is insufficient.

[0091] The driver monitoring system can determine whether the driver is in a low attention state based on a single type or multiple types of state detection information.

[0092] Exemplarily, the driver monitoring system determines whether the driver is in a low attention state based on eye movement tracking information only; for example, when detecting that the duration of the driver's line of sight deviating from the driving direction is greater than a second time, it is determined that the driver is in a low attention state. Alternatively, the driver monitoring system determines whether the driver is in a low attention state based on facial expression analysis information only; for example, feature extraction and analysis are performed on the facial expression analysis information, and when the driver is identified to be looking down, yawning, or turning his head, it is determined whether the driver is in a low attention state. Alternatively, the driver monitoring system determines whether the driver is in a low attention state based on physiological signal information only; for example, when the driver is detected to be in a relaxed state based on the fluctuation amplitude of the heart rate, and the duration of the relaxed state is greater than a third time, it is indicated that the driver may not be concentrating, and it is determined that the driver is in a low attention state; or the driver's posture can also be used to determine whether the driver's hands are holding the steering wheel, and if not, it is determined that the driver is in a low attention state.

[0093] Further, two or more types of information described above can also be combined to determine whether the driver is in a low attention state. For example, if the driver simultaneously satisfies the conditions that the duration of the line of sight deviating from the driving direction is greater than the second time, and the driver is identified to be looking down, yawning, or turning his head, it is determined whether the driver is in a low attention state, so as to improve the accuracy of the driver's driving state.

[0094] Alternatively, a convolutional neural network can also be used to extract and analyze visual data such as driver facial images and head posture collected by the vehicle-mounted camera, to construct a driver state recognition model. The training data covers a large number of image samples containing different low attention behaviors (such as looking down at the mobile phone, frequently turning the head to chat) and normal driving states, and by labeling key actions and posture features, the model learns the patterns and rules of low attention states. When the model receives real-time image data, it can quickly determine whether the driver is in a low attention state, and as the data continuously accumulates, the model can be optimized through continuous training to improve the recognition accuracy.

[0095] S323, in the case that the driver is in a fatigue state and / or a low attention state, determining that the driving state is a risk state.

[0096] After the driver monitoring system completes the determination of the fatigue state and the low attention state, the two are logically integrated. Exemplarily, the determination rule can be: if it is determined that the driver is in any one of the fatigue state or the low attention state, it is determined that the driving state of the driver is a risk state; if it is determined that the driver is neither in the fatigue state nor in the low attention state, it is determined that the driving state of the driver is a non-risk state. The sensitivity of the above determination rule is high, which can timely capture any risk tendency of the driver, maximally reduce the possibility of accidents caused by fatigue or distraction, and is suitable for scenarios with extremely high requirements for driving safety, such as long-distance freight transportation, complex driving environment, and the like.

[0097] Alternatively, the determination rule can also be: if it is determined that the driver is in both the fatigue state and the low attention state, it is determined that the driving state of the driver is a risk state; if it is determined that the driver is not in the fatigue state, or it is determined that the driver is not in the low attention state, it is determined that the driving state of the driver is a non-risk state. The sensitivity of the above determination rule is low, and thus the false positive rate is low. The above determination rule only triggers an alarm when the driver faces the double risks of fatigue and low attention, which can reduce unnecessary alarm interference, and is more suitable for scenarios with high requirements for driving experience and need to avoid frequent false positives, such as low-risk scenarios with simple driving environment.

[0098] The above two rules can be flexibly selected according to the vehicle use scenario and user demand in actual application, or the advantages of the two rules can be complemented by dynamically adjusting the threshold to improve the overall performance of the driving safety system.

[0099] In the embodiments of the present disclosure, the risk state is refined into the fatigue state and the low attention state, the quantification determination rules of the eye movement tracking information, the facial expression analysis information, and the physiological signal information are specified, and the accuracy of the determination is improved. In addition, multiple determination rules are provided, which can be flexibly selected according to scenarios. The high-sensitivity rule is suitable for high-safety-demand scenarios, and the low-false-positive-rate rule takes into account the driving experience.

[0100] Figure 5 As shown in the figure, in addition to the steps in the above embodiments, the vehicle control method provided in the embodiments of the present disclosure further includes the following steps. Figure 5 As shown in the figure, in addition to the steps in the above embodiments, the vehicle control method provided in the embodiments of the present disclosure further includes the following steps.

[0101] S510, in the case that the driver is in a non-risk state, switching the target vehicle from the first state to a third state.

[0102] The third state can be understood as an active starting state, which means that the target vehicle removes the brake restriction in the first state, and automatically adjusts the power output according to the driving state of the front vehicle to restore the state of following driving. At this time, the target vehicle has the ability to accelerate and decelerate following the preceding vehicle at a preset safe vehicle distance.

[0103] In the embodiments of the present disclosure, when it is detected that the driver is in a non-risk state, the first state is automatically switched to the third state, which is adapted to the scene of frequent start-stop of the preceding vehicle before the urban congestion section, and reduces the operation frequency of the driver. Moreover, the start of the target vehicle is based on the premise that the driver is in a non-risk state, which ensures that the driver has the ability to take over in time and improves the safety of the overall adaptive cruise control system.

[0104] It can be understood that the premise of switching the target vehicle from the first state to the third state should be that the preceding vehicle starts and begins to move.

[0105] Specifically, Figure 6 Fig. 1 shows a flowchart of the step of switching the target vehicle from the first state to the third state provided by an embodiment of the present disclosure. As shown in Fig. 1, Figure 6 The step of switching the target vehicle from the first state to the third state includes the following steps.

[0106] S610, obtaining preceding vehicle dynamic information of the target vehicle, the preceding vehicle dynamic information representing a driving state of a preceding vehicle of the target vehicle.

[0107] The preceding vehicle refers to the nearest motor vehicle in front of the target vehicle, and the preceding vehicle dynamic information is a parameter set of the motion state of the preceding vehicle, and at least includes one or more of the following: relative speed of the target vehicle and the preceding vehicle, relative distance of the target vehicle and the preceding vehicle, absolute speed of the preceding vehicle, brake light state of the preceding vehicle. The preceding vehicle dynamic information can be determined based on sensors such as radar modules and cameras.

[0108] As can be seen, based on the preceding vehicle dynamic information, the driving state of the preceding vehicle can be determined. The driving state includes whether the preceding vehicle starts or does not start.

[0109] S620, in the case of determining that the preceding vehicle starts based on the preceding vehicle dynamic information, controlling the target vehicle to switch to the third state.

[0110] In this step, the controller first receives the determination result of the driver monitoring system, and at the same time, monitors the driving state of the preceding vehicle in real time through the preceding vehicle dynamic information to detect whether the preceding vehicle starts. When the driver is in a non-risk state, and it is determined that the preceding vehicle starts based on the preceding vehicle dynamic information, the controller generates a state switching instruction to switch the adaptive cruise control system from the first state to the third state. Then, the adaptive cruise control system controls the target vehicle to start smoothly, and actively controls the following distance according to the road conditions in front.

[0111] In the embodiments of the present disclosure, the preceding vehicle dynamic information and the driving state of the driver are combined to make the target vehicle quickly follow the preceding vehicle under the condition of ensuring driving safety, and avoid traffic congestion caused by start lag.

[0112] In the above embodiments, it is introduced that the driving state of the driver can be continuously monitored during the target vehicle is in the first state. In this case, the situation that the driver monitoring system detects that the driver is in the non-risk state, but the front vehicle has not started, can occur. At this time, the target vehicle needs to maintain the first state and wait for the start signal of the front vehicle.

[0113] Specifically, Figure 7 The flowchart of the vehicle control method provided by another embodiment of the present disclosure is shown. As Figure 7 As shown, in addition to the steps in the above embodiments, the vehicle control method provided by the embodiments of the present disclosure further includes the following steps.

[0114] S710, in the case that the front vehicle is determined not to start based on the dynamic information of the front vehicle, the driving state of the driver is continuously detected until the duration is equal to the first time threshold.

[0115] The controller continuously monitors the driving state of the driver through the driver monitoring system, determines that the driver is in the non-risk state, and simultaneously monitors the position and speed information of the front vehicle in real time through the radar module. If it is detected that the relative distance between the front vehicle and the target vehicle does not change and the relative speed is always 0, it is determined that the front vehicle has not started.

[0116] In this process, the driving state of the driver is continuously detected until the duration that the target vehicle is in the first state is equal to the first time threshold.

[0117] S720, in the case that the duration is equal to the first time threshold and the driver is in the non-risk state, the target vehicle is maintained in the first state, and the dynamic information of the front vehicle of the target vehicle is continuously detected.

[0118] If the driver is always in the non-risk state within the first time threshold, the controller does not generate a state switching instruction, the target vehicle continues to maintain the first state, and the controller continuously detects the dynamic information of the front vehicle.

[0119] S730, in the case that the duration that the target vehicle is in the first state is less than the second time threshold and the front vehicle is determined to start based on the dynamic information of the front vehicle, the target vehicle is switched from the first state to the third state.

[0120] Wherein, the second time threshold is greater than the first time threshold.

[0121] During the period from the first time threshold to the second time threshold, the controller still continuously and synchronously monitors the driving state of the driver and the dynamic information of the front vehicle.

[0122] If the driving state of the subsequent driver is switched to the risk state, a control strategy in the risk state is triggered immediately, and the target vehicle is switched from the first state to the second state.

[0123] If the driving state of the driver remains in the non-risk state, and it is determined based on the preceding vehicle dynamic information that the preceding vehicle starts, the target vehicle is switched from the first state to the third state.

[0124] During the time period, the controller also pays attention to the duration of the first state. If the duration is equal to the second time threshold, the controller generates a state switching instruction to switch the adaptive cruise control system from the first state to the second state.

[0125] In the embodiments of the present disclosure, in the case that the driver is in the non-risk state, the duration of the first state can be appropriately prolonged to realize the rapid response start of the target vehicle, which improves the safety of the adaptive cruise control system and also takes into account the timeliness of the subsequent start.

[0126] In the above embodiments, the control logic of the target vehicle switching from the first state to the third state when the driver is in the non-risk state is introduced. Next, the present disclosure provides an optional embodiment to continue to introduce the vehicle control strategy when the duration of the first state is greater than the first time threshold, which is implemented as follows.

[0127] Figure 8 Fig. 6 shows a flowchart of a vehicle control method provided by another embodiment of the present disclosure. As shown in Fig. 6, in addition to the steps in the above embodiments, the vehicle control method provided by the embodiment of the present disclosure further includes the following steps. Figure 8

[0128] S810, in the case that the duration is greater than the first time threshold, the target vehicle is switched from the first state to the second state.

[0129] In the above embodiments, the duration of the first state of the target vehicle is continuously monitored from the time when the target vehicle enters the first state. In the case that the duration is less than the first time threshold, step S220 in the above embodiments is performed.

[0130] When the duration is greater than or equal to the first time threshold, and the controller confirms that the target vehicle is still in the first state, the controller generates a state switching instruction to switch the target vehicle from the first state to the second state.

[0131] When the duration is greater than the first time threshold, the target vehicle automatically releases the first state. At this time, even if the preceding vehicle starts, the target vehicle will not continue to follow the start, but wait for the driver's manual intervention to prompt the driver to keep alert at all times.

[0132] ​After the driver performs the corresponding operation (such as stepping on the accelerator pedal, pressing the activation button of the adaptive cruise control system, etc.), the adaptive cruise control system continues to work and restores the car-following function.

[0133] In the embodiments of the present disclosure, the duration of the first state is used as a condition for switching the state of the adaptive cruise control system, which cooperates with the scheme of using the driving state of the driver as a condition for switching the state of the adaptive cruise control system, forms a double guarantee, effectively reduces the safety risk of the adaptive cruise control system in the first state, and significantly improves the overall operation safety.

[0134] In the above embodiments, the adaptive cruise control system state is switched based on the duration of the first state, in order to avoid the driver's attention being diverted due to the target vehicle being followed for a long time. Therefore, if the driver monitoring system determines that the driver is in a non-risk state (i.e., the driver's attention is focused and the driver is not fatigued), the first time threshold can be appropriately extended to ensure the operational flexibility and driving efficiency of the adaptive cruise control system within a safe range.

[0135] For convenience of description, in the embodiments of the present disclosure, the first time threshold after extension is written as a third time threshold, and the third time threshold is greater than the first time threshold. Alternatively, the embodiments of the present disclosure can also be implemented as follows: after the target vehicle enters the first state, the duration of the target vehicle being in the first state is determined; during a time period in which the duration is less than the first time threshold, if the driver monitoring system determines that the driver is always in a non-risk state, the controller will not switch the state of the adaptive cruise control system to the second state at the time when the duration is equal to the first time threshold, but continue to monitor the driving state of the driver until the duration of the target vehicle being in the first state is greater than the third time threshold.

[0136] During the time period between the first time threshold and the third time threshold, if the driving state of the driver remains in a non-risk state and the radar module detects that the preceding vehicle starts, the controller generates a corresponding state switching instruction to switch the target vehicle from the first state to the third state, so as to realize the rapid response start of the target vehicle, which improves the safety of the adaptive cruise control system and also takes into account the timeliness of subsequent start.

[0137] During the time period between the first time threshold and the third time threshold, if the driver monitoring system detects that the driver is in a risk state, a corresponding state switching instruction is generated to switch the target vehicle from the first state to the second state.

[0138] In the above embodiments, it is introduced that the first time threshold can be appropriately extended in the non-risk state of the driver to balance the safety and driving efficiency of the adaptive cruise control system. Next, the disclosure provides an optional embodiment, which continues to introduce the fine state switching in the risk state of the driver in combination with the duration of the first state, and the specific implementation is as follows.

[0139] Figure 9 Fig. 6 shows a flowchart of the step of switching the target vehicle from the first state to the second state in the case where the driver is in the risk state according to an embodiment of the disclosure. As shown in Fig. 6, the step of switching the target vehicle from the first state to the second state in the case where the driver is in the risk state includes the following steps. Figure 9

[0140] S231, in the case where the driver is in the risk state, determining whether the duration is greater than a third time threshold.

[0141] In the case where the duration of the target vehicle in the first state is less than the first time threshold and the driver monitoring system detects that the driver is in the risk state, the controller can immediately generate a corresponding state switching instruction to switch the target vehicle from the first state to the second state. Alternatively, in order to avoid the controller from making a false judgment due to the transient risk state (such as the driver briefly lowering his head due to bumps, or the eyelids being closed momentarily due to wind) or being too sensitive to the slight risk state and frequently triggering the switching to increase the operation burden of the driver, the controller can not immediately generate a corresponding state switching instruction when the driver monitoring system detects that the driver is in the risk state, but appropriately shorten the first time threshold.

[0142] For convenience of description, in this embodiment, the shortened first time threshold is written as the third time threshold, and the third time threshold is less than the first time threshold.

[0143] This step can be specifically implemented as follows: in the case where the duration of the target vehicle in the first state is less than the first time threshold and the driver monitoring system detects that the driver is in the risk state, the controller continues to determine whether the duration is greater than the third time threshold.

[0144] S232, in the case where the duration is greater than the third time threshold, switching the target vehicle from the first state to the second state.

[0145] In the case where the duration is greater than the third time threshold, the controller generates a corresponding state switching instruction to switch the target vehicle from the first state to the second state.

[0146] ​If the duration is less than or equal to the third time threshold, the driving state of the driver is continuously monitored in a time period from the current time to a time corresponding to the third time threshold, and it is comprehensively determined whether the driver is in the risk state. If the driving state of the driver returns to the non-risk state in this process, the target vehicle continues to remain in the first state, and when the radar module detects that the preceding vehicle starts, the controller generates a corresponding state switching instruction to switch the target vehicle from the first state to the third state to realize the rapid response start of the target vehicle. If the driver is still in the risk state, the target vehicle is switched from the first state to the second state.

[0147] In the embodiments of the present disclosure, for the scenario that the driver is in the risk state, the time period between the first time threshold and the third time threshold is regarded as a safety redundancy in the risk state. If the risk state of the driver only appears temporarily, the adaptive cruise control system does not need to be immediately switched to the second state, avoiding frequent switching of the adaptive cruise control system state, reducing the operation burden of the driver, improving the driving efficiency of the adaptive cruise control system, making the adaptive cruise control system more efficient in response in scenarios such as congested road sections, and balancing safety and driving fluency.

[0148] In the above embodiments, the multi-type control logic for controlling the target vehicle to switch from the first state to the second state or the third state based on the duration of the first state and the driving state of the driver is introduced. Next, the present disclosure provides an optional embodiment to continue to introduce a matching prompt mechanism after the vehicle switches to the second state, which is implemented as follows.

[0149] Figure 10 Fig. 1 shows a flowchart of a vehicle control method provided by another embodiment of the present disclosure. As shown in Fig. 1, in addition to the steps in the above embodiments, the vehicle control method provided by the embodiment of the present disclosure further includes the following steps. Figure 8

[0150] S1010, after the target vehicle is switched from the first state to the second state, a prompt information is generated.

[0151] The above steps can be implemented by the controller of the target vehicle. Specifically, after the controller confirms that the target vehicle has completed the switching from the first state to the second state, a corresponding prompt information is generated, and the prompt information is sent to the multimedia system, and the multimedia system performs a corresponding prompt operation based on the prompt information.

[0152] The prompt information is used to prompt the driver to actively take over the target vehicle and perform preset operations such as stepping on the accelerator pedal, pressing the adaptive cruise control activation button, etc. to reactivate the adaptive cruise control system function, so as to avoid that the target vehicle is parked for too long, which hinders the traffic and affects the traffic efficiency. In addition, the prompt information is also used to remind the driver to pay attention to concentration.

[0153] ​Once the controller determines that the driver is attentive or has taken over the target vehicle, it will stop providing prompts. If the controller does not detect that the driver is attentive or has taken over, it will continue to output prompts until the controller determines that escalation of safety intervention is necessary. At this point, the driver can automatically activate the hazard lights or perform other safety procedures.

[0154] For example, the multimedia system includes a display screen. Upon receiving a prompt message, the prompt message is displayed on the screen to remind the driver to take over the target vehicle in an intuitive graphic format.

[0155] Optionally, the multimedia system includes a vehicle audio system. Upon receiving a prompt message, the system plays the message through the vehicle audio system to remind the driver to take over the target vehicle.

[0156] Optionally, the multimedia system includes a steering wheel vibration motor. Upon receiving a prompt, the steering wheel vibration motor vibrates to alert the driver to take control of the vehicle.

[0157] The various prompting methods described above are implemented simultaneously to ensure driving efficiency. Alternatively, they can be implemented in stages. For example, firstly, a prompt message is displayed on the screen; after a period of time, if the driver does not actively take over the vehicle, the steering wheel vibration motor vibrates to provide a prompt; then, if the driver still does not actively take over the vehicle after a period of time, a prompt message is played through the vehicle's audio system.

[0158] In this embodiment of the disclosure, after the target vehicle switches to the second state, a prompt message is automatically generated to remind the driver to take over the target vehicle. On the one hand, this prompts the driver to concentrate and pay attention to the vehicle's driving status; on the other hand, it also prevents the target vehicle from stopping for too long, thus affecting the traffic efficiency of vehicles behind.

[0159] The above text combined Figures 1 to 10 The method embodiments of this disclosure have been described in detail below, in conjunction with... Figure 11 The apparatus embodiments of this disclosure are described in detail below. It should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be referred to the foregoing method embodiments.

[0160] Figure 11 The diagram shown is a structural schematic of a vehicle control device provided in an embodiment of this disclosure. Figure 11 As shown, the vehicle control device 1100 of this embodiment includes: a first determining module 1110, a second determining module 1120, and a switching module 1130.

[0161] The first determination module 1110 is configured to determine a duration that the target vehicle is in the first state, in a case that the target vehicle is in the first state.

[0162] The second determination module 1120 is configured to determine a driving state of the driver, the driving state including a risk state and a non-risk state, in a case that the duration is less than the first time threshold.

[0163] The switching module 1130 is configured to switch the target vehicle from the first state to a second state, in a case that the driver is in the risk state.

[0164] In some embodiments, the second determination module 1120 is further configured to obtain state detection information of the driver, the state detection information including at least one of eye movement tracking information, facial expression analysis information, and physiological signal information of the driver; and determine the driving state of the driver based on the state detection information.

[0165] In some embodiments, the second determination module 1120 is further configured to determine that the driver is in a fatigue state, if the number of eye closures and / or the single eye closure time of the driver satisfies a first risk determination rule based on the eye movement tracking information; determine whether the driver is in a low attention state based on at least one of the eye movement tracking information, the facial expression analysis information, and the physiological signal information; and determine that the driving state is the risk state, in a case that the driver is in the fatigue state and / or the low attention state.

[0166] In some embodiments, the switching module 1130 is further configured to switch the target vehicle from the first state to a third state, in a case that the driver is in the non-risk state.

[0167] In some embodiments, the switching module 1130 is further configured to obtain front vehicle dynamic information of the target vehicle, the front vehicle dynamic information representing a driving state of a front vehicle of the target vehicle; and control the target vehicle to switch to the third state, in a case that the front vehicle starts based on the front vehicle dynamic information.

[0168] In some embodiments, the switching module 1130 is further configured to continue to detect the driving state of the driver, until the duration is equal to a second time threshold, in a case that the front vehicle does not start based on the front vehicle dynamic information; maintain the target vehicle in the first state and continue to detect the front vehicle dynamic information of the target vehicle, in a case that the duration is equal to the second time threshold and the driver is in the non-risk state; and switch the target vehicle from the first state to the third state, in a case that the duration that the target vehicle is in the first state is less than a third time threshold and the front vehicle starts based on the front vehicle dynamic information, the second time threshold being greater than the first time threshold, and the third time threshold being greater than the second time threshold.

[0169] In some embodiments, the switching module 1130 is further configured to switch the target vehicle from the first state to the second state if the duration is greater than a first time threshold.

[0170] In some embodiments, the switching module 1130 is further configured to determine whether the duration is greater than a third time threshold if the driver is in the risk state, the third time threshold being less than the first time threshold; and switch the target vehicle from the first state to the second state if the duration is greater than the third time threshold.

[0171] In some embodiments, the vehicle control apparatus 1100 further comprises a prompting module configured to generate a prompting information after the target vehicle is switched from the first state to the second state, the prompting information being used to prompt the driver to take over the target vehicle actively.

[0172] Hereinafter, an electronic device according to an embodiment of the disclosure will be described with reference to the accompanying drawings. Figure 12 As shown in FIG. 12, an electronic device 1200 according to an embodiment of the disclosure includes one or more processors 1210 and memory 1220. Figure 12 As shown in FIG. 12, an electronic device 1200 according to an embodiment of the disclosure includes one or more processors 1210 and memory 1220. Figure 12 As shown in FIG. 12, an electronic device 1200 according to an embodiment of the disclosure includes one or more processors 1210 and memory 1220.

[0173] The processor 1210 can be a central processing unit (CPU) or other form of processing unit that has data processing capabilities and / or instruction execution capabilities, and can control other components in the electronic device 1200 to perform desired functions.

[0174] The memory 1220 can include one or more computer program products, which can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like. Non-volatile memory, for example, can include read-only memory (ROM), hard disks, flash memory, and / or the like. One or more computer program instructions can be stored on the computer-readable storage media, and the processor 1210 can run the program instructions to implement the vehicle control method of various embodiments of the disclosure described above and / or other desired functions.

[0175] In some embodiments, the electronic device 1200 can further include an input device 1230 and an output device 1240, which are interconnected through a bus system and / or other form of connection mechanism (not shown).

[0176] The input device 1230 can include, for example, a touch screen, a microphone, a keyboard, a mouse, and / or the like. The output device 1240 can include, for example, a display, a speaker, a communication network and a remote output device connected thereto, and / or the like.

[0177] Of course, in order to simplify, Figure 12 Only some of the components of the electronic device 1200 related to the present disclosure are shown in the middle, and components such as buses, input / output interfaces, and the like are omitted. In addition, the electronic device 1200 can further include any other appropriate components according to a specific application.

[0178] In addition to the above method and device, an embodiment of the present disclosure can also be a computer program product, which includes computer program instructions that, when executed by a processor, cause the processor to perform the steps of the vehicle control method according to various embodiments of the present disclosure described above in the specification.

[0179] The computer program product can be written in any combination of one or more programming languages to perform the operations of the embodiments of the present disclosure, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as "C" language or similar programming languages. The program code can be executed entirely on a user computing device, partially on a user device, as an independent software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0180] In addition, an embodiment of the present disclosure can also be a computer readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps of the vehicle control method according to various embodiments of the present disclosure described above in the specification.

[0181] The computer readable storage medium can employ any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of readable storage medium include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any appropriate combination of the above.

[0182] In addition, an embodiment of the present disclosure can also be a vehicle, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the vehicle control method according to various embodiments of the present disclosure by executing the executable instructions.

[0183] The above describes the basic principles of the present disclosure in combination with specific embodiments, but it needs to be pointed out that the advantages, benefits, effects and the like mentioned in the present disclosure are only examples and are not limiting, and these advantages, benefits, effects and the like cannot be considered as necessary for each embodiment of the present disclosure. In addition, the above specific details of the disclosure are only for the purpose of example and for the purpose of understanding, and are not limiting, and the above details do not limit the present disclosure to be necessarily implemented with the above specific details.

[0184] The block diagrams of the devices, apparatuses, equipment, systems involved in the present disclosure are only illustrative examples and are not intended to require or imply the connection, arrangement, configuration shown in the block diagram. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, which mean "including but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0185] It also needs to be pointed out that in the system, equipment and method of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombination should be considered as equivalent solutions of the present disclosure.

[0186] The above description of the disclosed aspects is provided so that any person skilled in the art can make or use the present disclosure. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

[0187] The above description has been given for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain modifications, alterations, changes, additions and sub-combinations thereof.

Claims

1. A vehicle control method characterized by, The method comprises: in a case where the target vehicle is in a first state, determining a duration for which the target vehicle is in the first state; in a case where the duration is less than a first time threshold, determining a driving state of a driver, the driving state comprising a risk state and a non-risk state; in a case where the driver is in the risk state, switching the target vehicle from the first state to a second state.

2. The method of claim 1, wherein, The determining of the driving state of the driver comprises: obtaining state detection information of the driver, the state detection information comprising at least one of eye movement tracking information, facial expression analysis information, and physiological signal information of the driver; based on the state detection information, determining the driving state of the driver.

3. The method of claim 2, wherein, The determining of the driving state of the driver based on the state detection information comprises: if, based on the eye movement tracking information, the number of times of closing eyes and / or the time of a single closing of eyes of the driver satisfies a first risk determination rule, it is determined that the driver is in a fatigue state; based on at least one of the eye movement tracking information, the facial expression analysis information, and the physiological signal information, it is determined whether the driver is in a low attention state; in a case where the driver is in the fatigue state and / or the low attention state, the driving state is determined to be the risk state.

4. The method of claim 1, wherein, The method further comprises: in a case where the driver is in a non-risk state, switching the target vehicle from the first state to a third state.

5. The method of claim 4, wherein, The switching of the target vehicle from the first state to the third state comprises: obtaining front vehicle dynamic information of the target vehicle, the front vehicle dynamic information representing a driving state of a front vehicle of the target vehicle; in a case where, based on the front vehicle dynamic information, it is determined that the front vehicle starts, controlling the target vehicle to switch to the third state.

6. The method of claim 5, wherein, The method further comprises: in a case where, based on the front vehicle dynamic information, it is determined that the front vehicle does not start, continuously detecting the driving state of the driver until the duration is equal to the first time threshold; in a case where the duration is equal to the first time threshold and the driver is in the non-risk state, causing the target vehicle to remain in the first state and continuously detecting the front vehicle dynamic information of the target vehicle; in a case where the duration for which the target vehicle is in the first state is less than a second time threshold and, based on the front vehicle dynamic information, it is determined that the front vehicle starts, switching the target vehicle from the first state to the third state, the second time threshold being greater than the first time threshold.

7. The method of claim 1, wherein, The method further comprises: in a case where the duration is greater than the first time threshold, switching the target vehicle from the first state to the second state.

8. The method of claim 1, wherein, The switching of the target vehicle from the first state to the second state in a case where the driver is in the risk state comprises: in a case where the driver is in the risk state, determining whether the duration is greater than a third time threshold, the third time threshold being less than the first time threshold; In a case where the duration is greater than the third time threshold, switching the target vehicle from the first state to the second state.

9. The method of claim 1, wherein, Further comprising: generating a prompt information after the target vehicle is switched from the first state to the second state, the prompt information being used to prompt the driver to take over the target vehicle actively.

10. A vehicle characterized by comprising: Comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the vehicle control method of any one of claims 1 to 9 via execution of the executable instructions.

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