CN114898558A - Method, system, electronic device and storage medium for cooperative vehicle passing - Google Patents

Method, system, electronic device and storage medium for cooperative vehicle passing Download PDF

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CN114898558A
CN114898558A CN202210564028.2A CN202210564028A CN114898558A CN 114898558 A CN114898558 A CN 114898558A CN 202210564028 A CN202210564028 A CN 202210564028A CN 114898558 A CN114898558 A CN 114898558A
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李�杰
陈乾坤
熊胜健
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Dongfeng Yuexiang Technology Co Ltd
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Abstract

The application provides a method, a system, an electronic device and a storage medium for vehicle cooperative passage, comprising the following steps: acquiring first running information, wherein the first running information is running information of a host vehicle; predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle; sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle; and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene. The vehicles which are in cooperative passing can realize intelligent passing under the condition that road information is not needed, and the effectiveness of the intelligent passing under various scenes is guaranteed.

Description

Method, system, electronic device and storage medium for cooperative vehicle passage
Technical Field
The application belongs to the field of intelligent driving, and particularly relates to a method, a system, an electronic device and a storage medium for vehicle cooperative passage.
Background
The traffic handling capacity of multiple vehicles under complex road conditions is an important field of intelligent driving, such as the problem of sequential traffic of right-turn vehicles and straight-going vehicles at a crossroad, the problem of lane change and avoidance of vehicles and the like, which seriously affect the application of intelligent driving in practice. The prior art can only process single road conditions generally, and the processing process must rely on a map stored in the vehicle-mounted equipment.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a method, a system, electronic equipment and a storage medium for vehicle cooperative passing, so that the vehicles performing cooperative passing can realize intelligent passing under the condition of not needing road information, and the effectiveness of the intelligent passing under various scenes is ensured.
In a first aspect, a method for collaborative passage of vehicles is provided, the method comprising:
acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle, and the running track comprises: driving intent, predicted vehicle position;
sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle;
and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene.
In one possible implementation manner, the predicting the first travel information through the long-time memory network LSTM to obtain the first travel track includes:
acquiring the driving intention through the LSTM network according to the historical driving track of the vehicle and the first driving information;
and acquiring the predicted vehicle position through the LSTM network according to the driving intention, the historical driving track of the vehicle and the first driving information.
In another possible implementation manner, the predicting a traffic scene according to the first travel track and the second travel track, and performing cooperative traffic according to the traffic scene includes:
predicting the passing scene according to the first driving track and the second driving track, wherein the passing scene comprises: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
performing cooperative passage according to the passage scene, wherein the cooperative passage comprises t 2 : obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 69927DEST_PATH_IMAGE001
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold value, the vehicle with the shorter time accelerates to pass through the intersection point, if T 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
In another possible implementation manner, the predicting the traffic scene according to the first driving track and the second driving track includes:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
In a second aspect, a system for collaborative passage of vehicles is provided, the system comprising:
a first travel information obtaining module, configured to obtain first travel information, where the first travel information is travel information of a host vehicle, and the travel information includes: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
a first travel track obtaining module, configured to predict the first travel information through a long-term memory network LSTM to obtain a first travel track, where the first travel track is a predicted travel track of the host vehicle, and the travel track includes: driving intent, predicted vehicle position;
the second running track receiving module is used for sending the first running track to a distant vehicle for cooperative passing and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle;
and the cooperative passing module is used for predicting a passing scene according to the first running track and the second running track and performing cooperative passing according to the passing scene.
In one possible implementation manner, the first driving track obtaining module includes:
a driving intention acquisition unit, configured to acquire the driving intention through the LSTM network according to a vehicle historical driving track and the first driving information;
a predicted vehicle position acquisition unit for acquiring the predicted vehicle position through the LSTM network according to the driving intention, a vehicle history travel track, and first travel information.
In another possible implementation manner, the cooperative passage module includes:
a traffic scene prediction unit configured to predict the traffic scene according to the first travel track and the second travel track, the traffic scene including: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
the cooperative passage unit is used for performing cooperative passage according to the passage scene, and the cooperative passage comprises the following steps: obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 941063DEST_PATH_IMAGE001
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold value, the vehicle with the shorter time accelerates to pass through the intersection point, if T 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
In another possible implementation manner, the predicting the traffic scene according to the first driving track and the second driving track includes:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
In a third aspect, an electronic device is provided, which includes a memory, a processor and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the method for vehicle cooperative passage as provided in the first aspect.
In a fourth aspect, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the method for collaborative passage of vehicles as provided by the first aspect.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
FIG. 1 is a flow chart of a method for collaborative passage of vehicles according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for collaborative passage of vehicles according to another embodiment of the invention;
FIG. 3 is a flow chart of a method for collaborative passage of vehicles according to yet another embodiment of the present invention;
FIG. 4 is a block diagram of a system for collaborative navigation of vehicles according to an embodiment of the present invention;
FIG. 5 is a block diagram of a system for collaborative navigation of vehicles according to another embodiment of the present invention;
FIG. 6 is a block diagram of a system for collaborative navigation of vehicles according to yet another embodiment of the present invention;
fig. 7 is a schematic physical structure diagram of an electronic device according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar modules or modules having the same or similar functionality throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, modules, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, modules, components, and/or groups thereof. It will be understood that when a module is referred to as being "connected" or "coupled" to another module, it can be directly connected or coupled to the other module or intervening modules may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any module and all combinations of one or more of the associated listed items.
To make the objectives, technical solutions and advantages of the present application more clear, the following detailed description of the implementations of the present application will be made with reference to the accompanying drawings.
The technical solutions of the present application and the technical solutions of the present application, for example, to solve the above technical problems, will be described in detail with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a flowchart illustrating a method for collaborative passing of vehicles according to an embodiment of the present invention, where the method includes:
step 101, acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
step 102, predicting the first traveling information through a long-term memory network LSTM to obtain a first traveling track, where the first traveling track is a predicted traveling track of the host vehicle, and the traveling track includes: driving intent, predicted vehicle position;
step 103, sending the first driving track to a distant vehicle for cooperative passing, and receiving a second driving track sent by the distant vehicle, wherein the second driving track is a predicted driving track of the distant vehicle;
and 104, predicting a traffic scene according to the first running track and the second running track, and performing cooperative traffic according to the traffic scene.
In the embodiment of the invention, the running information of the main vehicle, namely the first running information, is acquired in real time through a sensor installed on the main vehicle, the first running information is predicted to be the first running track through an information processing device on the main vehicle according to a preset LSTM (Long-Short Term Memory) network, the first running track is sent to a remote vehicle needing cooperative passage, the running track of the remote vehicle sent by the remote vehicle, namely the second running track, is received, the information processing device on the main vehicle predicts the passage scene of the cooperative passage according to the first running track and the second running track, and the information processing device on the remote vehicle predicts the same passage scene according to the first running track and the second running track, so that the main vehicle and the remote vehicle can carry out the cooperative passage according to the same passage scene.
Wherein, the driving information includes but is not limited to: vehicle position information, speed information, direction information, steering wheel angle information, turn signal status information.
The driving trajectory includes but is not limited to: driving intention, predicted vehicle position. Wherein the driving intent comprises: straight, left-turning, right-turning.
According to the embodiment of the invention, first running information is obtained, the first running information is the running information of a main vehicle, the first running information is predicted through a long-term memory network LSTM, a first running track is obtained, the first running track is sent to a far vehicle for cooperative passage, a second running track sent by the far vehicle is received, a passage scene is predicted according to the first running track and the second running track, and the cooperative passage is carried out according to the passage scene. The vehicles which are in cooperative passing can realize intelligent passing under the condition that road information is not needed, and the effectiveness of the intelligent passing under various scenes is guaranteed.
Fig. 2 is a flowchart of a method for vehicle cooperative transit according to still another embodiment of the present invention, where the predicting the first travel information through the long-term and short-term memory network LSTM to obtain a first travel track includes:
step 201, acquiring the driving intention through the LSTM network according to a vehicle historical driving track and the first driving information;
and step S202, acquiring the predicted vehicle position through the LSTM network according to the driving intention, the historical driving track of the vehicle and the first driving information.
In an embodiment of the present invention, the driving intent, i.e., the driver's possible future direction of travel, includes: and turning forwards, turning left and turning right, calling the vehicle historical driving track and the first driving information which are locally stored in the vehicle as input information of the LSTM network, wherein the output information of the LSTM network is the driving intention. And inputting the driving intention and the first running information into the LSTM network again as input information, wherein the output information is the predicted vehicle position.
Fig. 3 is a flowchart of a method for collaborative passing of vehicles, according to another embodiment of the present invention, the predicting a passing scene according to the first traveling track and the second traveling track, and performing collaborative passing according to the passing scene, including:
step 301, predicting the traffic scene according to the first driving track and the second driving track, wherein the traffic scene comprises: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
step 302, performing cooperative passage according to the passage scene, wherein the cooperative passage comprises t 2 : obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 924062DEST_PATH_IMAGE001
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold value, the vehicle with the shorter time accelerates to pass through the intersection point, if T 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
In the embodiment of the present invention, the traffic scenario may be divided into: the intersection passes, a plurality of vehicles converge into the same road and the vehicles change the road, and the principle of following different passing scenes is as follows: a vehicle having a shorter time from the intersection of the travel locus accelerates preferentially through the intersection, and a vehicle having a longer time from the intersection of the travel locus delays through the intersection.
Wherein the predicting the traffic scene according to the first and second driving tracks comprises:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
Fig. 4 is a block diagram of a system for cooperative vehicle passing according to an embodiment of the present invention, where the system includes:
a first driving information obtaining module 401, configured to obtain first driving information, where the first driving information is driving information of a host vehicle, and the driving information includes: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
a first travel track obtaining module 402, configured to predict the first travel information through a long-term memory network LSTM, and obtain a first travel track, where the first travel track is a predicted travel track of the host vehicle, and the travel track includes: driving intent, predicted vehicle position;
a second driving track receiving module 403, configured to send the first driving track to a distant vehicle performing a cooperative passage, and receive a second driving track sent by the distant vehicle, where the second driving track is a predicted driving track of the distant vehicle;
and the cooperative passing module 404 is configured to predict a passing scene according to the first running track and the second running track, and perform cooperative passing according to the passing scene.
In the embodiment of the invention, the running information of the main vehicle, namely the first running information, is acquired in real time through a sensor installed on the main vehicle, the first running information is predicted to be the first running track through an information processing device on the main vehicle according to a preset LSTM (Long-Short Term Memory) network, the first running track is sent to a remote vehicle needing cooperative passage, the running track of the remote vehicle sent by the remote vehicle, namely the second running track, is received, the information processing device on the main vehicle predicts the passage scene of the cooperative passage according to the first running track and the second running track, and the information processing device on the remote vehicle predicts the same passage scene according to the first running track and the second running track, so that the main vehicle and the remote vehicle can carry out the cooperative passage according to the same passage scene.
Wherein, the driving information includes but is not limited to: vehicle position information, speed information, direction information, steering wheel angle information, turn signal status information.
The driving trajectory includes but is not limited to: driving intention, predicted vehicle position. Wherein the driving intent comprises: straight, left-turning, right-turning.
According to the embodiment of the invention, first running information is obtained, the first running information is the running information of a main vehicle, the first running information is predicted through a long-term memory network LSTM, a first running track is obtained, the first running track is sent to a far vehicle for cooperative passage, a second running track sent by the far vehicle is received, a passage scene is predicted according to the first running track and the second running track, and the cooperative passage is carried out according to the passage scene. The vehicles which are in cooperative passing can realize intelligent passing under the condition that road information is not needed, and the effectiveness of the intelligent passing under various scenes is guaranteed.
As shown in fig. 5, which is a block diagram of a system for collaborative vehicle passing according to still another embodiment of the present invention, the first driving trajectory acquiring module 402 includes:
a driving intention obtaining unit 501, configured to obtain the driving intention through the LSTM network according to a historical driving track of the vehicle and the first driving information;
a predicted vehicle position obtaining unit 502 for obtaining the predicted vehicle position through the LSTM network according to the driving intention, a vehicle history travel track, and first travel information.
In an embodiment of the present invention, the driving intent, i.e., the driver's possible future direction of travel, includes: and turning forwards, turning left and turning right, calling the vehicle historical driving track and the first driving information which are locally stored in the vehicle as input information of the LSTM network, wherein the output information of the LSTM network is the driving intention. And inputting the driving intention and the first running information into the LSTM network again as input information, wherein the output information is the predicted vehicle position.
As shown in fig. 6, which is a block diagram of a system for cooperative passing of vehicles according to another embodiment of the present invention, the cooperative passing module 404 includes:
a traffic scene prediction unit 601, configured to predict the traffic scene according to the first travel track and the second travel track, where the traffic scene includes: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
a cooperative passage unit 602, configured to perform a cooperative passage according to the passage scenario, where the cooperative passage includes: obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 771801DEST_PATH_IMAGE001
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold value, the vehicle with the shorter time accelerates to pass through the intersection point, if T 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
In the embodiment of the present invention, the traffic scenario may be divided into: the intersection passes, a plurality of vehicles converge into the same road and the vehicles change the road, and the principle of following different passing scenes is as follows: a vehicle having a shorter time from the intersection of the travel locus accelerates preferentially through the intersection, and a vehicle having a longer time from the intersection of the travel locus delays through the intersection.
Wherein the predicting the traffic scene according to the first and second driving tracks comprises:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
Fig. 7 illustrates a physical structure diagram of an electronic device, and as shown in fig. 7, the electronic device may include: a processor (processor)701, a communication Interface (Communications Interface)702, a memory (memory)703 and a communication bus 704, wherein the processor, the communication Interface and the memory complete communication with each other through the communication bus. The processor may invoke logic instructions in the memory to perform a method for collaborative navigation of a vehicle, the method comprising: acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information; predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle, and the running track comprises: driving intent, predicted vehicle position; sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle; and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene.
In addition, the logic instructions in the memory may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the method for collaborative passing of vehicles provided by the above-mentioned method embodiments, where the method includes: acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information; predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle, and the running track comprises: driving intent, predicted vehicle position; sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle; and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene.
In yet another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to execute the method for collaborative passing of vehicles provided by the foregoing embodiments, and the method includes: acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information; predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle, and the running track comprises: driving intent, predicted vehicle position; sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle; and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial implementation of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A method for collaborative passage of a vehicle, the method comprising:
acquiring first running information, wherein the first running information is running information of a host vehicle, and the running information comprises: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
predicting the first running information through a long-time memory network LSTM to obtain a first running track, wherein the first running track is a predicted running track of the main vehicle, and the running track comprises: driving intent, predicted vehicle position;
sending the first running track to a distant vehicle for cooperative passing, and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle;
and predicting a passing scene according to the first running track and the second running track, and performing cooperative passing according to the passing scene.
2. The method as claimed in claim 1, wherein the predicting the first travel information through a long-term memory network (LSTM) to obtain a first travel track comprises:
acquiring the driving intention through the LSTM network according to the historical driving track of the vehicle and the first driving information;
and acquiring the predicted vehicle position through the LSTM network according to the driving intention, the historical driving track of the vehicle and the first driving information.
3. The method of claim 1, wherein predicting a traffic scenario from the first and second travel trajectories and performing collaborative traffic according to the traffic scenario comprises:
predicting the passing scene according to the first driving track and the second driving track, wherein the passing scene comprises: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
performing cooperative passage according to the passage scene, wherein the cooperative passage comprises t 2 : obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 904492DEST_PATH_IMAGE002
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold, the vehicle with the shorter time is accelerated to pass through the intersection, if T is 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
4. The method of claim 3, wherein predicting the traffic scenario from the first and second travel trajectories comprises:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
5. A system for collaborative passage of vehicles, the system comprising:
a first travel information obtaining module, configured to obtain first travel information, where the first travel information is travel information of a host vehicle, and the travel information includes: vehicle position information, speed information, direction information, steering wheel angle information, and turn indicator light state information;
a first travel track obtaining module, configured to predict the first travel information through a long-term memory network LSTM to obtain a first travel track, where the first travel track is a predicted travel track of the host vehicle, and the travel track includes: driving intent, predicted vehicle position;
the second running track receiving module is used for sending the first running track to a distant vehicle for cooperative passing and receiving a second running track sent by the distant vehicle, wherein the second running track is a predicted running track of the distant vehicle;
and the cooperative passing module is used for predicting a passing scene according to the first running track and the second running track and performing cooperative passing according to the passing scene.
6. The system of claim 5, wherein the first travel track acquisition module comprises:
a driving intention acquisition unit, configured to acquire the driving intention through the LSTM network according to a vehicle historical driving track and the first driving information;
a predicted vehicle position acquisition unit for acquiring the predicted vehicle position through the LSTM network according to the driving intention, a vehicle history travel track, and first travel information.
7. The system of claim 5, wherein the collaborative passage module comprises:
a traffic scene prediction unit configured to predict the traffic scene according to the first travel track and the second travel track, the traffic scene including: the intersection passes, a plurality of vehicles are converged into the same road, and the vehicles change lanes;
the cooperative passage unit is used for performing cooperative passage according to the passage scene, and the cooperative passage comprises the following steps: obtaining the distance S of the intersection point of the main vehicle and the distant vehicle from the driving track 1 、S 2 According to
Figure 24894DEST_PATH_IMAGE002
Respectively acquiring the time T required by the main vehicle and the distant vehicle to reach the intersection 1 、T 2 If T is 1 And T 2 Is less than a preset time difference threshold value, the vehicle with the shorter time accelerates to pass through the intersection point, if T 1 And T 2 If the difference is larger than the preset time difference threshold value, the vehicle runs according to the normal running speed.
8. The system of claim 7, wherein predicting the traffic scenario from the first and second travel trajectories comprises:
if the driving intentions of the main vehicle and the distant vehicle are both straight and the driving directions are vertical, the passing scene is the intersection passing; or,
if the driving intentions of the main vehicle and the distant vehicles are that one vehicle is going straight and the other vehicle is turning, and the included angle of the driving directions is less than 45 degrees, the passing scene is that a plurality of vehicles merge into the same road; or,
and if the driving intentions of the main vehicle and the far vehicle are that the main vehicle and the far vehicle directly drive and turn, the position of the turning vehicle is in front of the position of the directly driving vehicle, and the driving directions are parallel to each other, the passing scene is that the vehicles change lanes.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, implements the method for collaborative passage of vehicles according to any of claims 1-4.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a method for collaborative passing of vehicles according to any of claims 1-4.
CN202210564028.2A 2022-05-23 2022-05-23 Method, system, electronic device and storage medium for cooperative vehicle passing Pending CN114898558A (en)

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Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106781692A (en) * 2016-12-01 2017-05-31 东软集团股份有限公司 The method of vehicle collision prewarning, apparatus and system
CN107274699A (en) * 2017-06-30 2017-10-20 重庆交通大学 Based on what position was shared passing method is cooperateed with without signal-control crossing vehicle certainly
CN110533913A (en) * 2019-09-17 2019-12-03 辰芯科技有限公司 Method for early warning, device, vehicle and the storage medium of vehicle collision
US20200062248A1 (en) * 2018-08-22 2020-02-27 Toyota Jidosha Kabushiki Kaisha Collision avoidance assist apparatus
CN110910657A (en) * 2019-12-04 2020-03-24 珠海深圳清华大学研究院创新中心 Intersection right-of-way distribution method and device and electronic equipment
CN111046919A (en) * 2019-11-21 2020-04-21 南京航空航天大学 Peripheral dynamic vehicle track prediction system and method integrating behavior intents
CN112002144A (en) * 2020-09-02 2020-11-27 中国科学技术大学 Method and system for evaluating driving risk situation of signalless intersection
CN112258841A (en) * 2020-10-26 2021-01-22 大连大学 Intelligent vehicle risk assessment method based on vehicle track prediction
CN112509314A (en) * 2020-10-23 2021-03-16 东风汽车集团有限公司 Intersection vehicle speed guiding method and device
WO2021134172A1 (en) * 2019-12-30 2021-07-08 华为技术有限公司 Trajectory prediction method and related device
CN113327458A (en) * 2021-07-08 2021-08-31 潍柴动力股份有限公司 Vehicle collision prediction method, vehicle collision prediction system, and electronic device
CN113838307A (en) * 2021-09-22 2021-12-24 中国重汽集团济南动力有限公司 Vehicle intersection collision early warning system and method
CN114333419A (en) * 2021-12-28 2022-04-12 杭州海康威视系统技术有限公司 Traffic conflict determination method, device, equipment and readable storage medium

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106781692A (en) * 2016-12-01 2017-05-31 东软集团股份有限公司 The method of vehicle collision prewarning, apparatus and system
CN107274699A (en) * 2017-06-30 2017-10-20 重庆交通大学 Based on what position was shared passing method is cooperateed with without signal-control crossing vehicle certainly
US20200062248A1 (en) * 2018-08-22 2020-02-27 Toyota Jidosha Kabushiki Kaisha Collision avoidance assist apparatus
CN110533913A (en) * 2019-09-17 2019-12-03 辰芯科技有限公司 Method for early warning, device, vehicle and the storage medium of vehicle collision
CN111046919A (en) * 2019-11-21 2020-04-21 南京航空航天大学 Peripheral dynamic vehicle track prediction system and method integrating behavior intents
CN110910657A (en) * 2019-12-04 2020-03-24 珠海深圳清华大学研究院创新中心 Intersection right-of-way distribution method and device and electronic equipment
WO2021134172A1 (en) * 2019-12-30 2021-07-08 华为技术有限公司 Trajectory prediction method and related device
CN112002144A (en) * 2020-09-02 2020-11-27 中国科学技术大学 Method and system for evaluating driving risk situation of signalless intersection
CN112509314A (en) * 2020-10-23 2021-03-16 东风汽车集团有限公司 Intersection vehicle speed guiding method and device
CN112258841A (en) * 2020-10-26 2021-01-22 大连大学 Intelligent vehicle risk assessment method based on vehicle track prediction
CN113327458A (en) * 2021-07-08 2021-08-31 潍柴动力股份有限公司 Vehicle collision prediction method, vehicle collision prediction system, and electronic device
CN113838307A (en) * 2021-09-22 2021-12-24 中国重汽集团济南动力有限公司 Vehicle intersection collision early warning system and method
CN114333419A (en) * 2021-12-28 2022-04-12 杭州海康威视系统技术有限公司 Traffic conflict determination method, device, equipment and readable storage medium

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