CN106781692B

CN106781692B - Vehicle collision early warning method, device and system

Info

Publication number: CN106781692B
Application number: CN201611092910.2A
Authority: CN
Inventors: 张珠华
Original assignee: Neusoft Corp
Current assignee: Neusoft Corp
Priority date: 2016-12-01
Filing date: 2016-12-01
Publication date: 2020-09-04
Anticipated expiration: 2036-12-01
Also published as: CN106781692A

Abstract

The invention discloses a vehicle collision early warning method, device and system, relates to the technical field of intelligent traffic, and solves the problem of low early warning accuracy of the existing collision early warning technology. The method of the invention comprises the following steps: acquiring vehicle information of a first vehicle and a second vehicle within a preset range from the first vehicle, wherein the vehicle information comprises position information, speed information and azimuth angle information; determining the type of a scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle; calling a preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library to calculate a danger coefficient of the first vehicle meeting with the second vehicle; and determining whether the vehicle collision is possible according to the danger coefficient, and realizing early warning of the vehicle collision. The method is applied to the vehicle collision early warning process.

Description

Vehicle collision early warning method, device and system

Technical Field

The invention relates to the technical field of intelligent traffic, in particular to a method, a device and a system for early warning of vehicle collision.

Background

With the rapid development of social economy, the number of motor vehicles is increased dramatically, and private automobiles bring people faster efficiency and more comfortable driving environment, and meanwhile, cause a lot of traffic problems, such as traffic accidents, traffic jams and the like. These traffic problems bring great economic and mental losses to human life, so how to reduce the occurrence of traffic problems has become an important issue for traffic safety in the world today.

The vehicle is influenced by factors such as traffic environment, weather and the like and the reaction capacity of a driver is limited in the driving process, so that traffic accidents are increased, and a plurality of conventional traffic accident risk factors cannot be effectively overcome by standardizing the behavior of the driver. Therefore, in recent ten years, the academic world and the industrial world have been working on the development of Intelligent Transportation Systems (ITS) to assist drivers in sensing the state information of surrounding traffic and vehicles, warning the existence of dangerous information, avoiding traffic accidents, and improving traffic efficiency. The ITS is the best path recognized at present for reducing traffic accidents, improving the driving environment, improving the traffic efficiency, reducing air pollution and the like. Therefore, development and research of the early warning system can acquire road or vehicle information in real time, remind a driver in time or automatically take measures to avoid accidents, and the early warning system becomes an important subject for solving the problem of road traffic safety.

At present, collision early warning technologies in existing danger early warning systems are generally vehicle collision avoidance technologies mainly based on a machine vision mode or a distance measurement mode. The collision early warning technology based on the machine vision mode is that external road information when a vehicle runs is collected through a vehicle-mounted camera and is processed through a computer to give an alarm for the dangerous situation about to happen in the front. The method has the advantages of large detection information amount and large data amount to be processed, and is also limited by the influence of road environment, road surface environment, climate conditions, light conditions and the like, so that the accuracy of data detection is difficult to ensure, and the early warning accuracy is likely to be reduced. The collision early warning technology based on the distance measurement mode has good accuracy on a straight road, but due to the high directionality of the distance measurement technology, the collision early warning technology based on the distance measurement mode cannot guarantee the accuracy of early warning because of the great limitation existing under the traffic environment of a curve or a crossroad and the accuracy of distance measurement cannot be guaranteed.

In conclusion, the existing collision early warning technology has low early warning accuracy.

Disclosure of Invention

In view of the above problems, the present invention provides a method, an apparatus, and a system for vehicle collision warning, which are used to solve the problem of low warning accuracy of the conventional collision warning technology.

In order to solve the above technical problem, in a first aspect, the present invention provides a method for early warning of vehicle collision, where the method includes:

acquiring vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle, wherein the vehicle information comprises position information, speed information and azimuth angle information;

determining the type of a scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle;

calling a preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library to calculate a danger coefficient of the first vehicle and the second vehicle meeting, wherein the preset collision early warning algorithm is a model for determining the danger coefficient according to position information, speed information and azimuth angle information among the vehicles, and the early warning algorithm library comprises the preset collision early warning algorithms corresponding to all the scene types;

and determining whether the vehicle collision is possible according to the danger coefficient, and realizing early warning of the vehicle collision.

Optionally, the determining the type of the scene where the first vehicle and the second vehicle meet according to the position information and the azimuth information of the first vehicle and the second vehicle includes:

determining the driving position of the second vehicle relative to the first vehicle according to the position information and the azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the driving of the first vehicle;

and if the position is located in front of driving, matching the difference value of the azimuth angle corresponding to the azimuth angle information of the first vehicle and the azimuth angle corresponding to the azimuth angle information of the second vehicle with a preset azimuth angle range, and determining the scene type, wherein the scene type comprises equidirectional driving, reverse driving and cross driving, and the preset azimuth angle range is in one-to-one correspondence with the scene type.

Optionally, the scene type is cross driving, the preset collision early warning algorithm is a cross collision early warning algorithm, and the preset collision early warning algorithm corresponding to the scene type is called from an early warning algorithm library to calculate a risk coefficient of the first vehicle encountering the second vehicle, including:

calculating the relative driving speed of the first vehicle and the second vehicle according to the speed information and the azimuth angle information of the first vehicle and the speed information and the azimuth angle information of the second vehicle;

calculating a projection value of the relative running speed on a connecting line of position points of the first vehicle and the second vehicle according to the position information of the first vehicle and the position information of the second vehicle;

calculating a collision time of the first vehicle with the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value;

and determining corresponding risk coefficients according to the range of the collision time, wherein different collision time ranges correspond to different risk coefficients.

Optionally, the calculating the collision time of the first vehicle and the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value includes:

and calculating the ratio of the distance between the first vehicle and the second vehicle to the projection value to obtain the collision time.

Optionally, the scene type is co-lane co-directional driving in co-directional driving, the preset collision early warning algorithm is a co-directional collision early warning algorithm, and the preset collision early warning algorithm corresponding to the scene type is called from an early warning algorithm library to calculate a risk coefficient of the first vehicle encountering the second vehicle, including:

determining whether the speed of the first vehicle is greater than the speed of the second vehicle;

if the speed of the first vehicle is greater than that of the second vehicle, calculating a safety early warning distance between the first vehicle and the second vehicle according to the speed information of the first vehicle and the second vehicle;

and determining the danger coefficient according to the relationship between the distance between the first vehicle and the second vehicle and the safety early warning distance.

Optionally, the determining whether a vehicle collision is possible according to the risk factor, and implementing the early warning of the vehicle collision includes:

determining whether the vehicle collision is possible according to whether the danger coefficient belongs to the danger coefficient range of the possible collision;

if the possibility of vehicle collision is determined, generating early warning signals and/or control signals corresponding to the danger coefficients, wherein different early warning signals and/or control signals correspond to different danger coefficients;

if it is determined that no vehicle collision is likely, the early warning signal and/or the control signal is not generated.

Optionally, the preset collision early warning algorithm is a homodromous collision early warning algorithm, and before the preset collision early warning algorithm corresponding to the scene type is called from an early warning algorithm library to calculate a risk coefficient of the first vehicle encountering with the second vehicle, the method further includes:

calculating a projection distance between the first vehicle and the second vehicle in the driving direction of the first vehicle according to the position information of the first vehicle and the second vehicle;

and comparing the projection distance with a preset lane width to determine whether the second vehicle and the first vehicle are positioned in the same lane.

Optionally, the method further includes:

broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle so that a second vehicle within the preset range from the first vehicle can receive the vehicle information of the first vehicle.

Optionally, the obtaining vehicle information of a second vehicle within a preset range from the first vehicle includes:

and receiving the vehicle information of the second vehicle sent by the second vehicle.

Optionally, before broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle, the method further includes:

and carrying out compression coding on the vehicle information of the first vehicle according to a preset coding mode so as to reduce the flow of information transmission.

Optionally, the obtaining vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle includes:

and vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle is acquired through a Global Positioning System (GPS).

In a second aspect, the present invention provides an apparatus for collision warning of a vehicle, the apparatus comprising:

the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle, and the vehicle information comprises position information, speed information and azimuth angle information;

the determining unit is used for determining the type of a scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle;

a risk coefficient calculation unit, configured to calculate a risk coefficient of an encounter between the first vehicle and the second vehicle by calling a preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library, where the preset collision early warning algorithm is a model that determines a risk coefficient according to position information, speed information, and azimuth information between vehicles, and the early warning algorithm library includes preset collision early warning algorithms corresponding to all scene types;

and the early warning unit is used for determining whether vehicle collision is possible according to the danger coefficient so as to realize early warning of the vehicle collision.

Optionally, the determining unit includes:

the position determining module is used for determining the running position of the second vehicle relative to the first vehicle according to the position information and the azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the first vehicle;

and the matching module is used for matching the difference value of the azimuth angle corresponding to the azimuth angle information of the first vehicle and the azimuth angle corresponding to the azimuth angle information of the second vehicle with a preset azimuth angle range if the first vehicle is positioned in front of driving, and determining the scene type, wherein the scene type comprises equidirectional driving, reverse driving and cross driving, and the preset azimuth angle range corresponds to the scene type one by one.

Optionally, the scene type is cross driving, the preset collision early warning algorithm is a cross collision early warning algorithm, and the risk coefficient calculating unit includes:

the first calculation module is used for calculating the relative driving speed of the first vehicle and the second vehicle according to the speed information and the azimuth angle information of the first vehicle and the speed information and the azimuth angle information of the second vehicle;

the second calculation module is used for calculating a projection value of the relative running speed on a connecting line of position points of the first vehicle and the second vehicle according to the position information of the first vehicle and the position information of the second vehicle;

a third calculation module, configured to calculate a collision time between the first vehicle and the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value;

and the danger coefficient determining module is used for determining corresponding danger coefficients according to the range of the collision time, and different collision time ranges correspond to different danger coefficients.

Optionally, the third computing module is configured to:

Optionally, the scene type is co-lane co-directional driving in co-directional driving, the preset collision early warning algorithm is a co-directional collision early warning algorithm, and the risk coefficient calculating unit further includes:

the judging module is used for judging whether the speed of the first vehicle is greater than that of the second vehicle;

the fourth calculation module is used for calculating the safety early warning distance between the first vehicle and the second vehicle according to the speed information of the first vehicle and the second vehicle if the speed of the first vehicle is greater than that of the second vehicle;

the danger coefficient determining module is further configured to determine the danger coefficient according to a size relationship between a distance between the first vehicle and the second vehicle and the safety early warning distance.

Optionally, the early warning unit includes:

the collision determining module is used for determining whether the vehicle collision is possible according to whether the danger coefficient belongs to the danger coefficient range in which the vehicle collision is possible;

the first early warning module is used for generating early warning signals and/or control signals corresponding to the danger coefficients if the possibility of vehicle collision is determined, and different early warning signals and/or control signals correspond to different danger coefficients;

and the second early warning module is used for not generating the early warning signal and/or the control signal if the fact that the vehicle collision is not possible is determined.

Optionally, the preset collision early warning algorithm is a homodromous collision early warning algorithm, and the apparatus further includes:

the projection distance calculation unit is used for calculating the projection distance of the first vehicle and the second vehicle in the driving direction of the first vehicle according to the position information of the first vehicle and the second vehicle before the preset collision early warning algorithm corresponding to the scene type is called from an early warning algorithm library to calculate the danger coefficient of the first vehicle and the second vehicle meeting;

and the comparison unit is used for comparing the projection distance with the preset lane width and determining whether the second vehicle and the first vehicle are positioned in the same lane.

Optionally, the apparatus further comprises:

the broadcasting unit is used for broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle, so that a second vehicle within the preset range from the first vehicle can receive the vehicle information of the first vehicle.

Optionally, the obtaining unit is configured to:

Optionally, the apparatus further comprises:

the encoding unit is used for compressing and encoding the vehicle information of the first vehicle according to a preset encoding mode before broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle, so as to reduce the flow of information transmission.

Optionally, the obtaining unit is further configured to:

In a third aspect, the invention provides a vehicle collision warning system, which includes a first vehicle and a second vehicle;

the first vehicle is used for acquiring vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle, wherein the vehicle information comprises position information, speed information and azimuth angle information; determining the type of a scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle; calling a preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library to calculate a danger coefficient of the first vehicle and the second vehicle meeting, wherein the preset collision early warning algorithm is a model for determining the danger coefficient according to position information, speed information and azimuth angle information among the vehicles, and the early warning algorithm library comprises the preset collision early warning algorithms corresponding to all the scene types; determining whether vehicle collision is possible according to the danger coefficient, and realizing early warning of vehicle collision;

the second vehicle is used for broadcasting the vehicle information of the second vehicle to the vehicles within a preset range from the second vehicle so that the first vehicle can acquire the vehicle information of the second vehicle.

By means of the technical scheme, the vehicle collision early warning method, the vehicle collision early warning device and the vehicle collision early warning system have the advantages that the information to be acquired only comprises the position information, the speed information and the azimuth angle information of the vehicle, and the environmental information, the road information and the like do not need to be acquired, so that the quantity of acquired and processed data is greatly reduced; in addition, the acquisition of the position information, the speed information and the azimuth angle information is not influenced by factors such as light conditions, weather conditions, road conditions (straight roads, curved roads, intersections and the like), and the accuracy of the information can be ensured. On the basis of ensuring that the acquired information is accurate, when the danger coefficient of the two vehicles meeting is determined according to the acquired position information, speed information and azimuth angle information of the first vehicle and the second vehicle, the accuracy of the danger coefficient can be ensured, and finally whether the vehicle collision is possible or not is determined according to the accurate danger coefficient, so that more accurate early warning of the vehicle collision is realized. In conclusion, compared with the prior art, the vehicle collision early warning method, the vehicle collision early warning device and the vehicle collision early warning system can improve the accuracy of collision early warning to a great extent.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 is a flow chart illustrating a method for vehicle collision warning according to an embodiment of the present invention;

FIG. 2 shows a schematic diagram of an azimuth range specification provided by an embodiment of the present invention;

FIG. 3 is a flow chart illustrating another method for vehicle collision warning provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram illustrating an example of determining a travel position of a second vehicle relative to a first vehicle provided by an embodiment of the present invention;

FIG. 5 is a schematic diagram illustrating an example of calculating a risk factor for a first vehicle crossing a second vehicle provided by an embodiment of the present invention;

FIG. 6 is a flow chart illustrating a further method of vehicle collision warning provided by an embodiment of the present invention;

fig. 7 is a block diagram illustrating a vehicle collision warning apparatus according to an embodiment of the present invention;

FIG. 8 is a block diagram showing another vehicle collision warning apparatus according to an embodiment of the present invention;

fig. 9 is a schematic functional structure diagram of a vehicle collision warning device according to an embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

In order to solve the problem of low early warning accuracy of the existing collision early warning technology, the embodiment of the invention provides a vehicle collision early warning method, as shown in fig. 1, the method comprises the following steps:

101. the method comprises the steps of obtaining vehicle information of a first vehicle and a second vehicle within a preset range from the first vehicle.

The first vehicle is the current vehicle where the program corresponding to the vehicle collision warning method in this embodiment is located. The second vehicle is any vehicle within a preset range from the first vehicle, and the preset range is a range in which normal network communication with the first vehicle can be performed. The specific manner of acquiring the vehicle information of the first vehicle is as follows: the third-party application located on the first vehicle may obtain the information, and the specific obtaining means is not limited, and may obtain the information through other communication methods such as a wireless communication network. The third party application refers to an application capable of accurately recording vehicle information of a vehicle. The program corresponding to the danger early warning method in the second vehicle can acquire the vehicle information of the second vehicle in the same way as the vehicle information of the first vehicle and send the acquired vehicle information to the first vehicle, so that the first vehicle can acquire the vehicle information of the second vehicle. The vehicle information of the second vehicle is acquired for performing collision early warning according to the vehicle information of the first vehicle and the vehicle information of the second vehicle.

The vehicle information of the first vehicle and the second vehicle includes position information, speed information, and azimuth information. It should be noted that the vehicle information is acquired periodically, and the specific acquisition period can be set freely according to actual requirements. The azimuth angle specified in the embodiment is an included angle between the direction of the vehicle head and the north, and the azimuth angle range is specified as shown in fig. 2. The range of azimuthal angles is (-180 °,180 °).

It should be noted that, in practical application, the first vehicle may acquire the vehicle information of all the second vehicles within the preset range, and perform subsequent collision early warning independently according to the vehicle information of different second vehicles and the vehicle information of the first vehicle, respectively.

102. And determining the type of the scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle.

The scene types of the vehicle-vehicle meeting include: the same-direction running meeting, the reverse running meeting and the cross running meeting. The cross driving meeting comprises a left cross driving meeting and a right cross driving meeting. The left-right intersection traveling meeting mainly refers to a scene where a first vehicle or a second vehicle meets at an intersection.

The corresponding judgment of different scene types whether collision is possible is different, that is, the algorithms used for subsequently calculating the risk coefficients are different, so that the encountered scene types of the vehicles need to be determined first, and the corresponding preset collision early warning algorithm can be selected in the subsequent step according to the encountered scene types.

103. And calling a preset collision early warning algorithm corresponding to the scene type from the early warning algorithm library to calculate the danger coefficient of the first vehicle meeting with the second vehicle.

The preset collision early warning algorithm is a model for determining a danger coefficient according to position information, speed information and azimuth angle information among vehicles, and the early warning algorithm library comprises preset collision early warning algorithms corresponding to different scene types. And calling a danger early warning algorithm corresponding to the scene type for the scene type of different vehicle-vehicle encounters. If the determined scene type is cross driving, calling a cross collision early warning algorithm; and if the determined scene type is the same-direction driving, calling a same-direction collision early warning algorithm and the like.

It should be noted that the risk coefficient refers to a risk level, for example, the risk level may be divided into two levels, one level is no risk, the corresponding risk coefficient may be set to 0, the second level is dangerous, and the corresponding risk coefficient is set to 1; or three levels are adopted, wherein one level is no danger, the corresponding danger coefficient can be set to be 0, the second level is low-level danger, the corresponding danger coefficient is set to be 2, the third level is high-level danger, and the corresponding danger coefficient is set to be 3; or more levels above three. The setting of the specific danger coefficient can be any representation form such as numbers, letters and the like which can distinguish different grades.

104. And determining whether the vehicle collision is possible according to the danger coefficient, and realizing early warning of the vehicle collision.

Corresponding to the risk level in step 103, if the risk factor is within a dangerous range, it is determined that a collision is likely to occur; if the risk factor is within a range that is not dangerous, it is determined that no collision is likely to occur. If the collision is possible, the early warning of the collision is carried out to remind a user to implement measures for preventing the collision or controlling the vehicle to automatically carry out the collision prevention, and the like. If no collision is possible, no collision warning is given.

According to the vehicle collision early warning method provided by the embodiment of the invention, the information to be acquired only comprises the position information, the speed information and the azimuth information of the vehicle, and the environmental information, the road information and the like do not need to be acquired, so that the quantity of acquired and processed data is greatly reduced; in addition, the acquisition of the position information, the speed information and the azimuth angle information is not influenced by factors such as light conditions, weather conditions, road conditions (straight roads, curved roads, intersections and the like), and the accuracy of the information can be ensured. On the basis of ensuring that the acquired information is accurate, when the danger coefficient of the two vehicles meeting is determined according to the acquired position information, speed information and azimuth angle information of the first vehicle and the second vehicle, the accuracy of the danger coefficient can be ensured, and finally whether the vehicle collision is possible or not is determined according to the accurate danger coefficient, so that more accurate early warning of the vehicle collision is realized. In conclusion, compared with the prior art, the vehicle collision early warning method provided by the embodiment of the invention can improve the accuracy of collision early warning to a great extent.

The embodiment of the present invention further provides a method for early warning of vehicle collision, as shown in fig. 3, by refining and expanding the method shown in fig. 1:

201. vehicle information of a first vehicle is acquired through a Global Positioning System (GPS).

The Global Positioning System (GPS) is a third-party application located in a vehicle, and vehicle information of the vehicle can be directly acquired through the GPS. Wherein the vehicle information includes position information, speed information, and azimuth information. The definition of the specific azimuth information is the same as the definition of the azimuth information referred to in step 101 of fig. 1. It should be noted that, in the manner of acquiring the vehicle information of the vehicle through the GPS, there is no need to add a new hardware device, and the cost can be well controlled.

After the vehicle information of the first vehicle is acquired, the vehicle information of the first vehicle is sent to all vehicles within a preset range from the first vehicle in a broadcast mode, so that other vehicles can judge the possibility of collision between the first vehicle and the own vehicle according to the vehicle information of the first vehicle. The preset range refers to a range in which normal network communication can be performed between vehicles.

In addition, in order to reduce the time delay of vehicle information transmission, the embodiment of the invention also performs compression coding on the acquired vehicle information according to a preset coding mode. The side receiving the vehicle information performs corresponding decompression to acquire the vehicle information. The compressed encoding of the vehicle information can reduce the network bandwidth occupied in the network transmission process, thereby reducing the time delay of vehicle information transmission and improving the performance of the system.

202. And receiving the vehicle information of the second vehicle sent by the second vehicle.

Wherein the second vehicle is any vehicle within a preset range from the first vehicle. The second vehicle can also acquire the vehicle information of the second vehicle through a GPS (global positioning system) positioned in the second vehicle, and then send the vehicle information of the second vehicle to all vehicles within a preset range from the second vehicle in a broadcasting manner, wherein all vehicles within the preset range from the second vehicle comprise the first vehicle, so that the first vehicle can receive the vehicle information of the second vehicle.

203. And determining the type of the scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle.

The specific process of determining the type of scene where the first vehicle meets the second vehicle is as follows:

firstly, determining the running position of a second vehicle relative to a first vehicle according to the position information and azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the first vehicle;

the travel position is defined with reference to the travel direction of the first vehicle, that is, the travel position of the second vehicle is specifically determined in the travel direction of the first vehicle. In the present embodiment, the position information of the first vehicle and the second vehicle is based on the position information of the longitude and latitude coordinate system, and therefore the position information is a coordinate value in the longitude and latitude coordinate system, the longitude and latitude coordinate system is based on the centroid as the origin, the north longitude direction is the positive y-axis direction (the y-axis represents the vehicle latitude), and the east latitude direction is the positive x-axis direction (the x-axis represents the vehicle longitude). Since the vehicle position reflected from the latitude and longitude coordinate system is an absolute position of the vehicle on the ground, it is impossible to determine the relative travel position of the second vehicle in the first vehicle traveling direction. Therefore, it is necessary to establish a running coordinate system relative to the first vehicle by using the current position of the first vehicle as the origin of coordinates, using the traveling direction of the first vehicle as the positive direction of the y-axis, and using the clockwise rotation of the y-axis by 90 degrees in the horizontal direction as the positive direction of the x-axis. And converting the longitude and latitude data of the first vehicle and the second vehicle from the longitude and latitude coordinate system into the running coordinate system. In the driving coordinate system, the driving position of the second vehicle relative to the first vehicle is determined, that is, the quadrant in the driving coordinate system in which the position coordinate of the second vehicle falls is determined, that is, the driving front in the first quadrant and the driving rear in the third quadrant and the fourth quadrant.

Given in detailThe example illustrates determining a travel position of a second vehicle relative to a first vehicle, as shown in fig. 4. Wherein the point H is the current position coordinate (X) of the first vehicle in the longitude and latitude coordinate system_h，Y_h) And N is the current position coordinate (X) of the second vehicle in the longitude and latitude coordinate system_n，Y_n) The coordinate system X ' HY ' is a running coordinate system with the first H point as the origin, the running coordinate system is parallel to the ground, the positive direction of Y ' is the traveling direction of the first vehicle, and then the head is_hIs the azimuth angle of the first vehicle, i.e. the angle between the direction of travel of the vehicle and the north. The dotted-line coordinate system XNY in fig. 4 is obtained by translating the origin of the latitude and longitude coordinate system to point H. According to the scenario of the relative position of the vehicle shown in fig. 4, the data mainly used for calculating the driving position of the second vehicle relative to the first vehicle is head_hAngle and theta angle, the theta angle is in the range of (-180 DEG, 180 DEG), and the theta-head is judged by_h) To determine the quadrant in which the N point is located, wherein the (theta-head) is_h) The value of (c) is the angle of the angle Y' HN, and is specifically determined as follows:

when | theta-head_hWhen the angle is less than or equal to 90 degrees, the point N is positioned in the first quadrant and the second quadrant of the X 'HY' coordinate system, and at the moment, the second vehicle is positioned in the driving front of the first vehicle;

when | theta-head_hWhen | > 90 °, the point N is located in the three and four quadrants of the X 'HY' coordinate system, and the second vehicle is located behind the first vehicle.

The theta angle can be obtained by calculating coordinates of point H, N, and the specific formula is as follows:

θ＝atan2((X_n-X_h)，(Y_n-Y_h))

secondly, if the second vehicle is located in front of the first vehicle, further matching a difference value between an azimuth angle corresponding to the azimuth angle information of the first vehicle and an azimuth angle corresponding to the azimuth angle information of the second vehicle with a preset azimuth angle range, and determining scene types, wherein the scene types comprise equidirectional driving, reverse driving and cross driving, and the preset azimuth angle range corresponds to the scene types one by one.

Specific examples are given for illustration according to azimuthThe difference determines the type of scenario implemented by assuming that the current position of the first vehicle is H, the current position of the second vehicle is N, and the azimuth angles are in the range of (-180 °,180 °), and the preset azimuth angle ranges are (- α), (180 ° - α,180 °), (-180 °, α -180 °), (α,180 ° - α), and (α -180 °, - α), assuming that the current azimuth angle of the first vehicle obtained according to the third party application is head_hThe current azimuth angle of the second vehicle is head_nAssuming α is 20 °, determining the scene type of the second vehicle and the first vehicle may be obtained as follows:

when | head_n-head_hWhen the angle is less than 20 degrees, the second vehicle runs in the same direction relative to the first vehicle;

when | head_n-head_hWhen the angle is larger than minus 160 degrees, the second vehicle runs in the reverse direction relative to the first vehicle;

when 20 ° < (head)_n-head_h) When the angle is less than 160 degrees, the second vehicle crossly runs to the left relative to the first vehicle;

when-160 ° < (head)_n-head_h) And when the angle is < -20 degrees, the second vehicle is driven to cross the first vehicle at the right.

Wherein α in the predetermined azimuth range can be adjusted appropriately according to actual requirements.

204. And calling a preset collision early warning algorithm corresponding to the scene type from the early warning algorithm library to calculate the danger coefficient of the first vehicle meeting with the second vehicle.

Different scene types correspond to different preset collision early warning algorithms. In this embodiment, two scene types are taken as an example for specific description.

The first scene type: a cross-drive encounter (including a left cross-drive encounter and a right cross-drive encounter).

The specific process of calculating the risk coefficient of the first vehicle meeting the second vehicle is as follows:

the position information of the first vehicle and the second vehicle is position coordinates based on a longitude and latitude coordinate system.

Firstly, calculating the relative driving speed of the first vehicle and the second vehicle according to the speed information, the azimuth angle information, the speed information and the azimuth angle information of the second vehicle;

secondly, calculating a projection value of the relative running speed on a connecting line of the position points of the first vehicle and the second vehicle according to the position information of the first vehicle and the position information of the second vehicle;

thirdly, calculating the collision time of the first vehicle and the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value in the second step;

the specific collision time is obtained by the ratio of the distance between the first vehicle and the second vehicle to the projection value.

Fourthly, determining corresponding danger coefficients according to the range of the collision time obtained in the third step, wherein different collision time ranges correspond to different danger coefficients.

Different risk factors correspond to different time ranges of collision. The risk coefficient refers to a risk level, for example, the risk level may be divided into two levels, one level is no risk, the corresponding risk coefficient may be set to 0, the second level is dangerous, and the corresponding risk coefficient is set to 1; or three levels are adopted, wherein one level is no danger, the corresponding danger coefficient can be set to be 0, the second level is low-level danger, the corresponding danger coefficient is set to be 2, the third level is high-level danger, and the corresponding danger coefficient is set to be 3; or more levels above three. The setting of the specific danger coefficient can be any representation form such as numbers, letters and the like which can distinguish different grades.

A specific example is given to describe the calculation of the risk coefficient of the first vehicle encountering the second vehicle. As follows:

establishing a vehicle longitude and latitude coordinate system, wherein the vehicle longitude and latitude coordinate system takes the geocenter as an origin, the northward longitude direction as the positive direction of the Y axis (the Y axis represents the vehicle latitude), the eastward latitude direction as the positive direction of the X axis (the X axis represents the vehicle longitude), the vehicle longitude and latitude coordinate system is defined as XOY, and in the XOY coordinate system, the position coordinate of a first vehicle is assumed to be N (the X axis represents the vehicle longitude), and in the XOY coordinate system, the position coordinate of the first vehicle is assumed₁，Y₁) The position information of the second vehicle is H (X)₂，Y₂) (ii) a In addition, the first vehicleHas an azimuth angle of H₁And a running speed V₁The azimuth angle of the second vehicle is H₂And a running speed V₂As shown in fig. 5. Wherein the azimuth angle represents the included angle between the direction of the vehicle head and the due north direction, and the range of the specified azimuth angle is (-180 degrees and 180 degrees).

Calculating V₁And V₂The velocity components in the X-and Y-axes, respectively, are denoted V_1xAnd V_1y，V_2xAnd V_2y. The specific calculation formula is as follows:

V_1x＝V₁sin H₁；V_1y＝V₁cos H₁

V_2x＝V₂sin H₂；V_2y＝V₂cos H₂

and calculating an included angle theta between a connecting line of the position points of the first vehicle and the second vehicle and the X axis, wherein the calculation formula of the theta is as follows:

calculating relative traveling speeds V of the second vehicle with respect to the first vehicle in X-axis and Y-axis directions, respectively_xAnd V_yThe specific calculation formula is as follows:

V_x＝V_2x-V_1x＝V₂sin H₂-V₁sin H₁

V_y＝V_2y-V_1y＝V₂cos H₂-V₁cos H₁

calculating a projection V of the traveling speed of the second vehicle relative to the first vehicle on a line connecting the two vehicle position points, i.e., NH_NHThe specific calculation formula is as follows:

V_NH＝V_xcosθ+V_ysinθ＝(V₂sin H₂-V₁sin H₁)cosθ+(V₂cos H₂-V₁cos H₁)sinθ

finally, it is deduced that:

V_NH＝V₂sin(H₂+θ)-V₁sin(H₁+θ)

calculating the time to collision TTC between the first vehicle and the second vehicle by the following specific calculation formula:

where | NH | represents a length value of a connection line between the position points of the first vehicle and the second vehicle.

The embodiment of the invention provides three different preset collision time ranges corresponding to the crossing and meeting scene, wherein the three different preset collision time ranges are TTC (0, a first threshold), TTC (a first preset threshold and a second preset threshold) and TTC (a second preset threshold and a plus infinity), the three collision time ranges respectively correspond to the second level, the third level and the first level of the danger level, and the corresponding danger coefficients are 1, 2 and 0 respectively. Therefore, the danger coefficient, namely the danger level, can be correspondingly determined according to the calculated collision time.

In addition, in the embodiment of the present invention, the first preset threshold is 4s, the second preset threshold is 8s, and both the first preset threshold and the second preset threshold are data obtained according to actual research.

The second scenario type: meet in the same direction

The same-direction travel meeting includes the same-direction travel of adjacent lanes, the same-direction travel of the same lane, and the like, and the same-direction travel scene of the same lane is taken as an example in the present embodiment. Therefore, it is first necessary to determine whether the lanes are the same, and the specific determination process is as follows: calculating a projected distance between the first vehicle and the second vehicle in the traveling direction of the first vehicle according to the position information of the first vehicle and the second vehicle, that is, a horizontal distance between the second vehicle and the first vehicle in the traveling coordinate system of the first vehicle, corresponding to the position relationship in fig. 4, specifically, the projected distance between the first vehicle and the second vehicle in the traveling direction of the first vehicle is Hor _ D, and Hor _ D is D (sin (θ -head)_h) D) is the distance between the first vehicle and the second vehicle in the longitude and latitude coordinate system; then comparing the projection distance with a preset lane width, in particular comparing Hor uD and 1/2 times of the width of the current lane, if the Hor _ D is less than or equal to 1/2 times of the width of the current lane, determining that the second vehicle and the first vehicle are located in the same lane, otherwise, determining that the second vehicle and the first vehicle are not located in the same lane. Then, calculating the danger coefficient of the scene running in the same lane in the same direction, specifically comprising the following steps:

firstly, judging whether the speed of a first vehicle is greater than that of a second vehicle;

secondly, if the speed of the first vehicle is larger than that of the second vehicle, calculating the safety early warning distance between the first vehicle and the second vehicle according to the speed information of the first vehicle and the second vehicle;

since it has been determined that the second vehicle is located ahead of the first vehicle in the traveling direction as described above, there is a possibility of a collision when the speed of the first vehicle is greater than that of the second vehicle, the calculation of the safety precaution distance is performed when the speed of the first vehicle is greater than that of the second vehicle.

The calculation formula of the safety early warning distance is as follows:

Dw＝(float)(v_rel*((Tr+Ts)/1000)+(v_rel*v_rel)/(2*phi*GGGG)+d0)；

wherein Dw is a safety early warning distance, v _ rel is the relative speed of the first vehicle and the second vehicle, Tr is the reaction time of the driver, and Tr can be modified; ts is the brake coordination time, and the default of Ts is 200ms in the embodiment; the phi road surface adhesion coefficient, in the embodiment, phi is 0.75; GGGG defaults to 9.8; d0 minimum safe parking distance, d0 is default 3m in this embodiment.

And thirdly, determining a danger coefficient according to the relationship between the distance between the first vehicle and the second vehicle and the safety early warning distance.

Comparing the actual distance between the first vehicle and the second vehicle with the safety early warning distance Dw, if the actual distance between the two vehicles is greater than Dw, no collision risk exists, namely the corresponding risk coefficient is 0, and if the actual distance between the two vehicles is greater than Dw, the collision risk is shown, and the corresponding risk coefficient is 1.

205. And if the first vehicle and the second vehicle are determined to be possible to collide according to the danger coefficient, generating an early warning signal and/or a control signal corresponding to the danger coefficient.

In order to timely perform corresponding anti-collision measures when it is determined that a collision is likely to occur, corresponding early warning signals and/or control signals are generally generated, where the generation of the early warning signals is to enable a user to timely know the existence of a collision risk and timely perform corresponding adjustments of the position or speed of a vehicle and the like to avoid the occurrence of the collision; the generation of the control signal is to generate a brake signal or the like capable of automatically controlling the vehicle, because a reaction of a person usually requires a certain time, and the reaction may not be possible in time of emergency.

For the above type of cross-encounter scenario, the generated risk coefficients have three cases, which are 0, 1 and 2. And 0 is the case without the risk of collision. 1 and 2 are the conditions that collision is possible, different danger coefficients representing the danger of collision correspond to different early warning signals, and the forms of the early warning signals can be sound, animation, indicator lights and the like. For example, 1 corresponds to a lower-level risk coefficient, a yellow indicator light can be used for early warning, and 2 corresponds to a higher-level risk signal, a red indicator light can be used for early warning. In addition, the control signals corresponding to different risk factors may also be different, for example, when the risk factor is 1, the corresponding control signal may be deceleration. With a risk factor of 2, the corresponding control signal may be braking.

For the scene type of the same-direction driving encounter, the generated danger coefficients are respectively 0 and 1, 0 is the case that no collision is possible, and 1 is the case that collision is possible, because only one danger coefficient is determined that collision is possible, the early warning signal and the control signal are not classified any more. In practical applications, the level may be subdivided in the case of a possible collision, and in this case, different warning signals and/or control signals may be set for different levels.

In addition, if it is determined that no collision is likely to occur, the warning signal and/or the control signal is not generated.

In order to more clearly describe the vehicle collision warning method in fig. 3, the embodiment further provides a flowchart corresponding to the vehicle collision warning method, as shown in fig. 6.

Wherein vehicle information of the first vehicle is periodically collected, corresponding to the step 201 of obtaining the vehicle information of the first vehicle, the step 202 of compression-coding the vehicle information of the first vehicle corresponds to the step 201 of compression-coding the vehicle information, the step 202 of receiving the vehicle information of the second vehicle corresponds to the step 201 of broadcasting the vehicle information of the first vehicle to the surrounding vehicles corresponds to the step 203 of sending the vehicle information of the first vehicle to the vehicles within the preset range in a broadcast mode, judging that the scene type of the first vehicle and the second vehicle meeting corresponds to the step 203, calling a preset collision early warning algorithm corresponding to the scene type to calculate the danger coefficient corresponding to the calculated danger coefficient in the step 204, judging whether the warning condition is met according to the risk factor corresponds to determining whether collision is possible according to the risk factor in step 204, and outputting the warning corresponds to step 205.

The vehicle collision early warning method in fig. 1 and fig. 3 has good expansibility, when a danger early warning algorithm is updated or a new danger early warning algorithm is added, in practical application, the updated danger early warning algorithm or the new danger early warning algorithm can be added into a preset algorithm library, parameters related to the vehicle and used by the updated danger early warning algorithm or the new danger early warning algorithm are correspondingly obtained, then the corresponding danger early warning algorithm is called according to the obtained related parameters to calculate the corresponding danger coefficient, and then whether the vehicle collision is possible or not is determined according to the danger coefficient, so that the early warning of the vehicle collision is realized.

Further, as an implementation of the foregoing embodiments, another embodiment of the embodiments of the present invention further provides a vehicle collision warning apparatus, which is used for implementing the methods described in fig. 1 and fig. 3. As shown in fig. 7, the apparatus includes: the system comprises an acquisition unit 31, a determination unit 32, a risk coefficient calculation unit 33 and an early warning unit 34.

The acquiring unit 31 is configured to acquire vehicle information of a first vehicle and a second vehicle within a preset range from the first vehicle, where the vehicle information includes position information, speed information, and azimuth information;

wherein the first vehicle is the current vehicle where the vehicle collision early warning device is located in the embodiment. The second vehicle is any vehicle within a preset range from the first vehicle, and the preset range is a range in which normal network communication with the first vehicle can be performed. The specific manner of acquiring the vehicle information of the first vehicle is as follows: the third-party application located on the first vehicle may obtain the information, and the specific obtaining means is not limited, and may obtain the information through other communication methods such as a wireless communication network. The third party application refers to an application capable of accurately recording vehicle information of a vehicle. The program corresponding to the danger early warning method in the second vehicle can acquire the vehicle information of the second vehicle in the same way as the vehicle information of the first vehicle and send the acquired vehicle information to the first vehicle, so that the first vehicle can acquire the vehicle information of the second vehicle. The vehicle information of the second vehicle is acquired for performing collision early warning according to the vehicle information of the first vehicle and the vehicle information of the second vehicle.

A determination unit 32 for determining a scene type of the first vehicle and the second vehicle encountering each other according to the position information and the azimuth information of the first vehicle and the second vehicle;

The risk coefficient calculation unit 33 is configured to calculate a risk coefficient of the first vehicle encountering with the second vehicle by calling a preset collision early-warning algorithm corresponding to the scene type from an early-warning algorithm library, where the preset collision early-warning algorithm is a model for determining the risk coefficient according to position information, speed information, and azimuth information between the vehicles, and the early-warning algorithm library includes preset collision early-warning algorithms corresponding to all the scene types;

And the early warning unit 34 is used for determining whether the vehicle collision is possible according to the danger coefficient, and realizing early warning of the vehicle collision.

Corresponding to the risk level in the risk coefficient calculation unit 33, if the risk coefficient is within a range having risk, it is determined that a collision is likely to occur; if the risk factor is within a range that is not dangerous, it is determined that no collision is likely to occur. If the collision is possible, the early warning of the collision is carried out to remind a user to implement measures for preventing the collision or controlling the vehicle to automatically carry out the collision prevention, and the like. If no collision is possible, no collision warning is given.

As shown in fig. 8, the determination unit 32 includes:

a position determining module 321, configured to determine a driving position of the second vehicle relative to the first vehicle according to the position information and the azimuth information of the first vehicle and the position information of the second vehicle, so as to determine that the second vehicle is located in front of or behind the first vehicle;

The matching module 322 is configured to, if the vehicle is located in front of driving, match a difference between an azimuth corresponding to the azimuth information of the first vehicle and an azimuth corresponding to the azimuth information of the second vehicle with a preset azimuth range, and determine a scene type, where the scene type includes co-directional driving, reverse driving, and cross driving, and the preset azimuth range corresponds to the scene type one to one.

A specific example is given to illustrate the implementation of determining the scene type based on the difference in azimuth angles, assuming that the current position of the first vehicle is H, the current position of the second vehicle is N, and the azimuth angles have values ranging from (-180 DEG, 180 DEG), preset azimuth angle ranges from (- α), (180 DEG- α,180 DEG, (-180 DEG, α -180 DEG), (α,180 DEG- α), and (α -180 DEG, - α), assuming that the current azimuth angle of the first vehicle obtained according to the third-party application is head_hThe current azimuth angle of the second vehicle is head_nAssuming α is 20 °, determining the scene type of the second vehicle and the first vehicle may be obtained as follows:

As shown in fig. 8, the scene type is cross driving, the preset collision warning algorithm is a cross collision warning algorithm, and the risk coefficient calculating unit 33 includes:

the first calculating module 331 is configured to calculate a relative traveling speed of the first vehicle and the second vehicle according to the speed information and the azimuth angle information of the first vehicle and the speed information and the azimuth angle information of the second vehicle;

a second calculating module 332, configured to calculate a projection value of the relative travel speed on a connection line between the position points of the first vehicle and the second vehicle according to the position information of the first vehicle and the position information of the second vehicle;

a third calculating module 333, configured to calculate a collision time between the first vehicle and the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value;

and the risk coefficient determining module 334 is configured to determine a corresponding risk coefficient according to the range of the collision time, where different collision time ranges correspond to different risk coefficients.

The third calculation module 333 is further configured to:

As shown in fig. 8, the scene type is co-lane co-directional driving in co-directional driving, the preset collision warning algorithm is a co-directional collision warning algorithm, and the risk coefficient calculating unit 33 further includes:

a determination module 335 for determining whether the speed of the first vehicle is greater than the speed of the second vehicle;

the fourth calculation module 336 is used for calculating the safety early warning distance between the first vehicle and the second vehicle according to the speed information of the first vehicle and the second vehicle if the speed of the first vehicle is greater than the speed of the second vehicle;

The calculation formula of the safety early warning distance is as follows:

Dw＝(float)(v_rel*((Tr+Ts)/1000)+(v_rel*v_rel)/(2*phi*GGGG)+d0)；

The risk factor determining module 334 is further configured to determine a risk factor according to a magnitude relationship between a distance between the first vehicle and the second vehicle and the safety precaution distance.

As shown in fig. 8, the warning unit 34 includes:

a collision determination module 341 configured to determine whether a vehicle collision is likely to occur according to whether the risk factor falls within a risk factor range in which a collision is likely to occur;

the first early warning module 342 is configured to generate an early warning signal and/or a control signal corresponding to a risk coefficient if it is determined that a vehicle collision is likely to occur, where different early warning signals and/or different control signals correspond to different risk coefficients;

a second early warning module 343 configured to not generate an early warning signal and/or a control signal if it is determined that a vehicle collision is not likely.

As shown in fig. 8, the preset collision warning algorithm is a homodromous collision warning algorithm, and the apparatus further includes:

the projection distance calculation unit 35 is configured to calculate a projection distance between the first vehicle and the second vehicle in the first vehicle driving direction according to the position information of the first vehicle and the second vehicle before a preset collision early warning algorithm corresponding to the scene type is called from the early warning algorithm library to calculate a risk coefficient of the first vehicle and the second vehicle encountering each other;

and the comparison unit 36 is used for comparing the projection distance with the preset lane width and determining whether the second vehicle and the first vehicle are located in the same lane.

The same-direction travel meeting includes the same-direction travel of adjacent lanes, the same-direction travel of the same lane, and the like, and the same-direction travel scene of the same lane is taken as an example in the present embodiment. Therefore, it is first necessary to determine whether the lanes are the same, and the specific determination process is as follows: calculating a projected distance between the first vehicle and the second vehicle in the traveling direction of the first vehicle according to the position information of the first vehicle and the second vehicle, that is, a horizontal distance between the second vehicle and the first vehicle in the traveling coordinate system of the first vehicle, corresponding to the position relationship in fig. 4, specifically, the projected distance between the first vehicle and the second vehicle in the traveling direction of the first vehicle is Hor _ D, and Hor _ D is D (sin (θ -head)_h) D) is the distance between the first vehicle and the second vehicle in the longitude and latitude coordinate system; and then comparing the projection distance with a preset lane width, specifically comparing Hor _ D with 1/2 times of the width of the current lane, and if Hor _ D is less than or equal to 1/2 times of the width of the current lane, determining that the second vehicle and the first vehicle are located in the same lane, otherwise, determining that the second vehicle and the first vehicle are not located in the same lane.

As shown in fig. 8, the apparatus further comprises:

the broadcasting unit 37 is configured to broadcast the vehicle information of the first vehicle within a preset range from the first vehicle, so that a second vehicle within the preset range from the first vehicle can receive the vehicle information of the first vehicle.

The obtaining unit 31 is further configured to:

As shown in fig. 8, the apparatus further comprises:

the encoding unit 38 is configured to, before broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle, perform compression encoding on the vehicle information of the first vehicle according to a preset encoding manner to reduce the traffic of information transmission.

In order to reduce the time delay of vehicle information transmission, the embodiment of the invention also performs compression coding on the acquired vehicle information according to a preset coding mode. The side receiving the vehicle information performs corresponding decompression to acquire the vehicle information. The compressed encoding of the vehicle information can reduce the network bandwidth occupied in the network transmission process, thereby reducing the time delay of vehicle information transmission and improving the performance of the system.

The obtaining unit 31 is further configured to:

vehicle information of a first vehicle and a second vehicle within a preset range from the first vehicle is acquired through a Global Positioning System (GPS).

The vehicle information of the vehicle is acquired through the GPS without adding new hardware equipment, so that the cost can be well controlled.

In order to more clearly explain the vehicle collision warning device in fig. 7 and fig. 8, the embodiment further provides a functional structure diagram corresponding to the vehicle collision warning device, specifically as shown in fig. 9: the system comprises 5 functional modules of information acquisition, message processing, message encoding and decoding, danger early warning and early warning output, wherein a main vehicle corresponds to a first vehicle, and a far vehicle corresponds to a second vehicle. The information acquisition module corresponds to the implementation of acquiring the vehicle information of the first vehicle in the above-mentioned acquisition unit 31. The information collection module is used for collecting vehicle information of a vehicle, the vehicle information in this embodiment includes position information, speed information, and azimuth information, and the actual information collection module can collect other vehicle information, such as vehicle state information (emergency brake information, turn light state, gyroscope data, etc.). If the collected information is the position information, the speed information and the azimuth angle information, the information is obtained through a GPS system, and if the collected information is the state information of the vehicle, the information is obtained through a vehicle body CAN bus and a Sensor. The message processing module corresponds to an implementation in the acquisition unit 31 of receiving the vehicle information transmitted by the second vehicle and an implementation in the broadcast unit 37 of broadcasting the vehicle information of the first vehicle. The message encoding and decoding module comprises the implementation of decompressing the acquired compressed codes and the implementation of encoding and compressing the vehicle information in the encoding unit 38. The danger early warning module comprises three sub-modules, wherein the vehicle target classification sub-module corresponds to the determination unit 32 and is used for determining the scene type according to the vehicle information of the first vehicle and the vehicle information of the second vehicle; the corresponding scene algorithm submodule corresponds to the early warning algorithm library and is used for providing algorithm support for the danger arbitration scheduling submodule; and the danger arbitration scheduling submodule, which corresponds to the danger coefficient calculating unit 33 and the early warning unit 34, is used for calling a corresponding preset collision early warning algorithm from the scene algorithm submodule according to the scene type, then calculating a corresponding danger coefficient, determining whether a vehicle collision is possible, and outputting the corresponding danger coefficient and the scene type corresponding to the danger coefficient to the early warning output module under the condition that the collision is possible, so that the early warning output module outputs a corresponding early warning signal and/or control signal. The pre-warning output module corresponds to the second pre-warning module 343.

According to the vehicle collision early warning device provided by the embodiment of the invention, the information to be acquired only comprises the position information, the speed information and the azimuth information of the vehicle, and the environmental information, the road information and the like do not need to be acquired, so that the quantity of acquired and processed data is greatly reduced; in addition, the acquisition of the position information, the speed information and the azimuth angle information is not influenced by factors such as light conditions, weather conditions, road conditions (straight roads, curved roads, intersections and the like), and the accuracy of the information can be ensured. On the basis of ensuring that the acquired information is accurate, when the danger coefficient of the two vehicles meeting is determined according to the acquired position information, speed information and azimuth angle information of the first vehicle and the second vehicle, the accuracy of the danger coefficient can be ensured, and finally whether the vehicle collision is possible or not is determined according to the accurate danger coefficient, so that more accurate early warning of the vehicle collision is realized. In conclusion, compared with the prior art, the vehicle collision early warning device provided by the embodiment of the invention can improve the accuracy of collision early warning to a great extent.

The last embodiment of the invention also provides a vehicle collision early warning system, which is used for realizing the method shown in the figures 1 and 3. The system embodiment corresponds to the method embodiment, and can realize all the contents in the method embodiment. For convenience of reading, the embodiments of the present system only schematically describe the contents of the foregoing method embodiments, and details of the method embodiments are not described in detail. The system comprises a first vehicle and a second vehicle, wherein the first vehicle comprises the device shown in the figure 7 or the figure 8. Specifically, the method comprises the following steps:

the system comprises a first vehicle and a second vehicle, wherein the first vehicle is used for acquiring vehicle information of the first vehicle and the second vehicle within a preset range from the first vehicle, and the vehicle information comprises position information, speed information and azimuth angle information; determining the type of a scene where the first vehicle and the second vehicle meet according to the position information and the azimuth angle information of the first vehicle and the second vehicle; calling a preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library to calculate a danger coefficient of the first vehicle and the second vehicle meeting, wherein the preset collision early warning algorithm is a model for determining the danger coefficient according to position information, speed information and azimuth angle information among the vehicles, and the early warning algorithm library comprises the preset collision early warning algorithms corresponding to all the scene types; determining whether vehicle collision is possible according to the danger coefficient, and realizing early warning of vehicle collision;

and the second vehicle is used for broadcasting the vehicle information of the second vehicle to the vehicles within a preset range from the second vehicle so that the first vehicle can acquire the vehicle information of the second vehicle.

According to the vehicle collision early warning system provided by the embodiment of the invention, the information to be acquired only comprises the position information, the speed information and the azimuth information of the vehicle, and the environmental information, the road information and the like do not need to be acquired, so that the quantity of acquired and processed data is greatly reduced; in addition, the acquisition of the position information, the speed information and the azimuth angle information is not influenced by factors such as light conditions, weather conditions, road conditions (straight roads, curved roads, intersections and the like), and the accuracy of the information can be ensured. On the basis of ensuring that the acquired information is accurate, when the danger coefficient of the two vehicles meeting is determined according to the acquired position information, speed information and azimuth angle information of the first vehicle and the second vehicle, the accuracy of the danger coefficient can be ensured, and finally whether the vehicle collision is possible or not is determined according to the accurate danger coefficient, so that more accurate early warning of the vehicle collision is realized. In conclusion, compared with the prior art, the vehicle collision early warning system provided by the embodiment of the invention can improve the accuracy of collision early warning to a great extent.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

It will be appreciated that the relevant features of the method and apparatus described above are referred to one another. In addition, "first", "second", and the like in the above embodiments are for distinguishing the embodiments, and do not represent merits of the embodiments.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the title of the invention (e.g., a vehicle collision warning device) in accordance with an embodiment of the invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Claims

1. A method of vehicle collision warning, the method being applied to a first vehicle, the method comprising:

determining whether vehicle collision is possible according to the danger coefficient, and realizing early warning of vehicle collision;

the determining the type of the scene where the first vehicle and the second vehicle meet according to the position information and the azimuth information of the first vehicle and the second vehicle comprises the following steps:

determining the driving position of the second vehicle relative to the first vehicle according to the position information and the azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the driving of the first vehicle; when | theta-head_h∣≤90^oWhen the second vehicle is located in front of the first vehicle in the traveling direction; when | theta-head_h∣＞90^oWhen the first vehicle is in the driving rear direction, the second vehicle is positioned behind the first vehicle, wherein theta is an included angle between the first vehicle and the second vehicle, head_hIs the azimuth of the first vehicle;

if the first vehicle is positioned in the driving front, the azimuth corresponding to the azimuth information of the first vehicle is compared with the first vehicleMatching the azimuth difference corresponding to the second vehicle azimuth information with a preset azimuth range to determine the scene type, wherein the preset azimuth range corresponds to the scene type one to one; when | head_n-head_h∣＜20^oWhen the vehicle is running, the second vehicle runs in the same direction relative to the first vehicle; when | head_n-head_h∣＞160^oWhen the vehicle is running, the second vehicle runs in the reverse direction relative to the first vehicle; when 20 is turned on^o＜（head_n-head_h）＜160^oWhen the vehicle is running, the second vehicle is in left crossing driving relative to the first vehicle; when-160^o＜（head_n-head_h）＜-20^oWhile the second vehicle is traveling right-cross to the first vehicle, wherein the head_nIs the azimuth of the second vehicle;

the scene types comprise equidirectional driving, reverse driving and cross driving;

when the scene type is cross driving, the preset collision early warning algorithm is a cross collision early warning algorithm, the preset collision early warning algorithm corresponding to the scene type is called from an early warning algorithm library to calculate the risk coefficient of the first vehicle meeting with the second vehicle, and the method comprises the following steps:

2. The method of claim 1, wherein the calculating a time of collision of the first vehicle with the second vehicle from the distance between the first vehicle and the second vehicle and the projected value comprises:

3. The method according to claim 1, wherein the scene type is co-lane co-driving in co-driving, the preset collision early warning algorithm is a co-directional collision early warning algorithm, and the step of calling the preset collision early warning algorithm corresponding to the scene type from an early warning algorithm library to calculate the risk coefficient of the first vehicle meeting with the second vehicle comprises the following steps:

4. The method according to any one of claims 2 or 3, wherein the determining whether a vehicle collision is likely to occur according to the risk factor, and the implementing the early warning of the vehicle collision comprises:

5. The method of claim 4, wherein the preset collision warning algorithm is a homodromous collision warning algorithm, and before the preset collision warning algorithm corresponding to the scene type is called from a warning algorithm library to calculate the risk coefficient of the first vehicle encountering with the second vehicle, the method further comprises:

6. The method of claim 5, further comprising:

broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle, so that a second vehicle within the preset range from the first vehicle can receive the vehicle information of the first vehicle.

7. The method of claim 6, wherein the obtaining vehicle information of a second vehicle within a preset range from the first vehicle comprises:

8. The method of claim 7, wherein prior to broadcasting the vehicle information of the first vehicle within a predetermined range from the first vehicle, the method further comprises:

9. The method of claim 8, wherein the obtaining vehicle information of the first vehicle and a second vehicle within a preset range from the first vehicle comprises:

10. A vehicle collision warning apparatus, the apparatus being located on a first vehicle side, the apparatus comprising:

the early warning unit is used for determining whether vehicle collision is possible according to the danger coefficient so as to realize early warning of the vehicle collision;

the determination unit includes:

the position determining module is used for determining the running position of the second vehicle relative to the first vehicle according to the position information and the azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the first vehicle; when | theta-head_h∣≤90^oWhen the second vehicle is located in front of the first vehicle in the traveling direction; when | theta-head_h∣＞90^oWhen the first vehicle is in the driving rear direction, the second vehicle is positioned behind the first vehicle, wherein theta is an included angle between the first vehicle and the second vehicle, head_hIs a first vehicleAn azimuth angle of the vehicle;

the matching module is used for matching the difference value of the azimuth angle corresponding to the azimuth angle information of the first vehicle and the azimuth angle corresponding to the azimuth angle information of the second vehicle with a preset azimuth angle range if the first vehicle is positioned in front of driving, and determining the scene type, wherein the preset azimuth angle range corresponds to the scene type one by one; when | head_n-head_h∣＞160^oWhen the vehicle is running, the second vehicle runs in the reverse direction relative to the first vehicle; when 20 is turned on^o＜（head_n-head_h）＜160^oWhen the vehicle is running, the second vehicle is in left crossing driving relative to the first vehicle; when-160^o＜（head_n-head_h）＜-20^oWhile the second vehicle is traveling right-cross to the first vehicle, wherein the head_nIs the azimuth of the second vehicle;

when the scene type is cross driving, the preset collision early warning algorithm is a cross collision early warning algorithm, and the risk coefficient calculation unit comprises:

11. The apparatus of claim 10, wherein the third computing module is configured to:

12. The apparatus according to claim 10, wherein the scene type is co-lane co-directional driving in co-directional driving, the preset collision warning algorithm is a co-directional collision warning algorithm, and the risk coefficient calculating unit further includes:

13. The apparatus according to any one of claims 11 or 12, wherein the early warning unit comprises:

14. The apparatus of claim 13, wherein the pre-determined pre-crash alert algorithm is a homodromous pre-crash alert algorithm, the apparatus further comprising:

15. The apparatus of claim 14, further comprising:

the broadcasting unit is used for broadcasting the vehicle information of the first vehicle within a preset range from the first vehicle so that a second vehicle within the preset range from the first vehicle can receive the vehicle information of the first vehicle.

16. The apparatus of claim 15, wherein the obtaining unit is configured to:

17. The apparatus of claim 16, further comprising:

18. The apparatus of claim 17, wherein the obtaining unit is further configured to:

19. A vehicle collision warning system is characterized by comprising a first vehicle and a second vehicle;

the second vehicle is used for broadcasting the vehicle information of the second vehicle to the vehicles within a preset range from the second vehicle so that the first vehicle can acquire the vehicle information of the second vehicle;

the first vehicle is used for determining the running position of the second vehicle relative to the first vehicle according to the position information and the azimuth angle information of the first vehicle and the position information of the second vehicle so as to determine that the second vehicle is positioned in front of or behind the first vehicle; when | theta-head_h∣≤90^oWhen the second vehicle is located in front of the first vehicle in the traveling direction; when | theta-head_h∣＞90^oWhen the first vehicle is in the driving rear direction, the second vehicle is positioned behind the first vehicle, wherein theta is an included angle between the first vehicle and the second vehicle, head_hIs the azimuth of the first vehicle; if the vehicle is located in the driving front, the difference value of the azimuth angle corresponding to the azimuth angle information of the first vehicle and the azimuth angle corresponding to the azimuth angle information of the second vehicle is compared with the preset valueMatching azimuth angle ranges to determine the scene types, wherein the preset azimuth angle ranges correspond to the scene types one by one; when | head_n-head_h∣＜20^oWhen the vehicle is running, the second vehicle runs in the same direction relative to the first vehicle; when | head_n-head_h∣＞160^oWhen the vehicle is running, the second vehicle runs in the reverse direction relative to the first vehicle; when 20 is turned on^o＜（head_n-head_h）＜160^oWhen the vehicle is running, the second vehicle is in left crossing driving relative to the first vehicle; when-160^o＜（head_n-head_h）＜-20^oWhile the second vehicle is traveling right-cross to the first vehicle, wherein the head_nIs the azimuth of the second vehicle;

the first vehicle is used for calculating the relative driving speed of the first vehicle and the second vehicle according to the speed information and the azimuth angle information of the first vehicle and the speed information and the azimuth angle information of the second vehicle when the scene type is cross driving and the preset collision early warning algorithm is a cross collision early warning algorithm; calculating a projection value of the relative running speed on a connecting line of position points of the first vehicle and the second vehicle according to the position information of the first vehicle and the position information of the second vehicle; calculating a collision time of the first vehicle with the second vehicle according to the distance between the first vehicle and the second vehicle and the projection value; and determining corresponding risk coefficients according to the range of the collision time, wherein different collision time ranges correspond to different risk coefficients.