Control system, method and equipment of intelligent cabin and medium

Abstract

The invention discloses an intelligent cabin control system, method and device and a medium, and the method comprises the steps: receiving an interaction instruction sent by a driver, and carrying out the analysis and execution of the interaction instruction through a task priority arbitration algorithm of a central control unit; the task priority is determined according to the running state of the vehicle, a corresponding management mode is determined according to the task priority, the running state comprises a running state and a loading and unloading state, and the management mode comprises a driving mode and a loading and unloading mode; the fatigue degree and distraction behaviors of the driver are determined, a safety reminding mechanism is determined according to the fatigue degree and the distraction behaviors, and the vehicle is controlled according to the safety reminding mechanism; and obtaining a cargo hold state, determining a corresponding regulation and control mechanism according to the cargo hold state, and controlling the cargo hold according to the regulation and control mechanism. The execution instruction can be efficiently analyzed, and modes can be flexibly switched according to the driving state; fatigue distraction is accurately recognized, and reasonable safety reminding is triggered; and the overall driving experience and safety are improved.

Description

Technical Field

[0001] The present application relates to the field of automotive electronics technology, and in particular to a control system, method, device, and medium for an intelligent cockpit. Background Art

[0002] With the continuous advancement of technology, the intelligence of automobiles is constantly increasing. In the past, driving a car was simply a means of transportation. Today, cars have evolved into intelligent mobile spaces. The emergence of smart cockpits has revolutionized our travel experience, with voice control and intelligent connectivity becoming the two core functions of smart cockpits. However, the smart cockpits currently available on the market lack adaptability to specific scenarios. Most interaction methods, which rely primarily on physical buttons, are unable to meet the fast operation requirements of scenarios such as loading and unloading and long-distance driving. Furthermore, severe environmental interference, cockpit noise, and the need for drivers to operate with gloves significantly reduce the reliability of voice and touch interaction. Overall, this seriously impacts the efficiency, safety, and convenience of commercial vehicle cockpit interaction. Summary of the Invention

[0003] In order to solve the above problems, the present application proposes a control system for an intelligent cockpit, including: a central control unit, which communicates with the vehicle's CAN bus and is used to integrate a task priority arbitration algorithm to perform task management according to the algorithm; a human-computer interaction module, which is arranged inside the vehicle and includes multiple interaction methods and is used to receive and process the driver's interaction instructions; an environmental perception module, which includes multiple sensors and is used to monitor the environmental conditions inside and outside the vehicle in real time; a cargo compartment management unit, which includes a cargo compartment door, a ventilation device and a cockpit display screen, and is used to obtain the monitoring information of the environmental perception module and manage the cargo compartment status according to the information.

[0004] In one example, the human-computer interaction module includes: a voice interaction submodule, which is equipped with a directional microphone array and a deep learning noise reduction model, and is used to recognize voice commands; a gesture interaction submodule, which is used to recognize multiple gesture commands, and the gesture commands include swiping with one hand to control the cargo door and clenching a fist to initiate emergency braking; a biometric authentication submodule, which is equipped with multiple biometric authentications, and is used to configure the driver according to the biometrics.

[0005] In one example, the environmental perception module includes: a cockpit camera for monitoring the driver's behavior and the environment in the cockpit; a cargo hold temperature and humidity sensor for monitoring the temperature and humidity in the cargo hold in real time; a cargo weight sensor for monitoring the weight of cargo in the cargo hold and connecting to the cargo hold management unit; and a driver status monitoring module for monitoring the driver's fatigue and distraction in real time.

[0006] On the other hand, the present application also proposes a control method for a smart cockpit, which is applied to a control system of a smart cockpit as shown in the above example, and the method includes: receiving interaction instructions issued by the driver, and parsing and executing the interaction instructions through the task priority arbitration algorithm of the central control unit; determining the task priority according to the driving status of the vehicle, and determining the corresponding management mode according to the task priority, the driving status includes driving and loading and unloading, and the management mode includes driving mode and loading and unloading mode; determining the driver's fatigue and distraction behavior, and determining a safety reminder mechanism according to the fatigue and distraction behavior, so as to control the vehicle according to the safety reminder mechanism; obtaining the cargo hold status, and determining the corresponding control mechanism according to the cargo hold status, so as to control the cargo hold according to the control mechanism.

[0007] In one example, after receiving the interactive command issued by the driver, the method further includes: using a directional microphone array to collect original voice input, extracting effective voice through background noise spectrum analysis and deep learning noise reduction model, and performing command recognition and execution feedback.

[0008] In one example, the task priority is determined according to the driving status of the vehicle, and the corresponding management mode is determined according to the task priority, specifically including: when the management mode is the driving mode, priority is given to interactive instructions related to driving safety, and the interactive instructions related to driving safety include emergency braking and lane keeping; when the management mode is the loading and unloading mode, priority is given to interactive instructions related to cargo loading and unloading and electronic signature.

[0009] In one example, the method also includes: analyzing the driver's fatigue in real time through a driver status monitoring module, the fatigue including blinking frequency and heart rate variability coefficient; monitoring the driver's head posture through a cockpit camera to determine distraction behavior based on the head posture, the head posture including the time the line of sight deviates from the road; and determining a safety reminder mechanism corresponding to the fatigue and the distraction behavior, the prime safety reminder mechanism including voice reminders, linkage with the dispatch center, speed limit, pausing the entertainment system and shrinking the central control screen interface.

[0010] In one example, the method further includes: determining through a cargo hold management unit whether there is an abnormal cargo hold state, wherein the abnormal cargo hold state includes cargo hold overloading and the hatch not being closed tightly; if there is an abnormal cargo hold state, an alarm is issued through seat vibration and flashing of a red frame on the screen.

[0011] On the other hand, the present application also proposes a control device for a smart cockpit, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the control device of the smart cockpit to execute: a method as described in any one of the above examples.

[0012] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to perform the method described in any one of the above examples.

[0013] This application integrates a central control unit, a human-machine interaction module, an environmental perception module, and a cargo compartment management unit, enabling comprehensive perception and efficient processing of vehicle information, improving the system's overall performance. Supporting multiple interaction methods such as voice, gestures, and biometric authentication, it provides a more natural and convenient interactive experience, reduces the risk of driver distraction, and improves interaction efficiency. Through the environmental perception module and driver status monitoring module, this application's system can monitor the vehicle's internal and external environment and driver status in real time, promptly identify potential safety hazards, and intervene through a safety alert mechanism, effectively improving driving safety. Based on the monitoring information from the environmental perception module, this application can accurately manage the cargo compartment status, such as automatically adjusting ventilation frequency and issuing overload warnings, thereby improving the safety and efficiency of cargo transportation. It can dynamically adjust task priorities based on the vehicle's driving status, ensuring efficient and safe operation in different scenarios, enhancing the system's flexibility and adaptability. By optimizing interaction processes, improving safety performance, and enhancing intelligent management, this system helps reduce fleet management costs, improve cargo transportation efficiency, and reduce losses, offering significant commercial value. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0015] Figure 1 This is a flow chart of a method for controlling a smart cockpit according to an embodiment of the present application;

[0016] Figure 2 This is a schematic diagram of a control device for an intelligent cockpit in an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

[0019] like Figure 1 As shown, in order to solve the above problems, an embodiment of the present application provides a control method for a smart cockpit, which is applied in a control system of a smart cockpit. The system includes:

[0020] A central control unit, communicating with the vehicle's CAN bus, is used to integrate a task priority arbitration algorithm to manage tasks according to the algorithm;

[0021] The human-computer interaction module is set inside the vehicle and includes multiple interaction modes for receiving and processing the driver's interaction instructions;

[0022] Environmental perception module, including multiple sensors, for real-time monitoring of the environmental conditions inside and outside the vehicle;

[0023] The cargo hold management unit, including the cargo hold door, ventilation device and cockpit display screen, is used to obtain monitoring information from the environmental perception module and manage the cargo hold status based on the information.

[0024] In one embodiment, the human-computer interaction module includes:

[0025] The voice interaction submodule is equipped with a directional microphone array and a deep learning noise reduction model. The voice interaction submodule is used to recognize voice commands;

[0026] The gesture interaction submodule is used to recognize various gesture commands, including swiping with one hand to control the cargo door and clenching a fist to activate emergency braking;

[0027] The biometric authentication submodule is equipped with multiple biometric authentication methods and is used to configure the driver based on the biometric characteristics.

[0028] In one embodiment, the environment perception module includes:

[0029] Cockpit cameras, used to monitor the pilot's behavior and the cockpit environment;

[0030] Cargo hold temperature and humidity sensor, used to monitor the temperature and humidity in the cargo hold in real time;

[0031] Cargo weight sensor, used to monitor the weight of cargo in the cargo hold and connect with the cargo hold management unit;

[0032] Driver status monitoring module, used to monitor driver fatigue and distraction in real time.

[0033] In one embodiment, the method includes:

[0034] S101 , receiving an interaction instruction issued by a driver, and parsing and executing the interaction instruction through a task priority arbitration algorithm of the central control unit.

[0035] The system utilizes a directional microphone array combined with a deep learning noise reduction model to achieve accurate speech recognition with a rate of at least 95% in a noise environment of 70dB. Furthermore, the system includes a dedicated gesture library, encompassing 10 gesture commands, including a single-hand swipe to control the cargo door and a clenched fist to activate emergency braking, to meet diverse operational needs. Furthermore, through fingerprint or voiceprint authentication, the system can automatically load the driver's personalized configuration, such as seat position and frequently used routes, enhancing driving convenience and comfort.

[0036] S102. Determine a task priority according to the driving state of the vehicle, and determine a corresponding management mode according to the task priority, wherein the driving state includes driving and loading and unloading, and the management mode includes driving mode and loading and unloading mode.

[0037] The system implements a dynamic task priority management strategy: in driving mode, non-essential touch operations are disabled while the vehicle is in motion to ensure driving safety. At the same time, the response delay of voice commands is strictly controlled within 0.3 seconds to ensure the immediacy of interaction. In loading and unloading mode, the system automatically switches to the cargo hold management interface, provides an electronic signature scanning function, and supports voice verification of the cargo list, thereby greatly improving the efficiency and accuracy of loading and unloading operations.

[0038] S103: Determine the driver's fatigue and distraction behavior, and determine a safety reminder mechanism based on the fatigue and distraction behavior, so as to control the vehicle according to the safety reminder mechanism.

[0039] The system is equipped with safety enhancement mechanisms, including graded fatigue warnings and distraction blocking. The graded fatigue warning system monitors the driver's fatigue status in real time. If mild fatigue is detected, such as blinking more than 15 times per minute, a voice reminder will be issued. If severe fatigue is detected, such as an abnormal heart rate accompanied by persistent yawning, the system will contact the dispatch center and automatically limit the vehicle speed to ensure driving safety. Regarding distraction blocking, if the system detects that the driver's eyes are away from the road for more than two seconds, the entertainment system functions will be immediately suspended and the central control screen interface will be reduced to reduce driving distraction and ensure driving concentration.

[0040] S104. Obtain the cargo hold status, determine a corresponding control mechanism according to the cargo hold status, and control the cargo hold according to the control mechanism.

[0041] The system realizes the linkage control function of the cargo hold and the cockpit: when the cargo hold is overloaded or not closed tightly, the system will warn the driver by means of seat vibration and flashing red frame on the screen; at the same time, the system can also automatically adjust the ventilation frequency of the cargo hold according to the type of cargo, such as fresh food, and synchronously display the temperature and humidity change curve on the cockpit display screen to ensure the environmental stability of the cargo during transportation.

[0042] In one embodiment, in the loading and unloading scenario, the system has designed an efficient interactive process: when the vehicle is parked, the system will automatically switch to loading and unloading mode through GPS positioning; then, the driver can use gestures to call up the cargo compartment management interface, and use the scanning function to read the cargo QR code to generate an electronic list; if the weight sensor detects that the cargo is overloaded during the closing process of the cargo compartment door, the system will immediately trigger a voice alarm, prompting "The cargo is overweight by 200kg, please reallocate"; after the loading and unloading operation is completed, the driver can sign the electronic receipt through touch operation and upload it to the cloud for storage and management.

[0043] In one embodiment, in the long-distance driving safety intervention mechanism, the system uses biosensors to continuously monitor the driver's driving status. When it detects that the driver has been driving continuously for 4 hours and the heart rate variability coefficient is lower than the preset safety threshold, the system will immediately initiate safety intervention measures: first, it will prompt the driver through voice "It is recommended to stop at the rest stop 2km ahead" and simultaneously lock the video playback function of the central control screen to reduce distraction; if the driver chooses to refuse to rest, the system will trigger a seat vibration reminder every 15 minutes until the driver stops to rest, thereby effectively ensuring the safety of long-distance driving.

[0044] This invention significantly improves the efficiency of scenario-based interactions. During loading and unloading, compared to the traditional method that requires multiple touches or buttons to operate the cargo door and the cumbersome process of paper receipt, this invention allows for easy door opening with a simple swipe gesture. Combined with AR cargo space visualization technology and electronic receipt scanning, this significantly reduces overall operation time by 40%. To effectively control distraction during long-distance driving, the system automatically hides non-driving screens, such as entertainment functions, when the vehicle speed exceeds 30 km / h, significantly reducing the risk of distraction. Secondly, in terms of safety, this invention uses composite fatigue detection technology to reduce false alarm rates by 62% compared to single-sensor solutions, effectively improving fatigue detection accuracy. Furthermore, the cargo compartment safety linkage mechanism ensures rapid response to abnormal situations such as overloading or unsecured cargo compartments, with an alarm response delay of less than 0.5 seconds, achieving a 90% efficiency improvement compared to traditional manual inspection methods. Finally, in terms of commercial value, this invention demonstrates a differentiated competitive advantage. By automatically uploading driver status data to the logistics scheduling platform, the efficiency of abnormal event handling has increased by 75%, contributing to the intelligent and efficient management of fleets. In addition, the system can also issue abnormal warnings for temperature and humidity of goods, effectively reducing transportation losses of fresh food, medicines and other goods, with the actual loss rate dropping by 18%.

[0045] like Figure 2 As shown, the embodiment of the present application further provides a control device for a smart cockpit, including:

[0046] at least one processor; and,

[0047] a memory communicatively connected to the at least one processor; wherein,

[0048] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the control device of the smart cockpit to execute: the method described in any one of the above embodiments.

[0049] An embodiment of the present application further provides a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to perform the method described in any one of the above embodiments.

[0050] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0051] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0052] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0053] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0054] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0056] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0057] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0058] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0059] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0060] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A control system for an intelligent cockpit, characterized in that: include: a central control unit, communicating with a CAN bus of the vehicle and configured to integrate a task priority arbitration algorithm to perform task management according to the algorithm; The human-computer interaction module is set inside the vehicle and includes multiple interaction modes for receiving and processing the driver's interaction instructions; Environmental perception module, including multiple sensors, for real-time monitoring of the environmental conditions inside and outside the vehicle; The cargo hold management unit includes a cargo hold door, a ventilation device and a cabin display screen, and is used to obtain the monitoring information of the environmental perception module and manage the cargo hold status according to the information.

2. The system according to claim 1, wherein: The human-computer interaction module includes: A voice interaction submodule, equipped with a directional microphone array and a deep learning noise reduction model, is used to recognize voice commands; A gesture interaction submodule, which is used to recognize various gesture commands, including swiping with one hand to control the cargo door and clenching a fist to activate emergency braking; The biometric authentication submodule is provided with multiple biometric authentications, and is used to configure the driver according to the biometrics.

3. The system according to claim 1, wherein: The environment perception module includes: Cockpit cameras, used to monitor the pilot's behavior and the cockpit environment; Cargo hold temperature and humidity sensor, used to monitor the temperature and humidity in the cargo hold in real time; Cargo weight sensor, used to monitor the weight of cargo in the cargo hold and connect with the cargo hold management unit; Driver status monitoring module, used to monitor driver fatigue and distraction in real time.

4. A method for controlling an intelligent cockpit, characterized in that: Applied in a control system for an intelligent cockpit as described in claims 1-3, the method comprises: receiving an interactive instruction from a driver, and parsing and executing the interactive instruction through a task priority arbitration algorithm of the central control unit; Determining a task priority according to a driving state of the vehicle, and determining a corresponding management mode according to the task priority, wherein the driving state includes driving and loading and unloading, and the management mode includes driving mode and loading and unloading mode; determining the driver's fatigue and distraction behavior, and determining a safety reminder mechanism based on the fatigue and distraction behavior, so as to control the vehicle according to the safety reminder mechanism; Obtain the cargo hold status, determine a corresponding control mechanism according to the cargo hold status, and control the cargo hold according to the control mechanism.

5. The method according to claim 4, characterized in that After receiving the interaction instruction issued by the driver, the method further includes: A directional microphone array is used to collect original voice input, and effective voice is extracted through background noise spectrum analysis and deep learning noise reduction model, and command recognition and execution feedback are performed.

6. The method according to claim 4, characterized in that Determining the task priority according to the driving state of the vehicle, and determining the corresponding management mode according to the task priority, specifically including: When the management mode is the driving mode, priority is given to interactive instructions related to driving safety, including emergency braking and lane keeping; When the management mode is the loading and unloading mode, priority is given to interactive instructions related to cargo loading and unloading and electronic signature.

7. The method according to claim 4, characterized in that The method further comprises: Analyze the driver's fatigue in real time through the driver status monitoring module, the fatigue level including blink frequency and heart rate variability coefficient; monitoring the driver's head posture via a cockpit camera to determine distracted behavior based on the head posture, including the time the driver's gaze is directed away from the road; According to the safety reminder mechanism corresponding to the fatigue level and the distraction behavior, the prime safety reminder mechanism includes voice reminders, linkage with the dispatch center, speed limit, suspension of the entertainment system and shrinking of the central control screen interface.

8. The method according to claim 4, characterized in that The method further comprises: Determining, by the cargo hold management unit, whether there is an abnormal cargo hold state, wherein the abnormal cargo hold state includes an overloaded cargo hold and a hatch not being closed tightly; If there is an abnormal condition in the cargo hold, an alarm will be issued through seat vibration and a flashing red frame on the screen.

9. A control device for an intelligent cockpit, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the control device of the smart cockpit to execute: the method according to any one of claims 4 to 8.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to: perform the method according to any one of claims 4 to 8.

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