CN114399916B - Virtual traffic light control reminding method for digital twin smart city traffic - Google Patents
Virtual traffic light control reminding method for digital twin smart city traffic Download PDFInfo
- Publication number
- CN114399916B CN114399916B CN202210058268.5A CN202210058268A CN114399916B CN 114399916 B CN114399916 B CN 114399916B CN 202210058268 A CN202210058268 A CN 202210058268A CN 114399916 B CN114399916 B CN 114399916B
- Authority
- CN
- China
- Prior art keywords
- information
- virtual
- vehicle
- traffic
- real
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000008569 process Effects 0.000 claims abstract description 15
- 230000008859 change Effects 0.000 claims description 59
- 230000000737 periodic effect Effects 0.000 claims description 39
- 238000012544 monitoring process Methods 0.000 claims description 25
- 238000013507 mapping Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 8
- 238000010276 construction Methods 0.000 claims description 6
- 239000000523 sample Substances 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 10
- 238000012545 processing Methods 0.000 description 8
- 238000004891 communication Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a virtual traffic light control reminding method of digital twin smart city traffic, which comprises the steps of constructing a digital twin traffic system based on actual data information of each road crossing, and distributing virtual traffic lights at each virtual road crossing in the digital twin traffic system; continuously acquiring real-time feedback data of the vehicle, and determining the real-time position of the vehicle in the digital twin traffic system; when the real-time position reaches any virtual road intersection, lane position information of the vehicle is determined based on the real-time feedback data, a control instruction is generated based on target virtual traffic light signal information corresponding to the lane position information, and the control instruction is sent to the vehicle. According to the invention, the actual traffic light information of the road intersection can be obtained in real time through the virtual traffic light even under a severe environment or under the condition that the view of the vehicle camera probe is blocked in the running process of the unmanned vehicle, and the safe running of the unmanned vehicle is ensured.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to a virtual traffic light control reminding method for digital twin smart city traffic.
Background
With the development of technology, the automatic driving technology has become the field of research of numerous technological companies. The unmanned automobile mainly depends on an unmanned system to realize the purpose of automatic driving, namely, an intelligent automobile which senses the road environment through a vehicle-mounted sensing system, automatically plans a driving route and controls the vehicle to reach a preset target. For unmanned vehicles and urban roads, the control of traffic lights is a difficulty in ensuring safe and efficient running of the automatic driving vehicles.
At present, most intersections still use traditional traffic light equipment, and as traffic light equipment of different intersections has certain differences in installation position, shape and the like, the traffic light identification technology based on cameras at present is high in false detection rate and low in robustness. In addition, the identification method based on the traffic light image is also easily affected by weather and surrounding environment, for example, when the vehicle is in heavy snow weather or the unmanned vehicle is shielded by a large vehicle, the image identification method is difficult to accurately identify the traffic light, and therefore the unmanned vehicle is in an unpredictable danger.
Disclosure of Invention
In order to solve the problems, the embodiment of the application provides a virtual traffic light control reminding method for digital twin smart city traffic.
In a first aspect, an embodiment of the present application provides a method for reminding virtual traffic lights of digital twin smart city traffic, where the method includes:
Constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system to enable the virtual traffic lights to be matched with the actual data information;
Continuously acquiring real-time feedback data of a vehicle, and determining the real-time position of the vehicle in the digital twin traffic system;
When the real-time position reaches any virtual road intersection, determining lane position information of the vehicle based on the real-time feedback data, generating a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle.
Preferably, the constructing a digital twin traffic system based on the actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system, so as to match the virtual traffic lights with the actual data information, includes:
Acquiring actual data information of each road intersection, and constructing a digital twin traffic system based on each actual data information, wherein the actual data information comprises first traffic light periodic signal change information;
virtual traffic lights are distributed at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the first traffic light periodic signal change information;
obtaining second traffic light periodic signal change information of each road intersection after a first preset time length passes, and comparing the second traffic light periodic signal change information with virtual traffic light periodic signal change information of the virtual traffic light;
And optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information when the comparison results are characterized as different.
Preferably, the actual data information further comprises video monitoring information;
The virtual traffic lights are distributed to each virtual road crossing in the digital twin traffic system, and the method comprises the following steps:
Acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow in the video monitoring information and weather and date;
And distributing virtual traffic lights at each virtual road crossing in the digital twin traffic system based on the mapping relation.
Preferably, the continuously acquiring real-time feedback data of the vehicle, determining a real-time position of the vehicle in the digital twin traffic system includes:
continuously acquiring real-time feedback data of the vehicle, wherein the real-time feedback data comprises GPS positioning information;
Determining a real-time position of the vehicle in the digital twin traffic system according to the GPS positioning information;
And acquiring the vehicle azimuth information acquired by each roadside sensor in the first preset range of the real-time position, and optimizing the real-time position based on the vehicle azimuth information.
Preferably, when the real-time position reaches any one of the virtual road intersections, determining lane position information of the vehicle based on the real-time feedback data includes:
And when the real-time position enters a judging range corresponding to any virtual road intersection, determining the lane position information of the vehicle based on the real-time feedback data.
Preferably, the real-time feedback data further comprises a vehicle driving steering angle;
the method further comprises the steps of:
and when the angle change value of the vehicle driving steering angle in the second preset time period is detected to be larger than the preset change value, updating the lane position information, repeating the process of generating a control instruction based on the target virtual traffic light signal information corresponding to the lane position information and sending the control instruction to the vehicle.
In a second aspect, an embodiment of the present application provides a virtual traffic light control reminding device for digital twin smart city traffic, where the device includes:
The construction module is used for constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the actual data information;
the acquisition module is used for continuously acquiring real-time feedback data of the vehicle and determining the real-time position of the vehicle in the digital twin traffic system;
and the control module is used for determining the lane position information of the vehicle based on the real-time feedback data when the real-time position enters a judging range corresponding to any virtual road intersection, generating a control instruction based on the target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle.
In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method as provided in the first aspect or any one of the possible implementations of the first aspect when the computer program is executed.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as provided by the first aspect or any one of the possible implementations of the first aspect.
The beneficial effects of the invention are as follows: in the running process of the unmanned vehicle, even under severe environment or under the condition that the view of the vehicle camera probe is blocked, the vehicle can still acquire the actual traffic light information of the road intersection in real time through the virtual traffic light, so that the safe running of the unmanned vehicle is ensured.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a virtual traffic light control reminding method of digital twin smart city traffic provided by the embodiment of the application;
Fig. 2 is a schematic structural diagram of a virtual traffic light control reminding device for digital twin smart city traffic provided by the embodiment of the application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application.
In the following description, the terms "first," "second," and "first," are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The following description provides various embodiments of the application that may be substituted or combined between different embodiments, and thus the application is also to be considered as embracing all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then the application should also be seen as embracing one or more of all other possible combinations of one or more of A, B, C, D, although such an embodiment may not be explicitly recited in the following.
The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the application. Various examples may omit, replace, or add various procedures or components as appropriate. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
Referring to fig. 1, fig. 1 is a schematic flow chart of a virtual traffic light control reminding method for digital twin smart city traffic provided by an embodiment of the application. In an embodiment of the present application, the method includes:
s101, constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the actual data information.
The execution subject of the present application may be a cloud server.
The digital twin can be understood as fully utilizing data such as a physical model, sensor update, operation history and the like, integrating simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and mapping is completed in a virtual space, so that the full life cycle process of corresponding entity equipment is reflected. Which may be considered as a digital mapping system of one or more important, mutually dependent equipment systems. The digital twin traffic system is to utilize the existing video monitoring resources of the current intersection, the millimeter wave radar collects data, and the real world information is imported into the twin traffic simulation system by fully fusing the data through holographic perception of traffic elements including motor vehicles, non-motor vehicles, pedestrians and the like in the traffic road network.
In the embodiment of the application, the digital twin traffic system can be regarded as a same virtual traffic system which is simulated based on the actual traffic system, so that in order to ensure the authenticity and the reliability of the system, the cloud server needs to acquire the equipment of each road junction in the actual traffic system and the actual data information acquired by the sensor, and the digital twin traffic system is constructed by the equipment and the sensor. After the digital twin traffic system is constructed, virtual traffic lights are distributed in each virtual road intersection corresponding to each road intersection in the digital twin traffic system, and the virtual traffic lights are matched with actual data information, so that the change condition of the virtual traffic lights in the digital twin traffic system can be ensured to be identical with that of the traffic lights of the actual road intersections. The construction process of a digital twin system is well known to those skilled in the art in the case where the actual data information required to construct the system is determined, and the specific construction process of the digital twin system is not an important point of the present application and is not described in detail herein.
In one embodiment, step S101 includes:
Acquiring actual data information of each road intersection, and constructing a digital twin traffic system based on each actual data information, wherein the actual data information comprises first traffic light periodic signal change information;
virtual traffic lights are distributed at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the first traffic light periodic signal change information;
obtaining second traffic light periodic signal change information of each road intersection after a first preset time length passes, and comparing the second traffic light periodic signal change information with virtual traffic light periodic signal change information of the virtual traffic light;
And optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information when the comparison results are characterized as different.
In the embodiment of the application, the most critical information in the actual data information is the first traffic light periodic signal change information, the cloud server characterizes the actual traffic light signal change condition of the intersection by the first traffic light periodic signal change information, and enables the virtual traffic light in the digital twin traffic system to be matched with the first traffic light periodic signal change information, namely, the first traffic light periodic signal change information is used as the virtual traffic light periodic signal change information of the virtual traffic light, so that the signal change condition of the virtual traffic light is ensured to be the same as the actual condition. In addition, in order to guarantee real-time accuracy of the virtual traffic lights, the cloud server can acquire the second traffic light periodic signal change information in the actual condition of the road intersection once again after a period of time, and compares the first traffic light periodic signal change information with the second traffic light periodic signal change information. If the signal change conditions of the virtual traffic lights are normal, the comparison results of the two signals are the same, so that when the comparison result features are different, the fact that the current signal lamp change conditions of the virtual traffic lights are abnormal is indicated, deviation possibly occurs between the current signal lamp change conditions and actual conditions, and the cloud server optimizes the virtual traffic light periodic signal change information according to the second traffic light periodic signal change information to ensure that the virtual traffic light periodic signal change information is continuous and accurate.
In one embodiment, the actual data information further includes video monitoring information;
The virtual traffic lights are distributed to each virtual road crossing in the digital twin traffic system, and the method comprises the following steps:
Acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow in the video monitoring information and weather and date;
And distributing virtual traffic lights at each virtual road crossing in the digital twin traffic system based on the mapping relation.
In the embodiment of the application, the actual data information also comprises video monitoring information shot by the monitoring cameras of the road junction, and the road traffic flow in a period of time can be calculated according to the video monitoring information. In practical situations, the number of people traveling on the road is different along with different weather and holidays, and then the traffic flow is different. Compared with the real traffic lights, the virtual traffic lights are still data information, and the virtual traffic lights need to be information-interacted with the matched vehicles to inform the vehicles of the actual traffic lights, so that in order to ensure the data processing efficiency of each virtual traffic light, the virtual traffic lights do not simultaneously information-interacted with too many vehicles. For the reasons mentioned above, in the trip peak period, in order to ensure the information interaction efficiency of the virtual traffic lights, and also in order to ensure that the vehicles going on can timely receive the relevant control data, a plurality of virtual traffic lights need to be set to work simultaneously. The cloud server can determine the traffic flow changes under different days and different days according to all video monitoring information in a preset monitoring period, so that the mapping relation between the traffic flow and weather and dates is determined. After the mapping relation is determined, the traffic flow of the current date can be estimated, and the corresponding number of virtual traffic lights can be distributed.
S102, continuously acquiring real-time feedback data of the vehicle, and determining the real-time position of the vehicle in the digital twin traffic system.
In the embodiment of the application, the real-time feedback data is continuously sent to the cloud server in the running process of the vehicle, so that the cloud server can determine the actual position of the vehicle by continuously acquiring the real-time feedback data sent by the vehicle, and further can determine the real-time position of the vehicle in the digital twin traffic system.
In one embodiment, step S102 includes:
continuously acquiring real-time feedback data of the vehicle, wherein the real-time feedback data comprises GPS positioning information;
Determining a real-time position of the vehicle in the digital twin traffic system according to the GPS positioning information;
And acquiring the vehicle azimuth information acquired by each roadside sensor in the first preset range of the real-time position, and optimizing the real-time position based on the vehicle azimuth information.
In the embodiment of the application, the real-time feedback data comprises GPS positioning information acquired by the vehicle according to the vehicle-mounted GPS, and the cloud server determines the actual position of the vehicle in the road according to the GPS positioning information, so as to determine the real-time position of the vehicle in the digital twin traffic system. In addition, since there may be an error in the positioning information determined by the GPS, roadside sensors are intermittently provided at the roadside of the road for accurately determining the position of the vehicle. The roadside sensor can acquire vehicle azimuth information of the vehicle according to the relative distance and the relative angle between the roadside sensor and the vehicle, and the cloud server adjusts the real-time position by acquiring the vehicle azimuth information, so that the accuracy of the optimized real-time position is ensured.
And S103, when the real-time position reaches any virtual road intersection, determining lane position information of the vehicle based on the real-time feedback data, generating a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle.
In the embodiment of the application, when the cloud server detects that the real-time position of the vehicle reaches a certain virtual road intersection, the cloud server indicates that the traffic light signal change needs to be carried out on the vehicle at the moment to carry out auxiliary reminding control, so that the vehicle can safely pass through the traffic light under the condition of observing the traffic regulations. Specifically, the cloud server determines lane position information of the vehicle at the moment through real-time feedback data continuously sent by the vehicle, namely, on which lane of the current road the vehicle is located, further determines target virtual traffic light signal information of target virtual traffic lights corresponding to the lane position information, determines traffic light conditions of the actual road through which the vehicle needs to pass, and finally generates a response control instruction to control the running process of the vehicle so as to assist the vehicle to safely pass the traffic lights.
In one embodiment, the determining lane position information of the vehicle based on the real-time feedback data when the real-time position reaches any one of the virtual road intersections includes:
And when the real-time position enters a judging range corresponding to any virtual road intersection, determining the lane position information of the vehicle based on the real-time feedback data.
In the embodiment of the application, each virtual road intersection is provided with a corresponding judgment range, and when the corresponding real-time position of the vehicle enters the judgment range, the cloud server considers that the vehicle reaches the virtual road intersection, and the lane position information of the vehicle is determined according to the real-time feedback data.
In one embodiment, the real-time feedback data further includes a vehicle travel steering angle;
the method further comprises the steps of:
and when the angle change value of the vehicle driving steering angle in the second preset time period is detected to be larger than the preset change value, updating the lane position information, repeating the process of generating a control instruction based on the target virtual traffic light signal information corresponding to the lane position information and sending the control instruction to the vehicle.
In the embodiment of the application, the real-time feedback data sent by the vehicle also comprises the running steering angle of the vehicle, namely the steering angle of the forward wheels of the vehicle in the running process. And when the vehicle driving steering angle continuously changes within the second preset duration and the angle change value is larger than the preset change value, the vehicle is considered to change lanes. For different lanes, the corresponding virtual traffic lights are different, and the actual traffic light change is also different. Therefore, after the lane change of the vehicle is determined, the cloud server updates the lane position information and regenerates the control command to control the vehicle newly, so that the latest control command of the vehicle is ensured to be in line with the running condition of the vehicle, and the running safety of the vehicle is ensured.
The virtual traffic light control reminding device for digital twin smart city traffic provided by the embodiment of the application is described in detail below with reference to fig. 2. It should be noted that, the virtual traffic light control reminding device of the digital twin smart city traffic shown in fig. 2 is used for executing the method of the embodiment shown in fig. 1 of the present application, for convenience of explanation, only the relevant parts of the embodiment of the present application are shown, and specific technical details are not disclosed, please refer to the embodiment shown in fig. 1 of the present application.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a virtual traffic light control reminding device for digital twin smart city traffic provided by an embodiment of the application. As shown in fig. 2, the apparatus includes:
The construction module 201 is configured to construct a digital twin traffic system based on actual data information of each road intersection, and allocate virtual traffic lights to each virtual road intersection in the digital twin traffic system, so as to match the virtual traffic lights with the actual data information;
An acquisition module 202, configured to continuously acquire real-time feedback data of a vehicle, and determine a real-time position of the vehicle in the digital twin traffic system;
And the control module 203 is configured to determine lane position information of the vehicle based on the real-time feedback data when the real-time position enters a judgment range corresponding to any one of the virtual road intersections, generate a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and send the control instruction to the vehicle.
In one embodiment, the build module 201 includes:
The construction unit is used for acquiring actual data information of each road intersection and constructing a digital twin traffic system based on each actual data information, wherein the actual data information comprises first traffic light periodic signal change information;
The first distribution unit is used for distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the first traffic light periodic signal change information;
The comparison unit is used for acquiring second traffic light periodic signal change information of each road intersection every time a first preset time period passes, and comparing the second traffic light periodic signal change information with the virtual traffic light periodic signal change information of the virtual traffic light;
and the first optimizing unit is used for optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information when the comparison results are characterized as different.
In one embodiment, the build module 201 further includes:
the mapping relation determining unit is used for obtaining all the video monitoring information in a preset monitoring period and determining the mapping relation between the traffic flow in the video monitoring information and weather and date;
and the second allocation unit is used for allocating virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
In one embodiment, the acquisition module 202 includes:
the acquisition unit is used for continuously acquiring real-time feedback data of the vehicle, wherein the real-time feedback data comprises GPS positioning information;
A position determining unit for determining a real-time position of the vehicle in the digital twin traffic system according to the GPS positioning information;
the second optimizing unit is used for acquiring the vehicle azimuth information acquired by each roadside sensor in the first preset range of the real-time position and optimizing the real-time position based on the vehicle azimuth information.
In one embodiment, the control module 203 includes:
and the judging unit is used for determining the lane position information of the vehicle based on the real-time feedback data when the real-time position enters a judging range corresponding to any virtual road intersection.
In one embodiment, the apparatus further comprises:
And the repeating module is used for updating the lane position information when detecting that the angle change value of the vehicle driving steering angle in the second preset duration is larger than the preset change value, repeating the process of generating a control instruction based on the target virtual traffic light signal information corresponding to the lane position information and sending the control instruction to the vehicle.
It will be clear to those skilled in the art that the technical solutions of the embodiments of the present application may be implemented by means of software and/or hardware. "unit" and "module" in this specification refer to software and/or hardware capable of performing a particular function, either alone or in combination with other components, such as Field-Programmable gate arrays (Field-Programmable GATE ARRAY, FPGA), integrated circuits (INTEGRATED CIRCUIT, ICs), and the like.
The processing units and/or modules of the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.
Referring to fig. 3, a schematic structural diagram of an electronic device according to an embodiment of the present application is shown, where the electronic device may be used to implement the method in the embodiment shown in fig. 1. As shown in fig. 3, the electronic device 300 may include: at least one central processor 301, at least one network interface 304, a user interface 303, a memory 305, at least one communication bus 302.
Wherein the communication bus 302 is used to enable connected communication between these components.
The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the central processor 301 may comprise one or more processing cores. The central processor 301 connects the various parts within the overall electronic device 300 using various interfaces and lines, performs various functions of the terminal 300 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the central processor 301 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), programmable logic array (Programmable Logic Array, PLA). The central processor 301 may integrate one or a combination of several of a central processor (Central Processing Unit, CPU), an image central processor (Graphics Processing Unit, GPU), a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the cpu 301 and may be implemented by a single chip.
The Memory 305 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like referred to in the above respective method embodiments. The memory 305 may also optionally be at least one storage device located remotely from the aforementioned central processor 301. As shown in fig. 3, an operating system, a network communication module, a user interface module, and program instructions may be included in the memory 305, which is a type of computer storage medium.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the central processor 301 may be used to invoke the virtual traffic light control reminder application of the digital twin smart city traffic stored in the memory 305 and specifically perform the following operations:
Constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system to enable the virtual traffic lights to be matched with the actual data information;
Continuously acquiring real-time feedback data of a vehicle, and determining the real-time position of the vehicle in the digital twin traffic system;
When the real-time position reaches any virtual road intersection, determining lane position information of the vehicle based on the real-time feedback data, generating a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle.
The present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method. The computer-readable storage medium may include, among other things, any type of disk including floppy disks, optical disks, DVDs, CD-ROMs, micro-drives, and magneto-optical disks, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, such as the division of the units, merely a logical function division, and there may be additional manners of dividing the actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or partly in the form of a software product, or all or part of the technical solution, which is stored in a memory, and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be performed by hardware associated with a program that is stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.
Claims (8)
1. The virtual traffic light control reminding method for the digital twin smart city traffic is characterized by comprising the following steps of:
Constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system to enable the virtual traffic lights to be matched with the actual data information;
Continuously acquiring real-time feedback data of a vehicle, and determining the real-time position of the vehicle in the digital twin traffic system;
When the real-time position reaches any virtual road intersection, determining lane position information of the vehicle based on the real-time feedback data, generating a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle;
wherein the actual data information further comprises video monitoring information;
The virtual traffic lights are distributed to each virtual road crossing in the digital twin traffic system, and the method comprises the following steps:
Acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow in the video monitoring information and weather and date;
and distributing corresponding quantity of virtual traffic lights at each virtual road crossing in the digital twin traffic system based on the mapping relation.
2. The method of claim 1, wherein the constructing a digital twin traffic system based on actual data information of each road junction and assigning virtual traffic lights at each virtual road junction in the digital twin traffic system to match the virtual traffic lights with the actual data information comprises:
Acquiring actual data information of each road intersection, and constructing a digital twin traffic system based on each actual data information, wherein the actual data information comprises first traffic light periodic signal change information;
virtual traffic lights are distributed at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the first traffic light periodic signal change information;
obtaining second traffic light periodic signal change information of each road intersection after a first preset time length passes, and comparing the second traffic light periodic signal change information with virtual traffic light periodic signal change information of the virtual traffic light;
And optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information when the comparison results are characterized as different.
3. The method of claim 1, wherein the continuously obtaining real-time feedback data of a vehicle, determining a real-time location of the vehicle in the digital twin traffic system, comprises:
continuously acquiring real-time feedback data of the vehicle, wherein the real-time feedback data comprises GPS positioning information;
Determining a real-time position of the vehicle in the digital twin traffic system according to the GPS positioning information;
And acquiring the vehicle azimuth information acquired by each roadside sensor in the first preset range of the real-time position, and optimizing the real-time position based on the vehicle azimuth information.
4. The method of claim 1, wherein the determining lane position information of the vehicle based on the real-time feedback data when the real-time position reaches any one of the virtual road intersections comprises:
And when the real-time position enters a judging range corresponding to any virtual road intersection, determining the lane position information of the vehicle based on the real-time feedback data.
5. The method of claim 1, wherein the real-time feedback data further comprises a vehicle travel steering angle;
the method further comprises the steps of:
and when the angle change value of the vehicle driving steering angle in the second preset time period is detected to be larger than the preset change value, updating the lane position information, repeating the process of generating a control instruction based on the target virtual traffic light signal information corresponding to the lane position information and sending the control instruction to the vehicle.
6. A virtual traffic light control reminding device for digital twin smart city traffic, the device comprising:
The construction module is used for constructing a digital twin traffic system based on actual data information of each road intersection, and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system so as to enable the virtual traffic lights to be matched with the actual data information;
the acquisition module is used for continuously acquiring real-time feedback data of the vehicle and determining the real-time position of the vehicle in the digital twin traffic system;
The control module is used for determining lane position information of the vehicle based on the real-time feedback data when the real-time position enters a judging range corresponding to any virtual road intersection, generating a control instruction based on target virtual traffic light signal information corresponding to the lane position information, and sending the control instruction to the vehicle;
wherein the actual data information further comprises video monitoring information;
the building block further comprises:
the mapping relation determining unit is used for obtaining all the video monitoring information in a preset monitoring period and determining the mapping relation between the traffic flow in the video monitoring information and weather and date;
and the second distribution unit is used for distributing corresponding quantity of virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
7. 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 implements the steps of the method according to any one of claims 1-5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210058268.5A CN114399916B (en) | 2022-01-19 | 2022-01-19 | Virtual traffic light control reminding method for digital twin smart city traffic |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210058268.5A CN114399916B (en) | 2022-01-19 | 2022-01-19 | Virtual traffic light control reminding method for digital twin smart city traffic |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114399916A CN114399916A (en) | 2022-04-26 |
| CN114399916B true CN114399916B (en) | 2024-05-28 |
Family
ID=81231960
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210058268.5A Active CN114399916B (en) | 2022-01-19 | 2022-01-19 | Virtual traffic light control reminding method for digital twin smart city traffic |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114399916B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114973687B (en) * | 2022-05-13 | 2024-03-05 | 北京百度网讯科技有限公司 | Traffic information processing method, device, equipment and medium |
| CN115098606B (en) * | 2022-05-30 | 2023-06-16 | 九识智行(北京)科技有限公司 | Traffic light query method and device for unmanned vehicle, storage medium and equipment |
| CN114943940A (en) * | 2022-07-26 | 2022-08-26 | 山东金宇信息科技集团有限公司 | Method, equipment and storage medium for visually monitoring vehicles in tunnel |
| CN115294766B (en) * | 2022-07-31 | 2023-06-23 | 东风汽车集团股份有限公司 | Virtual traffic light construction method, device, equipment and storage medium |
| CN115457791B (en) * | 2022-11-09 | 2023-03-24 | 北京数字众智科技有限公司 | Signal transmission method and system based on digital protocol |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102217870B1 (en) * | 2020-10-28 | 2021-02-19 | 주식회사 예향엔지니어링 | Traffic managing system using digital twin technology |
| CN112700636A (en) * | 2019-10-21 | 2021-04-23 | 百度在线网络技术（北京）有限公司 | Method and apparatus for updating information |
| CN112995309A (en) * | 2021-02-08 | 2021-06-18 | 南京航空航天大学 | Internet-connected cloud-control intelligent line-control chassis control system and control method thereof |
| CN113442929A (en) * | 2021-06-21 | 2021-09-28 | 国汽智控(北京)科技有限公司 | Vehicle control method, device, equipment and computer readable storage medium |
| WO2021222384A1 (en) * | 2020-04-28 | 2021-11-04 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| CN113645243A (en) * | 2021-08-12 | 2021-11-12 | 车百智能网联研究院(武汉)有限公司 | Operation module for traffic auxiliary basic service platform |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11284234B2 (en) * | 2019-11-14 | 2022-03-22 | Toyota Motor Engineering & Manufacturing North America, Inc. | Cloud-assisted virtual vehicular communication |
| US11234160B2 (en) * | 2019-11-21 | 2022-01-25 | Toyota Motor Engineering & Manufacturing North America, Inc. | Digital twin simulation-based vehicular communication planning |
| CN111611709B (en) * | 2020-05-20 | 2023-09-15 | 阿波罗智能技术(北京)有限公司 | Method, apparatus, electronic device, and storage medium for controlling a simulated vehicle |
-
2022
- 2022-01-19 CN CN202210058268.5A patent/CN114399916B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112700636A (en) * | 2019-10-21 | 2021-04-23 | 百度在线网络技术（北京）有限公司 | Method and apparatus for updating information |
| WO2021222384A1 (en) * | 2020-04-28 | 2021-11-04 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| KR102217870B1 (en) * | 2020-10-28 | 2021-02-19 | 주식회사 예향엔지니어링 | Traffic managing system using digital twin technology |
| CN112995309A (en) * | 2021-02-08 | 2021-06-18 | 南京航空航天大学 | Internet-connected cloud-control intelligent line-control chassis control system and control method thereof |
| CN113442929A (en) * | 2021-06-21 | 2021-09-28 | 国汽智控(北京)科技有限公司 | Vehicle control method, device, equipment and computer readable storage medium |
| CN113645243A (en) * | 2021-08-12 | 2021-11-12 | 车百智能网联研究院(武汉)有限公司 | Operation module for traffic auxiliary basic service platform |
Non-Patent Citations (1)
| Title |
|---|
| 基于STM32的智能交通灯系统;聂云浩;邱达;游超;王飞;李景花;;电子世界;20160623(第12期);第137-138页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114399916A (en) | 2022-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114399916B (en) | Virtual traffic light control reminding method for digital twin smart city traffic | |
| CN111123735B (en) | Automatic driving simulation operation method and device | |
| US11967230B2 (en) | System and method for using V2X and sensor data | |
| CN106715224B (en) | Functional licensing of highly automated driving functions | |
| CN113838284B (en) | Vehicle early warning method and device on accident-prone road section, storage medium and terminal | |
| US8160811B2 (en) | Method and system to estimate driving risk based on a hierarchical index of driving | |
| CN107389085B (en) | Method and device for determining road traffic attributes, computer and storage medium | |
| CN108248611B (en) | Automatic driving method, automobile control equipment, automobile and system | |
| CN113692373B (en) | Retention and range analysis for autonomous vehicle services | |
| CN113206874A (en) | Vehicle-road cooperative processing method and device, electronic equipment and storage medium | |
| JP2023024857A (en) | Road-to-vehicle cooperative information processing method, apparatus, system, electronic device, storage medium, and computer program | |
| CN113722342A (en) | High-precision map element change detection method, device and equipment and automatic driving vehicle | |
| JP6732053B2 (en) | Method, apparatus, and system for detecting reverse-drive drivers | |
| US20230126172A1 (en) | Method of outputting prompt information, device, medium, and vehicle | |
| US20230168368A1 (en) | Guardrail estimation method based on multi-sensor data fusion, and vehicle-mounted device | |
| CN112216137A (en) | System and method for identifying road indication sign for vehicle | |
| US20230256994A1 (en) | Assessing relative autonomous vehicle performance via evaluation of other road users | |
| WO2016206788A1 (en) | A system and a method for processing information of parking locations and a vehicle equipped with such system | |
| JP6971027B2 (en) | In-vehicle equipment, vehicle information provision system, server equipment | |
| CN116312045A (en) | Vehicle danger early warning method and device | |
| CN112685517B (en) | Method and apparatus for identifying diverging/converging regions | |
| CN114722931A (en) | Vehicle-mounted data processing method and device, data acquisition equipment and storage medium | |
| JP2021086169A (en) | Automatic driving control system, server device, and program | |
| CN116847401B (en) | Internet of vehicles testing method, device and readable storage medium | |
| JP7497781B2 (en) | Map update system and map update device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |