TWI740450B - Driving assistance method and vehicle - Google Patents

Abstract

The present invention provides a driving assistance method applied to an vehicle. The method includes establishing a database, the database pre-stores a plurality of keywords, the keywords are defined as words related to traffic; obtaining electronic texts of traffic laws and rules; extracting keywords from the electronic texts according to the database; generating a plurality of trigger conditions according to the extracted keywords; and obtaining current driving parameters of the vehicle, and when the driving parameters meet one of the trigger conditions, sending a driving assistance command to the vehicle. The invention also provides a vehicle.

Description

Driving assistance method and vehicle

The present invention relates to the technical field of vehicle driving assistance, in particular to a driving assistance method and a vehicle based on traffic laws.

With the increasing number of vehicles and increasingly busy road traffic, drivers who are unfamiliar with local traffic laws, such as novice drivers or driving vehicles in unfamiliar countries or regions, often drive illegally, resulting in fines and deductions. In severe cases, it may even cause traffic accidents.

In view of the above, it is necessary to provide a driving assistance method and vehicle that can reduce illegal driving.

The first aspect of the present invention provides a driving assistance method, applied to a vehicle, the method includes: establishing a database, the database pre-stored keywords, the keywords are defined as words associated with traffic; obtaining traffic laws Extract the keywords in the electronic text according to the database; generate trigger conditions based on the extracted keywords; and obtain the current driving parameters of the vehicle, when the current driving parameters meet the trigger conditions, Issue an assisted driving command.

Preferably, the step of “extracting the keywords in the electronic text according to the database” includes: matching the electronic text with the pre-stored keywords, and when the electronic text exists and the pre-stored keywords When the keywords match words, the words are stored.

Preferably, the keywords include traffic-related noun words, driving-related operation verb words, or a combination of the two.

Preferably, the step of "acquiring the electronic text of traffic regulations" includes obtaining the location information of the vehicle; and automatically downloading or automatically switching to obtain the electronic text of the traffic regulations according to the location information of the vehicle.

Preferably, the trigger condition includes a preset driving scene and a preset driving operation, the preset driving scene is constructed according to the keywords, the preset driving operation is a driving operation in compliance with traffic laws, and when the vehicle is in The preset driving scene, when the driving of the vehicle does not conform to the preset driving operation, it is determined that the trigger condition is met.

Preferably, the current driving parameters include at least one of vehicle-related parameters, driver-related parameters, passenger-related parameters, and traffic-related parameters.

Preferably, the vehicle-related parameters include at least one of vehicle speed, acceleration, relative position, yaw angle, indicator status, driving direction, mileage, accelerator pedal signal, braking signal, and steering signal.

Preferably, the traffic-related parameters include at least one of road-related parameters, pedestrian-related parameters, signal lamp-related parameters, traffic sign-related parameters, environment-related parameters, and the distance between front and rear, left, and right vehicles.

Preferably, the electronic text of the traffic law can be obtained through optical recognition of the paper file or downloaded from the Internet.

A second aspect of the present invention provides a vehicle, the vehicle including: a processor; and A memory, wherein a plurality of program modules are stored in the memory, and the plurality of program modules are loaded by the processor and execute the above-mentioned driving assistance method.

The above driving assistance method and vehicle can extract keywords in the electronic text of the traffic regulations, generate trigger conditions based on the extracted keywords, and issue driving assistance instructions when the current driving parameters of the vehicle meet the trigger conditions to Reduce illegal driving and improve driving safety.

It is necessary to propose a driving safety reminder method and vehicle, which can calculate the safety distance and provide driving safety reminders according to the real-time operation of the vehicle during driving, so as to effectively improve driving safety during driving.

1: Vehicle

10: processor

100: Driving assistance system

101: Create a module

102: Obtain modules

103: Extraction Module

104: Judgment Module

105: auxiliary module

20: memory

30: High-precision map

40: Sensor

50: camera

60: GPS module

In order to more clearly describe the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are merely It is an embodiment of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without creative work.

Fig. 1 is a schematic structural diagram of a vehicle provided by a preferred embodiment of the present invention.

Fig. 2 is a schematic structural diagram of a driving assistance system provided by a preferred embodiment of the present invention.

Fig. 3 is a flowchart of a driving assistance method provided by a preferred embodiment of the present invention.

FIG. 4 is a schematic diagram of the electronic text of the traffic law in the driving assistance method provided by the preferred embodiment of the present invention.

FIG. 5 is a schematic diagram of keyword extraction of electronic text of traffic laws in the driving assistance method provided by a preferred embodiment of the present invention.

Fig. 6 is a schematic diagram of generating trigger conditions in a driving assistance method provided by a preferred embodiment of the present invention.

The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings.

In order to be able to understand the above objectives, features and advantages of the present invention more clearly, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other if there is no conflict.

In the following description, many specific details are explained in order to fully understand the present invention. The described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention.

Please refer to FIG. 1, which is a schematic structural diagram of a preferred embodiment of a vehicle of the present invention. The vehicle may include computing equipment such as an onboard computer. Those skilled in the art can understand that the schematic diagram is only an example of the vehicle and does not constitute a limitation on the vehicle. It may include more or less components than those shown in the figure, or a combination of certain components, or different components, such as The vehicle may also include power and control devices, transmission systems, and the like. The vehicle 1 includes, but is not limited to, a processor 10, a memory 20, a sensor 40, a camera 50, and a GPS module 60. Wherein, the memory 20 stores a computer program and a high-precision map 30. The computer program can run on the processor 10. In this preferred embodiment, the computer program includes the driving assistance system 100. When the processor 10 executes the driving assistance system 100, the steps in the above driving assistance method embodiment are implemented, for example, steps S20 to S27 shown in FIG. 3. Alternatively, when the processor 10 executes the computer program, the function of each functional module in the embodiment of the driving assistance system 100 is realized, for example, the modules 101-105 in FIG. 2. The high-precision map 30 includes high-precision map data, and the high-precision map data includes lane parameters, signal lamp parameters, sign parameters, and actual street view of the lane. The high-precision map 30 obtains the high-precision positioning of the GPS module 60 and the street view image taken by the camera 50, and compares the lane parameters of the high-precision map data and the actual street view of the lane to accurately locate the vehicle 1 on the high-precision map In the driving lane.

The driving assistance system 100 may be divided into one or more functional modules, and the one or more functional modules are stored in the memory 20 and executed by the processor 10 to complete the present invention . The one or more functional modules may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the driving assistance system 100 in the vehicle 1.

As shown in FIG. 2, the driving assistance system 100 can be divided into the establishment module 101, the acquisition module 102, the extraction module 103, the judgment module 104 and the auxiliary module 105 in FIG. 2. For specific functions of each module, refer to the functions of each module in the driver assistance system embodiment.

The so-called processor 10 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), and dedicated integrated circuits (Application Specific Integrated Circuit, ASIC). , Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor 10 can also be any conventional processor, etc. The processor 10 is the control center of the vehicle 1 and connects various parts of the entire vehicle 1 through various interfaces and lines. .

The memory 20 can be used to store the computer programs and/or functional modules. The processor 10 runs or executes the computer programs and/or functional modules stored in the memory 20, and calls the computer programs and/or functional modules stored in the memory 20. The parameters in the memory 20 realize various functions of the vehicle 1. The memory 20 may mainly include a storage program area and a storage parameter area. The storage program area may store an operating system, an application program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; storage parameters The area can store parameters (such as audio parameters, phone book, etc.) created according to the use of the vehicle 1 and so on. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), and a secure digital (Secure Digital, SD) card, flash memory card (Flash Card), at least one magnetic disk memory device, flash memory device, or other volatile solid-state memory device.

The sensor 40 is used to sense the current driving parameters of the vehicle 1. The current driving parameters include vehicle-related parameters and traffic-related parameters. In this preferred embodiment, the vehicle-related parameters include at least one or more of speed, acceleration, relative position, yaw angle, indicator status, driving direction, mileage, accelerator pedal signal, brake signal, and steering signal. combination. In this preferred embodiment, the sensor 40 may be at least one or a combination of a laser radar, a speed sensor, an acceleration sensor, a deflection angle sensor, and an indicator light sensor. In this preferred embodiment, the acceleration sensor can sense linear velocity changes and angular velocity changes.

In this preferred embodiment, the number of the sensors 40 is multiple, and the multiple sensors 40 are arranged on the four wheels, the front of the vehicle, and the rear of the vehicle 1.

In another preferred embodiment, the sensor 40 may be 8 cameras, 12 ultrasonic radars, and 1 millimeter wave radar.

It can be understood that the sensor 40 is not limited to the aforementioned sensors, and may also include millimeter wave radar, ultrasonic radar, Lidar, infrared radar, wheel speed sensor, and thermal imaging sensor. A combination of one or more of, accelerator and gyroscope.

It can be understood that the vehicle-related parameters can be obtained from other methods other than the sensor 40 in addition to being obtained by the sensor 40, for example, obtained by a driving control computer (not shown) to obtain vehicle speed and accelerator pedal signals , Brake signal, turn signal, direction light signal and other driving information.

In another preferred embodiment, the camera 50 may be arranged outside the vehicle 1. The camera 50 can obtain images outside the vehicle, and through the existing image recognition technology, traffic parameters and vehicle-related parameters can be obtained from the image information, and the GPS module 60 can obtain accurate vehicle positioning information.

The traffic-related parameters include one or more of road-related parameters, pedestrian-related parameters, signal lamp-related parameters, traffic sign-related parameters, environment-related parameters, and the distance between front and rear, left, and right vehicles. Wherein, the road-related parameters include the number of lanes, lane types, lane markings, lane speed limit values, lane one-way driving requirements, lanes with no overtaking sections and intersection lane allocation, etc. However, the present invention is not limited to the above-mentioned traffic parameters. Those skilled in the art can understand that the traffic parameters may also include other traffic parameters such as temporary traffic control.

In a preferred embodiment, the camera 50 is installed in the vehicle 1. The camera 50 can acquire images in the vehicle, and through the image recognition technology, driver-related parameters and passenger-related parameters can be acquired from the image information. The driver-related parameters include driving time, head parameters, hand parameters, and foot parameters. The head parameters include blinking frequency, mouth opening frequency, and the like. The passenger-related parameters include the number of passengers. The driver-related parameters and passenger-related parameters can be used to determine whether there is a driving operation that violates traffic laws, such as fatigue driving and overloading.

In another preferred embodiment, the camera 50 may be set outside the vehicle 1 to obtain images outside the vehicle, and through the existing image recognition technology, the traffic-related parameters can be detected from the image information At least one of road-related parameters, pedestrian-related parameters, signal-related parameters, traffic sign-related parameters, environment-related parameters, and the distance between front and rear, left, and right vehicles. For example, the camera 50 can analyze the images outside the vehicle acquired by the camera 50 through image recognition technology to determine the number of lanes, lane types, lane markings, lane speed limit values, lane one-way driving requirements, and lane conditions. Forbidden to overtake the road section and the distribution of lane dividing lines at intersections, etc. The camera 50 can analyze the images outside the vehicle acquired by the camera 50 through image recognition technology to determine whether there is a pedestrian passing in front of the vehicle 1 or a pedestrian passing through the lane, and can also determine the traffic lights related parameters of the intersection, such as signal lights s color.

The GPS module 60 is used to locate the vehicle 1, combined with a built-in map database of the vehicle, to determine the current position of the vehicle 1. The GPS module 60 is a high-precision GPS module, and the detection accuracy can be Reach the lane where the vehicle 1 is located on the reconnaissance side. The high-precision map 30 is used to obtain the traffic parameters in the high-precision map, including lane parameters, signal lamp parameters, and sign parameters. Combined with GPS high-precision positioning and cameras, it can accurately locate the lane where the vehicle 1 is located. Please refer to Figure 2. A functional module diagram of a preferred embodiment of the driving assistance system 100 of the present invention.

In some embodiments, the driving assistance system 100 runs in the vehicle 1. The driving assistance system 100 may include multiple functional modules composed of code segments. The program code of each program segment in the driving assistance system 100 can be stored in the memory 20 of the vehicle 1 and executed by the at least one processor 10 to realize a driving assistance tool.

In this preferred embodiment, the driving assistance system 100 can be divided into multiple functional modules according to the functions it performs. Referring to FIG. 2, the functional modules may include a creation module 101, an acquisition module 102, an extraction module 103, a judgment module 104, and an auxiliary module 105. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in the memory 20. It can be understood that, in other embodiments, the above-mentioned modules may also be program instructions or firmware solidified in the processor 10.

The establishment module 101 is used to establish a database, the database pre-stores keywords, and the keywords are defined as words associated with traffic.

The acquisition module 102 is used to acquire electronic texts of traffic regulations. The acquisition module 102 is also used to acquire the current driving parameters of the vehicle 1 through the sensor 40, the camera 50, the high-precision map 30, and the GPS module 60.

The extraction module 103 is used to extract keywords in the electronic text according to the database.

The judgment module 104 is used to generate trigger conditions based on the extracted keywords. The judgment module 104 is also used to judge whether the current driving parameter meets the trigger condition.

The auxiliary module 105 is used to issue auxiliary driving instructions to the vehicle 1.

Please refer to FIG. 3, which is a flowchart of the driving assistance method provided by the present invention. According to different needs, the order of the steps in the flowchart can be changed, and some steps can be omitted.

Step S21, the establishment module 101 establishes a database, the database prestores keywords, and the keywords are defined as words associated with traffic.

The database may be established based on the traffic laws of multiple countries or regions, and therefore, may include keywords of different language types, such as English, simplified characters, and traditional characters. In one embodiment, the database can automatically download or automatically switch keywords of different language types in the database according to the location information obtained by the GPS module 60. The keywords include noun words related to traffic, verb words related to driving operations, or a combination of the two. The traffic-related noun words include road-type words and vehicle-type words. The road words include intersection, intersection, lane, Pedestrians, parking areas, sidewalks, etc. Vehicle terms include trucks, cars, and taxis. The verbal words for driving-related operations include acceleration, deceleration, left turn, right turn, lane change, overload, drunk driving, fatigue driving, etc.

In step S22, the obtaining module 102 obtains the electronic text of the traffic law. Please refer to FIG. 4, which shows the electronic text of some traffic laws. The electronic text of the traffic law can be pre-stored in the memory 20. When the vehicle 1 is started, the acquisition module 102 reads the electronic text from the memory 20. It can be understood that the electronic text of the traffic law can also be obtained by the acquisition module 102 from the paper file of the traffic law through OCR technology. In one embodiment, the acquiring module 102 can automatically download and acquire electronic texts of traffic laws corresponding to the location information based on the location information acquired by the GPS module 60.

In step S23, the extraction module 103 extracts keywords in the electronic text according to the database.

In the preferred embodiment, the extraction module 103 matches the electronic text with the pre-stored keywords, and when there are words in the electronic text that are consistent with the pre-stored keywords, it stores the Describe the same words as the pre-stored keywords. For example, please refer to Figure 5 together. The first sentence of the electronic text: "Not paying attention to the comings and goings of pedestrians, or not slowing down before turning", the extracted keywords include traffic-related noun words "pedestrian" And the verbal word "turn" for driving-related operations. The second sentence of the electronic text: "Passing the intersection does not reach the center, occupy the lane to turn left first", the extracted keywords include driving-related verbal words "Jing" and "Da" are related to traffic The combination of the noun words "intersection" and "center" "travel at the intersection" and "reach the center", and the verb "turn left" for driving-related operations.

It is understandable that when there are words inconsistent with the pre-stored keywords in the electronic text, the words that are inconsistent with the pre-stored keywords will be deleted. It is understandable, and it is also possible to use semantic analysis for the inconsistent words to find the close key Words or no action.

In step S24, the judgment module 104 generates a trigger condition according to the extracted keywords.

In this preferred embodiment, the trigger condition includes a preset driving scene and a corresponding preset driving operation, wherein the preset driving scene is constructed according to the keyword, and the preset driving operation is in compliance with traffic laws Driving operation.

In this preferred embodiment, the judgment module 104 uses each sentence in the electronic text as a unit to generate the trigger condition with the keywords contained therein, and each sentence corresponds to a trigger condition. In one embodiment. . For example, please refer to Figure 6 together. The keywords extracted from the first sentence of the electronic text are "pedestrian" and "turn", and the generated first trigger condition includes the preset driving scene being the preset of vehicle 1. There is a pedestrian or vehicle 1 before turning and the corresponding preset driving operation is slowing down. The keywords extracted from the third sentence of the electronic text are "traveling at an intersection", "reaching the center", and "turning left", and the generated second trigger condition includes the behavior that the preset driving scene is vehicle 1 At a fork in the road or when the vehicle 1 arrives at the center, a left turn and the corresponding preset driving operation are to enter the outer lane first.

In another embodiment, the sentence may also be a text that does not start with a digit sequence number or does not end with a period. For example, the beginning and the end of the sentence can be judged according to a preset text length.

In step S25, the acquisition module 102 acquires the current driving parameters of the vehicle 1 through the high-precision map 30, the sensor 40, the camera 50, and the GPS module 60.

The current driving parameters include at least one of vehicle-related parameters, driver-related parameters, passenger-related parameters, and traffic-related parameters. The vehicle-related parameters include at least one of vehicle speed, relative position, shape, yaw angle, indicator status, driving direction, mileage, accelerator pedal signal, braking signal, and steering signal, which are used to indicate the driving state of the vehicle. The driver-related parameters include at least one of driving time, head parameters, hand parameters, and foot parameters, which can be used to indicate the driving state of the driver, for example, whether the driver is driving fatigued. The passenger-related parameters include passenger information and passenger riding behavior, which can be used to indicate the passenger's status, such as whether it is overloaded, whether to use a seat belt, and so on. The traffic-related parameters include at least one of road-related parameters, pedestrian-related parameters, signal-related parameters, traffic sign-related parameters, environment-related parameters, and the distance between front and rear, left and right vehicles, and are used to indicate whether the driving of the vehicle 1 complies with road instructions, Signal light indication, etc.

In step S26, the judgment module 104 judges whether the current driving parameter satisfies the trigger condition.

When the vehicle 1 is in the preset driving scene, and the driving of the vehicle 1 does not conform to the preset driving operation, it is determined that the trigger condition is met; when the vehicle 1 is in the preset driving scene, the driving of the vehicle 1 conforms to the preset driving operation. When driving operation, it is judged that the trigger condition is not met.

In the first preferred embodiment of the present invention, the sensor 40 of the vehicle 1 senses that there is a pedestrian at a preset distance from the vehicle 1, or senses that the vehicle 1 is ready to turn, for example, the turn signal of the vehicle 1 has been Turn on, the driver’s hand parameters indicate that the vehicle is ready to turn, or the front wheels of the vehicle 1 have begun to deflect, that is, the vehicle 1 is in a preset driving scene. At this time, if the sensor 40 further senses that the vehicle 1 has decelerated Slow driving, that is, the driving of the vehicle 1 conforms to the preset driving operation and the traffic laws, and no action is taken. If the sensor 40 senses that the vehicle 1 is not slowing down, that is, the driving of the vehicle 1 does not conform to the expected driving operation. When driving operation, it is judged that the trigger condition is met, and step S27 is entered.

In the second preferred embodiment of the present invention, the determination module 104 can determine the position of the vehicle 1 located by the GPS module 60 and the high-precision map 30 according to the sensing data of the sensor 40 1. At the intersection of driving paths, reach the center and prepare to turn left, that is, the vehicle 1 is in the preset driving scene. At this time, if the sensor 40 further senses that the vehicle 1 has entered the outer lane, that is, the vehicle 1 If the driver complies with the preset driving operation and complies with the traffic laws, no action will be taken.

In another preferred embodiment, the judging module 104 can judge that the vehicle 1 needs to travel at the intersection to reach the center based on the sensor 40 sensing data combined with the position of the vehicle 1 located by the GPS module 60. It is ready to turn left, that is, the vehicle 1 is in a preset driving scene. At this time, if the camera 50 analyzes the captured image data, it further senses that the vehicle 1 has entered the outer lane, that is, the vehicle 1’s If the driver complies with the preset driving operation and complies with the traffic laws, no action will be taken. If the sensor 40 senses that the vehicle 1 does not enter the outer lane, that is, when the driving of the vehicle 1 does not meet the preset driving operation, it is determined that the trigger condition is met, and step S27 is entered.

In the third preferred embodiment of the present invention, the preset driving scene may be that the vehicle is in a driving state, and the judgment module 104 uses the driver-related parameters acquired by the camera 50 to And the relevant parameters of the passengers, it can be judged whether the driving of the vehicle complies with the preset driving operation, and if it complies with the traffic laws, no action will be taken. If the preset driving operation is not met, for example, fatigue driving, overloading, it is determined that the trigger condition is met, and step S27 is entered.

In step S27, the assisting module 105 issues an assisting driving instruction to the vehicle 1, and the driving assist includes at least one of emergency stop, deceleration, turn signal prompt, voice prompt, warning sound, on-vehicle light signal, or screen display prompt. For example, in the first preferred embodiment of the present invention, the auxiliary module 105 issues deceleration instructions and voice reminders to the vehicle 1 to avoid violating traffic laws, or promptly reminding to adjust driving operations when a traffic law is violated.

If the functional modules integrated in the vehicle 1 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiments and methods, and can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the foregoing method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of original program code, object code, executable file, or some intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only) Only Memory), Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunications signal, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or deleted according to the requirements of the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to the legislation and patent practice, the computer-readable medium Does not include electrical carrier signals and telecommunication signals.

The above driving assistance method and vehicle 1 extract keywords in the electronic text of the traffic regulations, generate trigger conditions based on the extracted keywords, and issue driving assistance instructions when the current driving parameters of the vehicle meet the trigger conditions, In order to reduce illegal driving and improve driving safety.

For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be in other specific forms without departing from the spirit or basic characteristics of the present invention. Type to realize the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description, and therefore it is intended to fall within the claims. All changes within the meaning and scope of the equivalent elements of are included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "including" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claims can also be implemented by the same unit or device through software or hardware. Words such as first and second are used to denote names, but do not denote any specific order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be Modifications or equivalent replacements are made without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

A driving assistance method, applied to a vehicle, the method includes: establishing a database, the database pre-stored keywords, the keywords are defined as words associated with traffic; obtaining electronic text of traffic laws; The database extracts keywords in the electronic text; generates trigger conditions based on the extracted keywords; and obtains the current driving parameters of the vehicle, and when the current driving parameters meet the trigger conditions, a driving assistance instruction is issued. The driving assistance method according to claim 1, wherein the step of "extracting keywords in the electronic text from the database" includes: matching the electronic text with the pre-stored keywords, when the When there are words consistent with the pre-stored keywords in the electronic text, the words are stored. The driving assistance method according to claim 1, wherein the keywords include traffic-related nominal words, driving-related operation verb words, or a combination of the two. The driving assistance method according to claim 1, wherein the step of "obtaining electronic text of traffic laws" includes: obtaining location information of the vehicle; and automatically downloading or automatically switching to obtain the traffic according to the location information of the vehicle Electronic text of regulations. The driving assistance method according to claim 1, wherein the trigger condition includes a preset driving scene and a preset driving operation, the preset driving scene is constructed according to the keyword, and the preset driving operation is in compliance with traffic laws When the vehicle is in a preset driving scene and the driving of the vehicle does not conform to the preset driving operation, it is determined that the trigger condition is met. The driving assistance method according to claim 1, wherein the current driving parameter includes at least one of vehicle-related parameters, driver-related parameters, passenger-related parameters, and traffic-related parameters. The driving assistance method according to claim 6, wherein the vehicle-related parameters include at least one of vehicle speed, acceleration, relative position, yaw angle, indicator status, driving direction, mileage, accelerator pedal signal, braking signal, and steering signal item. The driving assistance method according to claim 6, wherein the traffic-related parameters include at least one of road-related parameters, pedestrian-related parameters, signal-related parameters, traffic sign-related parameters, environment-related parameters, and vehicle distances between front and rear, left, and right. The driving assistance method according to claim 1, wherein the electronic text of the traffic law can be obtained through optical recognition of a paper file or downloaded from the Internet. A vehicle, the vehicle comprising: a processor; and a memory in which a plurality of program modules are stored, and the plurality of program modules are loaded by the processor and executed such as request items 1 to 9 The driving assistance method described in any one of.

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