CN110632626A - Positioning method and system based on Internet of vehicles - Google Patents
Positioning method and system based on Internet of vehicles Download PDFInfo
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- CN110632626A CN110632626A CN201911029091.0A CN201911029091A CN110632626A CN 110632626 A CN110632626 A CN 110632626A CN 201911029091 A CN201911029091 A CN 201911029091A CN 110632626 A CN110632626 A CN 110632626A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
- G01S19/41—Differential correction, e.g. DGPS [differential GPS]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
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Abstract
The invention discloses a positioning method and system based on a vehicle networking, and belongs to the field of vehicle networking. The method comprises the following steps: the road side unit acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication; carrying out differential calculation by utilizing a preset virtual reference station based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area; based on the enhanced position information, obtaining accurate position information of the target vehicle. The positioning method and system based on the internet of vehicles provided by the embodiment of the specification can realize high-precision positioning of vehicles and/or can identify information attacks such as signal camouflage and signal induction.
Description
Technical Field
The application relates to the field of Internet of vehicles, in particular to a positioning method and system based on the Internet of vehicles.
Background
An Intelligent networked automobile, namely an ICV (integrated circuit Vehicle), refers to the organic combination of an internet of vehicles and an Intelligent automobile, is a new-generation automobile which is provided with advanced Vehicle-mounted sensors, controllers, actuators and other devices, integrates modern communication and network technologies, realizes the exchange and sharing of Intelligent information such as automobile, people, automobile, road, background and the like, realizes safe, comfortable, energy-saving and efficient driving, and can finally replace people to operate. With the development of the intelligent networking automobile, accurate and reliable positioning of the automobile is a necessary condition for realizing automatic driving or unmanned driving and intelligent networking.
In the prior art, a carrier-time kinematic (RTK) and an Inertial Measurement Unit (IMU) are often used for high-precision positioning of a vehicle to obtain high-precision and high-frequency position information. According to the method for positioning the vehicle by adopting the RTK and the IMU, due to the fact that calculation input is single, information attacks such as signal camouflage and signal induction are difficult to resist, and the equivalent cost of an antenna of the vehicle is difficult to effectively control.
Therefore, a new vehicle positioning method is needed, which can realize high-precision vehicle positioning and/or can identify information attacks such as signal camouflage and signal induction.
Disclosure of Invention
In view of the foregoing disadvantages in the prior art, embodiments of the present specification provide a positioning method and system based on an internet of vehicles, which are used to solve the following technical problems: the method can realize high-precision positioning of the vehicle and/or can identify information attacks such as signal camouflage, signal induction and the like.
In order to solve the above technical problem, the embodiments of the present specification are implemented as follows:
the embodiment of the specification provides a positioning method based on internet of vehicles, which comprises the following steps:
the road side unit acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication;
carrying out differential calculation by utilizing a preset virtual reference station based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area;
based on the enhanced position information, obtaining accurate position information of the target vehicle.
Further, the method further comprises:
and judging whether the accurate position information is abnormal or not based on the accurate position information of the target vehicle.
Further, the road side unit acquiring the observed quantity information of the target vehicle specifically includes:
the roadside unit acquires observation information of the target vehicle through a cellular and/or V2V network, wherein the observation information comprises position information of the target vehicle and satellite information observed by a GNSS observation point, and the GNSS observation point is the roadside unit.
Further, the preset virtual reference station is obtained based on a road side unit, and specifically includes:
and taking the road side units in the target area as GNSS observation points, and enhancing the satellite information of one or more road side units preset as the virtual reference station through cloud joint calculation to obtain the virtual reference station.
Further, the roadside unit acquires observation amount information of a target vehicle, and further includes:
judging whether the observed quantity information of the target vehicle is abnormal or not based on the observed quantity information of the target vehicle;
and if the observed quantity information of the target vehicle is abnormal, rejecting the abnormal observed quantity information, and taking the observed quantity information obtained after rejecting the abnormal observed quantity information as the observed quantity information of the target vehicle.
Further, the determining whether the observation amount information of the target vehicle is abnormal based on the observation amount information of the target vehicle specifically includes:
the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to a cloud end, and the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
Further, the performing differential calculation based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle specifically includes:
and carrying out differential calculation on the observed quantity information according to differential correction information to obtain enhanced position information of the target vehicle, wherein the differential correction information is issued to the road side unit by the cloud.
Further, the obtaining of the accurate location information of the target vehicle based on the enhanced location information specifically includes:
the road side unit or the cloud sends the enhanced position information to the target vehicle, and the target vehicle fuses the enhanced position information and track information of the target vehicle to obtain accurate position information of the target vehicle, wherein the track information of the target vehicle is obtained based on an IMU (inertial measurement unit) system of the target vehicle.
The embodiment of this specification provides a positioning system based on car networking, includes:
an acquisition unit that acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication;
the calculation unit is used for carrying out differential calculation based on the observed quantity information of the target vehicle by utilizing a preset virtual reference station to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area;
and the accurate positioning unit is used for obtaining accurate position information of the target vehicle based on the enhanced position information.
Further, the system further comprises:
and judging whether the accurate position information is abnormal or not based on the accurate position information of the target vehicle.
Further, the road side unit acquiring the observed quantity information of the target vehicle specifically includes:
the roadside unit acquires observation information of the target vehicle through a cellular and/or V2V network, wherein the observation information comprises position information of the target vehicle and satellite information observed by a GNSS observation point, and the GNSS observation point is the roadside unit.
Further, the preset virtual reference station is obtained based on a road side unit, and specifically includes:
and taking the road side units in the target area as GNSS observation points, and enhancing the satellite information of one or more road side units preset as the virtual reference station through cloud joint calculation to obtain the virtual reference station.
Further, the roadside unit acquires observation amount information of a target vehicle, and further includes:
judging whether the observed quantity information of the target vehicle is abnormal or not based on the observed quantity information of the target vehicle;
and if the observed quantity information of the target vehicle is abnormal, rejecting the abnormal observed quantity information, and taking the observed quantity information obtained after rejecting the abnormal observed quantity information as the observed quantity information of the target vehicle.
Further, the determining whether the observation amount information of the target vehicle is abnormal based on the observation amount information of the target vehicle specifically includes:
the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to a cloud end, and the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
Further, the performing differential calculation based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle specifically includes:
and carrying out differential calculation on the observed quantity information according to differential correction information to obtain enhanced position information of the target vehicle, wherein the differential correction information is issued to the road side unit by the cloud.
Further, the obtaining of the accurate location information of the target vehicle based on the enhanced location information specifically includes:
the road side unit or the cloud sends the enhanced position information to the target vehicle, and the target vehicle fuses the enhanced position information and track information of the target vehicle to obtain accurate position information of the target vehicle, wherein the track information of the target vehicle is obtained based on an IMU (inertial measurement unit) system of the target vehicle.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
the method comprises the steps of obtaining observation quantity information of a target vehicle through a road side unit, wherein the target vehicle is a vehicle subjected to information authentication; carrying out differential calculation by utilizing a preset virtual reference station based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area; and obtaining the accurate position information of the target vehicle based on the enhanced position information, thereby realizing the high-precision positioning of the vehicle and/or identifying information attacks such as signal camouflage, signal induction and the like.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is a schematic flowchart of a positioning method based on internet of vehicles according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a security awareness provided by an embodiment of the present disclosure;
fig. 3 is a frame diagram of a positioning method based on internet of vehicles according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of another positioning method based on internet of vehicles according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of a positioning system based on a car networking according to an embodiment of the present disclosure.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any inventive step based on the embodiments of the present disclosure, shall fall within the scope of protection of the present application.
Fig. 1 is a schematic flowchart of a positioning method based on internet of vehicles according to an embodiment of the present disclosure, where the method includes:
step S101: a roadside unit acquires target vehicle observation amount information, wherein the target vehicle is an information-authenticated vehicle.
In the present application, the vehicle used for positioning is the target vehicle. After a target vehicle enters a target area, information authentication of the vehicle is firstly carried out, wherein the target area is an area with road side units. In the present application, the information authentication of the vehicle includes: the id of the target vehicle and/or whether the target vehicle is suitable for the GNSS system.
GNSS (Global navigation satellite system) generally refers to all satellite navigation systems, including Global, regional, and enhanced satellite navigation systems.
In the application, after the target vehicle enters the target area and is authenticated by the information, the GNSS module of the target vehicle receives the ephemeris information and initially positions the target vehicle. Ephemeris information includes, but is not limited to: information of satellite information, position, elevation angle, etc.
And obtaining the observation quantity information of the target vehicle based on the road side unit in the target area after the target vehicle is initially positioned. In the specific implementation process, the following method can be adopted for implementation:
and the road side unit is used for acquiring the observed quantity information of the target vehicle through a cellular and/or V2V network, wherein the observed quantity information comprises the position information of the target vehicle and the satellite information observed by a GNSS observation point, and the GNSS observation point is the road side unit.
In the present application, the cellular network may use CV2X or other cellular networks for joint positioning solution.
In this application, a GNSS observation point refers to a device that can be used to observe GNSS.
CV2X (full cellular vehicle-to-evolution), which utilizes LTE to implement communication between road users, CV2X mainly includes V2V, V2I, and V2N and V2P. Among them, V2V (vehicle-vehicle) can be used as information interaction and reminding between vehicles; V2I (vehicle-infrastructure), where a vehicle can communicate with a road and even other infrastructure, such as traffic lights, roadblocks, etc., and acquire road management information such as traffic light signals; V2N (car-internet) is the most widely used form of car networking at present, and its main function is to make the car connect to the cloud server through the mobile network, and use the navigation, entertainment, anti-theft application function provided by the cloud server; V2P (car-pedestrian) is used as a safety warning for pedestrians or non-motor vehicles on the road.
In a specific implementation process, the cloud calculates ephemeris information of a point where a road side unit is located according to the satellite observation station information and/or the road side unit observation station information, matches the ephemeris information with observation quantity information of the road side unit, and selects an optimal reference observation satellite so as to record initial observation quantity information.
In the application, after acquiring the observed quantity information of the target vehicle, the road side unit performs differential calculation on the observed quantity information of the target vehicle.
Step S103: and carrying out differential calculation by utilizing a preset virtual reference station based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area.
In order to obtain enhanced position information of the target vehicle, it is necessary to perform differential calculation based on the observed quantity information of the target vehicle to achieve correction of the observed quantity information.
The virtual reference station can help achieve high-precision positioning. The virtual reference station is formed by a plurality of reference stations distributed on the ground to form a GPS differential network, the measurement information of each station is comprehensively utilized, and the virtual reference station is generated through inverse solution, data packaging and sending and the like so as to realize the accurate determination of the position and the speed of a target. The virtual reference station is virtual and does not physically exist. Because the traditional virtual reference station needs to be realized through operations such as inverse resolving, data packaging and sending, and the like, the calculation process is complicated.
In the application, the road side unit in the target area is used as the virtual reference station. The observation values of the road side units are small in change, the road side units are used as GNSS observation points, the observation values of the GNSS observation points are transmitted to the cloud end through a network, and further the cloud end generates a virtual reference station for the road side units which are preset as the virtual reference station through joint calculation so as to realize accurate positioning of target vehicles in a target area. In this application, the consideration for performing joint calculation includes but is not limited to: GNSS position, phase difference, atmosphere, tide, pitch angle, etc.
In the present application, the target area is an area covered by the road side unit and/or an area containing the road side unit where the target vehicle travels.
In the embodiment of the present application, there may be one or more virtual reference stations, and the number of the virtual reference stations is determined according to the range of the target area.
In the embodiment of the present application, a roadside unit or multiple roadside units serving as a virtual reference station is preset, and due to the influence of GNSS signal intensity, position, and the like, the roadside unit serving as a GNSS observation point cannot observe GNSS located in an area above the roadside unit, and therefore, in order to ensure accurate positioning, joint solution needs to be performed on GNSS that cannot be observed by the roadside unit, so as to obtain GNSS observation amount information. In the method, the road side unit in the target area is used as the GNSS observation point, the observation value of the GNSS observation point is transmitted to the cloud end through the network, and further, the cloud end obtains the observation amount information of the GNSS which cannot be observed by the road side unit used as the virtual reference station through joint calculation. In an embodiment of the present application, the roadside unit at position a is used as a virtual reference station, and the roadside unit at position a can observe 22 GNSS satellites, where 12 satellite signals are strong, the roadside unit can directly obtain GNSS observation amount information, and the other 10 satellite signals are weak, and GNSS observation amount information cannot be obtained. For such a satellite in which the road side unit located at the position a cannot obtain GNSS observation information, the GNSS observation information can be obtained through cloud joint calculation based on the GNSS observation information of other road side units in the target area, so that the road side unit located at the position a can be used as a virtual reference station.
In particular implementations, the PRN code information of different satellites is spoofed to attack the GPS receiver on the vehicle due to the presence of a GPS spoofing attack. PRN (pseudo random noise code), C/A and P codes are pseudo noise codes. A pseudo-noise code is a discrete string of symbols with a period of values 0 and 1, which has an autocorrelation function similar to white noise. In order to ensure that the vehicle is not attacked by GPS spoofing, in the specific implementation process, after the roadside unit obtains the observed quantity information of the target vehicle, it needs to further determine whether the observed quantity information of the target vehicle is abnormal. And if the observed quantity information of the target vehicle is normal, correcting the observed quantity information, and taking the corrected observed quantity information as the observed quantity information of the target vehicle. And if the observed quantity information of the target vehicle is abnormal, correcting the observed quantity information after performing abnormal processing on the observed quantity information, and taking the corrected observed quantity information as the observed quantity information of the target vehicle.
In a specific implementation process, the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to the cloud, and the cloud judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
In one embodiment of the application, the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not according to ephemeris information, historical information data of other GNSS observation points, vehicles and the like and a digital model;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the historical information.
To facilitate understanding of the judgment of the observation quantity information abnormality, fig. 2 is a schematic view of security perception provided in the embodiment of the present specification. As shown in fig. 2, in the target area, the roadside unit uploads the observed quantity information of the target vehicle to the cloud, and the cloud determines whether the observed quantity information of the target vehicle is abnormal, or the roadside unit analyzes, determines camouflage and/or attack according to the observed quantity information of the target vehicle, and determines that the observed quantity is abnormal. And uploading the observed quantity information to a cloud end by the target vehicle outside the target area, and judging whether the observed quantity information of the target vehicle is abnormal or not by the cloud end. In a specific implementation process, the cloud can also realize data exchange of observation quantity information in a CORS center (a reference station network).
In one embodiment of the application, the road side unit judges that the observed quantity information of the target vehicle is abnormal, uploads the abnormal observed quantity information to the cloud, and the cloud processes the GPS spoofing attack in the abnormal area. In one embodiment of the present application, since the false signal power must be gradually increased during the GPS spoofing attack, if the signal frequency is increased too fast, it may be a false signal, and the observation information of the target vehicle obtained based on such a signal needs to be discarded to obtain the observation information of the target vehicle again.
And if the observed quantity information of the target vehicle is normal, the cloud end sends the difference correction information to the road side unit so that the road side unit can correct the observed quantity information of the target vehicle. In an embodiment of the application, the cloud sends the differential correction information to the road side unit, and the Ntrip protocol can be adopted for transmission. The Ntrip Protocol (network Transport of RTCM via Internet Protocol) enables RTK data transmission.
And after receiving the differential correction information, the road side unit serving as the virtual workstation performs differential calculation based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle. It should be noted that the enhanced position information of the target vehicle is obtained by differential solution at the road side unit.
Step S105: based on the enhanced position information, obtaining accurate position information of the target vehicle.
In the specific implementation process, the road side unit sends the enhanced position information of the target vehicle to the cloud end, and the cloud end or the road side unit sends the enhanced information of the target vehicle to the target vehicle.
And after the target vehicle acquires the enhanced information, fusing the enhanced position information of the target vehicle with the track information of the target vehicle to acquire the accurate positioning information of the target vehicle. In one embodiment of the present application, the target vehicle's own trajectory information is obtained based on the target vehicle's IMU system.
In the implementation, the accurate position information of the target vehicle obtained in step S105 needs to be further determined to determine whether the accurate position information of the target vehicle is abnormal. And if the accurate position of the target vehicle is abnormal, performing abnormal processing and reporting to the cloud and/or the road side unit. And if the accurate position information of the target vehicle is normal, outputting the accurate position information of the target vehicle. In one embodiment of the present application, the precise location information of the target vehicle is output in a broadcast manner.
The accuracy of vehicle positioning is closely related to the integrity of ephemeris information, the coverage strength of communication information, vision enhancement, radar enhancement and fusion information, and in the specific implementation process, in order to realize the accuracy of positioning, the integrity of ephemeris information and the full coverage of communication information are ensured as much as possible, and the accuracy of vision enhancement, radar enhancement and fusion information is realized.
To facilitate understanding of the positioning method based on the internet of vehicles provided by the present application, fig. 3 is a frame diagram of a positioning method based on the internet of vehicles provided by an embodiment of the present specification.
To further understand the positioning method based on the internet of vehicles provided by the present application, fig. 4 is a flowchart of another positioning method based on the internet of vehicles provided by the embodiment of the present specification.
According to the positioning method based on the internet of vehicles, the enhanced position information of the target vehicle is obtained through the cooperative differential solution of the vehicle road cloud, so that the target vehicle is accurately positioned; the GPS signal attack is realized through the cooperation of the vehicle cloud and the road cloud, so that the high-precision positioning of the vehicle can be realized and/or the information attacks such as signal camouflage, signal induction and the like can be identified.
The foregoing details a positioning method based on the internet of vehicles, and accordingly, the present application also provides a positioning system based on the internet of vehicles, as shown in fig. 5. Fig. 5 is a schematic view of a positioning system based on a car networking, provided in an embodiment of this specification, specifically including:
an acquisition unit 501 that acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication;
a calculating unit 503, configured to perform differential calculation based on observed quantity information of the target vehicle by using a preset virtual reference station, to obtain enhanced position information of the target vehicle, where the preset virtual reference station is one or more road side units in a target area;
and a precise positioning unit 505 for obtaining precise position information of the target vehicle based on the enhanced position information.
Further, the system further comprises:
a determination unit 507 that determines whether the precise position information is abnormal based on the precise position information of the target vehicle.
Further, the road side unit acquiring the observed quantity information of the target vehicle specifically includes:
the roadside unit acquires observation information of the target vehicle through a cellular and/or V2V network, wherein the observation information comprises position information of the target vehicle and satellite information observed by a GNSS observation point, and the GNSS observation point is the roadside unit.
Further, the preset virtual reference station is obtained based on a road side unit, and specifically includes:
and taking the road side units in the target area as GNSS observation points, and enhancing the satellite information of one or more road side units preset as the virtual reference station through cloud joint calculation to obtain the virtual reference station.
Further, the roadside unit acquires observation amount information of a target vehicle, and further includes:
judging whether the observed quantity information of the target vehicle is abnormal or not based on the observed quantity information of the target vehicle;
and if the observed quantity information of the target vehicle is abnormal, rejecting the abnormal observed quantity information, and taking the observed quantity information obtained after rejecting the abnormal observed quantity information as the observed quantity information of the target vehicle.
Further, the determining whether the observation amount information of the target vehicle is abnormal based on the observation amount information of the target vehicle specifically includes:
the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to a cloud end, and the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
Further, the performing differential calculation based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle specifically includes:
and carrying out differential calculation on the observed quantity information according to differential correction information to obtain enhanced position information of the target vehicle, wherein the differential correction information is issued to the road side unit by the cloud.
Further, the obtaining of the accurate location information of the target vehicle based on the enhanced location information specifically includes:
the road side unit or the cloud sends the enhanced position information to the target vehicle, and the target vehicle fuses the enhanced position information and track information of the target vehicle to obtain accurate position information of the target vehicle, wherein the track information of the target vehicle is obtained based on an IMU (inertial measurement unit) system of the target vehicle.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the embodiments of the apparatus, the electronic device, and the nonvolatile computer storage medium, since they are substantially similar to the embodiments of the method, the description is simple, and the relevant points can be referred to the partial description of the embodiments of the method.
The apparatus, the electronic device, the nonvolatile computer storage medium and the method provided in the embodiments of the present description correspond to each other, and therefore, the apparatus, the electronic device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (16)
1. A positioning method based on Internet of vehicles is characterized by comprising the following steps:
the road side unit acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication;
carrying out differential calculation by utilizing a preset virtual reference station based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area;
based on the enhanced position information, obtaining accurate position information of the target vehicle.
2. The method of claim 1, wherein the method further comprises:
and judging whether the accurate position information is abnormal or not based on the accurate position information of the target vehicle.
3. The method of claim 1, wherein the roadside unit obtaining target vehicle observation information specifically comprises:
the roadside unit acquires observation information of the target vehicle through a cellular and/or V2V network, wherein the observation information comprises position information of the target vehicle and satellite information observed by a GNSS observation point, and the GNSS observation point is the roadside unit.
4. The method of claim 1, wherein the predetermined virtual reference station is obtained based on a road side unit, and specifically comprises:
and taking the road side units in the target area as GNSS observation points, and enhancing the satellite information of one or more road side units preset as the virtual reference station through cloud joint calculation to obtain the virtual reference station.
5. The method of claim 1, wherein the roadside unit obtains observation information of a target vehicle, further comprising:
judging whether the observed quantity information of the target vehicle is abnormal or not based on the observed quantity information of the target vehicle;
and if the observed quantity information of the target vehicle is abnormal, rejecting the abnormal observed quantity information, and taking the observed quantity information obtained after rejecting the abnormal observed quantity information as the observed quantity information of the target vehicle.
6. The method according to claim 5, wherein the determining whether the observation information of the target vehicle is abnormal based on the observation information of the target vehicle includes:
the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to a cloud end, and the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
7. The method according to claim 1, wherein performing differential solution based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle specifically comprises:
and carrying out differential calculation on the observed quantity information according to differential correction information to obtain enhanced position information of the target vehicle, wherein the differential correction information is issued to the road side unit by the cloud.
8. The method according to any one of claims 1 to 7, wherein the obtaining of the precise location information of the target vehicle based on the enhanced location information specifically comprises:
the road side unit or the cloud sends the enhanced position information to the target vehicle, and the target vehicle fuses the enhanced position information and track information of the target vehicle to obtain accurate position information of the target vehicle, wherein the track information of the target vehicle is obtained based on an IMU (inertial measurement unit) system of the target vehicle.
9. A vehicle web-based positioning system, the system comprising:
an acquisition unit that acquires target vehicle observation amount information, wherein the target vehicle is a vehicle subjected to information authentication;
the calculation unit is used for carrying out differential calculation based on the observed quantity information of the target vehicle by utilizing a preset virtual reference station to obtain the enhanced position information of the target vehicle, wherein the preset virtual reference station is one or more road side units in a target area;
and the accurate positioning unit is used for obtaining accurate position information of the target vehicle based on the enhanced position information.
10. The system of claim 9, wherein the system further comprises:
and judging whether the accurate position information is abnormal or not based on the accurate position information of the target vehicle.
11. The system of claim 9, wherein the roadside unit obtaining target vehicle observation information specifically comprises:
the roadside unit acquires observation information of the target vehicle through a cellular and/or V2V network, wherein the observation information comprises position information of the target vehicle and satellite information observed by a GNSS observation point, and the GNSS observation point is the roadside unit.
12. The system of claim 9, wherein the predetermined virtual reference station is obtained based on a road side unit, and specifically comprises:
and taking the road side units in the target area as GNSS observation points, and enhancing the satellite information of one or more road side units preset as the virtual reference station through cloud joint calculation to obtain the virtual reference station.
13. The system of claim 9, wherein the roadside unit obtains observation information of a target vehicle, further comprising:
judging whether the observed quantity information of the target vehicle is abnormal or not based on the observed quantity information of the target vehicle;
and if the observed quantity information of the target vehicle is abnormal, rejecting the abnormal observed quantity information, and taking the observed quantity information obtained after rejecting the abnormal observed quantity information as the observed quantity information of the target vehicle.
14. The system according to claim 13, wherein the determining whether the observation information of the target vehicle is abnormal based on the observation information of the target vehicle includes:
the target vehicle or the road side unit uploads the observed quantity information of the target vehicle to a cloud end, and the cloud end judges whether the observed quantity information of the target vehicle is abnormal or not;
and/or
And the road side unit judges whether the observed quantity information of the target vehicle is abnormal or not according to the observed quantity information of the target vehicle.
15. The system according to claim 9, wherein the performing a differential solution based on the observed quantity information of the target vehicle to obtain the enhanced position information of the target vehicle specifically includes:
and carrying out differential calculation on the observed quantity information according to differential correction information to obtain enhanced position information of the target vehicle, wherein the differential correction information is issued to the road side unit by the cloud.
16. The system according to any one of claims 9 to 15, wherein the obtaining of the precise location information of the target vehicle based on the enhanced location information specifically comprises:
the road side unit or the cloud sends the enhanced position information to the target vehicle, and the target vehicle fuses the enhanced position information and track information of the target vehicle to obtain accurate position information of the target vehicle, wherein the track information of the target vehicle is obtained based on an IMU (inertial measurement unit) system of the target vehicle.
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