Intelligent driving assistance method and system for fatigue driving

Abstract

The present application is applicable to the field of intelligent driving technology, and in particular to an intelligent driving assistance method and system for fatigue driving, the method comprising: obtaining the driver's driving information; obtaining the destination according to the driver's driving information; obtaining the initial value of the remaining driving time according to the driver's driving information, and timing to obtain the remaining driving time; obtaining the vehicle's road condition information according to the destination; obtaining a driving allocation plan according to the road condition information and the remaining driving time; and obtaining prompt information according to the driving allocation plan. In this method, the system automatically obtains the driver's fatigue level and automatically determines the driving allocation plan throughout the process, which can maximize the driver's focus on the most complex road sections, effectively reduce the driver's fatigue level, and significantly reduce the risk of fatigue driving.

Description

Technical Field

[0001] The present application belongs to the field of intelligent driving technology, and in particular, to an intelligent driving assistance method and system for fatigue driving. Background Art

[0002] In recent years, intelligent driving assistance technology has developed rapidly and can help drivers make smarter decisions and prevent accidents in many ways. For example, when it detects that the driver is tired or distracted, it will issue a warning in time to remind the driver to rest or focus. For example, it can achieve fully autonomous driving on some special roads.

[0003] In the existing technology, there is already technology that can detect the driver's fatigue driving state, but there is no method to combine intelligent driving to target fatigue driving. There is also no method to reasonably allocate when to use intelligent driving and when to use manual driving. Therefore, before developing fully unmanned driving technology, there is an urgent need for a method that can use intelligent driving to allocate intelligent driving time and manual driving time for fatigue driving. Summary of the invention

[0004] The embodiments of the present application provide an intelligent driving assistance method and system for fatigue driving, which can solve the problem of not being able to reasonably allocate intelligent driving time and manual driving time for fatigue driving.

[0005] In a first aspect, an embodiment of the present application provides an intelligent driving assistance method for fatigue driving, the method being applied to a vehicle having an intelligent driving function, the method comprising:

[0006] Acquiring driving information of the driver; wherein the driving information is used to reflect the driving status of the driver;

[0007] Obtaining a destination according to the driving information of the driver;

[0008] Obtaining an initial value of the remaining driving time according to the driving information of the driver, and timing to obtain the remaining driving time; wherein the remaining driving time refers to the remaining time that the driver can drive safely;

[0009] Obtaining road condition information of the vehicle according to the destination; wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination;

[0010] A driving allocation scheme is obtained according to the road condition information and the remaining driving time; wherein the driving allocation scheme is used to reflect the allocation of intelligent driving and manual driving during the driving process;

[0011] Prompt information is obtained according to the driving allocation plan; wherein the prompt information is used to prompt the driver to drive or pay attention to road conditions and take over driving at any time.

[0012] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0013] The intelligent driving assistance method for fatigue driving provided by the present application can first obtain the driver's driving information, and the driving information can reflect whether the driver is driving fatigued and the degree of fatigue driving. Secondly, the destination is obtained according to the driver's driving information. When the driver is driving fatigued, he should stop and rest as soon as possible according to the law. For example, when the driving information indicates that the driver is in a fatigued driving state, the destination can be automatically determined by the vehicle, such as the destination can be the nearest parking point. Subsequently, the initial value of the remaining driving time is obtained according to the driver's driving information, and the remaining driving time is obtained by timing. The degree of driver fatigue driving is included in the driving information. Different initial values ​​of the remaining driving time can be set for different degrees of driving status, and the remaining driving time at each moment is obtained by timing from the initial value time. Subsequently, the road condition information of the vehicle is obtained according to the destination, and the road on which the vehicle is traveling is determined after the destination is obtained, and then the road condition of the road is obtained. Then, according to the road condition information and the remaining driving time, a driving allocation plan is obtained. After obtaining the road condition information, the road section that meets the intelligent driving requirements is determined according to the road condition information, and the road section is handed over as an intelligent driving section. The most complex road section that can be manually driven by the driver is determined according to the remaining driving time, and the road section is handed over as a manual driving section. The driving allocation plan is obtained according to the allocation of intelligent driving sections and manual driving sections. Finally, prompt information is obtained according to the driving allocation plan. After determining the driving allocation plan, the driver is prompted to make corresponding preparations at key nodes. Therefore, in this method, the system automatically obtains the driver's fatigue level throughout the process and automatically determines the driving allocation plan, which can maximize the driver's focus on the most complex road section, effectively reduce the driver's fatigue level, and significantly reduce the risk of fatigue driving.

[0014] In a second aspect, an embodiment of the present application provides an intelligent driving assistance system for fatigue driving, the system is applied to a vehicle with an intelligent driving function, and the system includes:

[0015] A fatigue driving warning unit, used to obtain the driver's driving information; wherein the driving information is used to reflect the driver's driving status;

[0016] A navigation unit, used for obtaining a destination according to the driving information of the driver;

[0017] A timing unit, used to obtain an initial value of the remaining driving time according to the driving information of the driver, and to perform timing to obtain the remaining driving time; wherein the remaining driving time refers to the remaining time that the driver can drive safely;

[0018] A road condition information collection unit, used to obtain road condition information of the vehicle according to the destination; wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination;

[0019] An analysis unit, configured to obtain a driving allocation scheme according to the road condition information and the remaining driving time; wherein the driving allocation scheme is used to reflect the allocation of intelligent driving and manual driving during the driving process;

[0020] A prompt information generating unit is used to obtain prompt information according to the driving allocation plan; wherein the prompt information is used to prompt the driver to drive or pay attention to the road conditions and take over the driving at any time.

[0021] In a third aspect, an embodiment of the present application provides an intelligent driving assistance device for fatigue driving, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the methods described in the first aspect when executing the computer program.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the first aspects above is implemented.

[0023] In the fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an intelligent driving assistance device for fatigue driving, the intelligent driving assistance device for fatigue driving executes the intelligent driving assistance method for fatigue driving described in any one of the above-mentioned first aspects.

[0024] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1It is a flowchart of an intelligent driving assistance method for fatigue driving provided by an embodiment of the present application;

[0027] Figure 2 It is a schematic diagram of the implementation process of an intelligent driving assistance method for fatigue driving provided by an embodiment of the present application;

[0028] Figure 3 is a structural diagram of an intelligent driving assistance system for fatigue driving provided by an embodiment of the present application;

[0029] Figure 4 It is a structural schematic diagram of an intelligent driving assistance device for fatigue driving provided in one embodiment of the present application. DETAILED DESCRIPTION

[0030] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0031] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0032] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0033] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0034] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0035] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0036] Among the related technologies, some simply classify fatigue driving and turn on automatic driving at a specific fatigue driving level, and turn off automatic driving when the fatigue is eliminated. It does not combine the driver's driving status and road condition information for analysis, and is overly dependent on the performance of automatic driving.

[0037] To solve the above problems, the embodiment of the present application provides an intelligent driving assistance method and system for fatigue driving. In this method, first, the driver's driving information can be obtained, and the driving information can reflect whether the driver is driving fatigued and the degree of fatigue driving. Secondly, the destination is obtained according to the driver's driving information. When the driver is driving fatigued, he should stop and rest as soon as possible according to the law. For example, the destination can be automatically determined by the vehicle in the fatigue driving state, such as the destination can be the nearest parking point. Subsequently, the initial value of the remaining driving time is obtained according to the driver's driving information, and the remaining driving time is obtained by timing. The degree of driver fatigue driving is included in the driving information. Different initial values ​​of the remaining driving time can be set for different degrees of driving states, and the remaining driving time at each moment is obtained by timing from the initial value time. Subsequently, the road condition information of the vehicle is obtained according to the destination, and the road on which the vehicle is traveling is determined after the destination is obtained, and then the road condition of the road is obtained. Then, according to the road condition information and the remaining driving time, a driving allocation plan is obtained. After obtaining the road condition information, the road section that meets the intelligent driving requirements is determined according to the road condition information, and the road section is handed over as an intelligent driving section. The most complex road section that can be manually driven by the driver is determined according to the remaining driving time, and the road section is handed over as a manual driving section. The driving allocation plan is obtained according to the allocation of intelligent driving sections and manual driving sections. Finally, prompt information is obtained according to the driving allocation plan. After determining the driving allocation plan, the driver is prompted to make corresponding preparations at key nodes. Therefore, in this method, the system automatically obtains the driver's fatigue level throughout the process and automatically determines the driving allocation plan, which can maximize the driver's focus on the most complex road section, effectively reduce the driver's fatigue level, and significantly reduce the risk of fatigue driving.

[0038] The intelligent driving assistance method for fatigue driving provided in the embodiment of the present application can be applied to vehicles with intelligent driving functions. The vehicles with intelligent driving functions may include intelligent driving assistance equipment for fatigue driving. In this case, the intelligent driving assistance equipment for fatigue driving is the executor of the intelligent driving assistance method for fatigue driving provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of intelligent driving assistance equipment for fatigue driving.

[0039] For example, the intelligent driving assistance equipment for fatigue driving may include an on-board intelligent device and a control device that is communicatively connected to the on-board intelligent device. The on-board intelligent device may include a fatigue driving warning module, a navigation module, and a prompt module. The fatigue driving warning module may be a fatigue driving warning device that comes with the vehicle, the navigation module may be an on-board computer with navigation software installed, and the prompt module may be a speaker or a mechanically vibrating seat. The control device may control the fatigue driving warning module to obtain the driver's driving information, and may also control the navigation module to obtain the destination according to the driver's driving information. The control device may obtain the initial value of the remaining driving time according to the driver's driving information, and perform timing to obtain the remaining driving time. The control device may also control the navigation module to obtain road condition information, and may also obtain a driving allocation plan according to the road condition information and the remaining driving time, and may also obtain prompt information according to the driving allocation plan. The control device may also control the prompt module to execute the prompt information.

[0040] The control device can be a single-chip microcomputer, a microprocessor, a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a smart large screen, a smart TV, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, and a satellite wireless device.

[0041] In order to better understand the intelligent driving assistance method for fatigue driving provided in the embodiment of the present application, the specific implementation process of the intelligent driving assistance method for fatigue driving provided in the embodiment of the present application is exemplarily introduced below.

[0042] Figure 1 A schematic flow chart of an intelligent driving assistance method for fatigue driving provided in an embodiment of the present application is shown. The intelligent driving assistance method for fatigue driving includes:

[0043] S100, obtaining driving information of the driver, wherein the driving information is used to reflect the driving status of the driver.

[0044] It can be understood that the driving information is used to indicate whether the driver is driving fatigued and the level of fatigue driving. The driver's driving information can be obtained by the vehicle's built-in fatigue driving warning system, or by an external device.

[0045] For example, a camera may be used to capture the driver's facial information, and the driver's driving status may be analyzed from the facial information. The specific implementation steps belong to the prior art and will not be described in detail.

[0046] S200, obtaining a destination according to the driving information of the driver.

[0047] It is understandable that according to the law, the driver should stop and rest as soon as possible when driving fatigued, so the destination should also change when the driving information indicates a different driving state. The destination can be changed to the nearest parking spot when the driver's driving state is frequent driving, or the driver can change it to other parking spots within a certain range.

[0048] Such a setting can automatically change the destination when the driver is in different driving states, thereby improving the driver's driving experience.

[0049] In a possible implementation, in step S200, obtaining a destination according to the driving information of the driver includes:

[0050] S210, when the driving information of the driver indicates that the driver is driving normally, the destination is obtained as the end point preset by the driver.

[0051] It is understandable that when the driver is driving normally, the destination set by the driver will not be automatically changed, and if no destination is preset, the method and system will not be activated.

[0052] Such a setting can reasonably and fully utilize the vehicle's intelligent driving function when the driver is driving normally, reducing the driver's driving fatigue.

[0053] S220, when the driving information of the driver indicates that the driver is driving fatigued, the destination is obtained as the nearest available parking spot.

[0054] It is understandable that when the driver is driving fatigued, the destination is automatically changed to the nearest available parking spot, or the user can select other parking spots. The nearest available parking spot can be obtained through the in-vehicle navigation software.

[0055] This setting can automatically determine the nearest available parking spot without any additional operations when the driver is driving fatigued, reducing the risk of driving fatigued.

[0056] S300, obtaining an initial value of the remaining driving time according to the driving information of the driver, and timing to obtain the remaining driving time. The remaining driving time refers to the remaining time that the driver can drive safely.

[0057] It can be understood that the fundamental difference between different driving states is that the driver's remaining driving time is different. According to the different driving states indicated by the driving information, different initial values ​​of the remaining driving time can be set, and then timing is performed (the remaining driving time is not counted during intelligent driving), so that the corresponding remaining driving time can be obtained at different times.

[0058] Such an arrangement can determine the remaining driving time of the driver at each moment, which is beneficial for subsequent steps that require the remaining driving time.

[0059] In a possible implementation, in step S300, obtaining an initial value of the remaining driving time according to the driving information of the driver includes:

[0060] S310, when the driving information of the driver indicates that the driver is driving normally, the driving time of the driver is obtained, and an initial value of the remaining driving time is obtained according to the driving time. The initial value of the remaining driving time is the maximum driving time minus the driving time, the driving time refers to the length of time the driver drives continuously, and the maximum driving time refers to the longest driving time prescribed by law.

[0061] It can be understood that the driving time refers to the time the driver has been driving continuously. When the driver is in a normal driving state, the driving time of the driver can be obtained through the driving recorder (intelligent driving time is not included in the driving time). The "Road Traffic Safety Law Implementation Regulations" stipulates that the driver shall not drive continuously for more than 4 hours, so the remaining driving time can be 4 hours minus the driving time.

[0062] Such an arrangement improves the accuracy of the initial value of the remaining driving time obtained in a normal driving state.

[0063] S320, when the driving information of the driver indicates that the driver is driving fatigued, the degree of driving fatigue of the driver is obtained, and an initial value of the remaining driving time is determined according to the degree of driving fatigue.

[0064] It can be understood that fatigue driving has different levels of fatigue, and the fatigue driving state can be graded, and different initial values ​​of the remaining driving time can be set for different levels of fatigue. The method for obtaining the driver's fatigue driving degree can adopt various methods that can obtain the driver's fatigue driving degree.

[0065] Exemplarily, the degree of fatigue driving can be divided into mild fatigue driving state, moderate fatigue driving state and severe fatigue driving state. The above states are used to distinguish different fatigue driving levels. When the driver's blinking times are within a first threshold, the fatigue driving degree can be set to mild fatigue driving state; when the driver's blinking times are within a second threshold, the fatigue driving degree can be set to moderate fatigue driving state; when the driver nods sleepily, the fatigue driving degree can be set to severe fatigue driving state. Different users can set different standards, and different initial values ​​of remaining driving time can be set for different fatigue driving levels.

[0066] Optionally, the initial value of the remaining driving time obtained subsequently overwrites the current remaining driving time. When possible, the system obtains an initial value of the remaining driving time at the beginning. As time goes by, the driver's driving fatigue level increases by one level, but there is already a remaining driving time that is counting down. In this case, the remaining driving time that is counting down is updated to the initial value of the remaining driving time corresponding to the fatigue level. For example, if the remaining driving time is C1 time at this time, and the driver changes to a severely fatigued driving state at the same time, the remaining driving time is updated from C1 time to the initial value of the remaining driving time corresponding to the severely fatigued driving state.

[0067] Such an arrangement improves the accuracy of the initial value of the remaining driving time obtained under fatigue driving conditions.

[0068] S400, obtaining road condition information of the vehicle according to the destination, wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination.

[0069] It is understandable that after the destination is determined, the navigation system can automatically recommend a driving route, or the driver can independently select a driving route. After the driving route is determined, the vehicle distribution of the driving route can be obtained from the big data of the navigation system, or the government can collect statistics on the vehicle distribution in the road monitoring and send the vehicle distribution to the vehicle. However, the accuracy of the vehicle distribution obtained at this time is not high enough and needs to be corrected in subsequent steps.

[0070] This setting can obtain high-precision road condition information.

[0071] In a possible implementation, in step S400, obtaining the road condition information of the vehicle according to the destination includes:

[0072] S410, obtaining traffic flow information on the road from the vehicle to the destination, wherein the traffic flow information is used to reflect the traffic flow of each traffic node on the road from the vehicle to the destination.

[0073] It can be understood that the traffic flow information can be the traffic flow of each traffic node on the driving road obtained from the big data of the navigation system, or the traffic flow of each traffic node obtained by government statistics on road monitoring.

[0074] With such settings, the traffic flow at each traffic node on the travel road is obtained.

[0075] S420, obtaining estimated road condition information according to the vehicle flow information, wherein the estimated road condition information is used to reflect the estimated vehicle distribution on the road from the vehicle to the destination.

[0076] It can be understood that obtaining the traffic flow at each traffic node means obtaining the discrete road vehicle distribution. Next, the continuous estimated vehicle distribution on the road can be obtained through a fitting algorithm (such as Fourier series fitting algorithm, high-order polynomial fitting algorithm, etc.). The continuous estimated vehicle distribution is the estimated road condition information, which is represented by a two-dimensional continuous curve of vehicle density-vehicle position.

[0077] With such a setting, the estimated vehicle distribution on the driving road can be obtained.

[0078] S430, obtaining surrounding road condition information of the vehicle, wherein the surrounding road condition information is used to reflect the distribution of vehicles on the road within the perceptible range of the vehicle.

[0079] It is understood that intelligent driving vehicles are equipped with various sensors or radars, which can be used to obtain the distribution of vehicles on the roads around the vehicle. The surrounding road condition information is represented by a two-dimensional continuous curve of vehicle density-vehicle position. The surrounding road condition information can be information about the distribution of vehicles on the roads around the vehicle.

[0080] With this configuration, the actual vehicle distribution within the vehicle's perceptible range is obtained, which is convenient for the subsequent step of estimating road condition information.

[0081] S440, the estimated road condition information is corrected according to the surrounding road condition information to obtain the corrected estimated road condition information. The correction is performed in an iterative manner, the corrected estimated road condition information is constantly corrected and changed, and the corrected estimated road condition information does not include the estimated vehicle distribution of the road section within the vehicle's perceptible range.

[0082] It can be understood that the method of obtaining high-precision road condition information is to correct the estimated road condition information based on the surrounding road condition information obtained by the vehicle, so that higher-precision estimated road condition information can be obtained, and as the vehicle moves, the accuracy of the estimated road condition information of the remaining road sections will become higher and higher. The correction process can be to replace the data of the corresponding range in the estimated road condition information with the surrounding road condition information detected by the vehicle, and according to the difference between the two data, the estimated road condition information of the remaining range in the estimated road condition information except the vehicle detection range is proportionally distributed to balance the data difference and achieve the correction effect.

[0083] Such a setting can effectively improve the accuracy of estimated road condition information.

[0084] In a possible implementation, in step S440, the estimated road condition information is corrected according to the surrounding road condition information to obtain the corrected estimated road condition information, including:

[0085] S441, obtaining the actual surrounding traffic flow in the surrounding road condition information, wherein the actual surrounding traffic flow refers to the actual traffic flow within the perceptible range of the vehicle.

[0086] It can be understood that traffic flow refers to the number of vehicles passing through an area per unit time. For a moving vehicle, a straight line that is relatively stationary to the ground can be set in front of the car in the direction of travel. Among the surrounding road conditions perceived by the vehicle, the number of vehicles passing this line per unit time is counted, which is the actual surrounding traffic flow.

[0087] S442, obtaining the estimated surrounding traffic volume in the estimated road condition information, wherein the estimated surrounding traffic volume refers to the estimated traffic volume within the corresponding range of the actual surrounding traffic volume.

[0088] It can be understood that the estimated traffic information can be divided into two parts, one part is the estimated traffic information of the surrounding sections (that is, the estimated surrounding traffic flow), and the other part is the estimated traffic information excluding the surrounding sections. The estimated surrounding traffic flow corresponds to the actual surrounding traffic flow, and both are the traffic flow in the vehicle detectable area. The difference is that one is calculated and derived, and the other is actually collected by the sensor. Therefore, while obtaining the actual surrounding traffic flow, the estimated surrounding traffic flow of the corresponding range can be obtained in the estimated road condition information.

[0089] Such a setting can improve the correspondence between the estimated surrounding traffic flow and the actual surrounding traffic flow, and improve the accuracy of the correction process.

[0090] S443, calculating the difference between the actual surrounding traffic flow and the estimated surrounding traffic flow to obtain a traffic flow difference, and obtaining a corrected estimated road condition information according to the traffic flow difference.

[0091] It can be understood that now that the actual surrounding traffic volume and the estimated surrounding traffic volume are known, the essence of the correction process is to replace the estimated road condition information of the surrounding road sections with the actual surrounding traffic volume actually collected by the vehicle, and to correct the estimated road condition information of the road sections that the vehicle cannot detect. The total number of vehicles on the road where the vehicle is traveling is known (the total number of vehicles on the road = the number of vehicles entering each entrance of the road - the number of vehicles leaving each exit of the road). Therefore, the difference in traffic volume around the vehicle means that there is a negative difference in traffic volume on the remaining sections of the road.

[0092] Exemplarily, if the traffic flow difference is +10 vehicles / second (meaning that the actual surrounding traffic flow is 10 vehicles / second more than the estimated surrounding traffic flow), the total traffic flow of the remaining sections of the driving section will be reduced by 10 vehicles / second. The reduced total traffic flow (10 vehicles / second) can be evenly divided to the remaining sections of the driving section, or the total traffic flow (10 vehicles / second) can be distributed in proportion to the estimated traffic flow of the remaining sections. For example, if the estimated traffic flow of the first section is twice that of the second section, the total traffic flow distributed to the first section is also twice that of the second section.

[0093] Such an arrangement can effectively improve the accuracy and precision of the road condition information of the remaining sections of the driving road except the surrounding sections.

[0094] S450, obtaining road condition information according to the surrounding road condition information and the corrected estimated road condition information, wherein the road condition information is the surrounding road condition information plus the corrected estimated road condition information.

[0095] It can be understood that the revised estimated road condition information can represent the estimated vehicle distribution of the remaining sections of the road except the surrounding sections. The surrounding road condition information and the revised estimated road condition information are two two-dimensional continuous curves of vehicle density (y)-vehicle position (x), and the range of the vehicle position (x) axis of the surrounding road condition information is from the vehicle position to the vehicle's perceptible range, while the vehicle position (x) axis of the revised estimated road condition information is from the vehicle's perceptible range to the end of the road. The x axes of the two two-dimensional continuous curves are non-overlapping and complementary, so the road condition information is equal to the revised estimated road condition information plus the actual surrounding road condition information detected by the vehicle. For example, when there is a revised estimated road condition information (such as a revised estimated traffic flow value) and multiple surrounding road condition information (actual surrounding traffic flow values), the estimated road condition information and the surrounding road condition information at the same timestamp can be added according to the timestamp to obtain the road condition information. The road condition information is also a two-dimensional continuous curve of vehicle density (y)-vehicle position (x), and its vehicle position (x) axis is from the vehicle position to the end of the road.

[0096] This arrangement improves the accuracy of the road condition information, and as the vehicle moves forward, the accuracy of the road condition information of the remaining road sections will become higher and higher.

[0097] S500: Obtain a driving allocation plan according to the road condition information and the remaining driving time, wherein the driving allocation plan is used to reflect the allocation of intelligent driving and manual driving during the driving process.

[0098] It is understandable that the remaining driving time can reflect the amount of manual driving, and the road condition information can reflect which road sections meet the safety requirements of intelligent driving. Therefore, by analyzing the road condition information and the remaining driving time, the distribution of intelligent driving and manual driving during the driving process can be obtained. Because the road condition information and the remaining driving time may be updated, the driving distribution plan will also be updated over time, and the final driving distribution plan shall prevail.

[0099] Such a setting can reasonably and fully utilize the vehicle's intelligent driving function and reduce the safety risks of fatigue driving.

[0100] In a possible implementation, in step S500, a driving allocation plan is obtained according to the road condition information and the remaining driving time, including:

[0101] S510, obtaining the traffic volume of each road section in the road condition information, and obtaining the first part of the road sections whose traffic volume exceeds the first traffic volume threshold value among the road sections. The first traffic volume threshold value is used to reflect the traffic volume threshold value at which the intelligent driving system of the vehicle can operate safely and autonomously, and the first part of the road sections refers to the collection of all road sections where the intelligent driving system of the vehicle cannot operate safely and autonomously due to excessive traffic volume.

[0102] It can be understood that the road sections that do not meet the intelligent driving safety requirements are first found. The first traffic flow threshold is determined according to the intelligent driving performance of the vehicle and can be obtained from the vehicle specification. After the first traffic flow threshold is obtained, it is compared with the traffic flow of each section in the road condition information to find the first section that is greater than the first traffic flow threshold. The first section refers to the section that does not meet the intelligent driving safety requirements of the vehicle. The first section can be a plurality of discrete separate sections.

[0103] With this setting, sections of the road that meet the intelligent driving safety requirements and sections that do not meet the intelligent driving safety requirements are found.

[0104] S520, obtaining the time consumption of the first section and the traffic flow information of the first section, wherein the time consumption of the first section refers to the time consumed by the vehicle to pass through the first section, and the traffic flow information of the first section refers to the information of the traffic flow of each section of the first section.

[0105] It is understandable that the time consumption of the first section can be automatically obtained through the navigation system, and various methods of obtaining the time through the navigation system in the relevant technology can be adopted. The traffic flow information of the first section can be directly obtained from the road condition information.

[0106] S530: If the time taken to drive the first section is less than or equal to the remaining driving time, the driving allocation scheme is that the first section is a manual driving section, and the remaining sections except the first section are intelligent driving sections. The manual driving section refers to a driving section dominated by the driver's operation, and the intelligent driving section refers to a driving section dominated by the vehicle's intelligent driving system.

[0107] It can be understood that the time spent on the first part of the road section is less than or equal to the remaining driving time, which means that the first part of the road section can be left to manual driving throughout the entire process. The sections other than the first part of the road section are sections that meet the requirements of intelligent driving and are set as intelligent driving sections.

[0108] With this arrangement, the situations where the time consumed by the first section of the road is less than or equal to the remaining driving time are listed, thereby improving the practicality of the method.

[0109] S540: If the time consumed by the first section is greater than the remaining driving time, a second traffic flow threshold is obtained according to the ratio of the time consumed by the first section to the remaining driving time and the traffic flow information of the first section.

[0110] It can be understood that the time spent on the first section is greater than the remaining driving time, which means that the first section cannot be driven by the driver throughout the entire process. The first section should be subdivided into a section with the most complex road conditions and given to the driver to drive. The method for determining the most complex section is to first obtain the second traffic flow threshold. The ratio of the time spent on the first section to the remaining driving time can be analyzed to determine the proportion of the manually driven section in the first section, and the analysis of the traffic flow information of the first section can obtain the complexity of each road condition in the first section, thereby obtaining the second traffic flow threshold.

[0111] With this setting, it can be ensured to the greatest extent that the sections with the most complicated road conditions are manually driven by the driver, while the rest of the sections are handed over to intelligent driving. This can minimize the safety risks of fatigue driving and improve the utilization rate of intelligent driving.

[0112] In a possible implementation, in step S540, a second traffic flow threshold is obtained according to the ratio of the time consumed in the first section to the remaining driving time and the traffic flow information of the first section, including:

[0113] S541, obtaining a first ratio according to the time consumed on the first section and the remaining driving time, wherein the first ratio refers to the value of the time consumed on the first section divided by the remaining driving time, and the first ratio is greater than zero.

[0114] It can be understood that the first ratio=time spent on the first part of the road segment / remaining driving time, and the first ratio can reflect the proportion of the manually driven road segment to the first part of the road segment.

[0115] S542: Obtain a first average traffic flow of the first section according to the traffic flow information of the first section, wherein the first average traffic flow refers to the average value of the traffic flow of each section of the first section.

[0116] It can be understood that the traffic flow of all sections in the traffic flow information of the first section is averaged to obtain the first average traffic flow, and the first average traffic flow can reflect the average level of traffic flow of the first section.

[0117] S543: Obtain a second vehicle flow threshold value according to the first ratio and the first average vehicle flow.

[0118] It can be understood that the first ratio reflects the proportion of manually driven sections in the first part of the sections, and the first average traffic flow reflects the average traffic flow level of the first part of the sections. It can be seen that the second traffic flow threshold = the first ratio × the first average traffic flow. A part of the section can be obtained from the second traffic flow threshold. This part of the section is the most complex section in the first part of the sections that needs to be driven by a driver.

[0119] With such a setting, the second vehicle flow threshold can be clearly obtained.

[0120] S550: When a second section of the road where the traffic volume exceeds the second traffic volume threshold value is obtained, a driving allocation scheme is determined that the second section is a manual driving section, and the remaining sections of the first section except the second section are manual and intelligent driving sections. The second section is a subsection of the first section, and the manual and intelligent driving section refers to a section where the driver and the vehicle's intelligent driving system respectively control a part of the driving operation.

[0121] It can be understood that the section with traffic flow greater than the second traffic flow threshold is the second section, and the second section is the part with the most complicated road conditions in the first section, so the second section is a manually driven section; in the remaining sections of the first section except the second section, it is known from the remaining driving time that this section is not enough for the driver to use manual driving, but this section does not meet the safety requirements of intelligent driving, so this section adopts a manual plus intelligent driving mode, which refers to a mode in which the driver and the vehicle's intelligent driving system respectively dominate a part of the driving operation; among all sections except the first section, the remaining sections are sections that meet the requirements of intelligent driving and are set as intelligent driving sections.

[0122] For example, the manual plus intelligent driving mode can be that the driver is responsible for acceleration and deceleration operations, and the vehicle intelligent driving system is responsible for steering wheel operations, or the driver is responsible for steering wheel operations and the vehicle intelligent driving system is responsible for acceleration and deceleration operations, or the vehicle intelligent driving system is responsible for steering wheel operations and acceleration and deceleration operations, and the driver is responsible for taking over steering wheel operations and acceleration and deceleration operations at any time. The driver's operation can be detected. In the manual plus intelligent driving mode, the driver's hands need to be on the steering wheel and the feet need to be on the brake. When the driver does not perform an operation, the intelligent driving system takes over the operation. When the driver performs an operation, the intelligent driving system stops taking over.

[0123] Such a setting fully considers various situations and can effectively improve the practicality and correctness of the obtained driving allocation plan.

[0124] Optionally, in step S550, the method further includes:

[0125] S551: When the distance between two adjacent separated sections in the first section is less than a first distance threshold, the section between the two adjacent separated sections in the first section is divided into the first section, wherein the first distance threshold is used to prevent the first section or the second section from being too dispersed.

[0126] It can be understood that the first distance threshold is used to prevent the first part of the road sections from being too dispersed, resulting in too frequent prompt information. Therefore, when the distance between two adjacent separated road sections is set to be less than the first distance threshold, the road section between the two is also divided into the corresponding road section.

[0127] Such a setting can effectively improve the driver's driving experience.

[0128] S552: When the distance between two adjacent separated road sections in the second partial road section is less than the first distance threshold, the road section between the two adjacent separated road sections in the second partial road section is divided into the second partial road section.

[0129] It can be understood that the first distance threshold is used to prevent the second part of the road sections from being too dispersed, resulting in too frequent prompt information. Therefore, when the distance between two adjacent separated road sections is set to be less than the first distance threshold, the road section between the two is also divided into the corresponding road section.

[0130] S600: Obtain prompt information according to the driving allocation plan, wherein the prompt information is used to prompt the driver to drive or pay attention to the road conditions and take over the driving at any time.

[0131] It is understandable that after obtaining the driving allocation plan, the plan needs to be prompted to the driver, and the prompt information includes driving tips, paying attention to road conditions and taking over driving tips at any time.

[0132] Exemplarily, when the vehicle is about to drive on a manual driving section, an AI voice prompt can be generated to remind the driver to drive; when the vehicle is about to drive on an intelligent driving section, an AI voice prompt can be generated to indicate that the intelligent driving mode is about to be turned on, and so on, but not limited to this.

[0133] Such a configuration can prompt the driver of the driving allocation plan.

[0134] In a possible implementation, in step S600, obtaining prompt information according to the driving allocation scheme includes:

[0135] S610: When the vehicle is located in the intelligent driving section in the driving allocation plan, the intelligent driving mode is turned on and a prompt message is obtained as the first message, wherein the first message is to prompt the driver to pay attention to the road conditions and take over the driving at any time.

[0136] It can be understood that when the vehicle is located in the smart driving section, the smart driving mode is automatically turned on and prompts are generated to pay attention to the road conditions and take over driving at any time. When the driver stops driving, the remaining driving time stops counting, and the user can cancel the smart driving mode on his own during this stage, at which time the remaining driving time continues to count.

[0137] Exemplarily, the first information can be an AI voice prompting the driver to pay attention to the road conditions and take over driving at any time, or it can be seat vibration plus a pop-up window on the display screen to prompt the driver to pay attention to the road conditions and take over driving at any time, etc., but not limited to this.

[0138] Such a setting can improve the accuracy of the remaining driving time.

[0139] S620: When the distance between the vehicle and the nearest artificial and intelligent driving section in the driving allocation plan reaches a second distance threshold, a prompt message is obtained to prompt the driver to prepare for driving. The second distance threshold is used to reflect that the vehicle is about to change the driving mode.

[0140] It can be understood that when the vehicle is about to enter a manual and intelligent driving section, a driving prompt is generated, and the second distance threshold is used to prompt the driver to prepare for driving in advance, and the intelligent driving mode is not turned off at this time.

[0141] Exemplarily, the prompt information can be an AI voice prompting the driver to prepare for driving, or it can be a seat vibration plus a display pop-up window prompting the driver to prepare for driving, etc., but not limited to this.

[0142] Such a setting can improve the driver's driving experience.

[0143] S630: When the distance between the vehicle and the nearest manual driving section in the driving allocation plan is a second distance threshold, a prompt message is obtained to prompt the driver to prepare for driving, and the intelligent driving mode is turned off when the vehicle is located in the manual driving section in the driving allocation plan.

[0144] It can be understood that when the vehicle is about to enter the manual driving section, a driving prompt is generated. The second distance threshold at this time is used to prompt the driver to make preparations before driving. After the vehicle enters the manual driving section, the intelligent driving is automatically turned off.

[0145] Exemplarily, the prompt information can be an AI voice prompting the driver to prepare for driving, or it can be a seat vibration plus a display pop-up window prompting the driver to prepare for driving, etc., but not limited to this.

[0146] Such a setting can improve the driver's driving experience.

[0147] exist Figure 2 A summary flow chart of the intelligent driving assistance method for fatigue driving of the above-mentioned embodiment is listed in the figure.

[0148] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0149] Corresponding to the intelligent driving assistance method for fatigue driving described in the above embodiment, the embodiment of the present application also provides an intelligent driving assistance system for fatigue driving, and the various modules of the system can implement the various steps of the intelligent driving assistance method for fatigue driving. Figure 3 A structural block diagram of an intelligent driving assistance system for fatigue driving provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0150] Reference Figure 3 The system comprises:

[0151] A fatigue driving warning unit, used to obtain the driver's driving information; wherein the driving information is used to reflect the driver's driving status;

[0152] A navigation unit, used for obtaining a destination according to the driving information of the driver;

[0153] A timing unit, used to obtain an initial value of the remaining driving time according to the driving information of the driver, and to perform timing to obtain the remaining driving time; wherein the remaining driving time refers to the remaining time that the driver can drive safely;

[0154] A road condition information collection unit, used to obtain road condition information of the vehicle according to the destination; wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination;

[0155] An analysis unit, configured to obtain a driving allocation scheme according to the road condition information and the remaining driving time; wherein the driving allocation scheme is used to reflect the allocation of intelligent driving and manual driving during the driving process;

[0156] A prompt information generating unit is used to obtain prompt information according to the driving allocation plan; wherein the prompt information is used to prompt the driver to drive or pay attention to the road conditions and take over the driving at any time.

[0157] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0158] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units is used as an example for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units as needed, that is, the internal structure of the system can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0159] The present application also provides an intelligent driving assistance device for fatigue driving. Figure 4 This is a schematic diagram of the structure of an intelligent driving assistance device for fatigue driving provided in an embodiment of the present application. Figure 4 As shown, the control device 3 of the intelligent driving assistance device for fatigue driving in this embodiment includes: at least one processor 30 ( Figure 4 Only one is shown), at least one memory 31 ( Figure 4 Only one is shown in the figure) and a computer program 32 stored in the at least one memory 31 and executable on the at least one processor 30, when the processor 30 executes the computer program 32, the intelligent driving assistance device 3 for fatigue driving implements the steps in any of the above-mentioned intelligent driving assistance method embodiments for fatigue driving, or the control device 3 of the intelligent driving assistance device for fatigue driving implements the functions of each unit in the above-mentioned device embodiments.

[0160] Exemplarily, the computer program 32 may be divided into one or more units, which are stored in the memory 31 and executed by the processor 30 to complete the present application. The one or more units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 32 in the intelligent driving assistance device 3 for fatigue driving.

[0161] The control device 3 of the intelligent driving assistance device for fatigue driving can be a computing device such as a single chip microcomputer, a microprocessor, a vehicle-mounted computer, etc. The control device of the intelligent driving assistance device for fatigue driving may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art can understand that Figure 4 It is only an example of the control device 3 of the intelligent driving assistance equipment for fatigue driving, and does not constitute a limitation on the control device 3 of the intelligent driving assistance equipment for fatigue driving. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0162] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0163] In some embodiments, the memory 31 may be an internal storage unit of the control device 3 of the intelligent driving assistance device for fatigue driving, such as a hard disk or memory of the control device 3 of the intelligent driving assistance device for fatigue driving. In other embodiments, the memory 31 may also be an external storage device of the control device 3 of the intelligent driving assistance device for fatigue driving, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the control device 3 of the intelligent driving assistance device for fatigue driving. Further, the memory 31 may also include both an internal storage unit and an external storage device of the control device 3 of the intelligent driving assistance device for fatigue driving. The memory 31 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0164] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0165] An embodiment of the present application provides a computer program product. When the computer program product runs on an intelligent driving assistance device for fatigue driving, the intelligent driving assistance device for fatigue driving implements the steps in any of the above-mentioned method embodiments.

[0166] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the intelligent driving assistance device for fatigue driving, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0167] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0168] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0169] In the embodiments provided in the present application, it should be understood that the disclosed intelligent driving assistance method for fatigue driving, the intelligent driving assistance equipment for fatigue driving, and the intelligent driving assistance device for fatigue driving can be implemented in other ways. For example, the embodiments of the intelligent driving assistance equipment for fatigue driving and the intelligent driving assistance device for fatigue driving described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0170] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An intelligent driving assistance method for fatigue driving, characterized in that: The method is applied to a vehicle having an intelligent driving function, and the method comprises: Acquiring driving information of the driver; wherein the driving information is used to reflect the driving status of the driver; Obtaining a destination according to the driving information of the driver; Obtaining an initial value of the remaining driving time according to the driving information of the driver, and timing to obtain the remaining driving time; wherein the remaining driving time refers to the remaining time that the driver can drive safely; Obtaining road condition information of the vehicle according to the destination; wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination; A driving allocation scheme is obtained according to the road condition information and the remaining driving time; wherein the driving allocation scheme is used to reflect the allocation of intelligent driving and manual driving during the driving process; Obtaining prompt information according to the driving allocation plan; wherein the prompt information is used to prompt the driver to drive or pay attention to road conditions and take over driving at any time; The obtaining of the road condition information of the vehicle according to the destination includes: Acquire traffic flow information on the road from the vehicle to the destination; wherein the traffic flow information is used to reflect the traffic flow at each traffic node on the road from the vehicle to the destination; Obtaining estimated road condition information according to the vehicle flow information; wherein the estimated road condition information is used to reflect the estimated vehicle distribution on the road from the vehicle to the destination; Acquire the surrounding road condition information of the vehicle; wherein the surrounding road condition information is used to reflect the distribution of vehicles on the road within the perceptible range of the vehicle; The estimated road condition information is modified according to the surrounding road condition information to obtain the modified estimated road condition information; wherein the modification is performed in an iterative manner, the modified estimated road condition information is continuously modified and changed, and the modified estimated road condition information does not include the estimated vehicle distribution of the road section within the vehicle's perceptible range; The road condition information is obtained according to the surrounding road condition information and the corrected estimated road condition information; wherein the road condition information is the surrounding road condition information plus the corrected estimated road condition information.

2. The intelligent driving assistance method for fatigue driving according to claim 1, characterized in that: The obtaining of a destination according to the driving information of the driver includes: When the driving information of the driver indicates that the driver is driving normally, the destination is obtained as a destination preset by the driver; When the driving information of the driver indicates that the driver is driving fatigued, the destination is obtained as the nearest available parking spot.

3. The intelligent driving assistance method for fatigue driving according to claim 1, characterized in that: The obtaining an initial value of the remaining driving time according to the driving information of the driver includes: When the driving information of the driver indicates that the driver is driving normally, the driving time of the driver is obtained, and the initial value of the remaining driving time is obtained according to the driving time; wherein the initial value of the remaining driving time is the maximum driving time minus the driving time, the driving time refers to the length of time the driver drives continuously, and the maximum driving time refers to the maximum driving time prescribed by law; When the driving information of the driver indicates that the driver is driving fatigued, the driver's driving fatigue degree is obtained, and the initial value of the remaining driving time is determined according to the driving fatigue degree.

4. The intelligent driving assistance method for fatigue driving according to claim 1, characterized in that: The step of correcting the estimated road condition information according to the surrounding road condition information to obtain the corrected estimated road condition information includes: Acquire the actual surrounding traffic flow in the surrounding road condition information; wherein the actual surrounding traffic flow refers to the actual traffic flow within the perceptible range of the vehicle; Obtaining the estimated surrounding traffic flow in the estimated road condition information; wherein the estimated surrounding traffic flow refers to the estimated traffic flow within the corresponding range of the actual surrounding traffic flow; The difference between the actual surrounding traffic flow and the estimated surrounding traffic flow is calculated to obtain a traffic flow difference, and the corrected estimated road condition information is obtained according to the traffic flow difference.

5. The intelligent driving assistance method for fatigue driving according to claim 1, characterized in that: The step of obtaining a driving allocation plan according to the road condition information and the remaining driving time includes: Obtaining the traffic volume of each road section in the road condition information, and obtaining a first part of the road sections whose traffic volume exceeds a first traffic volume threshold value among the road sections; wherein the first traffic volume threshold value is used to reflect the traffic volume threshold value at which the intelligent driving system of the vehicle can operate safely and autonomously, and the first part of the road sections refers to the set of all road sections where the intelligent driving system of the vehicle cannot operate safely and autonomously due to excessive traffic volume; Obtaining the time consumption of the first section and the traffic flow information of the first section; wherein the time consumption of the first section refers to the time consumed by the vehicle to pass through the first section, and the traffic flow information of the first section refers to the information of the traffic flow of each section of the first section; If the time taken to drive the first section of the road is less than or equal to the remaining driving time, the driving allocation scheme is that the first section of the road is a manual driving section, and the remaining sections except the first section of the road are intelligent driving sections; wherein the manual driving section refers to a driving section dominated by the driver's operation, and the intelligent driving section refers to a driving section dominated by the vehicle's intelligent driving system; If the time consumed by the first section is greater than the remaining driving time, a second traffic flow threshold is obtained according to the ratio of the time consumed by the first section to the remaining driving time and the traffic flow information of the first section; When a second part of the road sections whose traffic volume exceeds a second traffic volume threshold value is obtained from the various road sections, the driving allocation plan is determined as follows: the second part of the road sections is a manual driving section, and the remaining sections of the first part of the road sections except the second part of the road sections are manual plus intelligent driving sections; wherein the second part of the road sections is a sub-section of the first part of the road sections, and the manual plus intelligent driving section refers to a section where the driver and the vehicle's intelligent driving system respectively dominate a part of the driving operation.

6. The intelligent driving assistance method for fatigue driving according to claim 5, characterized in that: The obtaining of the second traffic flow threshold according to the ratio of the time consumed in the first section to the remaining driving time and the traffic flow information of the first section includes: Obtain a first ratio according to the time consumed by the first part of the road segment and the remaining driving time; wherein the first ratio refers to the value of the time consumed by the first part of the road segment divided by the remaining driving time, and the first ratio is greater than zero; Obtaining a first average traffic flow of the first section of the road according to the traffic flow information of the first section of the road; wherein the first average traffic flow refers to an average value of the traffic flow of each section of the first section of the road; The second vehicle flow threshold is obtained according to the first ratio and the first average vehicle flow.

7. The intelligent driving assistance method for fatigue driving according to claim 5, characterized in that: The method further comprises: When the distance between two adjacent separated road sections in the first partial road section is less than a first distance threshold, the road section between the two adjacent separated road sections in the first partial road section is divided into the first partial road section; wherein the first distance threshold is used to prevent the first partial road section or the second partial road section from being too dispersed; When the distance between two adjacent separated sections in the second partial section is less than a first distance threshold, the section between the two adjacent separated sections in the second partial section is divided into the second partial section.

8. The intelligent driving assistance method for fatigue driving as claimed in claim 5, characterized in that: The obtaining prompt information according to the driving allocation scheme includes: When the vehicle is located in the smart driving section in the driving allocation scheme, the smart driving mode is turned on and the prompt information is obtained as the first information; wherein the first information is to prompt the driver to pay attention to the road conditions and be ready to take over the driving at any time; When the distance between the vehicle and the nearest artificial plus intelligent driving section in the driving allocation scheme is a second distance threshold, the prompt information is obtained to prompt the driver to prepare for driving; wherein the second distance threshold is used to reflect that the vehicle is about to change the driving mode; When the distance between the vehicle and the nearest manually driven section in the driving allocation plan is within a second distance threshold, the prompt information is obtained to prompt the driver to prepare for driving, and the intelligent driving mode is turned off when the vehicle is located in the manually driven section in the driving allocation plan.

9. An intelligent driving assistance system for fatigue driving, characterized in that: The system is applied to a vehicle with an intelligent driving function, and the system includes: A fatigue driving warning unit, used to obtain the driver's driving information; wherein the driving information is used to reflect the driver's driving status; A navigation unit, used for obtaining a destination according to the driving information of the driver; A timing unit, used to obtain an initial value of the remaining driving time according to the driving information of the driver, and to perform timing to obtain the remaining driving time; wherein the remaining driving time refers to the remaining time that the driver can drive safely; A road condition information collection unit, used to obtain road condition information of the vehicle according to the destination; wherein the road condition information is used to reflect the distribution of vehicles on the road between the vehicle and the destination; An analysis unit, configured to obtain a driving allocation scheme according to the road condition information and the remaining driving time; wherein the driving allocation scheme is used to reflect the allocation of intelligent driving and manual driving during the driving process; A prompt information generating unit, used to obtain prompt information according to the driving allocation scheme; wherein the prompt information is used to prompt the driver to drive or pay attention to the road conditions and take over the driving at any time; Wherein, the road condition information collection unit is also used for: Acquire traffic flow information on the road from the vehicle to the destination; wherein the traffic flow information is used to reflect the traffic flow at each traffic node on the road from the vehicle to the destination; Obtaining estimated road condition information according to the vehicle flow information; wherein the estimated road condition information is used to reflect the estimated vehicle distribution on the road from the vehicle to the destination; Acquire the surrounding road condition information of the vehicle; wherein the surrounding road condition information is used to reflect the distribution of vehicles on the road within the perceptible range of the vehicle; The estimated road condition information is modified according to the surrounding road condition information to obtain the modified estimated road condition information; wherein the modification is performed in an iterative manner, the modified estimated road condition information is continuously modified and changed, and the modified estimated road condition information does not include the estimated vehicle distribution of the road section within the vehicle's perceptible range; The road condition information is obtained according to the surrounding road condition information and the corrected estimated road condition information; wherein the road condition information is the surrounding road condition information plus the corrected estimated road condition information.

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