Control method and device of vehicle, vehicle and storage medium

Abstract

The application relates to the technical field of automobiles, in particular to a vehicle control method and device, a vehicle and a storage medium. The vehicle control method comprises the following steps: obtaining facial image information of a driver in the vehicle and position information of the vehicle; determining fatigue state information of the driver according to the facial image information; sending the position information to the cloud according to the fatigue state information, so that the cloud determines a control strategy corresponding to the vehicle according to the position information, and the control strategy is used for indicating whether the vehicle changes lanes; receiving the control strategy sent by the cloud; and controlling the vehicle according to the control strategy. In the case that the driver has already driven while being tired, the vehicle can be controlled to change lanes according to the fatigue condition of the driver, the safe driving of the driver is ensured, and the accident rate is reduced.

Description

Technical Field

[0001] This application relates to the field of automotive technology, specifically to a vehicle control method, device, vehicle, and storage medium. Background Technology

[0002] Drivers experience fatigue, including drowsiness, weakness in the limbs, poor concentration, and impaired judgment, when driving for extended periods. This fatigue can lead to physiological and psychological dysfunction, as well as operational instability, significantly increasing the risk of traffic accidents. Currently, to reduce accidents caused by fatigue, driver fatigue is monitored, and drivers are alerted when fatigue is detected. However, these methods only provide temporary relief; the driver may soon relapse into fatigue driving, failing to address the root cause of the problem and compromising driving safety. Summary of the Invention

[0003] One objective of this application is to provide a vehicle control method that can reduce the accident rate when fatigue driving has already occurred; a second objective of this application is to provide a vehicle control device; a third objective of this application is to provide a vehicle; and a fourth objective of this application is to provide a storage medium.

[0004] To achieve the above objectives, in a first aspect, this application provides a vehicle control method, comprising:

[0005] Acquire facial image information of the driver in the vehicle and the location information of the vehicle;

[0006] Based on the facial image information, determine the driver's fatigue status information;

[0007] Based on the fatigue status information, the location information is sent to the cloud so that the cloud can determine the control strategy corresponding to the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes.

[0008] Receive the control policy sent from the cloud;

[0009] The vehicle is controlled according to the control strategy.

[0010] Furthermore, the step of sending the location information to the cloud based on the fatigue state information includes:

[0011] When the fatigue state information is at the first fatigue level, the target number of times the fatigue state information is continuously at the first fatigue level is obtained;

[0012] Acquire control image information of the steering wheel in the vehicle;

[0013] When the target number of times is reached and no human hand is present in the control image information, the location information is sent to the cloud.

[0014] Furthermore, the step of sending the location information to the cloud based on the fatigue state information includes:

[0015] When the fatigue status information is at the second fatigue level, the system controls the prompting device in the vehicle to operate to alert the driver.

[0016] After the prompting device prompts the driver for a first preset time, the step of acquiring the driver's facial image information in the vehicle is executed;

[0017] When the fatigue status information is still at the second fatigue level, the location information is sent to the cloud.

[0018] Furthermore, the cloud determines the control strategy corresponding to the vehicle based on the location information, including:

[0019] The cloud platform determines the attribute information of the road where the vehicle is located based on the location information;

[0020] Obtain road condition image information and vehicle speed;

[0021] Based on the road condition image information and the driving speed, determine the vehicle's lane change information;

[0022] Based on the attribute information and the lane change information, the control strategy corresponding to the vehicle is determined.

[0023] Furthermore, the cloud platform determines the control strategy corresponding to the vehicle based on the attribute information and the lane change information, including:

[0024] When the cloud determines that the attribute information indicates parking is allowed and the lane change information indicates lane change is allowed, it determines that the control strategy is the first control strategy.

[0025] Controlling the vehicle according to the control strategy includes:

[0026] When the control strategy is the first control strategy, the vehicle is controlled to change lanes to the target lane; and,

[0027] After controlling the vehicle to change lanes to the target lane, control the vehicle to stop and control the warning lights in the vehicle to turn on.

[0028] Furthermore, the method also includes:

[0029] After controlling the vehicle to stop and controlling the warning lights in the vehicle to turn on, the step of obtaining the driver's facial image information in the vehicle is executed.

[0030] When the fatigue status information indicates that the driver is awake, determine the first duration of rest the driver has taken.

[0031] If the first duration has not reached the second preset duration, a second rest duration is determined for the driver.

[0032] Based on the second duration, the prompting device in the vehicle is controlled to operate to prompt the driver.

[0033] Furthermore, the facial image information includes: eye image information and mouth image information;

[0034] Determining the driver's fatigue status information based on the facial image information includes:

[0035] Based on the eye image information, determine the driver's eye state information;

[0036] Based on the mouth image information, determine the driver's mouth state information;

[0037] The driver's fatigue status information is determined based on the eye and mouth status information.

[0038] To achieve the above objectives, in a second aspect, this application also provides a vehicle control device, which includes: an acquisition module for acquiring facial image information of the driver in the vehicle and the position information of the vehicle;

[0039] The determination module is used to determine the driver's fatigue status information based on the facial image information;

[0040] The sending module is used to send the location information to the cloud based on the fatigue state information, so that the cloud can determine the control strategy corresponding to the vehicle based on the location information, and the control strategy is used to instruct the vehicle whether to change lanes;

[0041] The receiving module is used to receive the control strategy sent from the cloud.

[0042] The control module is used to control the vehicle according to the control strategy.

[0043] To achieve the above objectives, in a third aspect, this application also provides a vehicle comprising: a processor and a memory, the processor being configured to execute a vehicle control program stored in the memory to implement the vehicle control method described above.

[0044] To achieve the above objectives, in a fourth aspect, this application also provides a storage medium storing one or more programs that can be executed by one or more processors to implement the vehicle control method described above.

[0045] The beneficial effects of this application are as follows: This application provides a vehicle control method that acquires the driver's facial image information and the vehicle's location information. Based on the facial image information, the driver's fatigue state information is determined. Based on the fatigue state information, the location information is sent to the cloud, so that the cloud can determine the corresponding control strategy for the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes. The method receives the control strategy sent by the cloud and controls the vehicle according to the control strategy. Thus, even if driver fatigue has occurred, the method can control the vehicle to change lanes based on the driver's fatigue level, ensuring the driver's safe driving and reducing the accident rate. Attached Figure Description

[0046] Figure 1 This illustration shows a structural schematic diagram of a vehicle control system provided in an embodiment of this application;

[0047] Figure 2 This illustration shows a flowchart of a vehicle control method provided in an embodiment of this application;

[0048] Figure 3 This illustration shows a flowchart of another vehicle control method provided in an embodiment of this application;

[0049] Figure 4 This illustration shows a flowchart of yet another vehicle control method provided in an embodiment of this application;

[0050] Figure 5 This illustration shows a structural schematic diagram of a vehicle control device according to an embodiment of this application;

[0051] Figure 6 This illustration shows a structural diagram of a vehicle according to an embodiment of this application;

[0052] in:

[0053] 101. Information collection equipment; 102. Vehicle control equipment; 103. Cloud computing;

[0054] 10. Acquisition Module; 20. Confirmation Module; 30. Sending Module; 40. Receiving Module; 50. Control Module;

[0055] 600. Vehicle; 601. Processor; 602. Memory; 6021. Operating system; 6022. Application program; 603. User interface; 604. Network interface; 605. Bus system. Detailed Implementation

[0056] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0057] To facilitate understanding of the embodiments of this application, the following will provide further explanation and description with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of this application.

[0058] refer to Figure 1 , Figure 1 This is a schematic diagram of a vehicle control system provided in an embodiment of this application. The vehicle control system provided in this embodiment includes: an information acquisition device 101, a vehicle control device 102, and a cloud platform 103. The information acquisition device 101 acquires facial image information of the driver and the vehicle's position information, and sends the acquired facial image information and position information to the vehicle control device 102. The vehicle control device 102 determines the driver's fatigue state information based on the acquired facial image information. The vehicle control device 102 sends the acquired position information to the cloud platform 103 based on the fatigue state information. The cloud platform 103 determines a corresponding control strategy for the vehicle based on the acquired position information, wherein the control strategy is used to indicate whether the vehicle should change lanes. After determining the corresponding control strategy, the cloud platform 103 sends the control strategy to the vehicle control device 102. The vehicle control device 102 controls the vehicle according to the acquired control strategy.

[0059] refer to Figure 2 , Figure 2 This is a flowchart illustrating a vehicle control method provided in an embodiment of this application. The vehicle control method provided in this application includes the following steps:

[0060] S201: Obtain facial image information of the driver in the vehicle and the vehicle's location information.

[0061] In this embodiment, the executing entity is the vehicle control device within the vehicle's control system. Facial image information and vehicle location information are collected by an information acquisition device and sent to the vehicle control device, enabling the vehicle control device to perform logical judgments based on the acquired information to control the vehicle.

[0062] S202: Determine the driver's fatigue status information based on facial image information.

[0063] In this embodiment, the driver's facial image information includes: eye image information and mouth image information. By analyzing the eye and mouth states in the facial image information, the driver's current fatigue state information is determined. Specifically, step S202, determining the driver's fatigue state information based on the facial image information, includes:

[0064] Based on eye image information, determine the driver's eye status information;

[0065] Based on the mouth image information, determine the driver's mouth status information;

[0066] Based on eye and mouth status information, the driver's fatigue status information is determined.

[0067] Specifically, eye status information includes: eyes open and eyes closed; mouth status information includes: mouth open and mouth closed. Fatigue status information includes: first fatigue level, second fatigue level, and alertness, where the second fatigue level is higher than the first fatigue level. When the eye status information is eyes open and the mouth status information is mouth closed, the driver's fatigue status is determined to be alert; when the eye status information is eyes closed and the mouth status information is mouth closed, the driver's fatigue status is determined to be first fatigue level; when the eye status information is eyes open and the mouth status information is mouth open, the driver's fatigue status is determined to be second fatigue level.

[0068] More specifically, eye and mouth state information can be detected using the YOLOv5 neural network model.

[0069] S203: Based on fatigue status information, the location information is sent to the cloud so that the cloud can determine the corresponding control strategy for the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes.

[0070] In this embodiment, after the vehicle control device determines the fatigue state information, it determines whether the vehicle's location information needs to be sent to the cloud for control strategy determination based on the fatigue state information. Once the vehicle control device determines to send the location information to the cloud based on the fatigue state information, the cloud can determine the corresponding control strategy for the vehicle based on the location information. When the fatigue state information is at the first fatigue level or the second fatigue level, the vehicle control device needs to further determine whether to send the location information to the cloud. When the fatigue state information is that the driver is conscious, the vehicle control device does not need to send the location information to the cloud, and the driver can control the vehicle. The specific implementation method of the vehicle control device sending the location information to the cloud based on the fatigue state information will be described below and will not be repeated here.

[0071] Specifically, in step S203, the cloud determines the corresponding control strategy for the vehicle based on the location information, including:

[0072] The cloud determines the attribute information of the road where the vehicle is located based on the location information;

[0073] The cloud acquires road condition images and vehicle speeds.

[0074] Based on road condition image information and driving speed, determine the vehicle's lane change information;

[0075] Based on attribute information and lane change information, determine the corresponding control strategy for the vehicle.

[0076] The attribute information includes: parking is permitted and parking is not permitted; lane change information includes: lane change is permitted and lane change is not permitted. Determining the attribute information of the road the vehicle is on based on location information can be understood as follows: if the location information determines the road is an urban road, it is determined whether a no-parking sign exists. If a no-parking sign exists, the attribute information of the urban road is no-parking; if no-parking sign does not exist, the attribute information of the urban road is parking permitted. Similarly, if the location information determines the road is a highway, it is determined whether an emergency lane exists. If an emergency lane exists, the attribute information of the highway is parking permitted; if no emergency lane does not exist, the attribute information of the highway is no-parking. Specifically, whether there are no-parking signs on urban roads and whether there are emergency lanes on highways can be determined using maps stored in the cloud.

[0077] Road condition images can be collected by information acquisition equipment, which then sends the collected images to the cloud for processing. This equipment includes cameras installed along the roadside to capture road condition images. Vehicle speeds can also be collected by the information acquisition equipment, which sends the collected vehicle speed data to the cloud for processing. This equipment includes speed measurement devices installed along the roadside to collect vehicle speed data. After receiving the road condition images and vehicle speeds, the cloud determines whether a lane change is appropriate, obtaining lane change information. Finally, based on attribute information and lane change information, it determines the appropriate control strategy for the vehicle.

[0078] Specifically, the aforementioned cloud-based system determines the corresponding control strategy for the vehicle based on attribute information and lane change information, including:

[0079] When the cloud determines that the attribute information indicates parking is allowed and the lane change information indicates lane change is allowed, the control strategy is set as the first control strategy.

[0080] When the cloud determines that the attribute information is "parking is not allowed" and the lane change information is "lane change is allowed", the control strategy is determined to be the second control strategy.

[0081] When the cloud determines that the attribute information is "parking is not allowed" and the lane change information is "lane change is not allowed", the control strategy is determined to be the second control strategy.

[0082] When the cloud determines that the attribute information indicates parking is allowed and the lane change information indicates lane change is not allowed, it determines the control strategy to be the second control strategy.

[0083] The first control strategy is used to instruct the vehicle to change lanes; the second control strategy is used to instruct the vehicle not to change lanes. The first and second control strategies will be described below, and will not be repeated here in this embodiment.

[0084] S204: Receive control policies sent from the cloud.

[0085] In this embodiment, after determining the control strategy corresponding to the vehicle in the cloud, the control strategy is sent to the vehicle control device so that the vehicle control device can control the vehicle according to the control strategy.

[0086] S205: Control the vehicle according to the control strategy.

[0087] In this embodiment, step S205 involves controlling the vehicle according to a control strategy, including:

[0088] When the control strategy is set to the first control strategy, the vehicle is controlled to change lanes to the target lane; and,

[0089] After controlling the vehicle to change lanes to the target lane, control the vehicle to stop and control the vehicle's warning lights to turn on.

[0090] Specifically, when the vehicle is on an urban road, the target lane is the rightmost lane. When the vehicle is on a highway, the target lane is the emergency lane. Controlling the vehicle's hazard lights to activate can be understood as controlling the vehicle to activate its hazard flashers.

[0091] Step S205, which involves controlling the vehicle according to the control strategy, also includes:

[0092] When the control strategy is the second control strategy, the vehicle's warning lights are activated; and...

[0093] A notification message is sent to the traffic management system so that the traffic management system can distribute the notification information to vehicles around the vehicle. The notification message contains the vehicle's license plate number and basic vehicle information.

[0094] In some cases, if a vehicle is unable to safely change lanes to the target lane and stop, the system can activate its hazard lights and send a notification message to the traffic management system. This notification message will then be distributed to surrounding vehicles, allowing them to be aware of the vehicle's situation and give it leeway. Alternatively, after receiving the notification message, the traffic management system can manually intervene to force the vehicle to stop. Basic vehicle information includes: vehicle model and vehicle color.

[0095] In this embodiment, when the control strategy is the first control strategy, after controlling the vehicle to change lanes and stop driving and controlling the warning lights in the vehicle to turn on, the following steps are also included:

[0096] After the vehicle stops and the warning lights are turned on, obtain the driver's facial image information in the vehicle.

[0097] When the driver's fatigue status is determined to be conscious based on facial image information, the first duration of rest is determined.

[0098] If the first duration does not reach the second preset duration, determine the second duration for which the driver needs to rest;

[0099] Based on the second duration, the vehicle's prompting device is activated to alert the driver.

[0100] The second preset duration can be set according to actual needs; in this embodiment, the specific value of the second preset duration is not limited. The prompting device includes a voice unit and a display unit. When the first duration has not reached the second preset duration, the voice unit can announce the second required rest duration for the driver, allowing the driver to rest according to the announced content. When the first duration has not reached the second duration, the display unit can also display the second required rest duration for the driver, allowing the driver to rest according to the displayed content. The second duration is equal to the second preset duration minus the first duration. Through these methods, the driver is guaranteed sufficient rest time, improving driving safety.

[0101] The vehicle control method provided in this application embodiment can control the vehicle to change lanes according to the driver's fatigue level when driver fatigue has occurred, thereby ensuring the driver's safe driving and reducing the accident rate.

[0102] refer to Figure 3 , Figure 3 This is a flowchart illustrating another vehicle control method provided in an embodiment of this application. The vehicle control method provided in this application includes the following steps:

[0103] S301: Obtain facial image information of the driver in the vehicle and the vehicle's location information.

[0104] S302: Determine the driver's fatigue status information based on facial image information.

[0105] In the above, step S301 is the same as step S201, and step S302 is the same as step S202. For details, please refer to the above description. In this embodiment, steps S301 and S302 will not be described in detail.

[0106] S303: When the fatigue state information is at the first fatigue level, obtain the target number of consecutive fatigue state information at the first fatigue level.

[0107] In this embodiment, the first fatigue level can be understood as the driver being in a drowsy state. After determining the fatigue state information as the first fatigue level, the result is recorded, and based on the recorded result, the target number of consecutive times the fatigue state information reaches the first fatigue level is obtained. It should be noted that each time the fatigue state information is determined to be the first fatigue level, the vehicle control equipment controls the prompting device to operate to prompt the driver, thereby waking the driver up. The prompting device includes a voice unit and a buzzer unit. When the prompting device includes a voice unit, the driver is prompted by a voice announcement. When the prompting device includes a buzzer unit, the driver is prompted by an alarm sounding the buzzer unit.

[0108] S304: Acquire control image information of the steering wheel in the vehicle.

[0109] In this embodiment, the control image information is collected by an information acquisition device, which then sends the collected control image information to the vehicle control device. The information acquisition device includes an in-vehicle camera that collects the control image information and sends it to the vehicle control device.

[0110] S305: When the target number of times is reached and no human figure is present in the control image information, the location information is sent to the cloud so that the cloud can determine the corresponding control strategy for the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes.

[0111] In this embodiment, the preset number of attempts can be set according to actual needs, and the specific value of the preset number of attempts is not limited in this embodiment. When the target number of attempts reaches the preset number of attempts and no human hand is present in the control image information, it indicates that the driver is in great danger and the vehicle needs to be controlled to reduce the possibility of driver danger. It should be noted that the preset number of attempts is variable and can be determined by the vehicle's driving speed. When sending the location information to the cloud, the vehicle's driving speed is obtained, and the preset number of attempts is determined based on the vehicle's driving speed. The preset number of attempts corresponding to the driving speed can be determined from the association relationship. The higher the driving speed, the smaller the preset number of attempts. The association relationship stores multiple sets of correspondences between driving speed and preset number of attempts. The cloud determines the control strategy corresponding to the vehicle based on the location information in step S305, which is consistent with step S203. For details, please refer to the above description, which will not be repeated here in this embodiment.

[0112] S306: Receive control policies sent from the cloud.

[0113] S307: Control the vehicle according to the control strategy.

[0114] In the above, step S306 is the same as step S204, and step S307 is the same as step S205. For details, please refer to the above description. In this embodiment, steps S306 and S307 will not be described in detail.

[0115] The vehicle control method provided in this application embodiment can control the vehicle to change lanes according to the driver's fatigue level when driver fatigue has occurred, thereby ensuring the driver's safe driving and reducing the accident rate.

[0116] refer to Figure 4 , Figure 4 This is a flowchart illustrating another vehicle control method provided in this application embodiment. The vehicle control method provided in this application embodiment includes the following steps:

[0117] S401: Obtain facial image information of the driver in the vehicle and the vehicle's location information.

[0118] S402: Determine the driver's fatigue status based on facial image information.

[0119] In the above, step S401 is the same as step S201, and step S402 is the same as step S202. For details, please refer to the above description. In this embodiment, steps S401 and S402 will not be described in detail.

[0120] S403: When the fatigue status information is at the second fatigue level, control the prompting device in the vehicle to activate to alert the driver.

[0121] In this embodiment, the second fatigue level can be understood as the driver being in a drowsy state. After determining that the fatigue state information is at the second fatigue level, the vehicle control equipment controls the prompting device to operate, thereby prompting the driver and waking him up. The prompting device includes a voice unit and a buzzer unit. When the prompting device includes a voice unit, the driver is prompted by a voice announcement. When the prompting device includes a buzzer unit, the driver is prompted by an alarm sounding the buzzer unit.

[0122] S404: After the prompting device prompts the driver for a first preset time, the driver's facial image information in the vehicle is acquired, so as to determine the driver's fatigue status information based on the facial image information.

[0123] In this embodiment, the first preset duration can be set according to actual needs, and the specific value of the first preset duration is not limited in this embodiment. After the prompting device prompts the driver for the first preset duration, it returns to execute steps S401 and S402 to re-determine the driver's fatigue status information.

[0124] S405: When the fatigue status information is still at the second fatigue level, the location information is sent to the cloud so that the cloud can determine the corresponding control strategy for the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes.

[0125] In this embodiment, after the fatigue status information is re-determined to the second fatigue level, it indicates that the driver cannot be successfully awakened, and driving by the driver is extremely dangerous. Vehicle control is required to reduce the possibility of driver injury. The cloud-based determination of the vehicle's control strategy based on location information is consistent with step S203, as described above; further details are omitted here.

[0126] S406: Receive control policies sent from the cloud.

[0127] S407: Control the vehicle according to the control strategy.

[0128] In the above, step S406 is the same as step S204, and step S407 is the same as step S205. For details, please refer to the above description. In this embodiment, steps S406 and S407 will not be described in detail.

[0129] The vehicle control method provided in this application embodiment can control the vehicle to change lanes according to the driver's fatigue level when driver fatigue has occurred, thereby ensuring the driver's safe driving and reducing the accident rate.

[0130] refer to Figure 5 , Figure 5 This is a schematic diagram of a vehicle control device provided in an embodiment of this application. The vehicle control device provided in this embodiment includes: an acquisition module 10, a determination module 20, a sending module 30, a receiving module 40, and a control module 50. The acquisition module 10 is used to acquire facial image information of the driver in the vehicle and the vehicle's position information; the determination module 20 is used to determine the driver's fatigue state information based on the facial image information; the sending module 30 is used to send the position information to the cloud based on the fatigue state information, so that the cloud can determine a control strategy corresponding to the vehicle based on the position information, the control strategy being used to instruct the vehicle whether to change lanes; the receiving module 40 is used to receive the control strategy sent by the cloud; and the control module 50 is used to control the vehicle according to the control strategy.

[0131] In this embodiment, the sending module 30 is further configured to:

[0132] When the fatigue state information is at the first fatigue level, the target number of times the fatigue state information is continuously at the first fatigue level is obtained;

[0133] Acquire control image information of the steering wheel in the vehicle;

[0134] When the target number of times is reached and no human hand is present in the control image information, the location information is sent to the cloud.

[0135] In this embodiment, the sending module 30 is further configured to:

[0136] When the fatigue status information is at the second fatigue level, the system controls the prompting device in the vehicle to operate to alert the driver.

[0137] After the prompting device prompts the driver for a first preset period of time, facial image information of the driver in the vehicle is acquired to determine the driver's fatigue status information;

[0138] When the fatigue status information is still at the second fatigue level, the location information is sent to the cloud.

[0139] In this embodiment, the cloud is also used for:

[0140] Based on the location information, determine the attribute information of the road where the vehicle is located;

[0141] Obtain road condition image information and vehicle speed;

[0142] Based on the road condition image information and the driving speed, determine the vehicle's lane change information;

[0143] Based on the attribute information and the lane change information, the control strategy corresponding to the vehicle is determined.

[0144] In this embodiment, the cloud is also used for:

[0145] When the cloud determines that the attribute information indicates parking is allowed and the lane change information indicates lane change is allowed, it determines the control strategy as the first control strategy.

[0146] In this embodiment, the control module 50 is further configured to:

[0147] When the control strategy is the first control strategy, the vehicle is controlled to change lanes to the target lane; and,

[0148] After controlling the vehicle to change lanes to the target lane, control the vehicle to stop and control the warning lights in the vehicle to turn on.

[0149] In this embodiment, the determining module 20 is further configured to:

[0150] After controlling the vehicle to stop and controlling the warning lights in the vehicle to turn on, the driver's facial image information is acquired in the vehicle to determine the driver's fatigue status information.

[0151] When the fatigue status information indicates that the driver is awake, determine the first duration of rest the driver has taken.

[0152] If the first duration has not reached the second preset duration, a second duration for which the driver needs to rest is determined.

[0153] In this embodiment, the control module 50 is further configured to:

[0154] Based on the second duration, the prompting device in the vehicle is controlled to operate to prompt the driver.

[0155] In this embodiment, the facial image information includes: eye image information and mouth image information.

[0156] In this embodiment, the determining module 20 is further configured to:

[0157] Based on the eye image information, determine the driver's eye state information;

[0158] Based on the mouth image information, determine the driver's mouth state information;

[0159] The driver's fatigue status information is determined based on the eye and mouth status information.

[0160] The vehicle control method provided in this application embodiment can control the vehicle to change lanes according to the driver's fatigue level when driver fatigue has occurred, thereby ensuring the driver's safe driving and reducing the accident rate.

[0161] Figure 6 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Figure 6 The vehicle 600 shown includes at least one processor 601, a memory 602, at least one network interface 604, and other user interfaces 603. The various components in the vehicle 600 are coupled together via a bus system 605. It is understood that the bus system 605 is used to implement communication between these components. In addition to a data bus, the bus system 605 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in… Figure 6 The general designated all buses as Bus System 605.

[0162] The user interface 603 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0163] It is understood that the memory 602 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 602 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0164] In some implementations, memory 602 stores elements, executable units or data structures, or subsets thereof, or extended sets thereof: operating system 6021 and application program 6022.

[0165] The operating system 6021 includes various system programs, such as a framework layer, a core library layer, and a driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 6022 includes various applications, such as a media player and a browser, used to implement various application functions. Programs implementing the methods of the embodiments of this application can be included in application program 6022.

[0166] In this embodiment, by calling the program or instructions stored in memory 602, specifically the program or instructions stored in application program 6022, processor 601 executes the method steps provided in each method embodiment, such as: acquiring facial image information of the driver in the vehicle and vehicle location information; determining driver fatigue state information based on facial image information; sending location information to the cloud based on fatigue state information, so that the cloud determines the corresponding control strategy for the vehicle based on location information, the control strategy being used to instruct whether the vehicle should change lanes; receiving the control strategy sent by the cloud; and controlling the vehicle according to the control strategy.

[0167] The methods disclosed in the embodiments of this application can be applied to or implemented by processor 601. Processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware or by instructions in the form of software in processor 601. The processor 601 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or can be executed by a combination of hardware and software units in the decoding processor. The software units may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 602. Processor 601 reads the information in memory 602 and, in conjunction with its hardware, completes the steps of the above method.

[0168] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0169] For software implementation, the techniques described herein can be implemented by units that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0170] The vehicle provided in this embodiment can be as follows: Figure 6 The vehicle shown can perform the following actions: Figures 2-4 All steps of the vehicle control method in China, thereby achieving Figures 2-4 For details on the technical effects of the vehicle control method shown, please refer to [link / reference]. Figures 2-4 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0171] This application also provides a storage medium (computer-readable storage medium). This storage medium stores one or more programs. The storage medium may include volatile memory, such as random access memory; it may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive; and it may also include combinations of the above types of memory.

[0172] When one or more programs in the storage medium can be executed by one or more processors to implement the vehicle control method described above, which is executed on the vehicle control device side.

[0173] The processor is used to execute the vehicle control program stored in the memory to implement the following steps of the vehicle control method executed on the vehicle control device side: acquiring the driver's facial image information and the vehicle's position information; determining the driver's fatigue state information based on the facial image information; sending the position information to the cloud based on the fatigue state information, so that the cloud can determine the corresponding control strategy for the vehicle based on the position information, the control strategy being used to instruct the vehicle whether to change lanes; receiving the control strategy sent by the cloud; and controlling the vehicle according to the control strategy.

[0174] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0175] It should be noted that the terms "one implementation," "embodiment," "exemplary embodiment," and "some embodiments" used in the specification indicate that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments, whether explicitly described or not, is within the knowledge scope of those skilled in the art.

[0176] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling a vehicle, characterized in that, include: Acquire facial image information of the driver in the vehicle and the location information of the vehicle; Based on the facial image information, determine the driver's fatigue status information; Based on the fatigue status information, the location information is sent to the cloud so that the cloud can determine the control strategy corresponding to the vehicle based on the location information. The control strategy is used to instruct the vehicle whether to change lanes. Receive the control policy sent from the cloud; The vehicle is controlled according to the control strategy. The step of sending the location information to the cloud based on the fatigue state information includes: When the fatigue state information is at the first fatigue level, the target number of times the fatigue state information is continuously at the first fatigue level is obtained; Acquire the control image information of the steering wheel in the vehicle and the driving speed of the vehicle; The preset number of times is determined based on the driving speed; the higher the driving speed, the smaller the preset number of times. When the target number of times is reached and no human hand is present in the control image information, the location information is sent to the cloud.

2. The method according to claim 1, characterized in that, The step of sending the location information to the cloud based on the fatigue state information includes: When the fatigue status information is at the second fatigue level, the system controls the prompting device in the vehicle to operate to alert the driver. After the prompting device prompts the driver for a first preset time, the step of acquiring the driver's facial image information in the vehicle is executed; When the fatigue status information is still at the second fatigue level, the location information is sent to the cloud.

3. The method according to claim 1, characterized in that, The cloud platform determines the control strategy corresponding to the vehicle based on the location information, including: The cloud platform determines the attribute information of the road where the vehicle is located based on the location information; Obtain road condition image information and vehicle speed; Based on the road condition image information and the driving speed, determine the vehicle's lane change information; Based on the attribute information and the lane change information, the control strategy corresponding to the vehicle is determined.

4. The method according to claim 3, characterized in that, The cloud platform determines the control strategy corresponding to the vehicle based on the attribute information and the lane change information, including: When the cloud determines that the attribute information indicates parking is allowed and the lane change information indicates lane change is allowed, it determines that the control strategy is the first control strategy. Controlling the vehicle according to the control strategy includes: When the control strategy is the first control strategy, the vehicle is controlled to change lanes to the target lane; and, After controlling the vehicle to change lanes to the target lane, control the vehicle to stop and control the warning lights in the vehicle to turn on.

5. The method according to claim 4, characterized in that, The method further includes: After controlling the vehicle to stop and controlling the warning lights in the vehicle to turn on, the step of obtaining the driver's facial image information in the vehicle is executed. When the fatigue status information indicates that the driver is awake, determine the first duration of rest the driver has taken. If the first duration has not reached the second preset duration, a second rest duration is determined for the driver. Based on the second duration, the prompting device in the vehicle is controlled to operate to prompt the driver.

6. The method according to claim 1, characterized in that, The facial image information includes: eye image information and mouth image information; Determining the driver's fatigue status information based on the facial image information includes: Based on the eye image information, determine the driver's eye state information; Based on the mouth image information, determine the driver's mouth state information; The driver's fatigue status information is determined based on the eye and mouth status information.

7. A vehicle control device, characterized in that, include: The acquisition module is used to acquire facial image information of the driver in the vehicle and the location information of the vehicle; The determination module is used to determine the driver's fatigue status information based on the facial image information; The sending module is used to send the location information to the cloud based on the fatigue state information, so that the cloud can determine the control strategy corresponding to the vehicle based on the location information, and the control strategy is used to instruct the vehicle whether to change lanes; The receiving module is used to receive the control strategy sent from the cloud. A control module is used to control the vehicle according to the control strategy; The sending module is further configured to, when the fatigue state information is at the first fatigue level, obtain the target number of times the fatigue state information is continuously at the first fatigue level; Acquire the control image information of the steering wheel in the vehicle and the driving speed of the vehicle; The preset number of times is determined based on the driving speed; the higher the driving speed, the smaller the preset number of times. When the target number of times is reached and no human hand is present in the control image information, the location information is sent to the cloud.

8. A vehicle, characterized in that, include: A processor and a memory, the processor being configured to execute a vehicle control program stored in the memory to implement the vehicle control method according to any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the vehicle control method according to any one of claims 1 to 6.

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