A single Beidou vehicle driving recorder with integrated safety assisted driving function

Abstract

The present invention provides a single Beidou vehicle driving recorder with integrated safety assisted driving function, comprising: a driving recording module for recording vehicle driving; a single Beidou positioning module for performing single Beidou positioning of the vehicle; a safety assisted driving module for predicting the vehicle's driving risks and dispatching the vehicle to perform emergency responses to the driving risks; and a module for predicting target influencing factors that may cause the driver of the vehicle to be distracted from driving in the future, and assisting the driver in avoiding driving distractions in advance based on the target influencing factors. The vehicle driving recorder of the present invention, through the single Beidou positioning module and the safety assisted driving module, achieves effective integration of precise positioning and safe assisted driving. While achieving precise positioning of the vehicle, prediction and response to driving risks, and assistance to the driver in avoiding driving distractions, it also ensures that it is very convenient to install on a vehicle, avoiding increasing the owner's management costs.

Description

Technical Field

[0001] The present invention relates to the field of driving assistance technology, and in particular to a single Beidou vehicle driving recorder with integrated safety assisted driving function. Background Art

[0002] Currently, accurate positioning is essential for efficient operation and maintenance of commercial vehicles. Furthermore, since commercial vehicle drivers often spend a lot of time driving alone, they are prone to driving risks and may become distracted. Therefore, the introduction of safety-assisted driving systems is particularly important.

[0003] However, installing precise positioning equipment and safety-assisted driving devices separately on a vehicle is not only cumbersome but also increases management costs for the owner. While dashcams, as a convenient external device, are widely used in vehicles, most existing dashcams only offer basic driving recording capabilities and cannot simultaneously achieve precise positioning and safety-assisted driving.

[0004] Therefore, how to effectively integrate precise positioning and safe assisted driving into a driving recorder has become an urgent problem to be solved. Summary of the Invention

[0005] One of the purposes of the present invention is to provide a single Beidou vehicle driving recorder with integrated safety assisted driving function to solve the problems in the background technology.

[0006] An embodiment of the present invention provides a single Beidou vehicle driving recorder with integrated safety assisted driving function, comprising:

[0007] Driving record module, used to record the driving of the car;

[0008] Single Beidou positioning module, used for single Beidou positioning of the car;

[0009] The safety assisted driving module is used to predict the driving risks of the car and dispatch the car to make an emergency response to the driving risks; it is also used to predict target influencing factors that may cause the driver of the car to be distracted in the future, and assist the driver in avoiding driving distractions in advance based on the target influencing factors.

[0010] Optionally, the safety assisted driving module predicts the driving risk of the car, including:

[0011] Based on the pre-trained AI model, the driving risk of the car is predicted according to the driver's driving habits, vehicle operating conditions, single Beidou positioning trajectory, road conditions, driver behavior monitoring information and environmental perception data.

[0012] Optionally, the safety assisted driving module dispatches the vehicle to perform an emergency response to the driving risk, including:

[0013] Dispatching the vehicle's safety control system to respond urgently to driving risks;

[0014] Among them, the safety control system includes at least one or a combination of: AEBS (Autonomous Emergency Braking System), ADAS (Advanced Driver Assistance System) and ESC (Electronic Stability Control).

[0015] Optionally, the safety assisted driving module predicts target influencing factors that may cause the driver of the car to be distracted in the future, including:

[0016] Identify the areas of origin of proximal factors that may cause drivers to become distracted in the future;

[0017] The possibility that the driver is passively focused on the road conditions and fails to consider the nearest influencing factors when determining the source area of ​​the car's future passage;

[0018] When the likelihood is lower than the likelihood threshold, the nearest influencing factor is used as the target influencing factor.

[0019] Optionally, determining the source area of ​​the nearest influencing factors that may cause the driver to be distracted from driving in the future includes:

[0020] Based on the driver's current trip history and personal profile, multiple standard influencing factors that may cause the driver to be distracted are matched from the standard influencing factor library;

[0021] Determine, from multiple areas that the vehicle will pass through in the future, multiple supporting areas that support the generation of any standard influencing factor and the standard influencing factors that each area supports;

[0022] Traverse each supported area in the order that the car will pass through in the future;

[0023] During each traversal, based on the road conditions and vehicle conditions of the support area that the car will pass through in the future, it is determined whether the standard influencing factors supported by the traversed support area will actually occur when the car passes through the support area in the future. If so, the traversal is stopped, and the standard influencing factors supported by the traversed support area are used as the most recent influencing factors, and the traversed support area is used as the source area.

[0024] Optionally, the determination of the possibility that the driver is unable to consider recent influencing factors due to passively focusing on road conditions when the car passes through the source area in the future includes:

[0025] Draw a driving route based on the road conditions when the car passes through the source area in the future;

[0026] Divide the driving route into N equal segments; N is a preset positive integer;

[0027] Matching the sub-road condition representative of each route segment from the ability database to enable the driver to passively pay attention to the road condition;

[0028] Matching the demand weight representing the relative position relationship between each route segment and the source area, which requires the driver to pay attention to the road conditions, from the demand weight library;

[0029] Based on the demand weights corresponding to each route segment, the capacity corresponding to each route segment is weightedly calculated to obtain the possibility.

[0030] Optionally, the step of assisting the driver in avoiding distracted driving in advance based on the target influencing factors includes:

[0031] Matching a distraction avoidance assistance method from a distraction avoidance assistance method library based on the target influencing factors, the vehicle's driving plan and road conditions before the target influencing factors may cause the driver to become distracted, historical distraction avoidance assistance methods used for drivers, and assistance methods supported by the vehicle;

[0032] Based on the driving distraction avoidance assistance mode, the driver is assisted in avoiding driving distractions in advance.

[0033] Optional single Beidou vehicle driving recorder with integrated safety assisted driving function also includes:

[0034] OTA module, used for remote online upgrade of vehicle software.

[0035] Optional single Beidou vehicle driving recorder with integrated safety assisted driving function also includes:

[0036] The communication security module is used to securely encrypt the vehicle's data storage and data.

[0037] Optional single Beidou vehicle driving recorder with integrated safety assisted driving function also includes:

[0038] The Ecall module is used to automatically dial the emergency rescue number when a car accident occurs, and transmit the accident location, accident time, vehicle model, driver information and accident type to the emergency rescue center.

[0039] The present invention has achieved the following beneficial effects:

[0040] The vehicle driving recorder of the present invention realizes the effective integration of precise positioning and safe assisted driving through a single Beidou positioning module and a safe assisted driving module. On the premise of realizing precise positioning of the vehicle, prediction and response to driving risks, and assistance to the driver in avoiding driving distraction, it also ensures that it is very convenient when installed on the vehicle, avoiding increasing the management cost of the owner.

[0041] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0042] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0044] Figure 1 This is a structural diagram of a single Beidou vehicle driving recorder with integrated safety assisted driving function in an embodiment of the present invention;

[0045] Figure 2 This is another structural diagram of a single Beidou vehicle driving recorder with integrated safety assisted driving function according to an embodiment of the present invention;

[0046] Figure 3 This is another structural diagram of a single Beidou vehicle driving recorder with integrated safety assisted driving function according to an embodiment of the present invention;

[0047] Figure 4 This is another structural diagram of a single Beidou vehicle driving recorder with integrated safety assisted driving function in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] Example 1:

[0050] The embodiment of the present invention provides a single Beidou vehicle driving recorder with integrated safety auxiliary driving function, such as Figure 1 Shown, including:

[0051] Driving record module 1, used for recording the driving of the car;

[0052] Single Beidou positioning module 2, used for single Beidou positioning of the car;

[0053] Safety Assisted Driving Module 3 is used to predict the driving risks of the car and dispatch the car to respond to the driving risks in an emergency. It is also used to predict target influencing factors that may cause the driver of the car to be distracted in the future, and assist the driver in avoiding driving distractions in advance based on the target influencing factors.

[0054] The automobile in the embodiment of the present invention can be a commercial vehicle, namely a passenger vehicle, a hazardous chemical transport vehicle and a heavy freight vehicle. The driving record module 1 provides the automobile with basic driving record functions, such as recording the real-time driving screen of the automobile. On this basis, the single Beidou positioning module 2 provides the automobile with a precise positioning function through the single Beidou technology, and obtains the precise positioning information of the automobile in real time. The positioning information can be remotely sent to the operation and maintenance management background of the commercial vehicle for relevant personnel to determine the position of the automobile in real time. In addition, the safety assisted driving module 3 also provides the automobile with a safety assisted driving function. Specifically, it can predict the driving risks of the automobile in advance, and dispatch the automobile to respond to the driving risks in an emergency to ensure the safety of the automobile. It also predicts the target influencing factors that may cause the driver of the car to be distracted in the future, and provides assistance to the driver in advance to avoid driving distraction, so as to avoid the driver being distracted by the target influencing factors in the future, thereby further improving driving safety.

[0055] The vehicle driving recorder of the present invention realizes the effective integration of precise positioning and safe assisted driving through a single Beidou positioning module and a safe assisted driving module. On the premise of realizing precise positioning of the vehicle, prediction and response to driving risks, and assistance to the driver in avoiding driving distraction, it also ensures that it is very convenient when installed on the vehicle, avoiding increasing the management cost of the owner.

[0056] Furthermore, it's important to note that existing driver distraction assistance technologies often identify whether the driver is distracted and, if so, prompt them to stop. This invention, however, predicts potential future driver distraction factors and assists the driver in avoiding them before they are affected by those factors, i.e., before they become distracted. This significantly reduces driver distraction and improves driving safety.

[0057] Example 2:

[0058] In an embodiment of the present invention, the safety auxiliary driving module predicts the driving risk of the car, including:

[0059] Based on the pre-trained AI model, the driving risk of the car is predicted according to the driver's driving habits, vehicle operating conditions, single Beidou positioning trajectory, road conditions, driver behavior monitoring information and environmental perception data.

[0060] The pre-training step for the AI ​​model in this embodiment of the present invention includes: using multiple vehicle driving data sets pre-labeled with driving risk labels (each vehicle driving data set includes one or more combinations of historically generated data on the driver's driving habits, vehicle operating conditions, single Beidou positioning trajectory, road conditions, driver behavior monitoring information, and environmental perception data) as training samples for machine learning training, and using the trained artificial intelligence model after convergence as the AI ​​model. At this point, the AI ​​model can predict the vehicle's driving risk based on the driver's driving habits, vehicle operating conditions, single Beidou positioning trajectory, road conditions, driver behavior monitoring information, and environmental perception data.

[0061] The driver's driving habits are the current driver's driving habits; the vehicle operating conditions are the vehicle's driving parameters; the single Beidou positioning trajectory history is the vehicle's single Beidou positioning trajectory; the road conditions are the vehicle's future road conditions, which can be extracted from the road condition broadcast information of relevant navigation software; the driver behavior monitoring information is the driver's current image, which can be obtained through the vehicle's in-vehicle camera; and the environmental perception data is the environmental data sensed by the vehicle's external cameras, radar, etc. Predicted driving risks include: fatigue driving, vehicle collision risk, and emergency road conditions.

[0062] Example 3:

[0063] In an embodiment of the present invention, the safety assisted driving module dispatches the vehicle to perform an emergency response to the driving risk, including:

[0064] Dispatching the vehicle's safety control system to respond urgently to driving risks;

[0065] Among them, the safety control system includes at least one or more combinations of AEBS, ADAS and ESC.

[0066] In embodiments of the present invention, a safety control system is utilized to dispatch vehicles to respond to driving risks. This safety control system can be a combination of one or more of AEBS, ADAS, and ESC, independently or collaboratively responding to driving risks. Examples include fatigue driver warnings, emergency braking to prevent collisions, and vehicle stabilization in emergency road conditions.

[0067] Example 4:

[0068] When driving a car, the driver focuses on two types of information: one is the current road conditions, and the other is the environment information while the car is driving.

[0069] In the future, factors that may cause drivers to be distracted by driving may all come from environmental information that the car passes by while driving (such as large roadside billboards, tourist attractions, construction buildings, etc.). However, not all of these factors will cause drivers to be distracted in the future. Drivers may be so focused on the current road conditions that they passively fail to take into account factors that may cause them to be distracted by driving. If this situation is not taken into account, it will be assumed that any of these factors will have an impact, resulting in unnecessary assistance to avoid driving distraction being executed, wasting assistance resources, causing unnecessary interference to the driver, and seriously affecting their driving experience.

[0070] To this end, in an embodiment of the present invention, the safety assisted driving module predicts target influencing factors that may cause the driver of the car to be distracted in the future, including:

[0071] Identify the areas of origin of proximal factors that may cause drivers to become distracted in the future;

[0072] The possibility that the driver is passively focused on the road conditions and fails to consider the nearest influencing factors when determining the source area of ​​the car's future passage;

[0073] When the likelihood is lower than the likelihood threshold, the nearest influencing factor is used as the target influencing factor.

[0074] First, the nearest influencing factor is identified. This factor is the most recent influencing factor that could potentially distract the driver in the future. The source region of the nearest influencing factor is then determined. The source region is the actual area that supports the nearest influencing factor. For example, if the nearest influencing factor is a large roadside billboard, the source region is the location and display area of ​​the billboard. Next, the probability that the driver will be distracted by the nearest influencing factor due to passive focus on road conditions when the car passes through the source region in the future is determined. This probability represents the degree to which the driver will be distracted by the nearest influencing factor due to their focus on the road conditions. The probability threshold is a pre-set threshold indicating an excessive probability. Therefore, when the probability falls below the threshold, it indicates that the probability of the driver being distracted by the nearest influencing factor due to passive focus on road conditions when the car passes through the source region in the future is not excessive. Therefore, the nearest influencing factor should be used as the target influencing factor to provide driver-responsive assistance to prevent driving distraction.

[0075] In determining the source area of ​​the most recent influencing factors that may cause the driver to be distracted from driving in the future, embodiments of the present invention take into account the possibility that the driver may be passively focused on road conditions and unable to consider the most recent influencing factors when the car passes through the source area in the future. This takes into account the special situation that the driver may be passively unable to consider the factors that may cause the driver to be distracted from driving due to being too focused on the current driving road conditions. When the probability is lower than the probability threshold, the most recent influencing factor is used as the target influencing factor to provide the driver with assistance to avoid driving distraction. This greatly improves the accuracy, comprehensiveness, and efficiency of the prediction of target influencing factors that may cause the driver to be distracted from driving in the future, avoids the execution of unnecessary assistance to avoid driving distraction, improves the utilization of assistance resources, and avoids unnecessary interference to the driver, thereby improving their experience.

[0076] Example 5:

[0077] In the embodiment of the present invention, determining the source area of ​​the nearest influencing factors that may cause the driver to be distracted from driving in the future includes:

[0078] Based on the driver's current trip history and personal profile, multiple standard influencing factors that may cause the driver to be distracted are matched from the standard influencing factor library;

[0079] Determine, from multiple areas that the vehicle will pass through in the future, multiple supporting areas that support the generation of any standard influencing factor and the standard influencing factors that each area supports;

[0080] Traverse each supported area in the order that the car will pass through in the future;

[0081] During each traversal, based on the road conditions and vehicle conditions of the support area that the car will pass through in the future, it is determined whether the standard influencing factors supported by the traversed support area will actually occur when the car passes through the support area in the future. If so, the traversal is stopped, and the standard influencing factors supported by the traversed support area are used as the most recent influencing factors, and the traversed support area is used as the source area.

[0082] In the embodiment of the present invention, the current trip history refers to the historical driving information of the driver during the current trip, including at least: the continuous driving time, the distance traveled, etc.; the personal portrait includes at least: age, gender, content of interest, etc. There are a large number of standard influencing factors corresponding to different groups of current trip histories and personal portraits in the standard influencing factor library. The standard influencing factors are the influencing factors that may cause the driver to be distracted from driving, as reflected by the current trip histories and personal portraits of the corresponding groups. For example, if the current trip history and personal portrait reflect that the driver has been driving for too long and may be fatigued, and the probability of distraction is high, and the driver is interested in mountain climbing, then the standard influencing factor is the high mountain scenic area that the car passes through. At this point, the standard influencing factors can be matched directly from the standard influencing factor library based on the current trip history and personal portrait of the driver.

[0083] After determining the standard influencing factors, multiple support areas that support any standard influencing factor and their respective supported standard influencing factors are determined from multiple areas that the car will pass through in the future (which can be determined based on the car's future driving conditions and the map). Continuing with the example of the standard influencing factor being a high mountain scenic spot, its support area is the area that includes the high mountain scenic spot that the car will pass through.

[0084] Next, each support area is traversed in sequence according to the order in which the car will pass through in the future. The order in which the car will pass through in the future refers to the order in which the car will pass through each support area in the future. During each traversal, based on the road conditions of the support area that the car will pass through in the future (the road conditions during the passage can be the route and time period of the car passing through the support area, which can be extracted from the future driving road condition information planned in the navigation software) and the vehicle conditions during the passage (the vehicle conditions during the passage refer to the visible field of view outside the driver's cabin window when the car passes through the support area, which can be determined based on the fixed visible field of view outside the window when the car is traveling in the direction of travel and the driving direction at different points along the route), it is determined whether the standard influencing factor supported by the traversed support area will actually occur when the car passes through the traversed support area in the future (for example, it is determined whether the total time that the standard influencing factor can be viewed in the visible field of view outside the driver's cabin window during the passage time period exceeds 1 / 5 of the passage time period; if so, it will actually occur). If it does occur, it indicates that the nearest influencing factor has been found, that is, the standard influencing factor supported by the traversed support area is used as the nearest influencing factor, and the traversed support area is then used as the source area.

[0085] The embodiment of the present invention first matches multiple standard influencing factors that may cause the driver to be distracted from driving based on the driver's current route history and personal portrait, then determines their support areas and traverses them in sequence. During each traversal, based on the road conditions and vehicle conditions when the car passes through the support area in the future, it is determined whether the standard influencing factors supported by the traversed support area will actually be generated when the car passes through the traversed support area in the future. If so, the standard influencing factors supported by the traversed support area are used as the most recent influencing factors, and the traversed support area is used as the source area. This greatly improves the accuracy, comprehensiveness and efficiency of determining the source area of ​​the most recent influencing factors that may cause the driver to be distracted from driving in the future, thereby improving the applicability of the system.

[0086] Example 6:

[0087] In an embodiment of the present invention, determining the possibility that the driver is unable to consider the nearest influencing factors due to passively focusing on the road conditions when the car passes through the source area in the future includes:

[0088] Draw a driving route based on the road conditions when the car passes through the source area in the future;

[0089] Divide the driving route into N equal segments; N is a preset positive integer;

[0090] Matching the sub-road condition representative of each route segment from the ability database to enable the driver to passively pay attention to the road condition;

[0091] Matching the demand weight representing the relative position relationship between each route segment and the source area, which requires the driver to pay attention to the road conditions, from the demand weight library;

[0092] Based on the demand weights corresponding to each route segment, the capacity corresponding to each route segment is weightedly calculated to obtain the possibility.

[0093] An embodiment of the present invention obtains the road conditions of a vehicle passing through a source area in the future. The road conditions during the passage include at least whether a lane change is required, whether a ramp needs to be entered, whether a traffic light needs to be passed, whether a traffic light needs to be waited for, and the degree of traffic congestion. These conditions can be determined using the future road condition information planned in real time by the navigation software. When plotting a driving route, the road conditions during the vehicle's future passage through the source area are divided into sub-road conditions at multiple waypoints. The order in which the vehicle will pass through each waypoint is then calculated, and the waypoints are sequentially connected to obtain a route. The sub-road conditions of each waypoint are then marked at the corresponding waypoint position on the route to obtain a driving curve.

[0094] The driving road condition route is divided into N route segments, and the sub-road condition of each route segment is the summary of the sub-road conditions of each waypoint on the route segment.

[0095] The capability library pre-sets the degree to which a driver can passively focus on road conditions for different route segments. This capability refers to the degree to which a route segment's sub-road conditions can cause the driver to focus solely on the road conditions, ignoring other surrounding environmental factors. For example, if a route segment's sub-road conditions require the driver to change lanes, navigate traffic lights, or experience heavy traffic, the driver will have no time to pay attention to other surrounding environmental factors and will only focus on the road conditions, resulting in a higher capability.

[0096] The demand weight library pre-sets the demand weights representing the need for the driver to pay attention to road conditions to avoid distraction, based on the relative positional relationships between different route segments and source regions. This demand weight refers to the degree to which the driver needs to pay attention to road conditions to avoid distraction when the route segment and source region are in that relative positional relationship. This demand weight is related to the degree of driver distraction caused by that relative positional relationship between the route segment and source region. For example, if the relative positional relationship indicates that the source region is in front of the route segment, the driver is more likely to subjectively check the source region, and the corresponding demand weight is set to a larger value. Another example is if the relative positional relationship indicates that the source region is to the side and rear of the route segment, the driver is less likely to subjectively check the source region, and the corresponding demand weight is set to a smaller value.

[0097] Finally, based on the demand weights of each route segment, the capacity of each route segment is weighted and calculated to obtain the possibility. The weighted calculation formula is: ,in, For the degree of possibility, For the The demand weight corresponding to each route segment is: For the The capability corresponding to each route segment is is the total number of route segments.

[0098] The embodiment of the present invention divides the driving road condition route into N equal route segments, and performs weighted calculation based on the ability of the driver to passively pay attention to the road condition represented by the sub-road condition of each route segment and the demand for the driver to pay attention to the road condition represented by the relative position relationship between each route segment and the source area. The calculation result is used as the possibility, which greatly improves the accuracy of determining the possibility that the driver will not be able to take into account the nearest influencing factors due to passively focusing on the road condition when the car passes through the source area in the future, thereby improving the accuracy of subsequent determination of whether to use the nearest influencing factor as the target influencing factor based on it.

[0099] Example 7:

[0100] In an embodiment of the present invention, the step of assisting the driver in avoiding driving distraction in advance based on target influencing factors includes:

[0101] Matching a distraction avoidance assistance method from a distraction avoidance assistance method library based on the target influencing factors, the vehicle's driving plan and road conditions before the target influencing factors may cause the driver to become distracted, historical distraction avoidance assistance methods used for drivers, and assistance methods supported by the vehicle;

[0102] Based on the driving distraction avoidance assistance mode, the driver is assisted in avoiding driving distractions in advance.

[0103] The distraction avoidance assistance method library of the embodiment of the present invention is pre-set with different groups of target influencing factors, the driving plan and road conditions of the vehicle before the target influencing factors may cause the driver to become distracted, the distraction avoidance assistance methods that have been historically used for the driver, and the assistance methods supported by the vehicle, reflecting the corresponding distraction avoidance assistance methods that are appropriate for the situation. The driving plan refers to the vehicle's driving plan, and the driving road conditions refer to the road conditions under which the vehicle is driving. The assistance methods supported by the vehicle refer to the assistance methods that the vehicle can support, such as voice reminders. For example, when the target influencing factors, the driving plan and road conditions of the vehicle before the target influencing factors may cause the driver to become distracted, the distraction avoidance assistance methods that have been historically used for the driver, and the assistance methods supported by the vehicle collectively indicate that the driver will be distracted by a large roadside billboard, and the driver has no plans to stop and has previously been reminded by a voice reminder, the corresponding distraction avoidance assistance method is to continue using the voice reminder to remind the driver to pay attention to driving. Improve the comprehensiveness, accuracy, and effectiveness of assisting drivers in avoiding driving distractions in advance by targeting influencing factors.

[0104] Example 8:

[0105] In an embodiment of the present invention, a single Beidou vehicle driving recorder with integrated safety assisted driving function, such as Figure 2 As shown, it also includes:

[0106] OTA module 4 is used to remotely upgrade the vehicle software online.

[0107] The single Beidou vehicle driving recorder of the present invention can also be provided with an OTA module to perform remote online upgrades on the vehicle software.

[0108] Example 9:

[0109] In an embodiment of the present invention, a single Beidou vehicle driving recorder with integrated safety assisted driving function, such as Figure 3 As shown, it also includes:

[0110] The communication security module 5 is used to securely encrypt the vehicle's data storage and data.

[0111] The single Beidou vehicle driving recorder of the present invention can also be provided with a communication security module to securely encrypt the vehicle's data storage and data storage to ensure communication security.

[0112] Example 10:

[0113] In an embodiment of the present invention, a single Beidou vehicle driving recorder with integrated safety assisted driving function, such as Figure 4 As shown, it also includes:

[0114] The Ecall module 6 is used to automatically dial an emergency rescue number when a car accident occurs, and transmit the accident location, accident time, vehicle model, driver information and accident type to the emergency rescue center.

[0115] The single Beidou car driving recorder of the present invention can also be provided with an Ecall module, which is convenient for automatically dialing the emergency rescue number when a car accident occurs, and transmitting the accident location, accident time, vehicle model, driver information and accident type to the emergency rescue center, so that the car can receive rescue in the first time.

[0116] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A single Beidou vehicle driving recorder with integrated safety assisted driving function, characterized in that: include: Driving record module, used to record the driving of the car; Single Beidou positioning module, used for single Beidou positioning of the car; The safety assistance driving module is used to predict driving risks and dispatch the car to respond to driving risks. It is also used to predict target factors that may cause the driver to distract from driving in the future and provide assistance to the driver to avoid driving distractions in advance based on these target factors. The safety assisted driving module predicts target factors that may cause the driver of the car to be distracted in the future, including: Identify the areas of origin of proximal factors that may cause drivers to become distracted in the future; The possibility that the driver is passively focused on the road conditions and fails to consider the nearest influencing factors when determining the source area of ​​the car's future passage; When the likelihood is lower than the likelihood threshold, the nearest influencing factor is used as the target influencing factor; The method of determining the source area of ​​the nearest influencing factors that may cause the driver to be distracted from driving in the future includes: Based on the driver's current trip history and personal profile, multiple standard influencing factors that may cause the driver to be distracted are matched from the standard influencing factor library; Determine, from multiple areas that the vehicle will pass through in the future, multiple supporting areas that support the generation of any standard influencing factor and the standard influencing factors that each area supports; Traverse each supported area in the order that the car will pass through in the future; During each traversal, based on the road conditions and vehicle conditions of the support area that the car will pass through in the future, it is determined whether the standard influencing factors supported by the traversed support area will actually occur when the car passes through the support area in the future. If so, the traversal is stopped, and the standard influencing factors supported by the traversed support area are used as the most recent influencing factors, and the traversed support area is used as the source area.

2. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: The safety assisted driving module predicts the driving risk of the car, including: Based on the pre-trained AI model, the driving risk of the car is predicted according to the driver's driving habits, vehicle operating conditions, single Beidou positioning trajectory, road conditions, driver behavior monitoring information and environmental perception data.

3. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: The safety assisted driving module dispatches the vehicle to perform an emergency response to driving risks, including: Dispatching the vehicle's safety control system to respond urgently to driving risks; Among them, the safety control system includes at least one or more combinations of AEBS, ADAS and ESC.

4. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: The possibility that the driver, when determining the source area that the car will pass through in the future, fails to consider the nearest influencing factors due to passively focusing on the road conditions when determining the source area that the car will pass through in the future includes: Draw a driving route based on the road conditions when the car passes through the source area in the future; Divide the driving route into N equal segments; N is a preset positive integer; Matching the sub-road condition representative of each route segment from the ability database to enable the driver to passively pay attention to the road condition; Matching the demand weight representing the relative position relationship between each route segment and the source area, which requires the driver to pay attention to the road conditions, from the demand weight library; Based on the demand weights corresponding to each route segment, the capacity corresponding to each route segment is weightedly calculated to obtain the possibility.

5. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: The aforementioned assistance to the driver in avoiding driving distraction in advance based on target influencing factors includes: Matching a distraction avoidance assistance method from a distraction avoidance assistance method library based on the target influencing factors, the vehicle's driving plan and road conditions before the target influencing factors may cause the driver to become distracted, historical distraction avoidance assistance methods used for drivers, and assistance methods supported by the vehicle; Based on the driving distraction avoidance assistance mode, the driver is assisted in avoiding driving distractions in advance.

6. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: Also includes: OTA module, used for remote online upgrade of vehicle software.

7. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: Also includes: The communication security module is used to securely encrypt the vehicle's data storage and data.

8. The single Beidou vehicle driving recorder with integrated safety assisted driving function as claimed in claim 1, characterized in that: Also includes: The Ecall module is used to automatically dial the emergency rescue number when a car accident occurs, and transmit the accident location, accident time, vehicle model, driver information and accident type to the emergency rescue center.

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