Vehicle driver distraction detection warning method, control device, vehicle and program product

Abstract

The invention discloses a vehicle driver distraction detection and warning method, a control device, a vehicle and a program product. The method comprises the steps that a target driving instruction is received; in response to the target driving instruction, determining driving operation behavior planning data and dynamically collecting driving behavior information; according to the driving behavior information and the driving operation behavior planning data, performing driving intention judgment, and determining a corresponding distraction detection level; and determining corresponding target driving warning information according to the distraction detection level, and performing distraction warning according to the target driving warning information. According to the method, intelligent driver distraction detection warning can be realized based on the driving behavior plan and the current driving behavior, the efficiency and accuracy of driver distraction detection are improved, the driving safety is improved, reliable guarantee is provided for safe travel of vast drivers, and the method can be widely applied to the technical field of driving safety.

Description

Technical Field

[0001] The present application relates to the field of driving safety technology, and in particular to a vehicle driver distraction detection and warning method, a control device, a vehicle, and a program product. Background Art

[0002] While driving, drivers are often distracted by their surroundings, unable to maintain full focus. Driver distraction is a major cause of traffic accidents. With the widespread adoption of smart in-vehicle devices and mobile internet devices, drivers are increasingly exposed to external information and are increasingly susceptible to distracted driving. This poses a serious challenge to traffic safety, and the issue of distracted driving has become a key focus of the industry.

[0003] Existing driver status detection methods primarily focus on driver fatigue. These typically use cameras to monitor the driver's face and head, and analyze images to identify driver fatigue. Fatigue can cause drivers to lose focus, but simply detecting driver fatigue alone can lead to problems such as limited recognition behavior, inaccurate recognition, and delayed processing.

[0004] Therefore, the above technical problems need to be solved urgently. Summary of the Invention

[0005] The main purpose of the embodiments of the present application is to provide a vehicle driver distraction detection and warning method, control device, vehicle and program product, which can improve the efficiency and accuracy of driver distraction detection.

[0006] In one aspect, an embodiment of the present application provides a method for detecting and warning a vehicle driver distraction, the method comprising the following steps: receiving target driving instructions; In response to the target driving instruction, determining driving operation behavior planning data and dynamically collecting driving behavior information; Performing driving intention judgment based on the driving behavior information and the driving operation behavior planning data, and determining a corresponding distraction detection level; According to the distraction detection level, corresponding target driving warning information is determined, and a distraction warning is performed according to the target driving warning information.

[0007] In some embodiments, receiving the target driving instruction specifically includes: Get the vehicle navigation planning path and current vehicle location; Identifying whether the vehicle is currently in a maneuvering path segment based on the current vehicle driving position and the vehicle-mounted navigation planned path, wherein the maneuvering path segment includes a turning segment, a U-turn segment, a lane change segment, and a roundabout segment; When it is identified that the vehicle is currently in the maneuvering path segment, the target driving instruction corresponding to the maneuvering path segment is dynamically received.

[0008] In some embodiments, determining driving operation behavior planning data and dynamically collecting driving behavior information in response to the target driving instruction specifically includes: In response to the target driving instruction, determining a target planned driving path, driving visual behavior planning data, and a current vehicle driving position; Determining the driving operation behavior planning data according to the target planned driving path and the current vehicle driving position; Dynamically collecting the driving behavior information, including current driving operation behavior data and current driving visual behavior data; determining an operation distraction result based on the driving operation behavior planning data and the current driving operation behavior data; A visual distraction level is determined according to the current driving visual behavior data and the driving visual behavior planning data.

[0009] In some embodiments, the dynamic collection of the driving behavior information specifically includes: Collecting the current driving operation behavior data, including the current steering wheel rotation angle, the current vehicle speed, and the current on / off status of the vehicle indicator lights; Obtain multiple preset gaze areas; According to each of the preset gaze areas, visual dynamic capture is performed to collect the current driving visual behavior data, including the current driving gaze duration corresponding to each of the preset gaze areas.

[0010] In some embodiments, determining the visual distraction level based on the current driving visual behavior data and the driving visual behavior planning data specifically includes: determining, based on the driving visual behavior planning data, a target gaze area and a target gaze duration determination condition corresponding to the target gaze area, wherein the target gaze duration determination condition includes a plurality of preset distraction levels and a duration determination rule corresponding to each of the preset distraction levels; Determining a plurality of visual judgment areas corresponding to the target gaze area from the plurality of preset gaze areas, and obtaining the current gaze duration corresponding to each of the visual judgment areas from the current driving visual behavior data; Visual distraction judgment is performed according to the current gaze duration corresponding to each visual judgment area and the target gaze duration judgment condition, and the corresponding visual distraction level is determined from a plurality of preset distraction levels.

[0011] In some embodiments, determining the distracted driving result based on the driving operation behavior planning data and the current driving operation behavior data specifically includes: Obtaining several data comparison items corresponding to the target driving instruction; For each of the data comparison items, determining, based on the data comparison item, first pre-comparison data that matches the data comparison item from the driving operation behavior planning data, and determining second pre-comparison data that matches the data comparison item from the current driving operation behavior data; performing a data comparison on the first pre-comparison data and the second pre-comparison data to determine a distraction detection result corresponding to the data comparison item; The operation distraction result is determined according to the distraction detection result corresponding to each of the data comparison items.

[0012] In some embodiments, determining corresponding target driving warning information based on the distraction detection level, and providing a distraction warning based on the target driving warning information specifically includes: obtaining preset driving warning information corresponding to the target driving instruction, the preset driving warning information including visual distraction warning information corresponding to each of the preset distraction levels and operational distraction warning information corresponding to a plurality of preset operational distraction results; determining, from the preset driving warning information, a first warning message and a second warning message according to the visual distraction level and the operational distraction result, wherein the first warning message matches the visual distraction level, and the second warning message matches the operational distraction result; The target driving warning information is determined according to the first warning information and the second warning information.

[0013] On the other hand, an embodiment of the present application proposes a vehicle control device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the above-mentioned vehicle driver distraction detection and warning method when executing the computer program.

[0014] On the other hand, an embodiment of the present application proposes a vehicle, comprising the above-mentioned vehicle control device.

[0015] On the other hand, an embodiment of the present application provides a computer program product, including a computer program, which implements the above-mentioned vehicle driver distraction detection and warning method when executed by a processor.

[0016] Embodiments of the present application include at least the following beneficial effects: The present application provides a vehicle driver distraction detection and warning method, control device, vehicle, and program product, which receives a target driving instruction, responds to the target driving instruction, determines driving operation behavior planning data, and dynamically collects driving behavior information. Based on the driving behavior information and driving operation behavior planning data, the method determines driving intent, determines a corresponding distraction detection level, determines corresponding target driving warning information based on the distraction detection level, and issues a distraction warning based on the target driving warning information. The present application can implement intelligent driver distraction detection and warning based on the driving behavior plan and current driving behavior, improve the efficiency and accuracy of driver distraction detection, enhance driving safety, and provide reliable protection for the safe travel of numerous drivers. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a vehicle driver distraction detection and warning method provided by an embodiment of the present application; Figure 2 This is a flowchart of step S101 in the embodiment of the present application; Figure 3 This is a flowchart of step S102 in the embodiment of the present application; Figure 4 Schematic diagram of the target planned driving path in an embodiment of the present application; Figure 5 This is a flowchart of step S303 in the embodiment of the present application; Figure 6 This is a flowchart of step S305 in the embodiment of the present application; Figure 7 This is a flowchart of step S304 in the embodiment of the present application; Figure 8 This is a flowchart of step S104 in the embodiment of the present application; Figure 9 Schematic diagram of the mapping table composition of the target driving instruction in the embodiment of the present application; Figure 10 This is a hardware structure diagram of a vehicle control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0019] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0020] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0022] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0023] Reference Figure 1 , Figure 1This is an optional flowchart of a vehicle driver distraction detection and warning method provided in an embodiment of the present application. The method may include but is not limited to steps S101 to S104: Step S101, receiving a target driving instruction; Step S102, in response to the target driving instruction, determining driving operation behavior planning data and dynamically collecting driving behavior information; Step S103, judging driving intention based on the driving behavior information and the driving operation behavior planning data, and determining a corresponding distraction detection level; Step S104 : determining corresponding target driving warning information according to the distraction detection level, and performing distraction warning according to the target driving warning information.

[0024] In some embodiments, for driving scenarios such as turning left or right, making U-turns, changing lanes, and driving around an island, the system detects whether the driver is visually distracted or operationally distracted, and issues a distraction warning to the driver based on the distraction detection results to improve driving safety.

[0025] In some embodiments, reference Figure 2 Step S101 may include but is not limited to steps S201 to S203: Step S201, obtaining the vehicle navigation planned path and the current vehicle driving position; Step S202: Identify whether the vehicle is currently in a maneuvering route segment based on the current vehicle driving position and the vehicle navigation planned route; Step S203 : When it is identified that the vehicle is currently in a maneuvering path segment, a target driving instruction corresponding to the maneuvering path segment is dynamically received.

[0026] In some embodiments, a vehicle navigation system is connected to receive target driving instructions corresponding to the maneuvering path segment from the vehicle navigation system. Optionally, the target driving instructions may include but are not limited to left turn instructions, right turn instructions, left lane change instructions, right lane change instructions, roundabout instructions, left U-turn instructions, and right U-turn instructions, etc.

[0027] In some embodiments, a maneuvering path segment refers to a path segment corresponding to a discrete driving action that the vehicle's onboard navigation system instructs the vehicle to perform during navigation. Discrete driving actions may include but are not limited to turning, U-turns, lane changes, and entering and exiting roundabouts. The corresponding maneuvering path segment may include but is not limited to turning segments, U-turn segments, lane change segments, and roundabout driving segments.

[0028] In some embodiments, reference Figure 3 Step S102 may include but is not limited to steps S301 to S305: Step S301, in response to a target driving instruction, determining a target planned driving path, driving visual behavior planning data, and a current vehicle driving position; Step S302, determining driving operation behavior planning data based on the target planned driving path and the current vehicle driving position; Step S303, dynamically collecting driving behavior information, including current driving operation behavior data and current driving visual behavior data; Step S304, determining the distracted driving result based on the driving operation behavior planning data and the current driving operation behavior data; Step S305 : determining the visual distraction level based on the current driving visual behavior data and the driving visual behavior planning data.

[0029] In some embodiments, for example, the target planned driving path corresponding to the target driving instruction is obtained, referring to Figure 4 Assuming that the target driving instruction is a left turn instruction, the left turn path segment A corresponding to the left turn instruction is obtained. Then, based on the current vehicle driving position O and the left turn path segment A, the target planned driving path S (the path shown in the red dotted box) corresponding to the left turn path segment is determined for the corresponding vehicle to travel from the current vehicle driving position.

[0030] In some embodiments, the driving operation behavior planning data includes a steering wheel rotation angle threshold, a vehicle speed threshold, and an indicator light on / off status. Assuming that the target planned driving path is the above-mentioned target planned driving path S, the turning radius of the target planned driving path S is obtained from the on-board navigation system. Based on the turning radius, combined with dynamic balance and geometric constraints, the steering wheel rotation angle threshold and the vehicle speed threshold are determined. At the same time, it is determined that the left turn indicator light remains on and the right turn indicator light is turned off until the vehicle passes the target planned driving path S.

[0031] In some embodiments, reference Figure 5 Step S303 may include but is not limited to steps S401 to S403: Step S401, collecting current driving operation behavior data, including the current steering wheel rotation angle, current vehicle speed, and the current on / off status of the vehicle indicator lights; Step S402, obtaining a plurality of preset gaze areas; Step S403 : performing visual dynamic capture according to each preset gaze area, and collecting current driving visual behavior data, wherein the current driving visual behavior data includes the current driving gaze duration corresponding to each preset gaze area.

[0032] In some embodiments, the preset gaze areas may be the front view (front window) area, the left rearview mirror area, and the right rearview mirror area, etc. A non-invasive eye tracker is set on each preset gaze area. The non-invasive eye tracker obtains the coordinates of the driver's gaze area based on the pupil corneal reflection method. The non-invasive eye tracker on each preset gaze area is used to capture visual dynamics and collect the current driving gaze duration of the driver corresponding to each preset gaze area. Optionally, the current driving gaze duration of each preset gaze area is calculated by the following formula: ; in, For the The current driving gaze duration corresponding to the preset gaze area, For the Preset gaze areas, is the calculation start time of the fixation time, i.e. the moment when the vehicle enters the maneuvering path segment, is the length of the time window, which indicates the time range for calculating the fixation time. Visibility function is an indicator function used to determine whether the driver is looking at the corresponding The preset attention area is usually 1 or 0, 1 means the driver is looking at the corresponding first area at a certain moment. preset gaze area, 0 means the driver is not looking at the corresponding preset gaze areas.

[0033] In some embodiments, reference Figure 6 Step S305 may include but is not limited to steps S501 to S503: Step S501: determining a target gaze area and target gaze duration determination conditions corresponding to the target gaze area based on the driving visual behavior planning data. The target gaze duration determination conditions include a plurality of preset distraction levels and duration determination rules corresponding to each preset distraction level. Step S502, determining multiple visual judgment areas corresponding to the target gaze area from multiple preset gaze areas, and obtaining the current gaze duration corresponding to each visual judgment area from the current driving visual behavior data; Step S503 : performing visual distraction judgment according to the current gaze duration corresponding to each visual judgment area and the target gaze duration judgment condition, and determining the corresponding visual distraction level from a plurality of preset distraction levels.

[0034] In some embodiments, different target driving instructions correspond to different visual judgment areas. For example, assuming that the preset gaze areas are the front view (front window) area, the left rearview mirror area, and the right rearview mirror area, if the target driving instruction is a left turn instruction, the corresponding visual judgment areas are the front view area and the left rearview mirror area. If the target driving instruction is a right turn instruction, the corresponding visual judgment areas are the front view area and the right rearview mirror area, and so on.

[0035] In some embodiments, the driving visual behavior planning data includes a target gaze area and a target gaze duration judgment condition corresponding to the target gaze area. The target gaze area includes several visual judgment areas. The duration judgment rules corresponding to each preset distraction level include the gaze duration judgment rules for each visual judgment area in the target gaze area, the gaze duration judgment rules for the total gaze time of the target gaze area, etc., wherein the total gaze time of the target gaze area is the sum of the gaze times of all visual judgment areas.

[0036] Optionally, a visual distraction detection mapping table is pre-set between different target driving instructions and preset distraction levels. Based on the visual distraction detection mapping table, the driving visual behavior planning data corresponding to the target driving instruction is determined. For example, assuming that the target driving instruction is a left turn instruction, a visual distraction detection mapping table between the left turn instruction and the visual distraction level is obtained, as shown in Table 1 below: Table 1 Visual distraction detection mapping table for left turn instructions

[0037] As can be seen from Table 1, the visual judgment areas for a left turn instruction are the front view area and the left rearview mirror area. The preset distraction level for a left turn instruction can be Level 0, Level 1, or Level 2. Each preset distraction level has different duration determination rules, including the cumulative duration of gazes at the front view and left rearview mirror, the cumulative duration of gazes in the front view area and the cumulative duration of gazes in the left rearview mirror, and the conditions met. Each preset distraction level is provided with a corresponding distraction warning message. For example, if the current driver's gaze duration in the front view area is 3 seconds and the current driver's gaze duration in the left rearview mirror area is 2 seconds, the current total gaze duration in the corresponding target gaze area is determined to be 5 seconds. If the current driver's gaze duration in the front view area is greater than 2 seconds (the cumulative duration of the front view area at Level 0), the current driver's gaze duration in the left rearview mirror area is equal to 2 seconds (the cumulative duration of the front view area at Level 0), and the current total gaze duration in the target gaze area is greater than 4 seconds (the cumulative duration of gazes in the front view and left rearview mirror at Level 0), then the three duration conditions for Level 0 are met and the visual distraction level is determined to be 0.

[0038] In some embodiments, reference Figure 7 Step S304 may include but is not limited to steps S601 to S604: Step S601, obtaining several data comparison items corresponding to the target driving instruction; Step S602: for each data comparison item, determining first pre-comparison data that matches the data comparison item from the driving operation behavior planning data, and determining second pre-comparison data that matches the data comparison item from the current driving operation behavior data according to the data comparison item; Step S603: performing data comparison on the first pre-comparison data and the second pre-comparison data to determine a distraction detection result corresponding to the data comparison item; Step S604: determining the distraction operation result according to the distraction detection result corresponding to each data comparison item.

[0039] In some embodiments, different target driving instructions include different data comparison items. The data comparison items may be steering wheel rotation angle comparison, indicator light on / off status comparison, and vehicle speed comparison. Each data comparison item includes multiple comparison result options, comparison analysis methods, and comparison data types. Based on the comparison data type of the data comparison item, first pre-comparison data matching the comparison data type is determined from the driving operation behavior planning data, and second pre-comparison data matching the comparison data type is determined from the current driving operation behavior data. The first pre-comparison data and the second pre-comparison data are compared using a comparison analysis method (such as numerical comparison or indicator light status comparison). Determine a comparison result corresponding to the data comparison item. Based on the comparison result, determine a target option corresponding to the comparison result from multiple comparison result options, i.e., the distraction detection result described above. For example, if the data comparison item is a steering wheel rotation angle comparison, its corresponding comparison data type is the steering wheel rotation angle. Determine a steering wheel rotation angle threshold that matches the steering wheel rotation angle from the driving operation behavior planning data. Determine a current steering wheel rotation angle that matches the steering wheel rotation angle from the current driving operation behavior data. The comparison analysis method is numerical comparison. Assuming that the steering wheel rotation angle threshold is greater than the current steering wheel rotation angle, the comparison result is that the current steering wheel rotation angle is too small, and so on.

[0040] In some embodiments, a distraction detection mapping table is established between the comparison result options of each data comparison item and the distraction detection result of the operation. According to the distraction detection result corresponding to each data comparison item, the corresponding distraction result is determined from the distraction detection mapping table. Assuming that the data comparison items include data comparison items 1 to 3, each data comparison item has three comparison result options, data comparison item 1 includes comparison result options 11 to 13, data comparison item 2 includes comparison result options 21 to 23, and data comparison item 3 includes comparison result options 31 to 33, the corresponding distraction detection mapping table is specifically shown in Table 2 below: Table 2 Operation distraction detection mapping table

[0041] As can be seen from Table 2, nine different distraction detection results are determined based on different combinations of distraction detection results for each data comparison item, including distraction detection results A to I. The descriptive information corresponding to the distraction detection results may include, but is not limited to, the distraction detection level, the distraction detection result code, and the textual summary of the distraction detection result, etc., which are not limited here.

[0042] In some embodiments, reference Figure 8 Step S104 may include but is not limited to steps S701 to S703: Step S701: obtaining preset driving warning information corresponding to the target driving instruction, where the preset driving warning information includes visual distraction warning information corresponding to each preset distraction level and operational distraction warning information corresponding to a plurality of preset operational distraction results; Step S702, determining a first warning message and a second warning message from preset driving warning messages based on the visual distraction level and the operational distraction result, wherein the first warning message matches the visual distraction level, and the second warning message matches the operational distraction result; Step S703: Determine target driving warning information according to the first warning information and the second warning information.

[0043] In some embodiments, optionally, a first warning information mapping table is established between each preset distraction level and the visual distraction warning information, and a second warning information mapping table is established between each preset operation distraction result and the operation distraction warning information. According to the visual distraction level, the corresponding first warning information is determined from the distraction warning information mapping table, and according to the operation distraction result, the corresponding second warning information is determined from the second warning information mapping table. For example, if the operation distraction result of the left turn instruction shows that the left turn signal is not turned on, the corresponding second warning information is a voice prompt to the driver to turn on the left turn signal or to control the vehicle-mounted warning unit to automatically assist the driver in turning on the left turn signal.

[0044] In some embodiments, the vehicle-mounted warning unit is controlled to output the first warning information and the second warning information. The vehicle-mounted warning unit includes a vehicle-mounted speaker, a vehicle-mounted display screen, and a vehicle-mounted lighting control system.

[0045] In some embodiments, reference Figure 9 Different target driving instructions have corresponding visual distraction detection mapping tables, operational distraction detection mapping tables, first warning information mapping tables, and second warning information mapping tables. For example, assuming there are target driving instructions A to N, target driving instruction A corresponds to visual distraction detection mapping table A, operational distraction detection mapping table A, first warning information mapping table A, and second warning information mapping table A, and so on.

[0046] An embodiment of the present invention also provides a vehicle control device, comprising a memory, a processor, and a program stored in the memory and executable on the processor. When the program is executed by the processor, the vehicle driver distraction detection and warning method of the above embodiment is implemented.

[0047] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0048] See also Figure 10 , Figure 10 The hardware structure of a vehicle control device according to another embodiment is shown. The vehicle control device includes: The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute the vehicle driver distraction detection and warning method of the embodiments of this application; Input / output interface 903, used to implement information input and output; Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.); Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 ); The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0049] For example, the processor and memory in a vehicle controller can be connected via a bus. Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. Furthermore, the memory can include high-speed random access memory and non-transitory memory, such as at least one disk drive, flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include memory remotely located relative to the control processor, and these remote memories can be connected to the control device via a network.

[0050] The non-transient software program and instructions required to implement the vehicle driver distraction detection and warning method of the above embodiment are stored in the memory, and when executed by the processor, the vehicle driver distraction detection and warning method of the above embodiment is executed. Figure 2 Steps S201 to S203 of the method, Figure 3 Steps S301 to S305 of the method, Figure 5 Method steps S401 to S403, etc.

[0051] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0052] An embodiment of the present invention further provides a vehicle, comprising the vehicle control device of the above embodiment.

[0053] The vehicle can be a private car, such as a sedan, SUV, MPV, or pickup truck. It can also be a commercial vehicle, such as a van, bus, small truck, or large trailer. The vehicle must have an electric motor that can output power or store mechanical energy as a generator. If the vehicle is a new energy vehicle, it can be a hybrid or a pure electric vehicle.

[0054] Since the vehicle applies all the technical solutions of the above-mentioned control device or vehicle controller, it has at least all the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be repeated here.

[0055] In addition, an embodiment of the present invention further provides a computer program product, including a computer program or computer instructions, the computer program or computer instructions being stored in a computer-readable storage medium, the processor of a computer device reading the computer program or computer instructions from the computer-readable storage medium, and the processor executing the computer program or computer instructions, so that the computer device executes the above-described robot control method. For example, the above-described Figures 1 to 7 The method steps in .

[0056] It is worth noting that since the computer program product of the embodiment of the present invention can execute the vehicle driver distraction detection and warning method of any of the above-mentioned embodiments, the specific implementation methods and technical effects of the computer program product of the embodiment of the present invention can refer to the specific implementation methods and technical effects of the vehicle driver distraction detection and warning method of any of the above-mentioned embodiments.

[0057] Those skilled in the art will appreciate that all or some of the steps and systems disclosed above can be implemented as software, firmware, hardware, or any suitable combination thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is well known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0058] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

Claims

1. A vehicle driver distraction detection and warning method, characterized in that: The method comprises the following steps: receiving target driving instructions; In response to the target driving instruction, determining driving operation behavior planning data and dynamically collecting driving behavior information; Performing driving intention judgment based on the driving behavior information and the driving operation behavior planning data, and determining a corresponding distraction detection level; According to the distraction detection level, corresponding target driving warning information is determined, and a distraction warning is performed according to the target driving warning information.

2. The vehicle driver distraction detection and warning method according to claim 1, characterized in that: The receiving of the target driving instruction specifically includes: Get the vehicle navigation planning path and current vehicle location; Identifying whether the vehicle is currently in a maneuvering path segment based on the current vehicle driving position and the vehicle-mounted navigation planned path, wherein the maneuvering path segment includes a turning segment, a U-turn segment, a lane change segment, and a roundabout segment; When it is identified that the vehicle is currently in the maneuvering path segment, the target driving instruction corresponding to the maneuvering path segment is dynamically received.

3. The vehicle driver distraction detection and warning method according to claim 1, characterized in that: The determining of driving operation behavior planning data and dynamically collecting driving behavior information in response to the target driving instruction specifically includes: In response to the target driving instruction, determining a target planned driving path, driving visual behavior planning data, and a current vehicle driving position; Determining the driving operation behavior planning data according to the target planned driving path and the current vehicle driving position; Dynamically collecting the driving behavior information, including current driving operation behavior data and current driving visual behavior data; determining an operation distraction result based on the driving operation behavior planning data and the current driving operation behavior data; A visual distraction level is determined according to the current driving visual behavior data and the driving visual behavior planning data.

4. The vehicle driver distraction detection and warning method according to claim 3, characterized in that: The dynamic collection of the driving behavior information specifically includes: Collecting the current driving operation behavior data, including the current steering wheel rotation angle, the current vehicle speed, and the current on / off status of the vehicle indicator lights; Obtain multiple preset gaze areas; According to each of the preset gaze areas, visual dynamic capture is performed to collect the current driving visual behavior data, including the current driving gaze duration corresponding to each of the preset gaze areas.

5. The vehicle driver distraction detection and warning method according to claim 4, characterized in that: The determining of the visual distraction level according to the current driving visual behavior data and the driving visual behavior planning data specifically includes: determining, based on the driving visual behavior planning data, a target gaze area and a target gaze duration determination condition corresponding to the target gaze area, wherein the target gaze duration determination condition includes a plurality of preset distraction levels and a duration determination rule corresponding to each of the preset distraction levels; Determining a plurality of visual judgment areas corresponding to the target gaze area from the plurality of preset gaze areas, and obtaining the current gaze duration corresponding to each of the visual judgment areas from the current driving visual behavior data; Visual distraction judgment is performed according to the current gaze duration corresponding to each visual judgment area and the target gaze duration judgment condition, and the corresponding visual distraction level is determined from a plurality of preset distraction levels.

6. The vehicle driver distraction detection and warning method according to claim 4, characterized in that: The determining of the distracted driving result according to the driving operation behavior planning data and the current driving operation behavior data specifically includes: Obtaining several data comparison items corresponding to the target driving instruction; For each of the data comparison items, determining, based on the data comparison item, first pre-comparison data that matches the data comparison item from the driving operation behavior planning data, and determining second pre-comparison data that matches the data comparison item from the current driving operation behavior data; performing a data comparison on the first pre-comparison data and the second pre-comparison data to determine a distraction detection result corresponding to the data comparison item; The operation distraction result is determined according to the distraction detection result corresponding to each of the data comparison items.

7. The vehicle driver distraction detection and warning method according to claim 1, characterized in that: The step of determining corresponding target driving warning information according to the distraction detection level and providing a distraction warning according to the target driving warning information specifically includes: obtaining preset driving warning information corresponding to the target driving instruction, the preset driving warning information including visual distraction warning information corresponding to each of the preset distraction levels and operational distraction warning information corresponding to a plurality of preset operational distraction results; determining, from the preset driving warning information, a first warning message and a second warning message according to the visual distraction level and the operational distraction result, wherein the first warning message matches the visual distraction level, and the second warning message matches the operational distraction result; The target driving warning information is determined according to the first warning information and the second warning information.

8. A vehicle control device, characterized in that: The invention comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the vehicle driver distraction detection and warning method according to any one of claims 1 to 7 is implemented.

9. A vehicle, characterized in that: Comprising the vehicle control device as claimed in claim 8.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the vehicle driver distraction detection and warning method according to any one of claims 1 to 7 is implemented.

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