CN116052475A - Vehicle risk early warning method, system, storage medium and device - Google Patents
Vehicle risk early warning method, system, storage medium and device Download PDFInfo
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Abstract
The invention provides a vehicle risk early warning method, a system, a storage medium and equipment, which belong to the technical field of vehicle risk early warning and comprise the following steps: acquiring the current driving state of a driver and the collision risk level of the current driving vehicle; based on the driving state and the collision risk level, obtaining the current vehicle risk level of the driving vehicle; transmitting the current vehicle risk level and the vehicle information to road side equipment of a current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section; and based on the vehicle risk grade and the real-time road risk early warning grade, realizing risk early warning of all vehicles on the current road section.
Description
Technical Field
The invention belongs to the technical field of vehicle risk early warning, and particularly relates to a vehicle risk early warning method, a system, a storage medium and equipment.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the continuous development of vehicle technology, the vehicle conservation amount approaches saturation, and the number of drivers is also rapidly increasing. The daily life of people is greatly facilitated, and the number of road traffic accidents and the huge economic loss amount are increased continuously. At present, a large number of auxiliary driving systems for ensuring road traffic safety are generated. The four factors of "person-vehicle-road-traffic environment" are the main factors of road traffic in actual driving.
The inventor finds that in the traditional vehicle risk early warning method, most vehicles around the driving vehicle are used as centers, vehicles possibly having risks around the current vehicle are perceived based on sensors such as radar, and the risk type is identified after the dangerous vehicles are found so as to perform early warning. In addition, most of the existing methods stand at the angle of the vehicle to sense the surrounding environment and perform auxiliary driving operation, the accuracy of the model is continuously improved from the angle of improving the safety of the vehicle, the uniformity in the aspect of macroscopic allocation is lacking, and the whole road traffic environment and the vehicle are not related to each other and are regarded as an intelligent network to be calculated as a whole.
Disclosure of Invention
The invention aims to solve the problems and provides a vehicle risk early warning method, a system, a storage medium and equipment.
According to a first aspect of an embodiment of the present invention, there is provided a vehicle risk early warning method, including:
the method comprises the steps of obtaining the current driving state of a driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
acquiring distance information between a currently driven vehicle and a front vehicle, speed information of the two vehicles and a relative course angle of the two vehicles, and acquiring predicted collision time when the currently driven vehicle collides with the front vehicle; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
based on the driving state and the collision risk level, obtaining a current vehicle risk level of the driving vehicle;
transmitting the current vehicle risk level and the vehicle information to road side equipment of a current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and based on the vehicle risk grade and the real-time road risk early warning grade, realizing risk early warning of all vehicles on the current road section.
Further, the calculation of the driving state specifically includes:
performing fatigue degree grade division based on the current driving time of the driver to obtain the fatigue degree grade of the driver;
periodically calculating a brake frequency of the driver based on the number of times the driver takes hard braking;
dividing the offence grade of the driver based on the deduction condition of the driver license in the preset period of the driver;
and obtaining the current driving state of the driver through the sum of the fatigue degree level, the braking frequency, the inverse of the braking reaction time and the illegal behavior level.
Further, a predicted collision time when the currently driven vehicle collides with the preceding vehicle is obtained, specifically using the following formula:
wherein d is the distance between the current driving vehicle and the geometrical center position connecting line of the front potential collision dangerous vehicle,
is the relative course angle of two vehicles, V 1 For the current driving vehicle speed, V 2 Is the forward vehicle speed.
Further, the vehicle information comprises license plate numbers and vehicle types, and the road environment information comprises road surface friction conditions, weather conditions, visible distances, vehicle densities, past traffic accident conditions and traffic accident grades at the current moment.
According to a second aspect of the embodiment of the present invention, there is provided a vehicle risk early warning system, including:
the driving state acquisition unit is used for acquiring the current driving state of the driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
a collision risk level obtaining unit, configured to obtain distance information between a currently driven vehicle and a vehicle ahead, speed information of the two vehicles, and a relative heading angle of the two vehicles, and obtain a predicted collision time when the currently driven vehicle collides with the vehicle ahead; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
a vehicle risk level acquisition unit for acquiring a current vehicle risk level of a driving vehicle based on the driving state and the collision risk level;
the road risk early warning grade acquisition unit is used for transmitting the current vehicle risk grade and vehicle information to the road side equipment of the current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and the risk early warning unit is used for realizing risk early warning of all vehicles on the current road section based on the vehicle risk grade and the real-time road risk early warning grade.
According to a third aspect of the embodiment of the present invention, there is provided a vehicle risk early warning system, including a vehicle-mounted device, a road side device, and a data cloud processing center, wherein:
the vehicle-mounted equipment is used for acquiring the current driving state of the driver and the collision risk level of the current driving vehicle; based on the driving state and the collision risk level, obtaining a current vehicle risk level of a driving vehicle, and transmitting the current vehicle risk level to road side equipment of a current road section;
the road side equipment is used for acquiring road environment information in real time, and acquiring real-time road risk early warning grades of the current road section based on the road environment information and vehicle risk grade average values of all vehicles of the current road section; broadcasting the obtained real-time road risk early warning grade and vehicle risk grade data of the current road section to vehicles in the current road section;
the data cloud processing center is used for receiving vehicle risk level data and real-time road risk early warning levels from road side equipment of each road section, and realizing data backup and macroscopic allocation of vehicle driving routes.
Further, the road side equipment is provided with a display guideboard for displaying the road environment information of the current road section.
According to a fourth aspect of the embodiment of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored to run on the memory, where the processor implements the vehicle risk early warning method when executing the program.
According to a fifth aspect of embodiments of the present invention, there is provided a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the vehicle risk early warning method.
Compared with the prior art, the invention has the beneficial effects that:
(1) The invention provides a vehicle risk early warning method, a system, a storage medium and equipment, wherein the scheme comprehensively considers the factor with coupling relation, namely 'people-vehicle-road-traffic environment', and plans as a whole, thereby effectively improving the accuracy of vehicle early warning;
(2) According to the scheme, when the risk of the vehicle is evaluated, consideration of road risk conditions is added, so that a driver can grasp the risk conditions of a road section to be driven in advance through communication of a data cloud processing center, and can grasp the current road section conditions through a display board of a road condition display module of road test equipment, so that a certain psychological expectation is provided, and additional reaction time is generated when the driver faces the danger;
(3) The scheme is based on road test equipment, and the current road risk early warning level and the road congestion level are obtained through measurement of current road surface friction force conditions, weather conditions (temperature and snowy weather), visibility conditions, traffic accident conditions and traffic accident level information and unified calculation of vehicle risk levels of vehicles in the current road section obtained through V2I communication; the road risk broadcasting module of the road side equipment is uploaded to the data cloud processing center, and the road risk broadcasting module is displayed in the road side display board, so that a driver can master current information in two modes.
(4) The scheme is based on the fact that the vehicle is easy to slip and out of control in snowy weather, and the reminding of the unexpected high-risk vehicle is introduced; the vehicle risk early warning module of the vehicle-mounted equipment immediately uses V2V communication to give an alarm to surrounding vehicles when the vehicle has a high risk condition, and prompts surrounding vehicle drivers, so that other vehicle drivers can obtain additional reaction time; meanwhile, the road risk broadcasting module of the drive test equipment can broadcast the situation of the high-risk vehicle to all vehicles on the current road section by using V2I communication so as to help other vehicle drivers to improve vigilance.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a flow chart of a vehicle risk early warning method according to an embodiment of the present invention;
fig. 2 is a schematic overall structure diagram of a vehicle risk early warning method according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Embodiment one:
the embodiment aims to provide a vehicle risk early warning method.
A vehicle risk early warning method comprising:
the method comprises the steps of obtaining the current driving state of a driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
acquiring distance information between a currently driven vehicle and a front vehicle, speed information of the two vehicles and a relative course angle of the two vehicles, and acquiring predicted collision time when the currently driven vehicle collides with the front vehicle; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
based on the driving state and the collision risk level, obtaining a current vehicle risk level of the driving vehicle;
transmitting the current vehicle risk level and the vehicle information to road side equipment of a current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and based on the vehicle risk grade and the real-time road risk early warning grade, realizing risk early warning of all vehicles on the current road section.
Further, the calculation of the driving state specifically includes:
performing fatigue degree grade division based on the current driving time of the driver to obtain the fatigue degree grade of the driver;
periodically calculating a brake frequency of the driver based on the number of times the driver takes hard braking;
dividing the offence grade of the driver based on the deduction condition of the driver license in the preset period of the driver;
and obtaining the current driving state of the driver through the sum of the fatigue degree level, the braking frequency, the inverse of the braking reaction time and the illegal behavior level.
Further, a predicted collision time when the currently driven vehicle collides with the preceding vehicle is obtained, specifically using the following formula:
wherein d is the distance between the current driving vehicle and the geometrical center position connecting line of the front potential collision dangerous vehicle,
is the relative course angle of two vehicles, V 1 For the current driving vehicle speed, V 2 Is the forward vehicle speed.
Further, the vehicle information comprises license plate numbers and vehicle types, and the road environment information comprises road surface friction conditions, weather conditions, visible distances, vehicle densities, past traffic accident conditions and traffic accident grades at the current moment.
In particular, for easy understanding, the following detailed description of the embodiments will be given with reference to the accompanying drawings:
in order to solve the problems in the prior art, the embodiment provides a vehicle risk early warning method, and the main idea of the scheme is to combine and consider the factors with coupling relations, namely 'people-vehicle-road-traffic environment', as a whole to plan, so that the accuracy of vehicle early warning is effectively improved. For convenience of understanding, the method in this embodiment is described in detail in view of module division with reference to fig. 2, and the method in this embodiment mainly includes relevant data processing of a vehicle-mounted device portion, a road side device portion, and a data cloud processing center portion, where the method obtains vehicle driving information, relevant conditions of a driver, and vehicle risk conditions through the vehicle-mounted device portion; the road testing equipment part obtains current road traffic information and vehicle risk information on a current road section to obtain a current road section risk condition; and the data cloud processing center part are communicated with each other, so that drivers and supervision departments can know the current vehicle risk condition in real time and visually, the road traffic safety degree is improved, and the urban traffic jam condition is reduced.
The following detailed description is given respectively:
vehicle-mounted equipment part
The vehicle-mounted equipment part comprises a driver state sensing module, a collision risk early warning module, a vehicle risk prediction module and a man-machine interaction module. The specific data calculation process is as follows:
(1) Driver state sensing module
It will be clear to those skilled in the art that the risk of collision caused by severe deceleration or emergency braking (i.e., occurrence of hard braking) can be observed from critical deceleration in the following situation, and therefore, the present embodiment selects to detect occurrence of hard braking using a fixed parameter, and the discrimination value of hard braking is set as: -5.892
。
Specifically, first, the driving duration h of the driver is obtained, and the fatigue degree level is performed
The higher the fatigue level, the higher the fatigue level of the driver, and the classification is shown in the following formula (1).
Secondly, obtaining the times of hard braking adopted by the driver in the current and previous driving processes, and calculating the braking frequency every 30min
. Then, the driver brake response time is obtained>
Its value is usually located +.>
，
The acquisition mode is as follows: the average value of the time difference between the peak values of the acceleration of the front and rear vehicles (i.e., the time point at which the maximum value of the acceleration in the present hard brake) in the present driver passing 100 times of hard brake data is calculated.
Furthermore, the deduction conditions of the driving license in the past year are graded to obtain deduction grades
The specific division is shown in the following formula (2):
wherein a is a deduction value.
Calculating the current driving state of the driver based on the four indexes
The calculation formula is shown as the following formula (3):
further, according to the driving state
The driving style is divided (aggressive, medium, conservative) and updated. The specific division is shown in the following formula (4):
(2) Collision risk early warning module
First, the preconditions for the occurrence of a collision need to be described: the precondition for the presence of a collision between vehicles in the present embodiment is considered as that the lateral distance between two vehicles is smaller than the body width k (m) of one vehicle, i.e
(wherein d is the distance of the line connecting the geometric center position of the currently driving vehicle and the vehicle having the potential collision risk,
Is the relative course angle, namely, the clockwise included angle from the longitudinal axis direction to the real running direction of the vehicle +.>
Clockwise angle +.A. from the longitudinal axis direction to the direction of the line between the rear vehicle and the front vehicle center>
The specific calculation formula is as follows:
). In combination with practical situations, the private car is generally 3.6-4.6 m long and 1.5-1.8 m wide, so that the average situation is selected in the scheme of the embodiment, the k value is set to 2 m, the information (speed, acceleration, geographic position and distance from surrounding vehicles) of the driven car is obtained in real time, and when real-time data is monitored>
In the present case, there is a potential collision risk by calculating the time of potential collision of the vehicle +.>
And comparing with a set safe anti-collision time threshold T (the time threshold at each moment is equal to the driver braking response time at that moment, < >>
) To judge the dangerous degree of the current situation and give out early warning information in real time. Equation (5) is a calculation equation for a specific predicted collision time when a frontal collision between a currently driving vehicle and another vehicle occurs:
where d is the distance of the line connecting the geometric center position of the currently driving vehicle and the vehicle with potential collision risk,
the unit is km/h for the current driving speed of the vehicle;
The speed of a vehicle for which there is a potential collision risk (i.e. a preceding vehicle relative to the currently driving vehicle) is in km/h.
Further, for the current collision risk level
Is represented by the following formula (6):
furthermore, other collision risk early warning models can be accessed to the scheme of the embodiment, so that the expandability of the scheme of the embodiment is effectively improved.
(3) Vehicle risk early warning module
The current vehicle risk level of the driven vehicle is calculated by integrating the relevant indexes calculated by the driver state sensing module and the collision risk early warning module
The calculation formula is shown as formula (7):
the predicted vehicle risk level, license plate number and vehicle type are transmitted to a road side equipment part of the current running road section of the vehicle through V2I (interaction between the vehicle and road infrastructure) communication, meanwhile, if a high risk level condition occurs, the predicted vehicle risk level, license plate number and vehicle type are transmitted to surrounding vehicles through V2V (interaction between the vehicle and the vehicle) communication to warn, and meanwhile, vehicle information acquired by the collision risk early warning module is uploaded to a data cloud processing center.
(4) Man-machine interaction module
And displaying the indexes calculated by the driver state sensing module and the collision risk early warning module in a vehicle display screen one by one, marking the high-risk index red, and warning the driver. And meanwhile, the color identification is carried out on the vehicle risk grade in the vehicle risk early warning module, so that a driver can grasp the overall state of the vehicle in real time.
(two) roadside device section
At the roadside device portion, comprising: the road environment sensing module, the road risk calculating module, the road risk broadcasting module and the road condition display module. The specific information calculation conditions are as follows:
(1) Road environment sensing module
Acquiring current road friction force condition K and weather condition in real time
；
Weather conditions are taken into consideration
The division is represented by the following formula (8):
according to the visible distance
Divide visibility case->
The division is shown in the following formula (9):
at the same time, the traffic accident situation E of the road section passing is obtained, if the road section is judged as the accident multiple road section
Otherwise, 0; and whether the road section has traffic accidents at the current moment or not, classifying the traffic accident level F, wherein the classification condition is shown in the following formula (10):
and integrating the related indexes, and carrying out real-time monitoring and updating.
(2) Road risk calculation module
And uniformly processing the related information acquired in the road environment sensing module. Meanwhile, the vehicle risk grades of all vehicles in the current road section obtained through V2I communication in the vehicle risk early warning module are accumulated, and are calculated together with the related information, so that the real-time road risk early warning grade G of the current road section is obtained, and the dividing situation is shown in the following formula (11):
wherein,,
the vehicle risk level for the i-th vehicle.
(3) Road risk broadcasting module
And broadcasting each vehicle entering the road section according to the real-time road risk early warning level predicted in the road risk calculation module and the vehicle condition of the high risk level condition in the vehicle risk early warning module, so that a driver has early psychological expectation. And simultaneously, the information acquired in the road risk calculation module is transmitted to a data cloud processing center in real time.
(4) Road condition display module
And setting up a display guideboard on each road side unit, displaying the road environment information obtained in the road environment sensing module on the guideboard in real time, and displaying the speed limit condition of the current road section. Meanwhile, a traffic jam road section display frame, a road wet road section display frame, an accident multiple road section display frame and a front accident detour display frame are arranged. And the real-time risk early warning grade condition of the road calculated in the road risk calculation module.
(III) data cloud processing center portion
And receiving the related information and the vehicle risk condition of each vehicle mentioned in the vehicle risk early warning module and the road condition information and the road risk condition of each road section mentioned in the road risk broadcasting module, and backing up and macroscopically allocating.
The road information with high risk and high congestion related to the planned route and within a preset range (the preset range is set within 3km according to actual requirements in the embodiment) near the target vehicle is used as the basis of the planned route, and a plurality of planned driving routes are provided for the driver in advance.
Further, since visibility is low during traveling when snowy weather occurs, the traveling speed of the vehicle is reduced; the road is slippery, and the road friction coefficient is reduced; the air temperature is lower, so that the performance of the vehicle is also changed, traffic accidents are easy to occur, the traffic jam is more serious, and the following effects can be generated according to the scheme in the embodiment aiming at the scene:
(1) When the risk of the vehicle is evaluated, consideration of road risk conditions is added, so that a driver can grasp the risk conditions of a road section to be driven in advance through communication of a data cloud processing center, and can grasp the current road section conditions through a display board of a road condition display module of road test equipment, thereby having a certain psychological expectation and generating additional reaction time when facing danger.
(2) The road test equipment obtains the current road risk early warning level and the road congestion level through the measurement of the current road surface friction force condition, the weather condition (temperature and snowy weather), the visibility condition, the traffic accident condition and the traffic accident level information, and the unified calculation of the vehicle risk level of each vehicle of the current road section obtained through V2I communication. The road risk broadcasting module is used for uploading the current information to the data cloud processing center, and the road risk broadcasting module is used for displaying the current information in the road side display board, so that a driver can master the current information in two modes.
(3) Meanwhile, the situation that the vehicle is easy to slip and out of control in snowy weather is solved, and reminding equipment for the unexpected high-risk vehicle is further added in the scheme. The vehicle risk early warning module at the vehicle-mounted equipment end immediately uses V2V communication to give an alarm to surrounding vehicles when the vehicle has a high risk condition, and prompts surrounding vehicle drivers, so that other vehicle drivers can obtain additional reaction time; meanwhile, the road risk broadcasting module of the drive test equipment can broadcast the situation of the high-risk vehicle to all vehicles on the current road section by using V2I communication so as to help other vehicle drivers to improve vigilance.
(4) Because of the large number of road traffic accidents in snowy weather, the current road section is required to be blocked to clear the scene after the traffic accidents occur. In order to avoid traffic jam and facilitate safe and quick passing of drivers, the scheme of the embodiment adds evasion and reminding measures for the accident road section. The data cloud processing center can avoid accident road sections when planning travel paths for drivers and displays the accident road sections in low-pass. Meanwhile, for the accident road section suddenly appearing in front of the driving course, a re-planned route is provided, so that the driver can travel conveniently.
Further, in order to prove the effectiveness of the solution described in this embodiment, this embodiment provides a corresponding test solution, specifically:
step 1, after a tested vehicle inputs a starting point and a finishing point, according to the currently mastered road information, a data cloud processing center avoids a road section with high risk and congestion (route selection priority: low risk and low congestion are higher than low risk and high congestion are higher than high risk and high congestion), and provides various route plans according to the information;
and 2, after the tested vehicle selects a route and starts the vehicle, starting the vehicle-mounted part equipment immediately.
Specifically, the driver state sensing module is utilized to start updating and evaluating the current driving state of the driver, the driving style is updated every half hour (specifically, the driving style can be set according to the actual requirement), and the driving style of the first half hour is generated by past driving data. And calculating the real-time collision risk of the current vehicle in real time by using the collision risk early-warning module. And the man-machine interaction module is used for displaying the current driving duration (the driver is continuously warned to prompt the rest after exceeding 4 hours), the driving style (the driver is prompted to keep reasonable inter-vehicle distance after frequent hard braking measures are taken), and the collision risk reminding (the driver is required to perform deceleration operation after seeing the risk reminding).
And step 3, uploading the selected path to a data cloud processing center after the tested vehicle starts to run.
And 4, uploading the real-time road risk early warning level and the road congestion condition level obtained by calculating different road information measured in the road environment sensing module through the road risk calculating module to the data cloud processing center by utilizing the road risk broadcasting module in the road testing equipment part.
And 5, continuously transmitting the vehicle risk grade and the vehicle information of the tested vehicle to a road test unit of the current road section through V2I communication in the vehicle risk early warning module when the tested vehicle runs on the current road section.
And 6, in the running process of the tested vehicle, transmitting the real-time road risk early warning level and the road congestion condition level of the next road section to the tested vehicle in advance through the data cloud processing center part so as to help a driver to grasp the front road condition in advance.
And 7, when the tested vehicle or surrounding vehicles have high risk conditions, warning is carried out by using the V2V communication in the vehicle risk early warning module, so that a driver is helped to better master the current vehicle risk conditions and respond in advance.
The validity verification of the scheme of the embodiment is realized based on the steps.
Embodiment two:
an object of the present embodiment is to provide a vehicle risk early warning system.
A vehicle risk early warning system comprising:
the driving state acquisition unit is used for acquiring the current driving state of the driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
a collision risk level obtaining unit, configured to obtain distance information between a currently driven vehicle and a vehicle ahead, speed information of the two vehicles, and a relative heading angle of the two vehicles, and obtain a predicted collision time when the currently driven vehicle collides with the vehicle ahead; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
a vehicle risk level acquisition unit for acquiring a current vehicle risk level of a driving vehicle based on the driving state and the collision risk level;
the road risk early warning grade acquisition unit is used for transmitting the current vehicle risk grade and vehicle information to the road side equipment of the current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and the risk early warning unit is used for realizing risk early warning of all vehicles on the current road section based on the vehicle risk grade and the real-time road risk early warning grade.
Further, the system in this embodiment corresponds to the method in the first embodiment, and the technical details thereof are described in the first embodiment, so that they will not be described herein.
Embodiment III:
it is an object of this embodiment to provide another vehicle risk early warning system.
The utility model provides a vehicle risk early warning system, includes on-vehicle equipment, road side equipment and data cloud processing center, wherein:
the vehicle-mounted equipment is used for acquiring the current driving state of the driver and the collision risk level of the current driving vehicle; based on the driving state and the collision risk level, obtaining a current vehicle risk level of a driving vehicle, and transmitting the current vehicle risk level to road side equipment of a current road section;
the road side equipment is used for acquiring road environment information in real time, and acquiring real-time road risk early warning grades of the current road section based on the road environment information and vehicle risk grade average values of all vehicles of the current road section; broadcasting the obtained real-time road risk early warning grade and vehicle risk grade data of the current road section to vehicles in the current road section;
the data cloud processing center is used for receiving vehicle risk level data and real-time road risk early warning levels from road side equipment of each road section, and realizing data backup and macroscopic allocation of vehicle driving routes.
Further, the road side equipment is provided with a display guideboard for displaying the road environment information of the current road section.
Further, the related technical details of the system in this embodiment are described in the first embodiment, so they are not described herein.
In further embodiments, there is also provided:
an electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the method of embodiment one. For brevity, the description is omitted here.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include read only memory and random access memory and provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store information of the device type.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the method of embodiment one.
The method in the first embodiment may be directly implemented as a hardware processor executing or implemented by a combination of hardware and software modules in the processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method. To avoid repetition, a detailed description is not provided herein.
Those of ordinary skill in the art will appreciate that the elements of the various examples described in connection with the present embodiments, i.e., the algorithm steps, can be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The vehicle risk early warning method, the system, the storage medium and the device provided by the embodiment can be realized, and have wide application prospects.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A vehicle risk early warning method, comprising:
the method comprises the steps of obtaining the current driving state of a driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
acquiring distance information between a currently driven vehicle and a front vehicle, speed information of the two vehicles and a relative course angle of the two vehicles, and acquiring predicted collision time when the currently driven vehicle collides with the front vehicle; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
based on the driving state and the collision risk level, obtaining a current vehicle risk level of the driving vehicle;
transmitting the current vehicle risk level and the vehicle information to road side equipment of a current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and based on the vehicle risk grade and the real-time road risk early warning grade, realizing risk early warning of all vehicles on the current road section.
2. The vehicle risk early warning method according to claim 1, wherein the calculation of the driving state is specifically:
performing fatigue degree grade division based on the current driving time of the driver to obtain the fatigue degree grade of the driver;
periodically calculating a brake frequency of the driver based on the number of times the driver takes hard braking;
dividing the offence grade of the driver based on the deduction condition of the driver license in the preset period of the driver;
and obtaining the current driving state of the driver through the sum of the fatigue degree level, the braking frequency, the inverse of the braking reaction time and the illegal behavior level.
3. The vehicle risk early warning method according to claim 1, wherein the predicted collision time when the currently driving vehicle collides with the preceding vehicle is obtained by using the following formula:
wherein d is the distance between the current driving vehicle and the geometrical center position connecting line of the front potential collision dangerous vehicle,
is the relative course angle of two vehicles, V 1 For the current driving vehicle speed, V 2 Is the forward vehicle speed.
4. The vehicle risk early warning method according to claim 1, wherein the vehicle information includes license plate number and vehicle type, and the road environment information includes road surface friction condition, weather condition, visible distance, vehicle density, past traffic accident condition and traffic accident level at the current moment of the current road section.
5. A vehicle risk early warning system, comprising:
the driving state acquisition unit is used for acquiring the current driving state of the driver, wherein the calculation of the driving state is calculated based on the current driving time length of the driver, the number of times of hard braking, the braking reaction time and the driving license deduction condition in a preset period;
a collision risk level obtaining unit, configured to obtain distance information between a currently driven vehicle and a vehicle ahead, speed information of the two vehicles, and a relative heading angle of the two vehicles, and obtain a predicted collision time when the currently driven vehicle collides with the vehicle ahead; the collision risk level of the currently driven vehicle is determined based on the predicted collision time by taking the driver braking reaction time corresponding to the current period as a threshold value;
a vehicle risk level acquisition unit for acquiring a current vehicle risk level of a driving vehicle based on the driving state and the collision risk level;
the road risk early warning grade acquisition unit is used for transmitting the current vehicle risk grade and vehicle information to the road side equipment of the current driving road section; acquiring road environment information in real time based on the road side equipment, and acquiring real-time road risk early warning level of the current road section based on the road environment information and the vehicle risk level average value of all vehicles in the current road section; the vehicle risk level data exceeding the preset threshold value and the real-time road risk early warning level of the current road section are transmitted to other vehicles of the current road section;
and the risk early warning unit is used for realizing risk early warning of all vehicles on the current road section based on the vehicle risk grade and the real-time road risk early warning grade.
6. The vehicle risk warning system of claim 5, wherein the calculation of the driving state is specifically:
performing fatigue degree grade division based on the current driving time of the driver to obtain the fatigue degree grade of the driver;
periodically calculating a brake frequency of the driver based on the number of times the driver takes hard braking;
dividing the offence grade of the driver based on the deduction condition of the driver license in the preset period of the driver;
and obtaining the current driving state of the driver through the sum of the fatigue degree level, the braking frequency, the inverse of the braking reaction time and the illegal behavior level.
7. The vehicle risk early warning system is characterized by comprising vehicle-mounted equipment, road side equipment and a data cloud processing center, wherein:
the vehicle-mounted equipment is used for acquiring the current driving state of the driver and the collision risk level of the current driving vehicle; based on the driving state and the collision risk level, obtaining a current vehicle risk level of a driving vehicle, and transmitting the current vehicle risk level to road side equipment of a current road section;
the road side equipment is used for acquiring road environment information in real time, and acquiring real-time road risk early warning grades of the current road section based on the road environment information and vehicle risk grade average values of all vehicles of the current road section; broadcasting the obtained real-time road risk early warning grade and vehicle risk grade data of the current road section to vehicles in the current road section;
the data cloud processing center is used for receiving vehicle risk level data and real-time road risk early warning levels from road side equipment of each road section, and realizing data backup and macroscopic allocation of vehicle driving routes.
8. The vehicle risk warning system according to claim 7, wherein the roadside apparatus is provided with a display guideboard for displaying road environment information of the current road section.
9. An electronic device comprising a memory, a processor and a computer program stored for execution on the memory, wherein the processor, when executing the program, implements a vehicle risk warning method as claimed in any one of claims 1 to 4.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a vehicle risk warning method according to any one of claims 1-4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117334066A (en) * | 2023-09-20 | 2024-01-02 | 广州亿胜鑫网络科技有限公司 | Risk analysis method, system, terminal and storage medium based on vehicle data |
| CN117601859A (en) * | 2024-01-22 | 2024-02-27 | 北京云驰未来科技有限公司 | Early warning system and method for preventing vehicle from collision |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104867327A (en) * | 2014-02-21 | 2015-08-26 | 中国移动通信集团公司 | Driving safety monitoring method and device |
| CN110264783A (en) * | 2019-06-19 | 2019-09-20 | 中设设计集团股份有限公司 | Vehicle collision avoidance early warning system and method based on bus or train route collaboration |
| CN113516847A (en) * | 2021-06-24 | 2021-10-19 | 华砺智行(武汉)科技有限公司 | Expressway anti-congestion control method and system based on Internet of vehicles V2X |
-
2023
- 2023-03-06 CN CN202310199938.XA patent/CN116052475A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104867327A (en) * | 2014-02-21 | 2015-08-26 | 中国移动通信集团公司 | Driving safety monitoring method and device |
| CN110264783A (en) * | 2019-06-19 | 2019-09-20 | 中设设计集团股份有限公司 | Vehicle collision avoidance early warning system and method based on bus or train route collaboration |
| CN113516847A (en) * | 2021-06-24 | 2021-10-19 | 华砺智行(武汉)科技有限公司 | Expressway anti-congestion control method and system based on Internet of vehicles V2X |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117334066A (en) * | 2023-09-20 | 2024-01-02 | 广州亿胜鑫网络科技有限公司 | Risk analysis method, system, terminal and storage medium based on vehicle data |
| CN117601859A (en) * | 2024-01-22 | 2024-02-27 | 北京云驰未来科技有限公司 | Early warning system and method for preventing vehicle from collision |
| CN117601859B (en) * | 2024-01-22 | 2024-04-23 | 北京云驰未来科技有限公司 | Early warning system and method for preventing vehicle from collision |
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