CN114399916A - 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
- CN114399916A CN114399916A CN202210058268.5A CN202210058268A CN114399916A CN 114399916 A CN114399916 A CN 114399916A CN 202210058268 A CN202210058268 A CN 202210058268A CN 114399916 A CN114399916 A CN 114399916A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- information
- virtual
- real
- traffic
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 230000008569 process Effects 0.000 claims abstract description 14
- 230000008859 change Effects 0.000 claims description 58
- 230000000737 periodic effect Effects 0.000 claims description 39
- 230000015654 memory Effects 0.000 claims description 25
- 238000012544 monitoring process Methods 0.000 claims description 20
- 238000013507 mapping Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 8
- 238000010276 construction Methods 0.000 claims description 7
- 239000000523 sample Substances 0.000 abstract description 2
- 230000000007 visual effect Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 10
- 238000012545 processing Methods 0.000 description 10
- 238000004891 communication Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 5
- 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
- 230000003993 interaction Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission 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
- 230000004927 fusion Effects 0.000 description 1
- 238000009434 installation Methods 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
Images
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 for digital twin smart city traffic, which comprises the 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; 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. The invention realizes that the vehicle can obtain the actual traffic light information of the road intersection in real time through the virtual traffic light even under the severe environment or the condition that the visual field of the vehicle camera probe is blocked in the driving process of the unmanned vehicle, thereby ensuring the safe driving of the unmanned vehicle.
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 a research field for a plurality of technology 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 automobile to reach a preset target. For unmanned vehicles and urban roads, the control of traffic lights is a difficult point for ensuring safe and efficient driving of automatic vehicles.
At present, most intersections still use traditional traffic light equipment, and due to certain differences of the traffic light equipment at different intersections in the aspects of installation positions, shapes and the like, most of the traffic light identification technologies based on the camera have high false detection rate and low robustness. In addition, the identification method based on the traffic light image is also easily affected by weather and surrounding environment, for example, in the case of heavy snow or the unmanned vehicle is shielded by a large vehicle, the image identification method is difficult to accurately identify the traffic light, and further causes an inestimable danger to the unmanned vehicle.
Disclosure of Invention
In order to solve the above problem, an embodiment of the present 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 virtual traffic light control reminding method for 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, 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.
Preferably, the constructing a digital twin traffic system based on actual data information of each road intersection, and allocating a virtual traffic light at each virtual road intersection in the digital twin traffic system to match the virtual traffic light 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;
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 periodic signal change information of the first traffic light;
acquiring second traffic light periodic signal change information of each road intersection every time 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 when the comparison results are characterized to be different, optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information.
Preferably, the actual data information further includes video monitoring information;
the distributing of virtual traffic lights at each virtual road intersection in the digital twin traffic system comprises:
acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow and the weather and date in the video monitoring information;
and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
Preferably, the continuously acquiring real-time feedback data of the vehicle and determining the real-time position of the vehicle in the digital twin traffic system comprises:
continuously acquiring real-time feedback data of a vehicle, wherein the real-time feedback data comprises GPS positioning information;
determining a real-time location of the vehicle in the digital twin traffic system from the GPS positioning information;
and acquiring vehicle azimuth information acquired by each roadside sensor within a 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 judgment range corresponding to any virtual road intersection, determining 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 following steps:
when the fact that the angle change value of the vehicle driving steering angle in a second preset time length is larger than a preset change value is detected, the lane position information is updated, the process that a control instruction is generated based on the target virtual traffic light signal information corresponding to the lane position information and sent to the vehicle is repeated.
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 a vehicle and determining the real-time position of the vehicle in the digital twin traffic system;
and 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 judgment 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.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method as provided in the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as provided in the first aspect or any one of the possible implementations of the first aspect.
The invention has the beneficial effects that: in the driving process of the unmanned vehicle, even under severe environment or under the condition that the visual field of the vehicle camera probe is blocked, the vehicle can still obtain the actual traffic light information of the road intersection in real time through the virtual traffic light, so that the safe driving of the unmanned vehicle is ensured.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of a virtual traffic light control reminding method for digital twin smart city traffic according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a virtual traffic light control reminding device for digital twin smart city traffic according to an embodiment of the present 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 drawings in the embodiments of the present application.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the present application, where different embodiments may be substituted or combined, and thus the present application is intended to include 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 this application should also be considered to include an embodiment that includes one or more of all other possible combinations of A, B, C, D, even though this embodiment may not be explicitly recited in text below.
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 disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different than the order 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 according to an embodiment of the present 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 to enable the virtual traffic lights to be matched with the actual data information.
The execution main body of the application can be a cloud server.
The digital twin can be understood in the embodiment of the application as fully utilizing data such as a physical model, sensor updating, operation history and the like, integrating simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and completing mapping in a virtual space so as to reflect the full life cycle process of corresponding entity equipment. Which can be viewed as a digital mapping system of one or more important, mutually dependent equipment systems. The digital twin traffic system utilizes the existing video monitoring resources at the current intersection and millimeter wave radar to collect data, and conducts full data fusion by holographic perception of traffic elements including motor vehicles, non-motor vehicles, pedestrians and the like in a traffic network, so as to lead real world information into the twin traffic simulation system.
In this embodiment of the application, the digital twin traffic system can be regarded as a same virtual traffic system that is simulated based on an actual traffic system, so in order to ensure the authenticity and reliability of the system, the cloud server needs to acquire actual data information acquired by devices and sensors at each road intersection in the actual traffic system, and thus the digital twin traffic system is constructed. 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 the same as the traffic lights of the actual road intersections. The construction process for the digital twin system, with the actual data information required to construct the system being determined, is well known to those skilled in the art, and the specific construction process for the digital twin system is not central to the present application and therefore will not be described in detail herein.
In one possible 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;
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 periodic signal change information of the first traffic light;
acquiring second traffic light periodic signal change information of each road intersection every time 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 when the comparison results are characterized to be different, optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information.
In the embodiment of the application, the most critical information in the actual data information is first traffic light periodic signal change information, the cloud server represents 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, that is, 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 ensure the real-time accuracy of the virtual traffic lights, the cloud server can obtain the second traffic light periodic signal change information in the actual situation of the road intersection once again every time, and compares the first traffic light periodic signal change information with the second traffic light periodic signal change information. If the signal change condition of the virtual traffic light is normal, the comparison result of the virtual traffic light and the comparison result should be the same, so when the representation of the comparison result is different, the current signal light change condition of the virtual traffic light is abnormal, and deviation possibly occurs with the actual condition, and the cloud server can optimize the periodic signal change information of the virtual traffic light according to the periodic signal change information of the second traffic light, so as to ensure the continuous accuracy of the periodic signal change information of the virtual traffic light.
In one embodiment, the actual data information further includes video monitoring information;
the distributing of virtual traffic lights at each virtual road intersection in the digital twin traffic system comprises:
acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow and the weather and date in the video monitoring information;
and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
In the embodiment of the application, the actual data information further includes video monitoring information shot by a monitoring camera at the road intersection, and the traffic flow of the road in a period of time can be calculated according to the video monitoring information. In practical situations, the number of people going out on roads is different according to different weather, festivals and holidays, and accordingly the traffic flow is different. Compared with the actual traffic lights, the virtual traffic lights are still data information in nature, and information interaction with matched vehicles is required to inform the actual traffic light conditions of the vehicles, so that in order to ensure the data processing efficiency of each virtual traffic light, the virtual traffic lights should not interact with too many vehicles at the same time. For the above reasons, during the peak time of a trip, in order to ensure the information interaction efficiency of the virtual traffic lights and also in order to ensure that the vehicles on the trip can receive the relevant control data in time, a plurality of virtual traffic lights need to be set to work simultaneously. The cloud server can determine traffic flow changes on different dates and different weathers according to all video monitoring information in a preset monitoring period, so that the mapping relation between the traffic flow and the weather and the date 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 vehicle can continuously send the real-time feedback data to the cloud server in the driving process, so that the cloud server can determine the actual position of the vehicle through continuously acquiring the real-time feedback data sent by the vehicle, and further determine the real-time position of the vehicle in the digital twin traffic system.
In one possible embodiment, step S102 includes:
continuously acquiring real-time feedback data of a vehicle, wherein the real-time feedback data comprises GPS positioning information;
determining a real-time location of the vehicle in the digital twin traffic system from the GPS positioning information;
and acquiring vehicle azimuth information acquired by each roadside sensor within a 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 a 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 the positioning information determined by the GPS may have errors, in order to accurately determine the position of the vehicle, roadside sensors are intermittently provided on the roadside of the road. The roadside sensor can acquire the vehicle position 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 position information, so that the accuracy of the optimized real-time position is guaranteed.
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 complying with 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 the vehicle is specifically on which lane of the current road, and further determines target virtual traffic light signal information of a target virtual traffic light corresponding to the lane position information, so that the traffic light condition of the actual road through which the vehicle needs to pass is determined, and finally a response control instruction is generated to control the driving process of the vehicle and assist the vehicle to safely pass through the traffic light.
In one embodiment, said determining lane position information of said vehicle based on said real-time feedback data when said real-time position reaches any of said virtual road intersections comprises:
and when the real-time position enters a judgment range corresponding to any virtual road intersection, determining 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 real-time position corresponding to 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 driving steering angle;
the method further comprises the following steps:
when the fact that the angle change value of the vehicle driving steering angle in a second preset time length is larger than a preset change value is detected, the lane position information is updated, the process that a control instruction is generated based on the target virtual traffic light signal information corresponding to the lane position information and sent to the vehicle is repeated.
In the embodiment of the application, the real-time feedback data sent by the vehicle further includes a vehicle driving steering angle, that is, a steering angle of a front wheel of the vehicle during driving. And when the driving steering angle of the vehicle continuously changes within the second preset duration and the angle change value is greater than the preset change value, determining that the lane change of the vehicle occurs. For different lanes, the corresponding virtual traffic lights are different, and the actual traffic light change conditions are also different. Therefore, after the lane change of the vehicle is determined, the cloud server updates the lane position information, regenerates the control instruction and controls the vehicle newly, so that the latest control instruction of the vehicle is ensured to be in accordance with the driving condition of the vehicle, and the driving safety of the vehicle is ensured.
The digital twin intelligent city traffic virtual traffic light control reminding device provided by the embodiment of the application will be described in detail below with reference to fig. 2. It should be noted that, the digital twin intelligent city traffic virtual traffic light control reminding device shown in fig. 2 is used for executing the method of the embodiment shown in fig. 1 of the present application, and for convenience of description, only the relevant portions of the embodiment of the present application are shown, and details of the specific technology 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 according to an embodiment of the present 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 a virtual traffic light at each virtual road intersection in the digital twin traffic system, so that the virtual traffic light is matched with the actual data information;
the acquisition module 202 is used for continuously acquiring real-time feedback data of a vehicle and determining the 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 possible implementation, the building module 201 includes:
the system comprises a construction unit, a data acquisition unit and a data transmission unit, wherein the construction unit is used for acquiring actual data information of each road intersection and constructing a digital twin traffic system based on the actual data information, and 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 periodic signal change information of the first traffic lights;
the comparison unit is used for acquiring second traffic light periodic signal change information of each road intersection every time 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 the first optimization 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 to be different.
In one possible implementation, the building module 201 further includes:
the mapping relation determining unit is used for acquiring all the video monitoring information in a preset monitoring period and determining the mapping relation between the traffic flow and the weather and date in the video monitoring information;
and the second distribution unit is used for distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
In one possible implementation, the obtaining module 202 includes:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for continuously acquiring real-time feedback data of a vehicle, and 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;
and the second optimization unit is used for acquiring the vehicle azimuth information acquired by each road side sensor in a first preset range of the real-time position and optimizing the real-time position based on the vehicle azimuth information.
In one possible 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 a second preset time length is larger than a 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 is clear to a person skilled in the art that the solution according to the embodiments of the present application can be implemented by means of software and/or hardware. The "unit" and "module" in this specification refer to software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), or the like.
Each processing unit and/or module in 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 a communication bus 302 is used to enable the connection communication between these components.
The user interface 303 may include a Display screen (Display) and 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.
The central processor 301 may include one or more processing cores. The central processor 301 connects various parts within the entire electronic device 300 using various interfaces and lines, and 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 calling data stored in the memory 305. Alternatively, the central Processing unit 301 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The CPU 301 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, 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 is understood that the modem may not be integrated into the cpu 301, but may be implemented by a single chip.
The Memory 305 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 may be used to store instructions, programs, code sets, or instruction sets. 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 various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 305 may alternatively be at least one storage device located remotely from the central processor 301. As shown in fig. 3, memory 305, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user to obtain data input by the user; the cpu 301 may be configured to call the virtual traffic light control reminding 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, 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.
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-described method. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, 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 above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some service interfaces, devices or units, and may be an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure are intended to be included 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 true scope and spirit of the disclosure being indicated by the following claims.
Claims (9)
1. A virtual traffic light control reminding method for digital twin smart city traffic is characterized by comprising the following steps:
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, 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.
2. The method of claim 1, wherein constructing a digital twin traffic system based on actual data information at each road intersection and assigning a virtual traffic light at each virtual road intersection in the digital twin traffic system to match the virtual traffic light to 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;
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 periodic signal change information of the first traffic light;
acquiring second traffic light periodic signal change information of each road intersection every time 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 when the comparison results are characterized to be different, optimizing the virtual traffic light periodic signal change information based on the second traffic light periodic signal change information.
3. The method of claim 1, wherein the actual data information further comprises video surveillance information;
the distributing of virtual traffic lights at each virtual road intersection in the digital twin traffic system comprises:
acquiring all the video monitoring information in a preset monitoring period, and determining the mapping relation between the traffic flow and the weather and date in the video monitoring information;
and distributing virtual traffic lights at each virtual road intersection in the digital twin traffic system based on the mapping relation.
4. The method of claim 1, wherein the continuously obtaining real-time feedback data of the vehicle, determining a real-time location of the vehicle in the digital twin traffic system, comprises:
continuously acquiring real-time feedback data of a vehicle, wherein the real-time feedback data comprises GPS positioning information;
determining a real-time location of the vehicle in the digital twin traffic system from the GPS positioning information;
and acquiring vehicle azimuth information acquired by each roadside sensor within a first preset range of the real-time position, and optimizing the real-time position based on the vehicle azimuth information.
5. The method of claim 1, wherein determining lane position information for the vehicle based on the real-time feedback data when the real-time position reaches any of the virtual road intersections comprises:
and when the real-time position enters a judgment range corresponding to any virtual road intersection, determining lane position information of the vehicle based on the real-time feedback data.
6. The method of claim 1, wherein the real-time feedback data further comprises a vehicle travel steering angle;
the method further comprises the following steps:
when the fact that the angle change value of the vehicle driving steering angle in a second preset time length is larger than a preset change value is detected, the lane position information is updated, the process that a control instruction is generated based on the target virtual traffic light signal information corresponding to the lane position information and sent to the vehicle is repeated.
7. A virtual traffic light control reminding device of digital twin wisdom urban traffic, its characterized in that, 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 a vehicle and determining the real-time position of the vehicle in the digital twin traffic system;
and 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 judgment 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.
8. 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 steps of the method according to any of claims 1-6 are implemented when the computer program is executed by the processor.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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 true CN114399916A (en) | 2022-04-26 |
| CN114399916B 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) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN114973687A (en) * | 2022-05-13 | 2022-08-30 | 北京百度网讯科技有限公司 | Traffic information processing method, device, equipment and medium |
| CN115098606A (en) * | 2022-05-30 | 2022-09-23 | 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 |
| CN115294766A (en) * | 2022-07-31 | 2022-11-04 | 东风汽车集团股份有限公司 | Virtual traffic light construction method, device, equipment and storage medium |
| CN115457791A (en) * | 2022-11-09 | 2022-12-09 | 北京数字众智科技有限公司 | Signal transmission method and system based on digital protocol |
Citations (9)
| 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 |
| US20210152995A1 (en) * | 2019-11-14 | 2021-05-20 | Toyota Motor Engineering & Manufacturing North America, Inc. | Cloud-assisted virtual vehicular communication |
| US20210160731A1 (en) * | 2019-11-21 | 2021-05-27 | Toyota Motor Engineering & Manufacturing North America, Inc. | Digital twin simulation-based vehicular communication planning |
| 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 |
| US20210365698A1 (en) * | 2020-05-20 | 2021-11-25 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method for controlling simulation vehicle, electronic device, and storage medium |
-
2022
- 2022-01-19 CN CN202210058268.5A patent/CN114399916B/en active Active
Patent Citations (9)
| 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 |
| US20210152995A1 (en) * | 2019-11-14 | 2021-05-20 | Toyota Motor Engineering & Manufacturing North America, Inc. | Cloud-assisted virtual vehicular communication |
| US20210160731A1 (en) * | 2019-11-21 | 2021-05-27 | Toyota Motor Engineering & Manufacturing North America, Inc. | Digital twin simulation-based vehicular communication planning |
| WO2021222384A1 (en) * | 2020-04-28 | 2021-11-04 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| US20210365698A1 (en) * | 2020-05-20 | 2021-11-25 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method for controlling simulation vehicle, electronic device, and storage medium |
| 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 |
|---|
| 聂云浩;邱达;游超;王飞;李景花;: "基于STM32的智能交通灯系统", 电子世界, no. 12, 23 June 2016 (2016-06-23), pages 137 - 138 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114973687A (en) * | 2022-05-13 | 2022-08-30 | 北京百度网讯科技有限公司 | Traffic information processing method, device, equipment and medium |
| 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 |
| CN115098606A (en) * | 2022-05-30 | 2022-09-23 | 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 |
| 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 |
| CN115294766A (en) * | 2022-07-31 | 2022-11-04 | 东风汽车集团股份有限公司 | Virtual traffic light construction method, device, equipment and storage medium |
| CN115457791A (en) * | 2022-11-09 | 2022-12-09 | 北京数字众智科技有限公司 | Signal transmission method and system based on digital protocol |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114399916B (en) | 2024-05-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114399916B (en) | Virtual traffic light control reminding method for digital twin smart city traffic | |
| JP7292338B2 (en) | Automatic driving function control method, device, electronic device and storage medium | |
| CN113838284B (en) | Vehicle early warning method and device on accident-prone road section, storage medium and terminal | |
| CN109389824B (en) | Driving risk assessment method and device | |
| CN111680362B (en) | Automatic driving simulation scene acquisition method, device, equipment and storage medium | |
| CN107389085B (en) | Method and device for determining road traffic attributes, computer and storage medium | |
| CN112106124A (en) | System and method for using V2X and sensor data | |
| CN106662454B (en) | Warning notice system and warning notice method | |
| US20140063196A1 (en) | Comprehensive and intelligent system for managing traffic and emergency services | |
| CN108248611B (en) | Automatic driving method, automobile control equipment, automobile and system | |
| CN113206874A (en) | Vehicle-road cooperative processing method and device, electronic equipment and storage medium | |
| CN114301938B (en) | Vehicle-road cooperative vehicle event determining method, related device and computer program product | |
| CN112580571A (en) | Vehicle running control method and device and electronic equipment | |
| CN112687125A (en) | Early warning method and device after illegal parking on road, storage medium and terminal | |
| CN114548512A (en) | Road operation data estimation method and device for digital twins | |
| CN112734242A (en) | Method and device for analyzing availability of vehicle running track data, storage medium and terminal | |
| JP2023024857A (en) | Road-to-vehicle cooperative information processing method, apparatus, system, electronic device, storage medium, and computer program | |
| CN115292435A (en) | High-precision map updating method and device, electronic equipment and storage medium | |
| CN114596704A (en) | Traffic event processing method, device, equipment and storage medium | |
| CN118262508A (en) | Unmanned aerial vehicle-based road real-time monitoring method, system, equipment and medium | |
| CN113722342A (en) | High-precision map element change detection method, device and equipment and automatic driving vehicle | |
| CN113160589A (en) | Vehicle early warning method and device, electronic equipment and computer readable storage medium | |
| CN110599792A (en) | Intelligent parking method, parking system and parking terminal | |
| US20230256994A1 (en) | Assessing relative autonomous vehicle performance via evaluation of other road users | |
| CN115973190A (en) | Decision-making method and device for automatically driving vehicle and electronic equipment |
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 |