CN111145589B - Vehicle omnidirectional anti-collision warning system based on vector algorithm - Google Patents

Abstract

The invention provides a vehicle omnidirectional anti-collision early warning system based on a vector algorithm, which belongs to the technical field of vehicle anti-collision early warning, and includes a data acquisition module to collect own vehicle information, target vehicle information and road information; The target vehicle information and road information calculate the warning information between the own vehicle and the target vehicle; the warning time and collision direction of the own vehicle and the target vehicle; the collision avoidance strategy module formulates the collision avoidance strategy for the own vehicle and the target vehicle to avoid collision according to the warning information; The collision warning module outputs warning information and collision avoidance strategies. The vector-based vehicle collision early warning algorithm of the present invention fully considers the actual position of the GPS positioning device in the vehicle, establishes a physical model based on the actual length and width of the vehicle in the early warning algorithm, and realizes the 360° full range of the vehicle in different scenarios. Azimuth collision warning, the algorithm is suitable for all scenarios such as urban roads, intersections and curves.

Description

Vehicle omnidirectional anti-collision warning system based on vector algorithm

technical field

The invention relates to the technical field of vehicle anti-collision warning, in particular to a vehicle omnidirectional anti-collision warning system based on a vector algorithm.

Background technique

In traffic accidents, vehicle collisions cause the most serious casualties. In vehicle collision accidents, in addition to vehicle frontal collisions, rear collisions (such as rear-end collisions) and side collisions (such as intersection accidents) also account for a large proportion. The causes of collisions include fatigue driving, drunk driving, speeding and running red lights and other illegal driving. At the same time, the driver's vision is blocked by weather (such as rain, snow, fog) or physical conditions (such as curves, intersections). , is also an important cause of vehicle crashes.

For vehicle collision warning, although the traditional adaptive cruise technology is relatively mature, these systems rely heavily on range sensor equipment such as vehicle radar, lidar or camera, which are usually expensive and need to meet the accuracy and stability of the safety warning system. Requirements, the price of the above equipment is even higher than the price of an ordinary car, it is impossible to popularize and apply at this stage. At the same time, the range sensor is easily interfered by factors such as bad weather and physical conditions, and the detection performance and detection range are limited. In some key scenarios (such as high-speed traffic flow scenarios), the adaptive cruise system still has many problems and cannot meet the safety requirements. At the same time, due to the limitation of sensor placement, the adaptive cruise system can only consider rear collisions, and it does not fully consider the side collision of vehicles, so its effectiveness in safety warning is very limited.

Emerging approaches use vehicle-to-vehicle (V2V) communication technology, which allows vehicles to exchange physical, motion, and trajectory information within their communication range. V2V technology is not affected by severe weather conditions, and the system has high applicability. One of the more in-depth research is dedicated short-range communication (DSRC) technology. Dedicated Short-Range Communication (DSRC) allows vehicles to communicate with each other, and DSRC-based Rear Collision Warning System (ReCWS) has its own unique advantages. However, there are some difficult problems in the early warning system based on DSRC, such as high false alarm rate and lost alarm rate. Limited by the data transmission quality of DSRC technology itself, it is impossible to improve the accuracy and stability of the ReCWS system only through parameter correction. On the other hand, the DSRC-based ReCWS system has not yet considered the information transmission delay in the process from data acquisition to warning decision-making, and has not considered the impact of GPS errors on the safety distance.

VANET uses the Dedicated Short-Range Communication (DSRC) standard, which uses a 75MHz bandwidth (in the 5.9GHz band), and these standards allow communication ranges from 300m to 1000m. But in practice, the DSRC transmission range is affected by many external factors such as physical conditions. Existing VANET standards are insufficient to meet the requirements of VANET's promised services, especially security services. Currently available VANET standards (IEEE 802.11p/DSRC) suffer from low bandwidth and transmission range due to low 5.9GHz band utilization and short communication range, while cellular networks (3G, LTE, and LTEA) suffer from high latency and information security issues. trouble, which poses a challenge to current security applications.

In current autonomous driving and driver assistance systems, lane-level vehicle self-localization is a challenging and significant problem. Almost all current collision warning systems do not consider lane-level positioning. Most of the collision warning models establish the assumption that vehicles always drive in one lane. These systems cannot be applied to multi-lane highways and urban road scenarios in practical situations. Lane-level positioning not only requires high-precision maps, but also expensive compensation equipment and government policy support. Although the collision warning model proposed in the present invention does not propose a compensation algorithm for lane-level positioning, the vector-based vehicle collision warning algorithm can be implemented by The change of vehicle speed and acceleration direction predicts the collision of vehicles in different lanes, and then releases all-round collision warning information for vehicles.

In terms of collision warning algorithms, most of the current researches only focus on the rear collision warning system (ReCWS). Based on the assumption that the vehicle always accelerates uniformly and that all vehicles are in the same lane, a simple early warning algorithm based on the linear physical motion model of the vehicle is proposed. , the vehicle safety distance or time interval is simply used as the basis for the judgment of collision, and it is impossible to accurately consider the change of collision and collision caused by the change of speed and acceleration direction. to collision. However, the problem of vehicle side collision caused by the obstruction of sight distance in the scene of urban intersections and curves accounts for a high proportion of actual accidents. Although there is a collision warning system for curved roads, the algorithm of this system is not fully applicable to straight roads. At the same time, multiple on-board sensors and curved roadside node units need to be installed, which heavily relies on V2I communication technology, and the equipment cost is extremely high. Based on this, the present invention proposes a vector-based vehicle collision warning algorithm, which calculates and analyzes the collision situation based on the change of the relative position of the vehicle, and realizes the 360° all-round collision warning of the vehicle in different scenarios. The algorithm is suitable for urban roads, intersections and bends. Road and all other scenarios.

On the other hand, all current collision warning algorithms do not consider the physical conditions of the vehicle itself. Under the assumption that the GPS positioning device is installed in the middle of the vehicle, only the GPS positioning result is used as the center of the circle to create a circular area with a specific radius. Indicates the vehicle location. At the same time, for large vehicles, the current warning algorithms almost do not consider the length and width of the vehicle body separately. Therefore, most of the current early warning algorithms have a high false alarm rate. In high-density traffic flow scenarios, vehicles will continue to alarm, which will seriously affect the driver's driving experience. At the same time, the high false alarm rate will also obscure the real early warning information and seriously restrict the early warning. system performance. Based on this, the present invention proposes a vector-based vehicle collision warning algorithm. The algorithm fully considers the actual position of the GPS positioning device in the vehicle, and sets a number of characteristic information such as the model, color, and physical size of the own vehicle during system installation. In the early warning algorithm, a physical model based on the actual length and width of the vehicle is established, which largely solves the problems of high false alarm rate and high lost alarm rate of the current early warning system.

In terms of hardware equipment of the early warning system, most of the current early warning systems are based on DSRC technology, and it is necessary to install on-board DSRC equipment, on-board smart computer and on-board display screen separately. However, the equipment that meets the safety warning performance is expensive, and the technical transformation of the vehicle is complicated, which does not meet the conditions for promotion. Based on this, the present invention proposes vehicle collision warning based on 5G communication and with the aid of mobile intelligent terminal equipment. The system only needs one mobile smart terminal device (such as a smart phone) to meet the equipment requirements of the security early warning system. The mobile smart terminal device obtains part of the motion information of its own vehicle through the USB data interface. The data analysis process is in the mobile smart terminal device. Running in the background does not affect other normal operations of the equipment. The system outputs graded early warning information and graded early warning collision avoidance strategies according to the emergency level of the warning. Vehicles and mobile intelligent terminal devices can also output collision avoidance strategies to the vehicle controller to realize automatic collision avoidance under emergency warning. At the same time, the system can also record accident data to provide data support for vehicle driving safety analysis. The vehicle omnidirectional collision warning system based on 5G communication proposed by the present invention does not need to refit the vehicle or add redundant physical equipment, is simple and convenient to operate, has extremely low operating cost, and can be popularized and used on the premise of satisfying the performance of the safety warning system.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a vehicle omnidirectional anti-collision warning system based on a vector algorithm, so as to solve at least one technical problem existing in the above background technology.

In order to achieve the above object, the present invention has adopted the following technical solutions:

The invention provides a vehicle omnidirectional anti-collision early warning system based on a vector algorithm, comprising a data acquisition module, a data transmission module, an early warning information calculation module, a collision avoidance strategy module and a collision early warning module;

The data collection module is used to collect own vehicle information, target vehicle information and road information, and send it to the data transmission module;

The data transmission module is configured to receive the own vehicle information, target vehicle information and road information collected by the data collection module, store them, and send them to the early warning information calculation module;

The early warning information calculation module is used to calculate the early warning information between the own vehicle and the target vehicle according to the own vehicle information, the target vehicle information and the road information; wherein, the early warning information includes: the early warning time of the own vehicle and the target vehicle and Collision direction, the collision direction includes rear collision, forward collision, forward side collision and side collision;

The collision avoidance strategy module is configured to formulate a collision avoidance strategy for avoiding a collision between the own vehicle and the target vehicle according to the warning information;

The collision warning module is used for outputting the warning information and collision avoidance strategy.

Preferably, the data collection module obtains the road information through a cloud electronic map; the data collection module obtains the own vehicle information through the vehicle OBD unit; the data collection module obtains the target vehicle information through the V2V Internet of Vehicles.

Preferably, the road information includes road physical information, road speed limit information and route navigation information; the own vehicle information includes motion information of the own vehicle and physical information of the own vehicle; the target vehicle information includes motion information of the target vehicle and Physical information of the target vehicle;

The motion information of the own vehicle includes the position, speed and acceleration information of the own vehicle, and the motion information of the target vehicle includes the position, speed and acceleration information of the target vehicle;

The physical information of the own vehicle includes the color, model and body size information of the own vehicle, and the physical information of the target vehicle includes the color, model and body size information of the target vehicle; the physical information of the own vehicle is preset in the own vehicle. In the on-board GPS system of the target vehicle, the physical information of the target vehicle is preset in the on-board GPS system of the target vehicle.

Preferably, the data transmission module is a 5G communication module.

Preferably, the early warning information calculation module includes:

a position calculation unit, configured to calculate the minimum relative position distance between the own vehicle and the target vehicle and the time when the minimum relative position distance occurs according to the own vehicle information and the target vehicle information;

The collision occurrence judgment unit is configured to judge the collision direction of the own vehicle and the target vehicle according to the minimum relative position distance and the time when the minimum relative position distance occurs, combined with the body size information.

Preferably, the collision warning module includes an intelligent mobile terminal, and the intelligent mobile terminal displays/broadcasts the collision information; or, the intelligent mobile terminal displays/broadcasts the collision avoidance strategy.

Preferably, the calculation by the position calculation unit of the minimum relative position distance between the own vehicle and the target vehicle and the time when the minimum relative position distance occurs includes:

When t is sufficiently small, it can be considered that the vehicle performs a uniform shifting motion within i time periods of t, and the motion formula is used to calculate the speeds VA _,i+1 and _VB,i+ of the own vehicle A and the target vehicle B in the next time interval respectively. ₁ and the displacements D _A,i , D _B,i passed in the t time interval:

Among them, VA _,i represents the initial speed of vehicle A at the ith time interval t, _VB,i represents the initial speed of vehicle B at the ith time interval t, and A _A,i represents the vehicle A at the ith time The acceleration of the interval t, A _{B, i} represents the acceleration of the vehicle B in the ith time interval t;

The position of the vehicle A at the end of the ith time interval t: P _A,i+1 =P _A,i +D _A,i ; the position of the vehicle B at the end of the ith time interval t: P _B,i+1 = P _B,i +D _B,i ;

Among them, P _A,i and P _B,i respectively represent the positions of vehicle A and vehicle B at the beginning of the ith time interval t;

D _AB,i represents the separation distance between vehicle A and vehicle B at the beginning of the i-th time interval t, then, the separation distance between vehicle A and vehicle B at the beginning of the i+1-th time interval t is:

D _AB,i+1 =D _AB,i +D _B,i -D _A,i ;

Find a point C on the connection line between P _B,i and P _B,i+1 , so that P _A,i is perpendicular to P _B,i P _B,i+1 ;

When the time interval t is small enough, the relative position of vehicle B and vehicle A moves from P _B,i along the line segment P _B,i P _B,i+1 to P _B,i+1 , that is, when vehicle B moves to point C , the relative distance between vehicle B and vehicle A is the shortest, and the vector AC represents the position vector of vehicle B and vehicle A at this time, and the length |AC| of line segment AC is the small relative position distance between vehicle A and vehicle B; The time for the minimum relative position distance is:

Preferably, the collision occurrence judging unit judging the collision direction of the own vehicle and the target vehicle includes:

When vehicle A and vehicle B move in the same direction, if |AC| is less than the backward warning distance, it is judged as a backward collision warning; wherein, the backward warning distance is L _W =L _A,A +L _B,B +L _S , L _{A, A} represents the length of the front of the vehicle A, that is, the distance between the installation position of the GPS system of the A vehicle and the front of the A vehicle, and L _{B, B} represents the length of the rear of the vehicle B, that is, the installation position of the GPS system of the B vehicle is the same as B distance from the rear of the car, L _S represents the preset additional safety distance;

When vehicle A and vehicle B move in opposite directions, if |AC| is less than the forward warning distance, it is judged as a forward collision warning; wherein, the forward warning distance L _W =L _{A, A} + L _{A, B} + L _S ;L _{A, B} represents the length of the front of the vehicle B, that is, the distance between the installation position of the GPS system of the B vehicle and the front of the B vehicle;

其中，W_B表示车辆B的宽度；When vehicle A and vehicle B move vertically, if |AC| is less than the positive lateral warning distance, it is judged as a positive lateral collision warning; among them, the positive lateral warning distance

Among them, WB represents the width of vehicle _B ;

其中，L_R,A表示车辆A的前侧向长度，即A车的GPS系统的安装位置与A车头外轮廓的最大距离。When vehicle A and vehicle B move laterally, if |AC| is less than the lateral warning distance, it is judged as a lateral collision warning; among them, the lateral warning distance

Among them, LR _,A represents the front lateral length of vehicle A, that is, the maximum distance between the installation position of the GPS system of vehicle A and the outer contour of the front of vehicle A.

Preferably, the collision avoidance strategy module, according to the warning information, formulates a collision avoidance strategy for avoiding a collision between the own vehicle and the target vehicle, including:

At the current initial speed, the minimum relative position distance between the early warning vehicle and the target vehicle is calculated to be greater than or equal to the minimum deceleration required for the safety warning distance; the warning level is determined according to the minimum deceleration, and the corresponding collision avoidance strategy is determined according to the warning level .

Preferably, the calculation method of the minimum deceleration a _s is as follows:

The shortest distance between the early warning vehicle and the target vehicle occurs when the relative speed of the two vehicles is 0, then:

ΔV ² -0 ² =2a _s (D _AB -L _W )

Among them, ΔV represents the speed difference between the own vehicle and the target vehicle.

The invention has beneficial effects: higher capacity, end-to-end ultra-low delay, higher data rate, and device connectivity are realized; D2D supports direct discovery of services and communication between nearby users, and realizes direct V2V and V2I communication, No need to traverse cellular infrastructure and traditional cellular (i.e. uplink/downlink) communications; D2D-based in-vehicle radio can achieve high spectral efficiency, high data transfer rates, low transmission power, and low latency, supporting data encryption via user plane and network slicing , safety parameters can be adjusted; the vector-based vehicle collision warning algorithm fully considers the actual position of the GPS positioning device in the vehicle, and sets the vehicle's model, color, physical size and other characteristic information when the system is installed. In the early warning algorithm, a physical model based on the actual length and width of the vehicle is established to realize the 360° all-round collision warning of the vehicle in different scenarios. The algorithm is suitable for all scenarios such as urban roads, intersections and curves.

Additional aspects and advantages of the present invention will be set forth in part in the following description, which will be apparent from the following description, or may be learned by practice of the present invention.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without any creative effort.

FIG. 1 is a schematic block diagram of the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 1 of the present invention.

FIG. 2 is a principle block diagram of the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 2 of the present invention.

FIG. 3 is a schematic diagram of the operation flow of the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 2 of the present invention.

4 is a schematic diagram showing an early warning interface of an intelligent terminal of a vehicle omnidirectional anti-collision early warning system based on a vector algorithm according to Embodiment 2 of the present invention.

FIG. 5 is a schematic diagram of displaying early warning information on a vehicle instrument panel of a vehicle omnidirectional anti-collision early warning system based on a vector algorithm according to Embodiment 2 of the present invention.

FIG. 6 is a schematic diagram of calculating the distance vector between vehicles in the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 3 of the present invention.

7 is a schematic diagram of the distance between two vehicles when the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 3 of the present invention calculates that the moving directions of the two vehicles do not change.

8 is a schematic diagram of the distance between two vehicles when the vehicle omnidirectional anti-collision warning system based on the vector algorithm according to Embodiment 3 of the present invention calculates that the moving directions of the two vehicles change.

FIG. 9 is a schematic diagram of judging the early warning direction of the vehicle omnidirectional anti-collision early warning system based on the vector algorithm according to Embodiment 3 of the present invention.

10 is a flow chart of formulating a collision avoidance strategy for a vehicle omnidirectional anti-collision warning system based on a vector algorithm according to Embodiment 3 of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below through the accompanying drawings are exemplary and are only used to explain the present invention, but not to be construed as a limitation of the present invention.

It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as herein, are not to be taken in an idealized or overly formal sense. explain.

It will be understood by those skilled in the art that the singular forms "a", "an", "the" and "the" as used herein can include the plural forms as well, unless expressly stated otherwise. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of stated features, integers, steps, operations, elements and/or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements and/or groups thereof.

In the description of this patent, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", The orientation or positional relationship indicated by "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present patent and simplifying the description, rather than indicating or implying The device or element referred to must have, be constructed, and operate in a particular orientation and is not to be construed as a limitation of this patent.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present invention. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and combine the different embodiments or examples described in this specification, as well as the features of the different embodiments or examples, without conflicting each other.

In the description of this patent, it should be noted that the terms "first" and "second" are only used for description purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, a feature delimited with "first", "second" may expressly or implicitly include at least one of that feature. In the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

Unless otherwise expressly specified and limited, the terms "installed", "connected", "connected" and "arranged" should be understood in a broad sense, for example, it may be fixedly connected, arranged, or detachably connected, arranged, or integrated ground connection and settings. For those of ordinary skill in the art, the specific meanings of the above terms in this patent can be understood according to specific situations.

In order to facilitate the understanding of the present invention, the present invention will be further explained and described below with reference to the accompanying drawings with specific embodiments, and the specific embodiments do not constitute limitations to the embodiments of the present invention.

Those skilled in the art should understand that the accompanying drawings are only schematic diagrams of the embodiments, and the components in the accompanying drawings are not necessarily necessary to implement the present invention.

Example 1

Embodiment 1 of the present invention provides an omnidirectional anti-collision warning system for vehicles. The system uses global satellite navigation and positioning technology (GPS/Beidou positioning) to accurately obtain the position information of the current vehicle, and uses 5G communication-based vehicle-vehicle communication (Vehicle-vehicle communication). to-Vehicle, V2V) technology selectively transmits the position, physical and motion information of target vehicles with potential collision risk in the area, and uses the vector-based omnidirectional collision warning algorithm to calculate and analyze the collision situation based on the change of the relative position of the vehicle to achieve 360° all-round collision warning for vehicles in different scenarios such as urban roads, intersections and curves. Use intelligent mobile terminal devices (such as smart phones) to send collision classification warning information to the driver to assist the driver in safe driving. In an emergency, the system can directly output the collision avoidance strategy to the vehicle controller. Through the advanced driver assistance system (ADAS, Advanced Driver Assistance System) implements collision avoidance strategies such as automatic deceleration, direction change or emergency braking. Finally, the purpose of reducing the risk of vehicle collision in different scenarios and improving driving safety is achieved.

As shown in Figure 1, the vehicle omnidirectional anti-collision warning system based on the vector algorithm includes: a data acquisition module, a data transmission module, an early warning information calculation module, a collision avoidance strategy module and a collision warning module;

The data collection module is used to collect own vehicle information, target vehicle information and road information, and send it to the data transmission module;

The data transmission module is configured to receive the own vehicle information, target vehicle information and road information collected by the data collection module, store them, and send them to the early warning information calculation module;

The early warning information calculation module is used to calculate the early warning information between the own vehicle and the target vehicle according to the own vehicle information, the target vehicle information and the road information; wherein, the early warning information includes: the early warning time of the own vehicle and the target vehicle and Collision direction, the collision direction includes rear collision, forward collision, forward side collision and side collision;

The collision avoidance strategy module is configured to formulate a collision avoidance strategy for avoiding a collision between the own vehicle and the target vehicle according to the warning information;

The collision warning module is used for outputting the warning information and collision avoidance strategy.

The data collection module obtains the road information through the cloud electronic map; the data collection module obtains the own vehicle information through the vehicle OBD unit; the data collection module obtains the target vehicle information through the V2V Internet of Vehicles.

The road information includes road physical information, road speed limit information and route navigation information; the own vehicle information includes the own vehicle motion information and the own vehicle physical information; the target vehicle information includes the target vehicle motion information and the target vehicle's physical information. physical information;

The motion information of the own vehicle includes the position, speed and acceleration information of the own vehicle, and the motion information of the target vehicle includes the position, speed and acceleration information of the target vehicle;

The physical information of the own vehicle includes the color, model and body size information of the own vehicle, and the physical information of the target vehicle includes the color, model and body size information of the target vehicle; the physical information of the own vehicle is preset in the own vehicle. In the on-board GPS system of the target vehicle, the physical information of the target vehicle is preset in the on-board GPS system of the target vehicle.

The data transmission module is a 5G communication module.

The early warning information calculation module includes:

a position calculation unit, configured to calculate the minimum relative position distance between the own vehicle and the target vehicle and the time when the minimum relative position distance occurs according to the own vehicle information and the target vehicle information;

The collision occurrence judgment unit is configured to judge the collision direction of the own vehicle and the target vehicle according to the minimum relative position distance and the time when the minimum relative position distance occurs, combined with the body size information.

The collision warning module includes an intelligent mobile terminal, and the intelligent mobile terminal displays/broadcasts the collision information; or, the intelligent mobile terminal displays/broadcasts the collision avoidance strategy.

Example 2

Embodiment 2 of the present invention provides a vehicle omnidirectional anti-collision warning system based on 5G communication and vector algorithm. The system completes the analysis of the collision information through the acquisition of the physical and motion information of the own vehicle and the acquisition of the physical and motion information of the target vehicle in the area. Calculation and formulation and publication of collision avoidance strategies.

As shown in Figure 2 and Figure 3, the system mainly includes data acquisition equipment, data analysis equipment, information release equipment and vehicle-workshop communication. Among them, 1) data collection: the information to be collected in the vehicle collision warning system includes road information, vehicle physical information and vehicle motion information. Road information includes road physical information, road speed limit information, route navigation information, etc. within a certain range of the own vehicle, which is mainly obtained through the electronic map in the cloud. Vehicle physical information includes vehicle physical size, color, model, etc., and is mainly obtained through the initial setting of the early warning system. Vehicle motion information includes real-time vehicle position, motion direction, speed, acceleration, etc., and is divided into own vehicle motion information and target vehicle motion information. 5G-based V2V Internet of Vehicles communication; 2) Data transmission (sharing): Each vehicle can accurately collect its own physical information and motion information, and transmit (share) it to possible collisions in the area through 5G-based V2V Internet of Vehicles communication. 3) Data analysis: After receiving the physical and motion information of the target vehicle, combined with the physical and motion information of the own vehicle, the vector-based vehicle omnidirectional collision warning algorithm is used to calculate and analyze whether there is a collision, the object vehicle that has collided, and 4) Information output: output the collision warning information and the collision avoidance strategy corresponding to the graded warning information, provide driving suggestions for the driver, and assist the driver to implement the collision avoidance strategy.

Specifically, the structural composition of the vehicle omnidirectional anti-collision warning system based on 5G communication and vector algorithm shown in Embodiment 2 of the present invention is mainly as follows:

1. Data acquisition equipment

Data acquisition equipment is divided into two parts: vehicle data acquisition equipment and mobile intelligent terminal equipment.

(1) Vehicle data acquisition equipment

The on-board data acquisition equipment integrates the acceleration sensor into the on-board diagnostic system (OBD, on-board diagnostic) to obtain the speed, acceleration, steering angle and other data of the own vehicle in real time.

(2) Mobile intelligent terminal equipment

Mobile intelligent terminal equipment is the core equipment of the system, and the data collection is divided into two parts: own vehicle data collection and target vehicle data collection. During the data collection process of the own vehicle, the driver sets the physical information such as the vehicle type, color, front length, and body width of the own vehicle before the system is used; during the operation of the system, the mobile intelligent terminal device uses the built-in GPS module to accurately locate the vehicle's position information , to obtain the longitude, latitude and other data of the own vehicle. The data collection process of the target vehicle is described in the following information receiving equipment section.

2. Information receiving equipment

The information receiving process of this early warning system is mainly realized through mobile intelligent terminal equipment. Mobile intelligent terminal equipment uses its built-in communication module and mature 5G communication technology to achieve high-quality transmission and reception of information. In order to ensure the efficiency and quality of information transmission and reception, the system will initially screen the objects of data transmission and reception through algorithms, and selectively transmit information on potential target vehicles that may collide.

3. Information analysis equipment

The information analysis process of this early warning system is mainly realized by the early warning software installed on the mobile intelligent terminal equipment. The software has built-in vector-based vehicle omnidirectional collision early warning algorithms and corresponding collision avoidance strategies. The information analysis process runs in the background of the system, and the interface is not designed separately, but it occupies more computing resources of the mobile intelligent terminal device and does not affect other operations of the mobile intelligent terminal device. The system uses the collected physical and motion information of its own vehicle and the target vehicle, and uses the vehicle omnidirectional collision warning algorithm to analyze and calculate information such as whether a collision occurs, the object vehicle that collided, and the time of the collision, and formulate corresponding avoidance. collision strategy.

4. Information output equipment

In this embodiment, the three contents of the mobile intelligent terminal device speaker, the mobile intelligent terminal device display screen and the advanced driving assistance system are used to jointly guide the driver's driving behavior, provide the driver with driving advice, and assist the driver to implement the collision avoidance strategy. To achieve the purpose of improving driving safety.

(1) Speakers of mobile smart terminal equipment

In this embodiment, the released graded warning information is mainly divided into two ways: auditory and visual. The auditory warning information is released in real time through the speaker of the mobile smart terminal device. When the mild warning information is issued, the loudspeaker emits a "di" alarm; when the moderate warning information is issued, the loudspeaker emits three consecutive "di, di, di" alarms; when the emergency warning information is issued, the loudspeaker emits a continuous high-pitched buzzer alarm . The sound warning alarm has the highest authority of the speaker of the mobile smart terminal device. When the alarm is triggered during the playback of music or a call, the current speaker content will be turned off and the warning information will be released. When the warning level decreases step by step, the sound warning alarm decreases step by step.

(2) Mobile intelligent terminal equipment display screen/vehicle dashboard display screen

In the embodiment of the present invention, the visual warning information of the system is released in real time through the display screen of the mobile intelligent terminal device, and mainly displays the warning level and the relevant information of the target vehicle of the warning.

This early warning system can output a number of information such as the current speed of the own vehicle, the expected safe speed, the minimum deceleration, the current speed of the target vehicle, the model, the color, and the estimated time of the collision, but as a safety early warning system, the main purpose is to provide drivers with Timely and accurate driving suggestions and collision avoidance strategies, if too much information is released, it will be difficult for drivers to obtain important information and make decisions in a very short period of time, and the safety warning performance of the system will be reduced accordingly. Therefore, the default warning information release interface of the system is shown in Figure 4. The system does not have a dedicated page. When a collision alarm is triggered, the system will pop up an early warning interface in the form of a pop-up window.

On the top of the warning interface are graded warning symbols, which are distinguished by different signs and colors. For example, a blue triangle sign is a mild warning, a yellow triangle sign is a moderate warning, and a red brake sign is an emergency warning. In the middle of the interface is a text reminder of the collision avoidance strategy, with "deceleration", "brake" and "brake" corresponding to the collision avoidance strategy of three warning levels. At the same time, the relative position and physical information of the collision target vehicle will be released, and the relative position of the target vehicle will be prompted with "front", "left", "right", etc. ”, “car”, etc. to prompt the model information of the target vehicle. The above information can help the driver to quickly locate the target vehicle that may collide and implement the corresponding collision avoidance strategy.

At the bottom of the interface is the speed instrument panel icon, in which the pointer points to the real-time speed of the own vehicle, and the speed range is distinguished by different colors, such as red, yellow, and green. The red zone represents the dangerous speed zone where a collision will occur or the speeding zone of the current road section; the green zone represents the safe speed zone that can avoid collision or the expected or comfortable speed zone under the current road section and traffic flow conditions; the yellow zone is red The transition interval between the interval and the green interval indicates a speed interval in which there is a potential collision risk and the driver needs to increase their attention or decelerate further to avoid the collision risk. The range of each level of interval changes continuously with the change of vehicle operation. If the instrument panel of your own vehicle can be displayed intelligently, the system can send the speed interval data to the on-board computer and display it directly on the vehicle instrument panel. The vehicle instrument panel display interface The design is shown in Figure 5, which can display information such as the relative position of the early warning target vehicle and its own vehicle, the type and color of the target vehicle in real time. Users can also customize the warning interface and choose to display more warning information.

(3) Advanced driver assistance system MCU controller

For vehicles already equipped with advanced driving assistance systems, the present invention will output collision avoidance strategies such as automatic deceleration, lane change, and braking to the vehicle MCU controller in the event of an emergency warning, so that the vehicle can avoid collisions with correct and precise operations in time. The data signal sends the collision avoidance strategy to the MCU through USB communication through the data interface of the mobile intelligent terminal device, avoiding the driver's reaction time, improving the reliability of braking, thereby increasing the reliability and safety of the early warning system .

Example 3

Embodiment 3 of the present invention proposes a vector-based omnidirectional vehicle collision warning algorithm, which fully considers the actual position of the GPS positioning device in the vehicle, and sets a number of characteristic information such as the vehicle type, color, and physical size of the vehicle when the system is installed. , In the early warning algorithm, a physical model based on the actual length and width of the vehicle is established, and the collision situation is calculated and analyzed based on the change of the relative position of the vehicle, so as to realize the 360° all-round collision warning of the vehicle in different scenarios. The algorithm is suitable for urban roads, All scenarios such as intersections and bends.

Algorithm notation explanation:

The car A represents the self-warning vehicle, and the car B represents the target vehicle for early warning; the self-warning vehicle is a vehicle that can effectively avoid collision by decelerating or braking.

P _A,i and P _B,i respectively represent the coordinate positions of vehicle A and vehicle B at the beginning of the ith time interval t;

The vector D _AB,i represents the distance vector between vehicle A and vehicle B at the beginning of the ith time interval t, including the distance length and direction;

Vectors VA _,i and _VB,i respectively represent the speed of vehicle A and vehicle B at the beginning of the ith time interval t, including the speed and direction;

Vectors A _A,i and A _B,i respectively represent the accelerations of vehicle A and vehicle B at the beginning of the ith time interval t, including the magnitude and direction of the acceleration;

The vectors D _A,i and D _B,i respectively represent the displacement of vehicle A and vehicle B passing through the time interval t, including the magnitude and direction of the displacement;

t is the minimum time interval of the early warning algorithm, which is related to the GPS position refresh frequency and speed acquisition frequency. The smaller the value, the higher the early warning accuracy;

T is the time when the minimum relative position distance to the target vehicle occurs.

Algorithm running process:

As shown in Figure 6, when t is sufficiently small, it can be considered that the vehicle performs a uniform shifting motion in i time periods of t, and the motion formula is used to calculate the speed V _A,i+1 of the own vehicle A and the target vehicle B in the next time interval respectively. , _VB,i+1 and the displacements D _A,i , D _B,i passed in the time interval t:

Among them, VA _,i represents the initial speed of vehicle A at the ith time interval t, _VB,i represents the initial speed of vehicle B at the ith time interval t, and A _A,i represents the vehicle A at the ith time The acceleration of the interval t, A _{B, i} represents the acceleration of the vehicle B in the ith time interval t;

When the car performs non-linear motion within the time interval t, that is, when the speed is inconsistent with the direction of acceleration (in the actual scene, it means that the car passes through a curve or turns at an intersection), the vector operation of the kinematic formula is still applicable, and the specific operation process is here. No longer.

The position of the vehicle A at the end of the ith time interval t: P _A,i+1 =P _A,i +D _A,i ; the position of the vehicle B at the end of the ith time interval t: P _B,i+1 = P _B,i +D _B,i ;

Among them, P _A,i and P _B,i respectively represent the positions of vehicle A and vehicle B at the beginning of the ith time interval t;

D _AB,i represents the separation distance between vehicle A and vehicle B at the beginning of the i-th time interval t, then, the separation distance between vehicle A and vehicle B at the beginning of the i+1-th time interval t is:

D _AB,i+1 =D _AB,i +D _B,i -D _A,i ;

Based on the new position vector, the velocity and acceleration of the next time interval, the above operation is repeated continuously to obtain the position vector of the next time interval. As shown in Figure 7 and Figure 8, a point C can always be found on the connection line between PB _,i and PB _,i+1 , so that AC is perpendicular to PB _,i PB _,i+1 . When the time interval t is sufficiently small, it can be considered that the relative positions of vehicle B and vehicle A move from P _B,i along the line segment P _B,i P _B,i+1 to P _B,i+1 , that is, when vehicle B moves to C At the point, the relative distance between vehicle B and vehicle A is the shortest, and the position vector of vehicle B and vehicle A at this time is represented by vector AC. The length |AC| of the line segment AC is the minimum relative position distance between vehicle A and vehicle B; then, the time when the minimum relative position distance occurs is:

Collision judgment rules:

Collision judgment rules determine what calculation results will be considered collisions. In this embodiment, the physical size of the vehicle is considered first. Due to different types of vehicles, there are obvious differences in the length and width of vehicles, which cannot be ignored in collision warning, and whether the physical size of vehicles is considered adequately or not will significantly affect the accuracy of collision warning. At the same time, the GPS positioning device (i.e., the intelligent mobile terminal) of the system is installed on the control panel in front of the driving seat of the vehicle.

in:

在确定车辆间的最短相对位置距离后，即可根据相对位置向量的不同方向分别计算是否发生碰撞，判断过程如图9所示： _W represents the total width of the vehicle; LA represents the length of the front of the vehicle, that is, the distance between the driver's seat control panel and the front of the vehicle; _{LB represents the rear length of the vehicle, that is, the distance between the driver's seat control panel and the rear of the vehicle; L S represents} the preset The additional safety distance of the collision warning is the same in different directions in this system; _{L W} represents the warning distance, that is, the distance of the vehicle that the system judges as a collision; _LR represents the front lateral length of the vehicle, that is, the driving position control panel and the The maximum distance of the outer contour of the front of the car can be approximated as

After determining the shortest relative position distance between vehicles, it is possible to calculate whether a collision occurs according to the different directions of the relative position vector. The judgment process is shown in Figure 9:

When vehicle A and vehicle B move in the same direction, if |AC| is less than the backward warning distance, it is judged as a backward collision warning; wherein, the backward warning distance is L _W =L _A,A +L _B,B +L _S , L _{A, A} represent the length of the front of the vehicle A, that is, the distance between the installation position of the system GPS system and the front of A, LB _{, B} represent the length of the rear of the vehicle B, that is, the driving position control panel (the installation position of the GPS system) The distance from the rear of vehicle B, L _S represents the preset additional safety distance;

When vehicle A and vehicle B move in opposite directions, if |AC| is less than the forward warning distance, it is judged as a forward collision warning; wherein, the forward warning distance L _W =L _{A, A} + L _{A, B} + L _S ;L _A,B represents the length of the front of the vehicle B, that is, the distance between the driver's position control panel and the front of B;

其中，W_B表示车辆B的宽度；When vehicle A and vehicle B move vertically, if |AC| is less than the positive lateral warning distance, it is judged as a positive lateral collision warning; among them, the positive lateral warning distance

Among them, WB represents the width of vehicle _B ;

其中，L_R,A表示车辆A的前侧向长度，即驾驶位控制面板与A车头外轮廓的最大距离。When vehicle A and vehicle B move laterally, if |AC| is less than the lateral warning distance, it is judged as a lateral collision warning; among them, the lateral warning distance

Among them, LR _,A represents the front lateral length of vehicle A, that is, the maximum distance between the driver's seat control panel and the outer contour of the front of A's vehicle.

Define the alert level:

The early warning system can not only output collision warning information, but also output corresponding collision avoidance strategies to the driver and the vehicle, as a safety assisted driving system to improve driving safety. Therefore, it is particularly important to classify the warning state and formulate the corresponding collision avoidance strategy.

An important measure for collision avoidance is deceleration, and the system can calculate the minimum deceleration corresponding to collision avoidance. But it is very difficult for the driver to maintain a certain deceleration after receiving the warning information. Therefore, in addition to outputting the corresponding deceleration, the system should also output the collision avoidance strategy of the corresponding level.

In this embodiment, according to the warning information, the collision avoidance strategy module formulates a collision avoidance strategy for avoiding a collision between the own vehicle and the target vehicle, including:

At the current initial speed, the minimum relative position distance between the early warning vehicle and the target vehicle is calculated to be greater than or equal to the minimum deceleration required for the safety warning distance; the warning level is determined according to the minimum deceleration, and the corresponding collision avoidance strategy is determined according to the warning level .

The minimum deceleration a _s is calculated as follows:

When it is a rear collision warning, the shortest distance between the warning vehicle and the target vehicle occurs when the relative speed of the two vehicles is 0, then:

ΔV ² -0 ² =2a _s (D _AB -L _W )

Where ΔV=V _A -V _B , that is, the speed of the early warning vehicle is reduced by the speed of the target vehicle. In this example of rear collision warning, it can be understood that the speed of the rear vehicle is reduced by the speed of the front vehicle.

The calculation formula of a _s is the same in all collision types in all directions, and the calculation formula of ΔV is also the same. The above announcement is applicable to vector calculation. The relative position and direction are different to distinguish different collision situations.

The current related research has not proposed a collision algorithm that is applicable to all directions. The above-mentioned vector calculation method proposed in this embodiment can succinctly and uniformly determine collision warnings in all directions.

As shown in FIG. 10 , in this embodiment, the judgment of the graded warning strategy of the vehicle omnidirectional collision warning algorithm is as follows: the reference accelerations ^-2m /s2 and ^-5.5m /s2 of the set graded range can be used in different road conditions and Appropriate adjustment to vehicle conditions. The proposed collision avoidance strategy is shown in Table 1.

Table 1:

First, calculate whether the collision can be avoided with the acceleration of -2m/s ² . If the collision can be avoided effectively, the output is a mild warning ^; If the collision can be effectively avoided, the output is a moderate warning; otherwise, the output is an emergency warning, and a suitable braking and lane-changing strategy is immediately formulated, requiring the vehicle ADAS system to execute immediately. As the vehicle speed gradually decreases, the collision warning level will gradually decrease, and the warning information will be released step by step, which helps the driver to intuitively feel the cancellation of the collision warning.

To sum up, the vehicle anti-collision warning system based on the vector algorithm described in the embodiment of the present invention makes full use of the characteristics of high data transmission rate, low transmission power and low delay enabled by 5G communication in D2D communication, making up for the traditional cellular network ( 3G, LTE and LTEA) and DSRC technology have the disadvantages of low frequency band utilization, short communication range, high data transmission delay and unguaranteed information security; the vector-based vehicle collision warning algorithm fully considers the actual position of the GPS positioning device in the vehicle , and set the vehicle's model, color, physical size and other feature information when the system is installed, and establish a physical model based on the actual length and width of the vehicle in the early warning algorithm to realize the 360° full range of the vehicle in different scenarios. Orientation collision warning, the algorithm is suitable for all scenarios such as urban roads, intersections and curves; vehicle collision warning for early warning is realized with the help of mobile intelligent terminal equipment. The system only needs a mobile smart terminal device (such as a common smart phone) to meet the equipment requirements of the security early warning system, and obtains the motion information of its own vehicle with the help of a USB data cable. The data analysis process runs in the background of the mobile smart terminal device, and Does not affect other normal operation of the device.

The system outputs graded early warning information and graded early warning and collision avoidance strategies according to the urgency of the early warning. The graded early warning information is released in the form of a floating pop-up window through sight and hearing. For vehicles equipped with a driving assistance system, the mobile intelligent terminal equipment can also directly control the vehicle. The device outputs the collision avoidance strategy to realize automatic collision avoidance under emergency warning. At the same time, the system can also record accident data to provide data support for vehicle driving safety analysis. The vehicle omnidirectional collision warning system based on 5G communication proposed in the embodiment of the present invention does not need to modify the vehicle or add redundant physical equipment, is simple and convenient to operate, and has extremely low operating cost, and can be popularized and used under the premise of satisfying the performance of the safety warning system.

The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited to this. Substitutions should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims (7)

1. A vehicle omnidirectional anti-collision early warning system based on a vector algorithm is characterized by comprising a data acquisition module, a data transmission module, an early warning information calculation module, a collision avoidance strategy module and a collision early warning module;

the data acquisition module is used for acquiring vehicle information, target vehicle information and road information and sending the information to the data transmission module;

the data transmission module is used for receiving the self vehicle information, the target vehicle information and the road information which are acquired by the data acquisition module, storing the information and sending the information to the early warning information calculation module;

the early warning information calculation module is used for calculating early warning information between the vehicle and the target vehicle according to the vehicle information, the target vehicle information and the road information; wherein the early warning information comprises: the early warning time and the collision direction of the self vehicle and the target vehicle are determined, wherein the collision direction comprises backward collision, forward and lateral collision;

the collision avoidance strategy module is used for making a collision avoidance strategy for avoiding collision between the vehicle and the target vehicle according to the early warning information;

the collision early warning module is used for outputting the early warning information and a collision avoidance strategy;

the road information comprises road physical information, road speed limit information and path navigation information; the self-vehicle information comprises self-vehicle motion information and physical information of the self-vehicle; the target vehicle information includes motion information of a target vehicle and physical information of the target vehicle;

the motion information of the vehicle comprises the position, the speed and the acceleration information of the vehicle, and the motion information of the target vehicle comprises the position, the speed and the acceleration information of the target vehicle;

the physical information of the self vehicle comprises the color, the vehicle type and the vehicle body size information of the self vehicle, and the physical information of the target vehicle comprises the color, the vehicle type and the vehicle body size information of the target vehicle; the physical information of the vehicle is preset in a vehicle-mounted GPS system of the vehicle, and the physical information of the target vehicle is preset in the vehicle-mounted GPS system of the target vehicle;

the early warning information calculation module comprises:

a position calculation unit configured to calculate a minimum relative position distance between the host vehicle and the target vehicle and a time at which the minimum relative position distance occurs, based on the host vehicle information and the target vehicle information;

the collision occurrence judging unit is used for judging the collision direction of the self vehicle and the target vehicle by combining the vehicle body size information according to the minimum relative position distance and the time when the minimum relative position distance appears;

the position calculation unit calculating the minimum relative position distance between the own vehicle and the target vehicle and the time at which the minimum relative position distance occurs includes:

when t is sufficiently small, the vehicle can be considered to do uniform variable speed motion in i time periods t, and the speed V of the vehicle A and the target vehicle B at the next time interval is respectively calculated by utilizing a motion formula_A,i+1、V_B,i+1And a passing displacement D in the t time interval_A,i、D_B,i：

V_A,i+1＝V_A,i+A_A,i×t，V_B,i+1＝V_B,i+A_B,i×t，

Wherein, V_A,iRepresenting the initial speed, V, of the vehicle A during the ith time interval t_B,iTo representInitial speed of vehicle B at i-th time interval t, A_A,iRepresenting the acceleration of the vehicle A during the ith time interval t, A_B,iRepresents the acceleration of the vehicle B at the ith time interval t;

position of vehicle a at the end of ith time interval t: p_A,i+1＝P_A,i+D_A,i(ii) a Position of vehicle B at the end of ith time interval t: p_B,i+1＝P_B,i+D_B,i；

Wherein, P_A,i、P_B,iRespectively representing the positions of the vehicle A and the vehicle B at the beginning of the ith time interval t;

D_AB，ithe separation distance between the vehicle a and the vehicle B at the beginning of the ith time interval t is represented, and then the separation distance between the vehicle a and the vehicle B at the beginning of the (i + 1) th time interval t is:

D_AB,i+1＝D_AB,i+D_B,i-D_A,i；

at P_B,iAnd P_B,i+1Find a point C on the connection line of (A) so that P_A,iPerpendicular to P_B,iP_B,i+1；

When the time interval t is sufficiently small, the relative positions of the vehicle B and the vehicle A are determined by P_B,iAlong line segment P_B,iP_B,i+1Move to P_B,i+1When the vehicle B moves to the point C, the relative distance between the vehicle B and the vehicle a is the shortest, the vector AC represents the position vector of the vehicle B and the vehicle a at the moment, and the length | AC | of the line segment AC is the minimum relative position distance between the vehicle a and the vehicle B; then, the time at which the minimum relative position distance occurs is:

2. the vehicle omnidirectional anti-collision early warning system based on the vector algorithm as claimed in claim 1, wherein: the data acquisition module acquires the road information through a cloud electronic map; the data acquisition module acquires the self-vehicle information through a vehicle OBD unit; the data acquisition module acquires the target vehicle information through the V2V Internet of vehicles.

3. The vehicle omnidirectional anti-collision early warning system based on the vector algorithm as claimed in claim 1, wherein: the data transmission module is a 5G communication module.

4. The vehicle omnidirectional anti-collision early warning system based on the vector algorithm according to claim 1, wherein the collision early warning module comprises an intelligent mobile terminal, and the intelligent mobile terminal displays/broadcasts the collision information; or the intelligent mobile terminal displays/broadcasts the collision avoidance strategy.

5. The vehicle omnidirectional anti-collision warning system based on the vector algorithm according to claim 1, wherein the collision occurrence determination unit determining the collision direction of the own vehicle with the target vehicle comprises:

when the vehicle A and the vehicle B move in the same direction, if the absolute value AC is smaller than the backward early warning distance, judging that backward collision early warning is carried out; wherein the backward early warning distance is L_W＝L_A,A+L_B,B+L_S，L_A,AIndicates the length of the head of the vehicle A, i.e. the distance between the installation position of the GPS system of the vehicle A and the head of the vehicle A, L_B,BIndicating the length of the tail of vehicle B, i.e. the distance between the GPS system of vehicle B and the tail of vehicle B, L_SRepresenting a preset additional safety distance;

when the vehicle A and the vehicle B move oppositely, if the absolute value AC is smaller than the forward early warning distance, the vehicle A and the vehicle B judge that the vehicle A and the vehicle B are in forward collision early warning; wherein, the forward early warning distance L_W＝L_A，A+L_A，B+L_S；L_A,BThe length of the head of the vehicle B is represented, namely the distance between the installation position of the GPS system of the vehicle B and the head of the vehicle B;

when the vehicle A and the vehicle B move vertically, if the absolute value AC is smaller than the positive lateral early warning distance, judging that the vehicle A and the vehicle B perform positive lateral collision early warning; wherein, the positive side direction early warning distance

Wherein, W_BRepresents the width of the vehicle B;

when the vehicle A and the vehicle B move laterally, if the absolute value AC is smaller than the lateral early warning distance, judging that the vehicle A and the vehicle B perform lateral collision early warning; wherein, the lateral early warning distance

Wherein L is_R,AThe front lateral length of the vehicle A is shown, namely the maximum distance between the installation position of the GPS system of the vehicle A and the outer contour of the head of the vehicle A.

6. The vehicle omnidirectional anti-collision early warning system based on the vector algorithm as claimed in claim 5, wherein the collision avoidance strategy module, according to the early warning information, making a collision avoidance strategy for avoiding collision between the own vehicle and the target vehicle comprises:

under the current initial speed, calculating the minimum relative position distance between the early warning vehicle and the target vehicle to be more than or equal to the minimum deceleration required by the safety early warning distance; and determining an early warning level according to the minimum deceleration, and determining a corresponding collision avoidance strategy according to the early warning level.

7. The vector algorithm-based omnidirectional anti-collision warning system for vehicles according to claim 6, wherein the minimum deceleration a is_sThe calculation method of (2) is as follows:

when the shortest distance between the early warning vehicle and the target vehicle occurs when the relative speed of the two vehicles is 0, then:

ΔV²-0²＝2a_s(D_AB-L_W)

where Δ V represents a speed difference between the own vehicle and the target vehicle.

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