WO2023273512A1

WO2023273512A1 - Early-warning method, electronic device, and computer readable storage medium

Info

Publication number: WO2023273512A1
Application number: PCT/CN2022/086697
Authority: WO
Inventors: 陈文蓉; 王亚飞; 吴胜杰; 张强
Original assignee: 中兴通讯股份有限公司
Priority date: 2021-06-30
Filing date: 2022-04-13
Publication date: 2023-01-05
Also published as: CN115547099A

Abstract

An early-warning method, an electronic device, and a computer readable storage medium. The early-warning method comprises: acquiring vehicle data of a main vehicle and vehicle data of multiple far vehicles (101); selecting, according to the vehicle data of the main vehicle and the vehicle data of the multiple far vehicles, a target far vehicle having a potential collision risk with the main vehicle (102); upon determining that the target far vehicle and the main vehicle are located on the same lane (103), predicting a relative distance between the target far vehicle and the main vehicle after a preset safety time (104); and outputting forward collision risk early-warning information when the relative distance is less than a preset safety distance (105).

Description

Early warning method, electronic device and computer readable storage medium

Cross References to Related Applications

This disclosure claims the priority of Chinese patent application CN202110739230.X filed on June 30, 2021, entitled "Early Warning Method, Electronic Device, and Computer-Readable Storage Medium", the entire contents of which are incorporated into this disclosure by reference.

technical field

Embodiments of the present disclosure relate to the technical field of Internet of Vehicles, and in particular, to an early warning method, electronic equipment, and a computer-readable storage medium.

Background technique

Forward collision warning means that when the main vehicle is driving on the road, there may be a risk of rear-end collision with a distant vehicle in the same lane ahead. Therefore, in order to detect the collision risk between the main vehicle and the vehicle in front in time, the related technologies usually adopt the following Method: Use the electromagnetic wave sensor to detect the yaw rate information of the vehicle. When it is determined according to the yaw rate information that the vehicle is in a turning state, adjust the monitoring range of the forward collision to the specified threshold. Within the specified threshold, if the forward obstacle collides with the When the collision time between vehicles and/or the time headway meet the warning conditions, a forward collision warning signal is generated and an alarm is given.

In this method, the yaw rate information of the vehicle needs to be detected by an electromagnetic wave sensor, that is, a special sensing device needs to be provided, so the cost is relatively high. Moreover, the number of forward obstacles directly affects the warning rate. If the number of forward obstacles is large, each forward obstacle must be judged whether the warning condition is satisfied, and the processing pressure is high.

Contents of the invention

The main purpose of the embodiments of the present disclosure is to provide an early warning method, an electronic device and a computer-readable storage medium, aiming at reducing the cost and processing pressure of realizing forward collision early warning and increasing the early warning rate.

In order to achieve the above purpose, an embodiment of the present disclosure provides an early warning method, including: acquiring the vehicle data of the main vehicle and the vehicle data of multiple remote vehicles; data, to screen out the target remote vehicle that has a potential collision risk with the main vehicle; The relative distance after time; when the relative distance is less than the preset safety distance, forward collision risk warning information is output.

To achieve the above object, an embodiment of the present disclosure further provides an electronic device, including: at least one processor; and a memory connected to the at least one processor in communication; Instructions executed by a processor, the instructions are executed by the at least one processor, so that the at least one processor can execute the above-mentioned early warning method.

In order to achieve the above purpose, an embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned early warning method is realized.

Description of drawings

Fig. 1 is a flow chart of the early warning method mentioned in the embodiment of the present disclosure;

FIG. 2 is a flowchart of the implementation process of step 102 mentioned in the embodiment of the present disclosure;

Fig. 3 is a schematic diagram of the distribution of the main vehicle and candidate remote vehicles in the lane mentioned in the embodiment of the present disclosure;

FIG. 4 is a flowchart of an implementation of step 104 mentioned in an embodiment of the present disclosure;

FIG. 5 is a flow chart of the implementation of step 103 mentioned in the embodiment of the present disclosure;

FIG. 6 is a flow chart of the implementation of step 503 mentioned in the embodiment of the present disclosure;

Fig. 7 is a schematic diagram of the geometric relationship between the positions of the main vehicle and the remote vehicle mentioned in the embodiment of the present disclosure;

Fig. 8 is a schematic diagram of another geometric relationship between the positions of the main vehicle and the remote vehicle mentioned in the embodiment of the present disclosure;

Fig. 9 is a schematic diagram of the geometric relationship between the positions of the main vehicle and the remote vehicle in the straight road scene mentioned in the embodiment of the present disclosure;

FIG. 10 is a flow chart of the implementation of step 202 mentioned in the embodiment of the present disclosure;

Fig. 11 is a schematic structural diagram of an electronic device mentioned in an embodiment of the present disclosure.

detailed description

In order to make the purpose, technical solutions, and advantages of the embodiments of the present disclosure clearer, various embodiments of the present disclosure will be described in detail below in conjunction with the accompanying drawings. However, those skilled in the art can understand that in various embodiments of the present disclosure, many technical details are provided for readers to better understand the present disclosure. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in the present disclosure can be realized. The division of the following embodiments is for the convenience of description, and should not constitute any limitation to the specific implementation of the present disclosure, and the embodiments can be combined and referenced to each other on the premise of no contradiction.

The embodiments of the present disclosure relate to an early warning method, which is mainly used to provide early warning for possible forward collisions. Forward collision early warning means that when the main vehicle is driving on the road, there may be a rear-end collision with a distant vehicle in the same lane directly ahead. Therefore, in order to timely detect the collision risk between the main vehicle and the vehicle in front, this embodiment provides an early warning method, which can be applied to electronic equipment. The electronic device is set on the main vehicle, for example, it may be a V2X device on the main vehicle. The vehicle-to-everything (V2X) technology is the key technology of the future intelligent transportation system, which enables communication between vehicles, vehicles and base stations, and base stations. In order to obtain a series of traffic information such as real-time road conditions, road information, and pedestrian information, so as to improve driving safety, reduce congestion, improve traffic efficiency, and provide in-vehicle entertainment information. However, in a specific implementation, the electronic device can also be an on-board unit (On board Unit, referred to as: OBU), a driving recorder and other on-board equipment, or it can also be a terminal device such as a mobile phone and a tablet computer. Both the on-board device and the terminal device can be An application program for realizing the early warning method in this embodiment is stored. The implementation details of the early warning method in this embodiment will be described in detail below, and the following content is only implementation details provided for easy understanding, and is not necessary for implementing this solution.

In one embodiment, the flowchart of the early warning method may refer to FIG. 1 , which may include, but not limited to, the following steps.

Step 101: Obtain vehicle data of the main vehicle and vehicle data of multiple remote vehicles;

Step 102: According to the vehicle data of the main vehicle and the vehicle data of a plurality of remote vehicles, screen out the target remote vehicle that has a potential collision risk with the main vehicle;

Step 103: Determine whether the target remote vehicle and the main vehicle are located in the same lane; if yes, execute step 104, otherwise the process ends;

Step 104: Predict the relative distance between the target remote vehicle and the main vehicle after a preset safety time;

Step 105: When the relative distance is less than the preset safety distance, output forward collision risk warning information.

In this embodiment, through the preprocessing of the vehicle data, that is, according to the vehicle data of the main vehicle and the vehicle data of multiple remote vehicles, the target remote vehicles that have potential collision risks with the main vehicle are first screened out, and then based on the screened target vehicles, The remote car decides whether to issue forward collision risk warning information, which greatly relieves the processing pressure. Considering that vehicles in the same lane have a greater risk of forward collision, when it is determined that the target distant vehicle is in the same lane as the main vehicle, the relative distance between the target distant vehicle and the main vehicle after the preset safety time is predicted, so that Determining whether to issue forward collision risk warning information based on the relative distance is equivalent to further screening the target distant vehicles with potential collision risks, which is conducive to further reducing the processing pressure, improving the warning rate, and assisting the driver to avoid or reduce forward collisions. , Improve road safety. Moreover, the embodiment of the present disclosure is equivalent to the early warning judgment based on the safety time and the safety distance, and the accuracy of the early warning is also higher. At the same time, in the embodiment of the present disclosure, special sensing equipment is not required to realize the early warning, so the cost can be reduced, and the applicability of the early warning algorithm to general vehicles (such as vehicles not equipped with special sensing equipment) is improved.

In step 101, the vehicle data may include driving data of the vehicle during driving, such as Global Positioning System (Global Positioning System, GPS) data, speed, acceleration, heading angle, driving route, etc. of the vehicle. Wherein, the acceleration may include lateral acceleration and longitudinal acceleration, and the longitudinal acceleration may also be referred to as lateral acceleration. That is to say, the vehicle data of the host vehicle may include any combination of the following: GPS data of the host vehicle, speed of the host vehicle, acceleration of the host vehicle, driving route of the host vehicle, and the like. The vehicle data of the remote vehicle may include any combination of the following: GPS data of the remote vehicle, speed of the remote vehicle, acceleration of the remote vehicle, driving route of the remote vehicle, etc. Among them, the host vehicle (Host Vehicle, referred to as: HV) can be understood as the current vehicle, that is, to determine which vehicles may have a forward collision risk with itself, and the remote vehicle (Remote Vehicle, referred to as: RV) can be understood as the other vehicles. HV can be understood as a target vehicle equipped with an on-board unit and running an application program; RV can be understood as a background vehicle that cooperates with HV and can regularly broadcast V2X messages.

In an example, the V2X device on the main vehicle (hereinafter referred to as the first V2X device) may acquire the vehicle data of the main vehicle, and acquire the vehicle data of each remote vehicle. The vehicle data of the remote vehicle may be sent to the first V2X device by a V2X device obtained on the remote vehicle (hereinafter referred to as the second V2X device). That is to say, the second V2X device may send the vehicle data of the remote vehicle to the first V2X device through the V2X technology.

In an example, the vehicle data of the host vehicle may include: GPS data of the host vehicle, and the first V2X device may obtain the data of the host vehicle, and then calculate the heading angle, speed and acceleration of the host vehicle according to the GPS data. Wherein, the GPS data may include latitude and longitude information of multiple consecutive frames, and the first V2X device may calculate the heading angle of the main vehicle according to the latitude and longitude information of multiple consecutive frames, and obtain the speed and speed of the main vehicle according to the latitude and longitude information and time information of multiple consecutive frames. acceleration.

In one example, the vehicle data of the remote vehicle includes the heading angle, speed and acceleration of the remote vehicle. The first V2X device can analyze the heading angle, speed and acceleration of the remote vehicle from the vehicle data of the remote vehicle. For example, the second V2X device can obtain the GPS data of the remote car, and then calculate the heading angle, speed and acceleration of the remote car according to the GPS data of the remote car, and then send the calculated heading angle, speed and acceleration of the remote car through V2X. to the first V2X device, so that the first V2X device can directly obtain the heading angle, speed and acceleration of the remote vehicle, avoiding the first V2X device needing calculations to obtain the heading angle, speed and acceleration of the distant vehicle, which is conducive to alleviating the Computational pressure of a V2X device.

In one example, the vehicle data of the remote vehicle includes the GPS data of the remote vehicle, and the first V2X device may receive the GPS data of the remote vehicle, and then calculate the heading angle, speed and acceleration of the remote vehicle according to the GPS data of the remote vehicle. For example, the second V2X device can obtain the GPS data of the remote car, and then send the GPS data of the remote car to the first V2X device through V2X, so that the first V2X device can calculate the distance of the remote car based on the received GPS data of the remote car. heading angle, velocity and acceleration.

In step 102, the first V2X device may filter out a target remote vehicle that has a potential collision risk with the host vehicle according to the vehicle data of the host vehicle and the vehicle data of each remote vehicle. For example, the target remote vehicle can be screened out according to the relationship between the heading angle of the main vehicle and the heading angles between the remote vehicles, and the distance relationship between the main vehicle and the remote vehicles.

In one embodiment, step 102 may be implemented through the following steps:

Step 201: According to the vehicle data of the main vehicle and the vehicle data of multiple remote vehicles, determine multiple candidate distant vehicles traveling in the same direction as the main vehicle;

Step 202: Calculate the separation distance between the main vehicle and multiple candidate remote vehicles;

Step 203: The candidate faraway vehicle whose separation distance from the main vehicle is within a preset distance range is regarded as a target faraway vehicle having a potential collision risk with the main vehicle.

In this embodiment, considering the possibility of collisions between candidate remote vehicles traveling in the same direction as the main vehicle and the main vehicle, the possibility of potential collision risk between the candidate main vehicle and the main vehicle with the separation distance within the preset range is relatively high , therefore, based on the two conditions of whether it is traveling in the same direction as the host vehicle and whether the distance from the host vehicle is within the preset distance range, the distant target vehicle that may have a potential collision risk with the host vehicle can be accurately screened out.

In step 201, the vehicle data may include a heading angle, and the first V2X device may determine each candidate remote vehicle traveling in the same direction as the main vehicle according to the heading angle of the main vehicle and the heading angles of each remote vehicle; wherein, the heading angle of the main vehicle The included angle between the heading direction represented by the angle and the heading direction represented by the heading angle of the candidate remote vehicle is within a preset included angle range. Wherein, the preset included angle range can be set according to actual needs, for example, it can be obtained through experimental testing. In one embodiment, multiple sets of experiments can be carried out. In each set of experiments, the heading angles of two vehicles traveling in the same direction are measured. The included angle between the characterized heading directions, and then according to the multiple included angles obtained from multiple sets of experimental results, the included angle range is obtained as the preset included angle range. In a specific implementation, it is also possible to directly determine whether the difference between the heading angle of the main vehicle and the heading angle of the remote vehicle is within the above-mentioned preset angle range, so as to determine whether the main vehicle and the remote vehicle are traveling in the same direction. In one embodiment, the preset included angle range may be -45° to 45°. -45° to 45° is determined to be more accurate in the same direction. In the specific implementation, the preset angle range is not limited to this. For example, it can also be -40° to 40°, -50° to 50° etc.

In one example, when it is confirmed that there is a remote vehicle in the target state in each remote vehicle, the obtained heading angle of the remote vehicle in the target state is the heading angle of the remote vehicle in the target state before entering the target state; wherein, the target state These include: stationary conditions and/or conditions where the speed is below a preset speed threshold. The preset speed threshold can be set according to actual needs, and is intended to indicate that the vehicle speed is low. That is to say, if the remote vehicle is stationary or driving at a low speed, considering that the heading angle information cannot be directly calculated from the latitude and longitude coordinates of the vehicle when it is stationary or the heading angle calculated when driving at low speed is unreliable, the most recent effective heading angle of the remote vehicle can be used. It is guaranteed that the distant car that is originally stationary can also get a heading angle to participate in the early warning of the risk of forward collision.

In a specific implementation, the separation distance calculated in step 202 may be a vertical distance, a horizontal distance, or a relative distance. The following mainly takes the separation distance as the longitudinal distance as an example for illustration.

In step 202, the first V2X device may calculate the longitudinal distance between the host vehicle and multiple candidate remote vehicles according to the vehicle data of the host vehicle and the vehicle data of multiple candidate remote vehicles. Among them, the longitudinal distance can be understood as the projection distance of the connection line between two vehicles in the length direction of the lane, and the lateral distance related to the longitudinal distance can be understood as the projection distance of the connection line between two vehicles in the width direction of the lane distance. For example, referring to Figure 3, the main vehicle is located at point X1 in the lane, and the candidate distant vehicle is located at point X2 in the lane. The longitudinal distance between the main vehicle and the candidate distant vehicle can be the distance between X1X0, and the lateral distance can be X2X0 The distance between X1 and X2 can be called the relative distance or straight-line distance between the main vehicle and the candidate remote vehicle.

In an example, the vehicle data includes GPS data, and the GPS data may specifically be latitude and longitude information. If the host vehicle and the candidate remote vehicle are located in the straight road, the first V2X device may calculate the longitudinal distance between the host vehicle and the candidate remote vehicle according to the latitude and longitude information of the host vehicle and the latitude and longitude information of the candidate remote vehicle. For example, the latitude and longitude information can be specifically the latitude and longitude coordinates. The first V2X device can first convert the latitude and longitude coordinates of the main vehicle and the longitude and latitude coordinates of the candidate remote vehicles into rectangular coordinates in the Cartesian coordinate system, and then according to the Cartesian coordinates of the main vehicle and the candidate distant vehicles Calculate the longitudinal distance between the main vehicle and the candidate remote vehicle.

In step 203, the first V2X device can compare the longitudinal distance between each candidate remote vehicle and the host vehicle with the preset distance range, and then use the candidate remote vehicles within the preset distance range as the sum The host vehicle has a potential collision risk with the target distant vehicle. Wherein, the preset distance range can be set according to actual needs, for example, it can be set as 0 to 200 meters, but it is not limited to this in specific implementation.

In step 103, the first V2X device may determine whether the target remote vehicle and the host vehicle are located in the same lane according to the lateral distance between the target remote vehicle and the host vehicle and the width of the lane. For example, if the lateral distance between the main vehicle and the target distant vehicle is less than or equal to the width of the lane, it can be determined that the main vehicle and the target distant vehicle are in the same lane; if the lateral distance between the main vehicle and the target distant vehicle is greater than the width of the lane , it can be determined that the host vehicle and the target distant vehicle are not in the same lane. Wherein, the width of the lane can be preset, and the width of the lane where the main vehicle is located can also be directly recognized. For example, according to my country's standards and regulations, the lane width mainly considers factors such as "design vehicle speed, vehicle type, intersection, and reconstruction and expansion conditions". The lane width is generally 2.8 to 3.75 meters. If the lane width is preset, then this A person skilled in the art may select one of 2.8 to 3.75 meters as the preset lane width and store it in the first V2X device. In some implementation manners, the preset lane width may also be obtained according to a received MAP message.

In one example, if the lateral distance between the host vehicle and the target distant vehicle is less than or equal to one-third of the width of the lane, it can be determined that the host vehicle and the target distant vehicle are in the same lane, otherwise it can be determined that the host vehicle and the target distant vehicle are farther apart. Cars are not in the same lane. If the main vehicle and the target distant vehicle are not in the same lane, it can be considered that there is no forward collision risk between the main vehicle and the target distant vehicle.

In an example, the vehicle data includes GPS data, and the GPS data may specifically be latitude and longitude information. If the host vehicle and the target remote vehicle are located in the straight road, the first V2X device may calculate the lateral distance between the host vehicle and the candidate remote vehicle according to the latitude and longitude information of the host vehicle and the latitude and longitude information of the target remote vehicle. For example, the latitude and longitude information can be specifically latitude and longitude coordinates. The first V2X device can first convert the latitude and longitude coordinates of the main vehicle and the target remote vehicle into rectangular coordinates in a Cartesian coordinate system, and then use the Cartesian coordinates of the main vehicle and the target remote vehicle to Calculate the lateral distance between the main vehicle and the target remote vehicle.

The embodiment of the present disclosure is equivalent to obtaining the GPS data of the vehicle itself for early warning judgment, without the need for road test equipment to obtain information, and without installing radar and cameras. On the one hand, the cost is reduced, and on the other hand, the difficulty of algorithm development is reduced.

In the embodiments of the present disclosure, after preprocessing the vehicle data, the host vehicle obtains the vehicle data of remote vehicles that may have potential collision risks, and then performs same-lane detection on these remote vehicles that may have potential collision risks. There is a risk of forward collision between the main vehicle and the distant vehicle in the same lane, and there is no risk of forward collision between the main vehicle and the distant vehicle not in the same lane. Therefore, by judging the same lane, the vehicle with forward collision risk with the main vehicle can be further accurately screened out from distant vehicles with potential collision risk.

In step 104, the first V2X device may predict the relative distance between the target remote vehicle and the host vehicle after a preset safety time according to the vehicle data of the target remote vehicle and the vehicle data of the host vehicle. Wherein, the preset safety time can be set according to actual needs, for example, it can be set to 3 seconds, but it is not limited to this in specific implementation.

In one embodiment, the vehicle data includes: heading angle, acceleration, and speed. The implementation of step 104 can refer to FIG. 4 , which can include:

Step 401: Determine the relative position information between the target remote vehicle and the main vehicle at the current moment;

Step 402: Calculate the target remote vehicle according to the relative position information at the current moment, the heading angle of the main vehicle, the acceleration of the main vehicle, the speed of the main vehicle, the heading angle of the target remote vehicle, the acceleration of the target remote vehicle, and the speed of the target remote vehicle Relative position information with the main vehicle after the preset safety time;

Step 403: Predict the relative distance between the target remote vehicle and the host vehicle after the preset safety time according to the relative position information of the target remote vehicle and the host vehicle after the preset safety time.

In one example, the relative position information includes a lateral distance and a longitudinal distance. In step 401, the first V2X device may calculate the relative distance between the target remote vehicle and the host vehicle according to the latitude and longitude information of the target remote vehicle and the latitude and longitude information of the host vehicle. Distance dis, according to the relative distance and an included angle θ, the horizontal distance and the longitudinal distance between the target remote vehicle and the main vehicle at the current moment are obtained, and the included angle θ is the distance between the location point of the target remote vehicle and the location point of the main vehicle The angle between the connecting line and the true north direction of the main vehicle's location point. For example, the lateral distance x _i and longitudinal distance y _i between the target remote vehicle and the main vehicle at the current moment can be calculated by the following formula:

x _i =dis×cosθ, y _i =dis×sinθ;

In one example, the relative position information includes the lateral distance and the longitudinal distance, and the acceleration includes the lateral acceleration and the longitudinal acceleration. Lateral acceleration and longitudinal acceleration, the speed of the main vehicle, the heading angle of the target remote vehicle, the lateral acceleration and longitudinal acceleration of the target remote vehicle, the speed of the target remote vehicle, and calculate the lateral distance between the target remote vehicle and the main vehicle after the preset safety time and vertical distance. For example, the relative position information of the target remote vehicle and the main vehicle after a preset safety time can be calculated by the following formula:

Among them, x _f and y _f are respectively the lateral distance and longitudinal distance between the target remote vehicle and the main vehicle after the preset safety time, and x _i and y _i are the lateral distance and the current distance between the target remote vehicle and the main vehicle respectively. Longitudinal distance, v _RV and v _HV are the speed of the target remote vehicle and the speed of the main vehicle respectively, α and β are the heading angles of the target remote vehicle and the heading angle of the main vehicle respectively, a _yRV and a _xRV are the distances of the target remote vehicle Longitudinal acceleration and lateral acceleration, a _yHV and a _xHV are the longitudinal acceleration and lateral acceleration of the main vehicle respectively, and t is the preset safety time.

In step 403, the first V2X device can predict the relative distance between the target remote vehicle and the main vehicle after the preset safety time according to the horizontal and vertical distances between the target remote vehicle and the main vehicle after the preset safety time, for example, by The following formula obtains the relative distance L between the target distant vehicle and the main vehicle after the preset safety time:

L＝x _f ×cos((α+β)/2)+y _f ×sin((α+β)/2)

In step 105, the first V2X device can compare the relative distance calculated in step 104 with the preset safety distance, and if the relative distance is smaller than the preset safety distance, send forward collision risk warning information to remind the host vehicle to avoid in time Forward collision risk. Wherein, the preset safety distance can be set according to actual needs, for example, it can be set to 5 meters, but in specific implementation, it is not limited thereto.

In this embodiment, when predicting the relative distance between the target remote vehicle and the main vehicle after the preset safety time, the relative position information of the target remote vehicle and the main vehicle at the current moment, and the respective headings of the target remote vehicle and the main vehicle are combined Angle, acceleration, and speed are conducive to accurately predicting the traveling trend of the target remote vehicle and the main vehicle, so as to accurately predict the relative distance between the target remote vehicle and the main vehicle after the preset safety time, so as to improve the accuracy of early warning.

In one embodiment, the early warning method can be applied to the forward collision risk warning in the straight road scene and the forward collision risk warning in the curve scene at the same time. For example, the specific implementation of determining whether the target remote vehicle and the main vehicle are located in the same lane in step 103 above can refer to FIG. 5 , which may include, but is not limited to, the following steps:

Step 501: Obtain the heading angle of the main vehicle, and obtain the heading angle of the target remote vehicle;

Step 502: Determine the location of the main vehicle and the location of the target remote vehicle;

Step 503: According to the heading angle of the main vehicle, the heading angle of the target remote vehicle, the location of the main vehicle and the location of the target remote vehicle, determine the lateral distance between the main vehicle and the target remote vehicle;

Step 504: According to the lateral distance and the width of the preset lane, it is confirmed whether the host vehicle and the target remote vehicle are located in the same lane.

In the embodiment of the disclosure, in the process of judging the same lane, it is not necessary to obtain driving road pictures through the camera, the cost is relatively low, and the calculation of the lateral distance based on the angle, position and other information is equivalent to the calculation of the lateral distance based on the geometric method. The lateral distance obtained by the method based on visual recognition in the technology is more reliable and less difficult. At the same time, the embodiment of the present disclosure avoids the inaccurate fitting curve obtained by fitting the historical track points, thereby avoiding the inaccuracy of the same-vehicle judgment result caused by the inaccurate fitting curve. That is, the embodiments of the present disclosure can improve the accuracy and reliability of same-lane judgment, reduce the cost and difficulty of realizing same-lane judgment, thereby reducing the cost and difficulty of forward collision risk warning.

In step 501, the way of obtaining the heading angle of the host vehicle and the heading angle of the target remote vehicle can refer to the relevant introduction about obtaining the heading angle in the above-mentioned embodiments, and to avoid repetition, details are not repeated here.

In step 502, the first V2X device may determine the location of the host vehicle and the location of the target remote vehicle. Wherein, the location may be represented by latitude and longitude information. The first V2X device can determine the location of the main vehicle according to the GPS data of the main vehicle, the first V2X device can obtain the GPS data of the target remote vehicle from the received V2X data sent by the second V2X device, and The data determines where the target remote vehicle is located.

In step 503, the first V2X device can determine the lateral distance between the host vehicle and the target remote vehicle according to the heading angle of the host vehicle, the heading angle of the target remote vehicle, the location of the host vehicle, and the location of the target remote vehicle . Among them, the heading angle of the main vehicle, the heading angle of the target remote vehicle, the location of the main vehicle and the location of the target remote vehicle can reflect the straight-line distance (also called the relative distance) between the main vehicle and the target remote vehicle, the lateral distance The geometric relationship between the distance and the longitudinal distance, the first V2X device can calculate the lateral distance between the main vehicle and the target remote vehicle according to the geometric relationship.

In one embodiment, the implementation of step 503 may be as shown in Figure 6, including:

Step 601: Calculate the distance of the first straight line connecting the position of the main vehicle and the position of the target remote vehicle;

Step 602: Determine the first angle between the north direction of the main vehicle's location and the first straight line;

Step 603: Determine the lateral distance between the host vehicle and the target remote vehicle according to the heading angle of the host vehicle, the heading angle of the target distant vehicle, the distance of the first straight line and the first included angle.

In order to facilitate the understanding of the above-mentioned steps, a schematic diagram of the geometric relationship between the positions of the main vehicle and the target remote vehicle, ie, FIG. 7 , will be described below.

In Fig. 7, the host vehicle (HV) is located at point B ₁ , the target remote vehicle 1 (RV1) is located at A ₁ , and the target remote vehicle 2 (RV2) is located at G. That is, the lane in FIG. 7 is a curved road, and there are three vehicles on the curved road, namely, the main vehicle, the target distant vehicle 1 and the target distant vehicle 2.

In Figure 7, the following assumptions are made based on the actual situation:

(1) The vehicle that needs to be warned is on a curve with the same curvature, which can be approximately considered to be on a circular arc;

(2) Under normal circumstances, the vehicle basically runs along the centerline of the lane, that is, the heading coincides with the arc tangent.

If the curve is formed by connecting roads with different curvature radii, when the difference between the curvature radii of the two roads is within a certain range, the judgment of the same lane can still be realized. After several simulation tests, when the difference between the curvature radii of the two roads is within 50m, the judgment is more accurate.

In Figure 7, points A ₁ and B ₁ represent RV1 and HV respectively; vectors u and v are the velocities of RV1 and HV, which coincide with the tangents of the arc at points A ₁ and B ₁ ; vectors w and a point to the true north direction ; α=∠CA ₁ B is the course angle of RV1, β=∠AB ₁ D is the course angle of HV. Point G represents RV2 in the adjacent lane of RV1, and runs in parallel with RV1 in the same direction, that is, the speed of RV2 is in the same direction as that of RV1 and the line A ₁ G passes through the center of the arc; two concentric arcs represent adjacent Centerline of the lane.

In step 601, the first V2X device may calculate the distance of the first straight line connecting the location of the host vehicle and the location of the target remote vehicle according to the GPS data of the host vehicle and the GPS data of the target remote vehicle, This distance can be understood as the relative distance between the main vehicle and the target remote vehicle. The GPS data of the host vehicle may include the latitude and longitude information of the host vehicle, the GPS data of the target remote vehicle may include the latitude and longitude information of the remote vehicle, and the first V2X device may calculate the first straight line according to the latitude and longitude information of the host vehicle and the latitude and longitude information of the target remote vehicle distance. Referring to Fig. 7, if the distance between the position of the host vehicle HV and the position of the target remote vehicle RV1 is calculated, the distance _of the _first straight line can be between A1 and B1. The straight-line distance h between the points; if the calculation is the distance of the first straight line connected between the position of the main vehicle HV and the position of the target remote vehicle RV2, the distance of the first straight line can be B ₁ and the straight-line distance l between the two points G.

In step 602, the first V2X device may determine a first included angle between the true north direction of the host vehicle's location and the above-mentioned first straight line. In _a specific implementation, if the lateral distance between the host vehicle HV and the target remote vehicle RV1 is to be calculated, then with reference to FIG. The included angle θ of the straight line (A ₁ B ₁ )=∠AB ₁ A ₁ . θ can also be referred to as the starting angle of the shortest path h of RV1 and HV. If the lateral distance between the host vehicle HV and the target distant vehicle RV2 is to be calculated, the first included angle obtained in step 602 is: the included angle between the true north direction (vector w) _of position B1 and the straight line ( _B1G ) ∠AB ₁ G.

In step 603, the first V2X device may, under the constructed first geometric model for calculating the lateral distance, according to the heading angle of the host vehicle, the heading angle of the target remote vehicle, the distance of the first straight line and the first included angle , to determine the lateral distance between the main vehicle and the target remote vehicle; wherein, the first geometric model is based on the location of the main vehicle, the location of the target remote vehicle, the speed direction of the main vehicle, the speed direction of the target remote vehicle, and the location of the main vehicle The true north direction of the position of the target vehicle is constructed. The first geometric model can be obtained through pre-construction and stored in the first V2X device, so that the first V2X device can calculate the lateral distance between the host vehicle and the remote vehicle according to the first geometric model. The lateral distance between the main vehicle and the target remote vehicle can be obtained simply and quickly through the first geometric model.

In one example, referring to Fig. 7, assume that the position of the host vehicle is B ₁ , and the position of the target distant vehicle is A ₁ , according to the position A ₁ , B ₁ , the velocity direction of the host vehicle (vector v), the target distant vehicle The velocity direction (vector u), the true north direction (vector w) of position B ₁ , and the true north direction (vector a) of position A ₁ can be constructed to obtain the first geometric model as follows:

Among them, dis _lateral is the lateral distance, β is the heading angle of the main vehicle, α is the heading angle of the target remote vehicle, dis1 is the distance of the first straight line, and θ1 (marked as θ in the figure) is the first included angle. For RV1, dis1 is h in Figure 7, and for RV2, dis1 is l in Figure 7. In a specific implementation, the values of α, β, θ1, and dis1 may be substituted into the above-mentioned first geometric model to calculate the lateral distance between the host vehicle and the target distant vehicle.

It can be seen from FIG. 7 that HV and RV1 are located in the same lane, and the lateral distance between them is 0; HV and RV2 are located in different lanes, and the lateral distance between them is GA ₁ . Referring to Fig. 8, dotted lines f and g are tangents of points A ₁ and B ₁ on the arc, ∠HB ₁ A ₁ =θ-β, ∠HB ₁ A ₁ =∠HA ₁ B ₁ , ∠HA ₁ B=α -θ, so when HV and RV1 are in the same lane, the heading angles β and α of HV and RV1 and the starting angle θ of the shortest path between HV and RV1 satisfy the following relationship:

then will

Substituting into the first geometric model above, it can be obtained that the lateral distance between HV and RV1 is 0.

That is to say, when the main vehicle and the target remote vehicle are in the same lane, the first heading angle β, the second heading angle α and the included angle θ satisfy the following relationship:

For HV and RV2, that is, when calculating the lateral distance between HV and RV2, the heading angle of HV is β, the heading angle of RV2 is α, and the starting angle of the shortest path between HV and RV2 is θ'=∠AB ₁ G (ie The angle between the true north direction w where HV is located and the straight line B ₁ G). pass

It can be seen that ∠A ₁ B ₁ G＝θ'-θ＝θ'-(α+β)/2, ∠B ₁ A ₁ G＝∠HA ₁ G-∠HA ₁ B ₁ ＝90°-(α-θ) =90°-((α-β)/2), ∠B ₁ GA ₁ =90°-θ'+α, the linear distance dis1 between HV and RV2 is B ₁ G. According to the sine law, the lateral distance A ₁ G between HV and RV2 is:

In one embodiment, the first geometric model is used to calculate the lateral distance between the main vehicle and the distant target vehicle in the curve scene, and is used to calculate the lateral distance between the main vehicle and the distant target vehicle in the straight road scene. Distance, that is, the above-mentioned judging method for the same lane is also applicable to judging the same lane for vehicles in the straight road.

The above-mentioned embodiment introduces that the first geometric model is used to calculate the lateral distance between the main vehicle and the target distant vehicle in the curved road scene. The following mainly introduces that the first geometric model is also used to calculate the main vehicle and the target vehicle in the straight road scene. Lateral distance between distant vehicles.

Referring to Fig. 9, when the host vehicle HV and the target remote vehicle RV are both located on the straight road, since the straight road can be considered as a circular arc with an infinite radius of curvature, the above-mentioned first geometric model for calculating the lateral distance obtained from a general circular arc is also applicable It is used to calculate the lateral distance between two vehicles in a straight road. For example, in Figure 9, point A represents the location of the main vehicle HV, point B represents the location of RV1 in the same lane as the HV, and point C represents the location of RV2 in a different lane from the HV. Obviously, the transverse distance between HV and RV1 should be 0 in theory; the transverse distance between HV and RV2 should be BC in theory. Next, it is verified that the above-mentioned first geometric model is also applicable to the calculation of the lateral distance between vehicles in the straight road by calculating the lateral distance through the above-mentioned first geometric model.

When calculating the lateral distance between HV and RV1, the heading angle of HV is β, the heading angle of RV1 is α, and the starting angle θ of the shortest path between HV and RV1 (that is, the angle between the true north direction where HV is located and the straight line AB ), the size of these three included angles is equal, that is, θ=α=β, the relative distance dis1=AB between the two cars of HV and RV1, and the values of α, β, θ, and dis1 can be substituted into the above-mentioned first geometric model. Calculate the lateral distance between HV and RV1, the calculation process is as follows:

It can be seen that when using the first geometric model to calculate the lateral distance between the host vehicle HV and the target remote vehicle RV1, the calculated result is the same as the theoretical lateral distance between the HV and RV1.

When calculating the lateral distance between HV and RV2, the course angle of HV is β, the course angle of RV2 is α, α=β, and the starting angle of the shortest path from HV to RV2 is θ (that is, the direction of true north where HV is located and the straight line The angle between AC ∠EAC), the relative distance between the two vehicles dis1=AC, and the values of α, β, θ1, and dis1 are substituted into the first geometric model above to calculate the lateral distance between HV and RV2. The calculation process is as follows :

It can be seen that when using the first geometric model to calculate the lateral distance between the host vehicle HV and the target remote vehicle RV2, the calculated result is the same as the theoretical lateral distance between the HV and RV2.

The first geometric model in the embodiment of the present disclosure is not only applicable to the calculation of the lateral distance between vehicles in a curve, but also applicable to the calculation of the lateral distance between vehicles in a straight road, so that the scene in this embodiment has strong applicability, Can be applied to most roads. In the related technology, it is difficult to fit the path of the curve by fitting the historical track points, that is, it is not very applicable to the judgment of the same lane in the curve scene. The embodiments of the present disclosure can be used for the curve scene and the straight road scene Using the same geometric model to calculate the lateral distance saves computing power and reduces the difficulty and cost of judging the same lane, thereby reducing the cost and difficulty of forward collision risk warning.

In one embodiment, when the early warning method is applicable to the forward collision risk warning in the straight road scene and the forward collision risk warning in the curve scene at the same time, the above step 202 calculates the longitudinal distance between the main vehicle and each candidate remote vehicle. The implementation can refer to Figure 10, including:

Step 1001: Obtain the heading angle of the main vehicle, and obtain the heading angles of each candidate remote vehicle;

Step 1002: Determine the location of the main vehicle and the locations of multiple candidate remote vehicles;

Step 1003: Determine the longitudinal distance between the host vehicle and multiple candidate remote vehicles according to the heading angle of the main vehicle, the heading angles of multiple candidate remote vehicles, the location of the main vehicle, and the locations of multiple candidate remote vehicles.

Wherein, steps 1001 to 1002 are substantially the same as the way of obtaining the heading angle and the way of determining the position mentioned in steps 501 to 502 mentioned above, and to avoid repetition, details are not repeated here.

In step 1003, the first V2X device can respectively calculate the distance between the position of the main vehicle and the positions of the candidate remote vehicles and the distance of the second straight line, and determine the distance between the true north of the position of the main vehicle and the second straight line. For the second included angle of the straight line, the longitudinal distance between the main vehicle and each candidate remote vehicle is determined according to the heading angle of the main vehicle, the heading angles of each candidate remote vehicle, the distance of the second straight line, and the second included angle.

In an example, the first V2X device may, under the second geometric model constructed for calculating the longitudinal distance, according to the heading angle of the main vehicle, the heading angles of each candidate remote vehicle, the distance of the second straight line, and the second included angle , to determine the longitudinal distance between the main vehicle and each candidate distant vehicle; wherein, the second geometric model is based on the position of the main vehicle, the position of the candidate distant vehicle, the speed direction of the main vehicle, the speed direction of the candidate remote vehicle, the main vehicle The true north direction of the position and the true north direction of the position where the candidate remote vehicle is located are constructed.

In one example, referring to Fig. 8, assume that the position of the main vehicle is B ₁ , the position of the candidate distant vehicle is A ₁ , according to the position A ₁ , B ₁ , the velocity direction of the main vehicle (vector v), the candidate distant vehicle The velocity direction (vector u), the true north direction (vector w) _of position B1, and the true north direction (vector _a ) of position A1 can be constructed to obtain the second geometric model as follows:

Among them, dis _longitudinal is the longitudinal distance, β is the heading angle of the main vehicle, α is the heading angle of the candidate remote vehicle, dis2 is the distance of the second straight line, and θ2 (marked as θ in the figure) is the second included angle.

Assume that in Figure 8, position A ₁ is the candidate remote vehicle RV1, position G is the candidate remote vehicle RV2, and position B ₁ is the main vehicle HV. It can be seen from the figure that HV and RV1 are located in the same lane, and the longitudinal distance can be approximately replaced by A ₁ B ₁ ; HV and RV2 are located in different lanes, and the longitudinal distance can be approximately replaced by B ₁ G.

Among them, α is the heading angle of RV1, β is the heading angle of HV, θ is the angle between the true north direction (vector w) of position B ₁ and the straight line A ₁ B ₁ , dis2 is the distance between point A ₁ and point B ₁ relative distance. θ can also be understood as the starting angle of the shortest path between RV1 and HV.

Among them, α is the heading angle of RV2, β is the heading angle of HV, θ' is the angle between the true north direction (vector w) _of position B1 and the straight line _B1G , _dis2 is the distance between point G and point B1 relative distance. θ' can also be understood as the starting angle of the shortest path between RV2 and HV.

When both HV and RV are located on the straight road, since the straight road can be considered as a circular arc with an infinite radius of curvature, the geometric model of the horizontal and vertical distances obtained from the general circular arc above is obviously applicable to the straight road. As shown in Figure 9, point A represents the HV, point B represents RV1 in the same lane as the HV, and point C represents RV2 in a different lane from the HV. Obviously, the theoretical longitudinal distance between HV and RV1 is AB; the theoretical longitudinal distance between HV and RV2 is AB.

When calculating the longitudinal distance between HV and RV1 through the above-mentioned second geometric model, θ2=α=β, the starting angle of the shortest path from HV to RV1 is θ2, and the relative distance between the two vehicles is dis2=AB,

It can be seen that when the longitudinal distance between HV and RV1 is calculated using the second geometric model, the calculated result is the same as the theoretical longitudinal distance between HV and RV1.

When calculating the longitudinal distance between HV and RV2 through the above-mentioned second geometric model, α=β, the starting angle of the shortest path from HV to RV2 is θ2, and the relative distance between the two vehicles is dis2=AC,

It can be seen that when the longitudinal distance between HV and RV2 is calculated using the second geometric model, the calculated result is the same as the theoretical longitudinal distance between HV and RV2.

The second geometric model in the embodiment of the present disclosure is not only applicable to the calculation of the longitudinal distance between vehicles in a curve, but also applicable to the calculation of the longitudinal distance between vehicles in a straight road, so that the scene applicability of this embodiment is strong, and it can Suitable for most roads. In related technologies, it is difficult to fit the path of the curve by fitting the historical track points, that is, it is not very applicable to the judgment of the same lane in the curve scene. The embodiments of the present disclosure can be used for the curve scene and the straight road scene Using the same geometric model to calculate the longitudinal distance saves computing power and reduces the difficulty and cost of judging the same lane, thereby reducing the cost and difficulty of forward collision risk warning.

The step division of the above various methods is only for the sake of clarity of description. During implementation, it can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent. ; Adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of the algorithm and process are all within the scope of protection of this patent.

Embodiments of the present disclosure also relate to an electronic device, as shown in FIG. 11 , including at least one processor 1101; and a memory 1102 connected in communication with at least one processor 1101; wherein, the memory 1102 stores information that can be processed by at least one The instructions executed by the processor 1101 are executed by at least one processor 1101, so that the at least one processor 1101 can execute the early warning method in the above embodiment.

Wherein, the memory 1102 and the processor 1101 are connected by a bus, and the bus may include any number of interconnected buses and bridges, and the bus connects one or more processors 1101 and various circuits of the memory 1102 together. The bus may also connect together various other circuits such as peripherals, voltage regulators, and power management circuits, all of which are well known in the art and therefore will not be further described herein. The bus interface provides an interface between the bus and the transceivers. A transceiver may be a single element or multiple elements, such as multiple receivers and transmitters, providing means for communicating with various other devices over a transmission medium. The data processed by the processor 1101 is transmitted on the wireless medium through the antenna. In one embodiment, the antenna also receives the data and transmits the data to the processor 1101 .

The processor 1101 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management and other control functions. And the memory 1102 may be used to store data used by the processor 1101 when performing operations.

The embodiment of the present disclosure also provides a computer-readable storage medium storing a computer program. The above method embodiments are implemented when the computer program is executed by the processor.

That is, those skilled in the art can understand that all or part of the steps in the method of the above-mentioned embodiments can be completed by instructing related hardware through a program, the program is stored in a storage medium, and includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods described in the various embodiments of the present disclosure. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. .

Those of ordinary skill in the art can understand that the above-mentioned embodiments are specific examples for realizing the present disclosure, and in practical applications, various changes can be made in form and details without departing from the spirit and spirit of the present disclosure. scope.

Claims

An early warning method, including:

Obtain the vehicle data of the main vehicle and the vehicle data of multiple remote vehicles;

According to the vehicle data of the main vehicle and the vehicle data of the plurality of remote vehicles, select a target remote vehicle that has a potential collision risk with the main vehicle;

After confirming that the target distant vehicle and the main vehicle are located in the same lane, predicting the relative distance between the target distant vehicle and the main vehicle after a preset safety time;

When the relative distance is less than the preset safety distance, forward collision risk warning information is output.
The early warning method according to claim 1, wherein, according to the vehicle data of the main vehicle and the vehicle data of the plurality of remote vehicles, screening out the target remote vehicles that have a potential collision risk with the main vehicle includes :

According to the vehicle data of the main vehicle and the vehicle data of the plurality of remote vehicles, determine a plurality of candidate distant vehicles traveling in the same direction as the main vehicle;

Calculate the separation distances between the main vehicle and the plurality of candidate remote vehicles, and use the candidate remote vehicles whose separation distances from the main vehicle are within a preset distance range as potential candidates for the main vehicle. The risk of collision with the target is far from the car.
The early warning method according to claim 2, wherein the vehicle data includes heading angle;

The determining a plurality of candidate distant vehicles traveling in the same direction as the main vehicle according to the vehicle data of the main vehicle and the vehicle data of the plurality of remote vehicles includes:

According to the heading angle of the main vehicle and the heading angles of the plurality of remote vehicles, determine a plurality of candidate remote vehicles traveling in the same direction as the main vehicle; wherein, the heading direction represented by the heading angle of the main vehicle is the same as The included angles between the heading directions represented by the heading angles of the candidate remote vehicles are within a preset angle range.
The early warning method according to claim 3, wherein the included angle ranges from -45° to 45°.
The early warning method according to claim 3, wherein the method further comprises: when it is confirmed that there is a remote vehicle in the target state among the remote vehicles, the acquired heading angle of the remote vehicle in the target state is The heading angle of the remote vehicle in the target state before entering the target state; wherein, the target state includes: a stationary state and/or a state in which the speed is lower than a preset speed threshold.
The early warning method according to claim 1, wherein the vehicle data includes: heading angle, acceleration, and speed, and the prediction of the relative distance between the target remote vehicle and the main vehicle after a preset safety time includes:

determining the relative position information between the target remote vehicle and the host vehicle at the current moment;

According to the relative position information at the current moment, the heading angle of the main vehicle, the acceleration of the main vehicle, the speed of the main vehicle, the heading angle of the target remote vehicle, the acceleration of the target remote vehicle, the the speed of the target remote vehicle, and calculate the relative position information between the target remote vehicle and the main vehicle after a preset safety time;

Predicting the relative distance between the target remote vehicle and the host vehicle after the preset safety time has elapsed according to the relative position information between the target remote vehicle and the host vehicle after the preset safety time has elapsed.
The early warning method according to claim 6, wherein the relative position information includes a lateral distance and a longitudinal distance, and the acceleration includes a lateral acceleration and a longitudinal acceleration;

According to the relative position information at the current moment, the heading angle of the main vehicle, the acceleration of the main vehicle, the speed of the main vehicle, the heading angle of the target remote vehicle, and the acceleration of the target remote vehicle . The speed of the target remote vehicle, calculating the relative position information between the target remote vehicle and the main vehicle after a preset safety time, including:

The relative position information of the target remote vehicle and the main vehicle after a preset safety time is obtained by the following formula:

Among them, x f and y f are respectively the lateral distance and longitudinal distance between the target remote vehicle and the main vehicle after a preset safety time, and x i and y i are respectively the distance between the target remote vehicle and the main vehicle. The lateral distance and longitudinal distance at the current moment, v RV and v HV are the speed of the target remote vehicle and the speed of the main vehicle respectively, α and β are the course angle of the target remote vehicle and the main vehicle The heading angle of the vehicle, a yRV and a xRV are the longitudinal acceleration and lateral acceleration of the target remote vehicle respectively, a yHV and a xHV are the longitudinal acceleration and lateral acceleration of the main vehicle respectively, and t is the preset safety time .
The early warning method according to claim 7, wherein, according to the relative position information of the target distant vehicle and the main vehicle after a preset safety time, it is predicted that the target remote vehicle and the main vehicle pass through a preset distance. Relative distance after safety time, including:

The relative distance between the target remote vehicle and the main vehicle after the preset safety time is obtained by the following formula:

L＝x f ×cos((α+β)/2)+y f ×sin((α+β)/2)

Among them, L is the relative distance.
An electronic device, comprising: at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory is stored with instructions executable by the at least one processor, the instructions are executed by the at least one processor, so that the at least one processor can perform any one of claims 1 to 8 early warning method.
A computer-readable storage medium storing a computer program, wherein the computer program implements the early warning method according to any one of claims 1 to 8 when executed by a processor.