CN111145569A - Road monitoring and vehicle running control method and device and vehicle-road cooperative system - Google Patents
Road monitoring and vehicle running control method and device and vehicle-road cooperative system Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The application relates to a road monitoring and vehicle running control method, a device and a vehicle-road cooperative system, wherein the road monitoring method comprises the following steps: acquiring a road image obtained by shooting a road; identifying a first object on the road according to the road image to obtain first object information of the first object; determining a first motion track of the first object according to the first object information; and generating monitoring information corresponding to the road according to the first motion trail. According to the technical scheme, the traffic condition on the road can be monitored, the monitoring information can be sent to the vehicles running on the road so as to carry out traffic reminding, and the vehicle drivers or the automatic driving vehicles can make driving decisions according to the traffic reminding, so that the driving safety of the road is improved, and the safety of the whole road traffic is further improved.
Description
Technical Field
The application relates to the field of automatic driving, in particular to a road monitoring and vehicle running control method, a road monitoring and vehicle running control device and a vehicle and road cooperation system.
Background
With the development of technologies such as car networking, 5G, cloud computing, etc., the field of unmanned driving or automatic driving receives more and more attention.
Although the unmanned automobile industry develops rapidly, the current unmanned technical route mainly depends on the sensing and decision of automobile equipment, and a huge computing system is placed in an automobile, but various requirements of automatic driving, especially the requirements on safety, cannot be perfectly met. In addition, the intelligent automobile has extremely high bearing pressure and high cost. The current unmanned vehicle needs self-perception and self-decision, so the requirements on environment perception and recognition capability are extremely high.
In unmanned and automatic driving applications, the prediction of future form tracks of dynamic objects possibly appearing on roads such as automobiles, pedestrians, non-motor vehicles and the like is to improve the driving safety and accuracy of vehicles. The existing prediction is generally completed by a vehicle, the vehicle acquires relevant motion parameters of dynamic objects in a detection range, and the future motion trail of each dynamic object is predicted by combining the current environment condition.
However, the problem of visual blind spots cannot be completely solved only by the vehicle, and particularly for intersections with complex traffic conditions, the vehicle cannot sense dynamic objects outside the detection range of the sensor, so that the motion trajectory cannot be predicted, and the safety of unmanned vehicles passing through the intersections is difficult to guarantee.
Disclosure of Invention
In order to solve the technical problems or at least partially solve the technical problems, the application provides a road monitoring and vehicle running control method, a device and a vehicle-road coordination system.
In a first aspect, the present application provides a road monitoring method, including:
acquiring a road image obtained by shooting a road;
identifying a first object on the road according to the road image to obtain first object information of the first object;
determining a first motion track of the first object according to the first object information;
and generating monitoring information corresponding to the road according to the first motion trail.
Optionally, the method further includes:
receiving driving information of a vehicle, wherein the driving information comprises driving route information;
determining the driving track of the vehicle on the road according to the driving route information;
analyzing a second object which conflicts with the vehicle in the first object according to the first motion track and the driving track;
determining second object information corresponding to the second object;
determining a second motion track of the second object according to the second object information;
and generating the monitoring information according to the first motion trail and/or the second motion trail.
Optionally, the first object information includes: object position information, direction of motion, and speed of motion; the object position information comprises actual coordinates of the first object;
the determining a first motion trajectory of the first object according to the first object information includes:
determining a first prediction point coordinate according to a preset prediction algorithm and the actual coordinate, the motion direction and the motion speed;
multiplying the difference value between the actual coordinate and the first prediction point coordinate by a preset coefficient to obtain a product result;
adding the product result and the actual coordinate to obtain a second predicted point coordinate;
and obtaining a first motion track of the first object according to the second predicted point coordinate.
Optionally, the driving information further includes driving speed and vehicle position information of the vehicle;
the analyzing a second object which is in conflict with the vehicle running in the first object according to the first motion track and the running track comprises the following steps:
determining an intersection point of the first motion track and the driving track;
determining first time when the vehicle reaches the intersection point according to the running speed and the vehicle position information of the vehicle, and determining second time when the first object reaches the intersection point according to the movement speed and the object position information of the first object;
determining the first object as a second object having a conflict with the vehicle when a difference between the first time and the second time is less than or equal to a preset threshold.
Optionally, the method further includes:
and when the vehicle meets the preset reminding condition, sending the monitoring information to a terminal corresponding to the vehicle.
Optionally, the road image includes: at least two road images shot at a preset time interval and/or at least two road images extracted at the preset time interval from a shot road video;
identifying a first object on the road from the road image, comprising:
and calling a function in a preset function library to process and identify the road image to obtain the first object.
In a second aspect, the present application provides a vehicle travel control method including:
receiving monitoring information of a road, wherein the monitoring information is generated according to the embodiment of the road monitoring method;
when the fact that the vehicles have driving conflict on the road is determined according to the driving information of the vehicles and the monitoring information, driving conflict information is generated;
and carrying out running control according to the running conflict information.
In a third aspect, the present application provides a road monitoring device comprising:
the acquisition module is used for acquiring a road image obtained by shooting a road;
the identification module is used for identifying a first object on the road according to the road image to obtain first object information of the first object;
the analysis module is used for determining a first motion track of the first object according to the first object information;
and the generating module is used for generating the monitoring information corresponding to the road according to the first motion trail.
In a fourth aspect, the present application provides a vehicle travel control apparatus comprising:
the receiving module is used for receiving monitoring information of a road, and the monitoring information is generated according to the embodiment of the road monitoring method;
the generating module is used for generating running conflict information when the running conflict of the vehicle on the road is determined according to the running information of the vehicle and the monitoring information;
and the control module is used for carrying out running control according to the running conflict information.
In a fifth aspect, the present application provides a vehicle-road coordination system, including: the device comprises a camera device and an edge calculating device which are arranged on a road;
the camera device is used for shooting the road and sending the shot road image to the edge computing device;
the edge calculation device is configured to identify a first object on the road according to the road image, obtain first object information of the first object, determine a first motion trajectory of the first object according to the first object information, and generate monitoring information corresponding to the road according to the first motion trajectory.
Optionally, the system further comprises: an in-vehicle terminal located on a vehicle,
the edge computing device is used for sending the monitoring information to the vehicle-mounted terminal;
the vehicle-mounted terminal is used for receiving the monitoring information; when the fact that the vehicles have driving conflict on the road is determined according to the driving information of the vehicles and the monitoring information, driving conflict information is generated; and carrying out running control according to the running conflict information.
In a sixth aspect, the present application provides an electronic device, comprising: the system comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus;
the memory is used for storing a computer program;
the processor is configured to implement the above method steps when executing the computer program.
In a seventh aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the above-mentioned method steps.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages:
the method comprises the steps of monitoring objects on the road by shooting road images, determining the motion trail of the objects, and generating corresponding monitoring information according to the motion trail. Therefore, the monitoring of the traffic condition on the road can be realized, the monitoring information can be sent to the vehicles running on the road so as to carry out traffic reminding, and the vehicle drivers or the automatic driving vehicles can make driving decisions according to the traffic reminding, so that the driving safety of the road is improved, and the safety of the whole road traffic is further improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a block diagram of a road side system based on vehicle-road cooperation according to an embodiment of the present application;
fig. 2 is a schematic deployment diagram of a roadside system based on vehicle-road cooperation according to an embodiment of the present application;
fig. 3 is a schematic deployment diagram of a roadside system based on vehicle-road coordination according to another embodiment of the present application;
fig. 4 is a block diagram of a vehicle-road coordination system according to an embodiment of the present disclosure;
fig. 5 is a flowchart of a road monitoring method according to an embodiment of the present disclosure;
fig. 6 is a flowchart of a road monitoring method according to another embodiment of the present application;
fig. 7 is a flowchart of a road monitoring method according to another embodiment of the present application;
fig. 8 is a flowchart of a road monitoring method according to another embodiment of the present application;
fig. 9 is a schematic diagram of road monitoring information provided in an embodiment of the present application;
fig. 10 is a flowchart of a vehicle driving control method according to an embodiment of the present application;
fig. 11 is a block diagram of a road monitoring device according to an embodiment of the present disclosure;
fig. 12 is a block diagram of a vehicle travel control apparatus according to an embodiment of the present application;
fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The road monitoring method is mainly applied to road side systems based on vehicle-road cooperation.
Vehicle-road cooperation refers to the connection of all elements in a traffic system with all vehicles and roadside infrastructure in a wireless communication manner to form a complete system for providing dynamic information sharing. The road side system based on the cooperation of the vehicle and the road collects traffic information on the road, uses the edge computing equipment to carry out identification processing, and provides more comprehensive and accurate auxiliary information for the vehicle in time.
Fig. 1 is a block diagram of a road side system based on vehicle-road cooperation according to an embodiment of the present application. As shown in fig. 1, the road side system based on vehicle-road cooperation includes: the device comprises a camera device, an edge calculation device and a central calculation device which are arranged on a road. At least one camera device 10 is arranged on each first preset length of the road to shoot the road section with the first preset length; at least two camera devices 10 are connected with the edge calculation device 20; a first predetermined number of edge computing devices 20 are connected to a central computing device 30.
And the camera device 10 is used for uploading the shot image to the edge calculation device connected with the camera device. And an edge computing device 20 for performing recognition processing on the image and transmitting the recognition result to a central computing device connected with the edge computing device. And the central computing device 30 is used for carrying out data processing according to the identification result. The edge computing device can be an edge computing industrial personal computer, and the central computing device can be an edge computing workstation.
Fig. 2 is a schematic deployment diagram of a road side system based on vehicle-road cooperation according to an embodiment of the present application. As shown in fig. 2, on an expressway, in which at least one image pickup device 10 is provided per a first preset length on the road, the first preset length of a link is photographed. At least two cameras 10 are connected to the edge calculation device 20. A first predetermined number of edge computing devices 20 are connected to a central computing device 30.
For example, 1 image pickup device 10 may be provided at each end of a road segment of 100 meters. The 2 image pickup devices 10 relatively photograph the 100-meter link. Meanwhile, the 2 image pickup devices 10 are connected to the 1 edge calculation device 20. The 5 edge computing devices 20 are connected to the 1 central computing device 30.
The camera 10 and the edge computing device 20 are connected to a power over ethernet switch 41, and the central computing device 30 is connected to a power over core ethernet switch 42.
The roadside system further includes: the firewall device 50, the edge computing device 20, and the central computing device 30 are connected to a cloud server on the network side through the firewall device 50, respectively.
Fig. 3 is a schematic deployment diagram of a roadside system based on vehicle-road cooperation according to another embodiment of the present application. As shown in fig. 3, at least two image pickup devices 10 are provided on each side of the intersection, and the image pickup devices 10 take images toward the intersection. The camera means 10 arranged on each side are connected to an edge calculation means 20. Each edge computing device 20 is connected to 1 central computing device.
For example, 2 cameras 10 are provided on each side of the intersection, and the 2 cameras on each side are connected to one edge calculation device 20. The crossroads worker has 4 edge computing devices 20, each of the 4 edge computing devices 20 being connected to 1 central computing device 30.
The image pickup device 10 and the edge computing device 20 are connected to a power over ethernet switch 41, and the central computing device 30 is connected to a core power over ethernet switch 42.
The edge computing device 20 and the central computing device 30 may be connected to a cloud server, and upload an image recognition result or a data processing result to the cloud server, or receive an instruction or data sent by the cloud server.
By the roadside system, real-time monitoring of road conditions can be realized.
Fig. 4 is a block diagram of a vehicle-road coordination system according to an embodiment of the present application. As shown in fig. 4, the vehicle-road cooperation system according to the embodiment of the present application includes: the image pickup device 10 and the edge calculation device 20 are disposed on the road based on the above-described arrangement of the embodiment.
The image capturing device 10 is configured to capture an image of a road and transmit the captured image of the road to the edge calculating device 20.
And the edge calculating device 20 is configured to identify a first object on the road according to the road image, obtain first object information of the first object, determine a first moving track of the first object according to the first object information, and generate monitoring information corresponding to the road according to the first moving track.
As shown in fig. 4, the vehicle-road cooperation system further includes: an in-vehicle terminal 40 located on the vehicle.
And the edge computing device 20 is used for sending the monitoring information to the vehicle-mounted terminal 40. The vehicle-mounted terminal 40 is used for receiving monitoring information; when the fact that the vehicles have driving conflict on the road is determined according to the driving information and the monitoring information of the vehicles, generating driving conflict information; and performing running control according to the running conflict information.
In an optional embodiment, the vehicle-road coordination system further comprises: a central computing device 30. The edge calculation device 20 is configured to identify only the first object on the road from the road image, obtain first object information of the first object, and send the first object information to the central calculation device 30. The central computing device 30 is configured to determine a first moving track of the first object according to the first object information, generate monitoring information corresponding to the road according to the first moving track, and send the monitoring information to the vehicle-mounted terminal 40.
The following describes a road monitoring method provided by an embodiment of the present invention.
Fig. 5 is a flowchart of a road monitoring method according to an embodiment of the present application. As shown in fig. 5, the method comprises the steps of:
step S11, acquiring a road image obtained by shooting a road;
step S12, identifying a first object on the road according to the road image to obtain first object information of the first object;
step S13, determining a first motion track of the first object according to the first object information;
and step S14, generating monitoring information corresponding to the road according to the first motion trail.
In this embodiment, the road image is captured, the object on the road is monitored, the movement track of the object is determined, and corresponding monitoring information is generated according to the movement track. Therefore, the monitoring of the traffic condition on the road can be realized, the monitoring information can be sent to the vehicles running on the road so as to carry out traffic reminding, and the vehicle drivers or the automatic driving vehicles can make driving decisions according to the traffic reminding, so that the driving safety of the road is improved, and the safety of the whole road traffic is further improved.
Optionally, the first object comprises a dynamic object and/or a static object. The dynamic object includes: motor vehicles, bicycles, pedestrians, etc., static objects including: traffic lights, road barriers, obstacles to road maintenance, vehicles parked on the road in the event of a traffic accident, and the like. For dynamic objects, the object information may include: type of object (e.g., car, truck, van, bicycle, electric bike, pedestrian, etc.), size, object location, direction of movement, speed of movement, etc. For static objects, the object information may include: object type (traffic lights, road barriers, roadblocks, vehicles, etc.), size, object location, etc.
Therefore, by monitoring the dynamic objects and the static objects, the road traffic condition can be monitored more comprehensively and accurately, a vehicle driver or an automatic driving vehicle can make a driving decision accurately according to monitoring information, the occurrence of traffic conflicts is avoided, the driving safety of the vehicle road is improved, and the safety of the whole road traffic is further improved.
Fig. 6 is a flowchart of a road monitoring method according to another embodiment of the present application. As shown in fig. 6, the method further comprises the steps of:
step S21, receiving the driving information of the vehicle, wherein the driving information comprises driving route information; the driving information of the vehicle can be sent by a vehicle-mounted terminal located on the vehicle;
step S22, determining the driving track of the vehicle on the road according to the driving route information;
step S23, analyzing a second object which conflicts with the vehicle according to the first motion track and the driving track;
step S24, determining second object information corresponding to the second object;
step S25, determining a second motion track of the second object according to the second object information;
and step S26, generating monitoring information according to the first motion trail and/or the second motion trail.
For example, based on the traveling route information of the vehicle, it is determined that the traveling locus of the vehicle is traveling from east to west on the road and turning right at the intersection a. Through the motion track predicted for the identified first object, the step of determining that the second object conflicts with the vehicle running track comprises the following steps: also, a vehicle turning right at the intersection a is driven from east to west, a vehicle passing through the intersection a from south to north, pedestrians crossing the road at the east and north sides of the intersection, and so on. As for other vehicles, bicycles, pedestrians, and the like, since the movement locus thereof does not conflict with the vehicle, the monitoring information may be generated from only the movement locus of the second object when generating the monitoring information for the vehicle.
Therefore, the monitoring information is generated for the vehicle according to the vehicle running route in a targeted manner, so that a vehicle driver or an automatic driving vehicle can conveniently and accurately make a running decision according to the monitoring information, the occurrence of traffic conflict is avoided, the running safety of the vehicle road is improved, and the safety of the whole road traffic is further improved.
Optionally, the first object information includes: object position information, direction of motion, and speed of motion. The location information may include latitude and longitude information, GPS information, or actual coordinates, among others.
Fig. 7 is a flowchart of a road monitoring method according to another embodiment of the present application. Optionally, the driving information further includes driving speed of the vehicle and vehicle position information. As shown in fig. 7, the step S23 includes:
step S31, determining the intersection point of the first motion track and the driving track;
step S32, determining the first time when the vehicle reaches the intersection point according to the running speed and the position information of the vehicle, and determining the second time when the first object reaches the intersection point according to the movement speed and the position information of the first object;
in step S33, when the difference between the first time and the second time is less than or equal to a preset threshold, the first dynamic object is determined as a second object that conflicts with the vehicle travel.
In this embodiment, the time when the vehicle respectively reaches the intersection point may be calculated according to the speed of the vehicle running and the speed of the dynamic object, and if the time difference is less than or equal to the preset threshold, for example, when the time difference is less than or equal to 10 seconds, the time difference and the time when the vehicle runs and the speed when the vehicle runs.
In addition, in the embodiment, the traffic jam condition can be determined by identifying the dynamic object and the static object, and at the moment, corresponding monitoring information can be generated to remind a driver of the vehicle, so that the driver or the automatic driving vehicle can reselect a driving route to avoid a jammed road section, the driving time is saved, and the smoothness of road traffic is improved.
In the embodiment of the application, when the traffic light exists at the intersection, the time of the vehicle reaching the intersection and the traffic light information when the vehicle reaches the intersection, such as the red light or the green light, the light changing time and the like, can be further analyzed according to the vehicle running track, and the monitoring information is generated for the vehicle by combining the traffic light information and the monitoring conditions of the static object and the dynamic object, so that a driver or an automatic driving vehicle can more accurately know the traffic condition of the intersection.
In an optional embodiment, the method further comprises: and when the vehicle meets the preset reminding condition, sending the monitoring information to a terminal corresponding to the vehicle.
For example, when the vehicle is a preset distance away from the intersection, the terminal corresponding to the vehicle can be set to transmit the monitoring information of the intersection. Or, the monitoring information is fed back to the terminal sending the request road monitoring information, or the vehicle corresponding to the terminal is subscribed with the service of obtaining the road monitoring information, and the corresponding monitoring information can be sent according to the position or the route of the vehicle.
In an alternative embodiment, the road image comprises: the method comprises the steps of shooting at least two road images at preset time intervals, and/or extracting at least two road images at the preset time intervals from a shot road video. The step S12 includes: and calling a function in a preset function library to process and identify the road image to obtain a first dynamic object.
Optionally, the preset function library may be a cross-platform computer vision library OpenCV (including opencv2.0, opencv3.0, and the like). Specifically, the method comprises the following steps of:
(1) reading the road image, or extracting the road image from the road video.
(2) And calling a Rect function to select and set a region of interest (ROI) in the road image.
(3) And calling a GaussianBlur function to perform smoothing processing. For example, gaussian smoothing may be used, which is subject to current interference when a video is captured, but the current interference is uniformly present, so that the current interference can be removed by using gaussian smoothing.
(4) Calling the cvtColor function to perform gray processing, and converting the original frame into a gray image because the RGB image causes certain interference on identification or increases the processing difficulty.
(5) And calling an absdiff function to perform frame difference processing. By the frame difference processing, the outline of the object can be roughly recognized.
(6) And calling a threshold function to carry out binarization processing, wherein the threshold type can select CV _ THRESH _ BINARY, namely when the current point value is greater than the threshold value, Maxval is taken, namely a fourth parameter is taken, and otherwise, the fourth parameter is set to be 0. Optionally, because the original pictures of the objects are dark, a threshold value may be set to 30, and when the current point value is greater than the threshold value, the color is taken as white 255.
(7) And (4) calling a dilate function to perform expansion processing on the result obtained in the step (6). The purpose of expansion is to splice the identified contours into a complete individual for identification purposes.
(8) And calling an enode function to perform corrosion treatment, wherein the corrosion aims at removing bonding caused by expansion and non-critical points and areas so as to achieve the purpose of distinguishing the marks.
(9) And calling a findContours function to identify the outline of the object, and calling a rectangle function to convert the coordinates of the identified object into coordinates in the original image.
Through the preset function library, dynamic objects can be identified from the road image, and object information such as positions, sizes, speeds and the like of the dynamic objects can be further obtained, so that the motion trail of the dynamic objects can be predicted based on the object information in the following process.
In the embodiment of the application, the prediction of the motion trajectory of the dynamic object can be realized by using a computer vision library OpenCV with a kalman filter. The Kalman filter predicts the motion trail of the dynamic object through a recursion calculation process of continuously predicting the state of the object and updating the state prediction based on a measurement result.
However, it is impossible to immediately obtain the predicted point by directly processing the actual coordinate point by using the kalman filter, and it is seen from the actual use that the result of the processing is delayed from the current coordinate point (the coordinate point at the moment when the image pickup device recognizes the target), then regressed and advanced from the current point, but regressed and advanced from the current point again, and so on. Thus, when predicting a dynamic object, the predicted point may be behind the current point during the initial period of time, and even if the actual point is caught up by the subsequent predicted point, the target may have changed direction of motion or moved out of view. Therefore, the prediction effect of directly using the Kalman filter on the motion of the object is poor.
In the present embodiment, the following technical means are adopted to overcome the above problems.
Fig. 8 is a flowchart of a road monitoring method according to another embodiment of the present application. As shown in fig. 8, the first object information includes: object position information, direction of motion, and speed of motion; the object position information comprises actual coordinates of the first object. The step S13 includes:
step S41, determining coordinate information of a first prediction point according to a preset prediction algorithm and an actual coordinate, a motion direction and a motion speed;
step S42, multiplying the difference between the actual coordinate information and the first prediction point coordinate information by a preset coefficient to obtain a product result;
step S43, adding the product result and the actual coordinate information to obtain a second predicted point coordinate;
and step S44, obtaining a first motion track of the first dynamic object according to the second predicted point coordinates.
In this embodiment, the distance between the predicted point and the actual point is multiplied by a preset coefficient and then added to the coordinates of the actual point, thereby realizing motion prediction. During actual prediction, in the initial stage, the predicted point may be ahead of the actual point, but the distance between the predicted point and the actual point is gradually shortened in the subsequent stage, and finally the predicted point and the actual point are overlapped, so that the prediction effect is more accurate for the dynamic object.
Fig. 9 is a schematic view of road monitoring information provided in an embodiment of the present application. As shown in fig. 9, the driving directions, speeds, and traffic light conditions of all vehicles and pedestrians at the intersection are shown. The driver or the automatic driving vehicle can clearly and accurately know the traffic condition of the intersection according to the map, and make a traffic decision in advance, so that the driving safety and the traffic safety of the whole road can be improved.
In this embodiment, the method further includes: when it is determined that there is a motion collision or a second object having a driving collision with the vehicle according to the first motion trajectory, the state of the signal lamp may be controlled according to the collision.
For example, when it is found that a driving conflict may occur between the vehicle and a pedestrian crossing the road when the vehicle turns right at the intersection, the right turn signal lamp may be controlled to be in a red state when the vehicle reaches the intersection, and a time for the right turn signal lamp to maintain the red state may be determined according to a time for the pedestrian to pass the road, and when the time is reached, the right turn signal lamp may be controlled to turn green so that the vehicle may turn right. Thereby avoiding traffic conflict and improving traffic safety on roads.
The following describes a vehicle travel control method provided by an embodiment of the present invention.
Fig. 10 is a flowchart of a vehicle driving control method according to an embodiment of the present application. As shown in fig. 10, the method is applied to a vehicle-mounted terminal, and comprises the following steps:
step S51, receiving monitoring information of a road, the monitoring information being generated according to the above-mentioned road monitoring method embodiment;
step S52, when it is determined that the vehicle has a driving conflict on the road according to the driving information and the monitoring information of the vehicle, generating driving conflict information;
in step S53, the driving control is performed based on the driving collision information.
Wherein, the monitoring information may include: all the first object information on the road, and/or the second object information on the road which conflicts with the running of the vehicle. The vehicle-mounted terminal determines that the vehicle collision information is generated when the vehicle collision exists on the road according to the monitoring information and the driving information of the vehicle, such as the driving route, the driving speed, the position information and the like.
Wherein the driving conflict information may include: the current driving speed, position and driving route of the vehicle may have traffic conflict with other vehicles, pedestrians, etc. at a certain intersection, and the speed, driving direction, etc. of the vehicles or pedestrians having traffic conflict.
Based on the driving conflict information, corresponding driving control operations can be executed, for example, for a vehicle driven by the driver, reminding can be performed according to the driving conflict information, such as generating a new driving route and recommending the driver to change the route, recommending the driver to change the driving speed, and the like; for an autonomous vehicle, the vehicle travel speed may be automatically adjusted or the travel route may be changed, etc., according to the travel conflict information.
In this embodiment, the vehicle-mounted terminal performs travel control according to the monitoring information, thereby improving the safety of road travel and further improving the safety of the whole road traffic. The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application.
Fig. 11 is a block diagram of a road monitoring device provided in an embodiment of the present application, which may be implemented as part or all of an electronic device through software, hardware, or a combination of the two. As shown in fig. 11, the road monitoring device includes:
the acquisition module 61 is used for acquiring a road image obtained by shooting a road;
the identification module 62 is configured to identify a first object on the road according to the road image, and obtain first object information of the first object;
the analysis module 63 determines a first motion track of the first object according to the first object information;
and a generating module 64, configured to generate the monitoring information according to the first motion trajectory.
Fig. 12 is a block diagram of a vehicle travel control device provided in an embodiment of the present application, which may be implemented as part or all of an electronic device through software, hardware, or a combination of the two. As shown in fig. 12, the vehicle travel control device includes:
a receiving module 71, configured to receive monitoring information of a road, where the monitoring information is generated according to the embodiment of the road monitoring method;
the generating module 72 is used for generating running conflict information when it is determined that the vehicle runs conflict on the road according to the running information and the monitoring information of the vehicle;
and a control module 73 for performing travel control according to the travel conflict information.
An embodiment of the present application further provides an electronic device, as shown in fig. 13, the electronic device may include: the system comprises a processor 1501, a communication interface 1502, a memory 1503 and a communication bus 1504, wherein the processor 1501, the communication interface 1502 and the memory 1503 complete communication with each other through the communication bus 1504.
A memory 1503 for storing a computer program;
the processor 1501, when executing the computer program stored in the memory 1503, implements the steps of the method embodiments described below.
The communication bus mentioned in the electronic device may be a peripheral component interconnect (pci) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method embodiments described below.
It should be noted that, for the above-mentioned apparatus, electronic device and computer-readable storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiments.
It is further noted that, herein, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (13)
1. A method of road monitoring, comprising:
acquiring a road image obtained by shooting a road;
identifying a first object on the road according to the road image to obtain first object information of the first object;
determining a first motion track of the first object according to the first object information;
and generating monitoring information corresponding to the road according to the first motion trail.
2. The method of claim 1, further comprising:
receiving driving information of a vehicle, wherein the driving information comprises driving route information;
determining the driving track of the vehicle on the road according to the driving route information;
analyzing a second object which conflicts with the vehicle in the first object according to the first motion track and the driving track;
determining second object information corresponding to the second object;
determining a second motion track of the second object according to the second object information;
and generating the monitoring information according to the first motion trail and/or the second motion trail.
3. The method of claim 2, wherein the first object information comprises: object position information, direction of motion, and speed of motion; the object position information comprises actual coordinates of the first object;
the determining a first motion trajectory of the first object according to the first object information includes:
determining a first prediction point coordinate according to a preset prediction algorithm and the actual coordinate, the motion direction and the motion speed;
multiplying the difference value between the actual coordinate and the first prediction point coordinate by a preset coefficient to obtain a product result;
adding the product result and the actual coordinate to obtain a second predicted point coordinate;
and obtaining a first motion track of the first object according to the second predicted point coordinate.
4. The method of claim 3, wherein the travel information further includes travel speed and vehicle location information of the vehicle;
the analyzing a second object which is in conflict with the vehicle running in the first object according to the first motion track and the running track comprises the following steps:
determining an intersection point of the first motion track and the driving track;
determining first time when the vehicle reaches the intersection point according to the running speed and the vehicle position information of the vehicle, and determining second time when the first object reaches the intersection point according to the movement speed and the object position information of the first object;
determining the first object as a second object having a conflict with the vehicle when a difference between the first time and the second time is less than or equal to a preset threshold.
5. The method according to any one of claims 1-4, further comprising:
and when the vehicle meets the preset reminding condition, sending the monitoring information to a terminal corresponding to the vehicle.
6. The method of claim 1, wherein the road image comprises: at least two road images shot at a preset time interval and/or at least two road images extracted at the preset time interval from a shot road video;
identifying a first object on the road from the road image, comprising:
and calling a function in a preset function library to process and identify the road image to obtain the first object.
7. A vehicle travel control method characterized by comprising:
receiving monitoring information for a roadway, the monitoring information generated according to the method of any one of claims 1-6;
when the fact that the vehicles have driving conflict on the road is determined according to the driving information of the vehicles and the monitoring information, driving conflict information is generated;
and carrying out running control according to the running conflict information.
8. A road monitoring device, comprising:
the acquisition module is used for acquiring a road image obtained by shooting a road;
the identification module is used for identifying a first object on the road according to the road image to obtain first object information of the first object;
the analysis module is used for determining a first motion track of the first object according to the first object information;
and the generating module is used for generating the monitoring information corresponding to the road according to the first motion trail.
9. A vehicle travel control device characterized by comprising:
a receiving module for receiving monitoring information of a road, the monitoring information being generated according to the method of any one of claims 1-6;
the generating module is used for generating running conflict information when the running conflict of the vehicle on the road is determined according to the running information of the vehicle and the monitoring information;
and the control module is used for carrying out running control according to the running conflict information.
10. A vehicle-road coordination system, comprising: the device comprises a camera device and an edge calculating device which are arranged on a road;
the camera device is used for shooting the road and sending the shot road image to the edge computing device;
the edge calculation device is configured to identify a first object on the road according to the road image, obtain first object information of the first object, determine a first motion rail of the first object according to the first object information, and generate monitoring information corresponding to the road according to the first motion track.
11. The system of claim 10, further comprising: an in-vehicle terminal located on a vehicle,
the edge computing device is used for sending the monitoring information to the vehicle-mounted terminal;
the vehicle-mounted terminal is used for receiving the monitoring information; when the fact that the vehicles have driving conflict on the road is determined according to the driving information of the vehicles and the monitoring information, driving conflict information is generated; and carrying out running control according to the running conflict information.
12. An electronic device, comprising: the system comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus;
the memory is used for storing a computer program;
the processor, when executing the computer program, implementing the method steps of any of claims 1-7.
13. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method steps of any one of claims 1 to 7.
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