CN112885135A - Intelligent traffic parking management system based on cloud platform - Google Patents
Intelligent traffic parking management system based on cloud platform Download PDFInfo
- Publication number
- CN112885135A CN112885135A CN202110092581.6A CN202110092581A CN112885135A CN 112885135 A CN112885135 A CN 112885135A CN 202110092581 A CN202110092581 A CN 202110092581A CN 112885135 A CN112885135 A CN 112885135A
- Authority
- CN
- China
- Prior art keywords
- parking space
- vehicle
- parking
- target
- urban
- 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
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
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
- G08G1/148—Management of a network of parking areas
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention relates to a cloud platform-based intelligent traffic parking management system, which comprises: the intelligent traffic cloud platform is in communication connection with the parking auxiliary equipment and the vehicle terminal; wisdom traffic cloud platform includes: the parking space model building system comprises a parking space model building module, a target parking space analyzing module, a vehicle relative pose module, a parking path planning module and a database, wherein communication connection is formed among the modules. And the target parking space analysis module obtains a target parking space according to the urban parking space model and the vehicle parking request. And the vehicle relative pose module analyzes the pose according to the vehicle pose image and the vehicle distance induction data to obtain the vehicle relative pose. And the parking path planning module carries out parking path planning according to the relative pose of the vehicle to obtain a parking planning path and sends a parking command generated according to the parking planning path to the corresponding vehicle terminal.
Description
Technical Field
The invention relates to the field of intelligent traffic cloud platforms and big data, in particular to a cloud platform-based intelligent traffic parking management system.
Background
The smart city is a city that uses various information technologies or innovative concepts to communicate and integrate the system and service of the city to improve the efficiency of resource utilization, optimize city management and service, and improve the quality of life of citizens.
The smart city comprises a smart community, smart security and intelligent traffic, the smart traffic is based on the intelligent traffic, high and new IT technologies such as Internet of things, cloud computing, big data and mobile internet are integrated, traffic information is collected through the high and new technologies, and traffic information service under real-time traffic data is provided. Data processing technologies such as data models and data mining are largely used, and systematicness, real-time performance, information exchange interactivity and service universality of intelligent traffic are achieved.
In the existing urban road, because the roadside parking is full, the vehicle owner can not observe the vacancy condition of the vehicle visually, and therefore the vehicle can only be driven to move forwards at a slow speed and can go forward at a short distance to look for vacant parking spaces on the road, so that the driving is suddenly slow, and traffic jam is easily caused.
Disclosure of Invention
In view of this, the present invention provides a smart transportation parking management system based on a cloud platform, which includes:
the intelligent traffic cloud platform is in communication connection with the parking auxiliary equipment and the vehicle terminal;
wisdom traffic cloud platform includes: the system comprises a parking place model building module, a target parking place analyzing module, a vehicle relative pose module, a parking path planning module and a database, wherein the modules are in communication connection;
the intelligent traffic cloud platform receives parking space live information sent by each parking auxiliary device and a vehicle parking request sent by a vehicle terminal;
the parking space model building module builds an urban parking space model according to all parking space live information, the target parking space analysis module obtains vehicle coordinate points and parking space coordinate points in a target area according to the urban parking space model and a vehicle parking request, and the vehicle coordinate points are respectively connected with each parking space coordinate point in the target area to obtain a parking space mapping vector so as to obtain a parking space planning model;
the target parking space analysis module decomposes each parking space mapping vector in the parking space planning model into a plurality of parking space mapping sub-vectors according to the target road data to obtain the real-time distance between each parking space coordinate point and the vehicle coordinate point, obtains the matching degree between the target vehicle and each vacant parking space in the target parking area according to the real-time distance between each parking space coordinate point and the vehicle coordinate point, and then selects the vacant parking space with the highest matching degree in the target parking area as the target parking space;
when a target vehicle reaches a target parking space, the parking auxiliary equipment acquires a vehicle pose image and vehicle distance induction data of the target vehicle in real time and sends the vehicle pose image and the vehicle distance induction data to the intelligent traffic cloud platform;
the vehicle relative pose module carries out pose analysis according to the vehicle pose image and the vehicle distance induction data to obtain a vehicle relative pose;
and the parking path planning module carries out path planning according to the relative pose of the vehicle to obtain a parking planning path and sends a parking command generated according to the parking planning path to the corresponding vehicle terminal.
In a further embodiment, the establishment of the urban parking stall model by the parking stall model establishment module according to the actual parking stall information in the city comprises:
the parking place model building module builds an urban parking place coordinate system by taking the urban center as an origin of coordinates, and acquires the real-time parking place state of each parking place in the city according to the real-time parking place information of each parking place;
the parking space model building module generates an urban parking space state table according to the real-time parking space state of each parking space in the city; the vehicle is characterized in that the parking space state table comprises a plurality of urban parking space state items, and the urban parking space state items are used for expressing the mapping relation among parking space real-time states, parking space numbers and parking space positions;
the parking space model building module selects an urban parking space state item with a parking space real-time state being an idle state in the urban parking space state table to generate an urban idle parking space table; the city idle parking space table comprises a plurality of city parking space state items with parking spaces in idle states in real time;
the parking space model building module maps the parking space position of each free parking space in the urban free parking space table to an urban parking space coordinate system to obtain a parking space coordinate point of each free parking space in the urban parking space coordinate system, and marks a corresponding parking space number for each parking space coordinate point to obtain an urban parking space model; and each parking space coordinate point corresponds to a unique free parking space.
In a further embodiment, the obtaining of the parking space planning model by the target parking space analysis module according to the urban parking space model and the vehicle parking request includes:
the target parking space analysis module acquires the real-time position of a target vehicle according to the vehicle parking request, and maps the real-time position of the target vehicle into an urban parking space coordinate system to obtain vehicle coordinate points of the target vehicle in the urban parking space coordinate system, wherein each vehicle coordinate point corresponds to a unique target vehicle;
the target parking space analysis module acquires a target parking area according to the vehicle parking request, acquires a plurality of area edge positions of the target parking area, maps the plurality of area edge positions of the target parking area to an urban parking space coordinate system to obtain a plurality of area edge coordinate points, and then connects the area edge coordinate points in the urban parking space coordinate system to obtain a target area in the urban parking space coordinate system;
the target parking space analysis module obtains parking space coordinate points in a target area in an urban parking space coordinate system, the vehicle coordinate points are respectively connected with all parking space coordinate points in the target area in the urban parking space coordinate system to obtain parking space mapping vectors corresponding to all parking space coordinate points in the target area, and then a parking space planning model is obtained according to all parking space mapping vectors.
In a further embodiment, the obtaining, by the target parking space analysis module according to the parking space planning model, the matching degree between the target vehicle and each vacant parking space in the target parking area includes:
the target parking space analysis module acquires a parking space mapping vector corresponding to each parking space coordinate point in a target area in an urban parking space coordinate system according to the parking space planning model;
the target parking space analysis module acquires a city map of the location of a target vehicle from the database, acquires target road data in a target parking area according to the city map, and then decomposes each parking space mapping vector into a plurality of parking space mapping sub-vectors according to the target road data;
the target parking space analysis module acquires a plurality of parking space mapping sub-vectors of each parking space mapping vector, acquires a model of each parking space mapping sub-vector, and then acquires the real-time distance between each parking space coordinate point and a vehicle coordinate point according to the models of all parking space mapping sub-vectors of each parking space mapping vector;
the target parking space analysis module acquires target road data in a target parking area and analyzes the vehicle condition of each road to obtain the vehicle condition coefficient of each free parking space in the target parking area; the vehicle condition coefficient is used for indicating the road condition and the complexity of the vehicle condition from the target vehicle to the corresponding idle parking space;
and the target parking space analysis module acquires the matching degree of the target vehicle and each free parking space in the target parking area according to the matching degree function, the real-time distance between each parking space coordinate point and the vehicle condition coefficient of each free parking space.
In a further embodiment, the vehicle relative pose module performs pose analysis according to the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose, and the vehicle relative pose comprises:
the vehicle relative pose module establishes a target parking space coordinate system by taking the parking auxiliary equipment as a center, taking the length direction of the parking space as a longitudinal axis and taking the width direction of the parking space as a transverse axis;
the vehicle relative pose module acquires the change direction and the change amplitude of each pixel point in the vehicle pose image according to the vehicle pose image;
the vehicle relative pose module calculates a continuous weight coefficient of each pixel point according to the abscissa and the ordinate of each pixel point, and performs weighted average on each pixel point of the vehicle pose image according to the change direction, the change amplitude and the continuous weight coefficient of each pixel point to obtain a pixel change amplitude of each pixel point.
In a further embodiment, the vehicle relative pose module performs pose analysis according to the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose, and the vehicle relative pose comprises:
the vehicle relative pose module compares the pixel change amplitude of each pixel point with an amplitude threshold value, and takes the pixel points with the pixel change amplitudes larger than the amplitude threshold value as step pixel points.
The vehicle relative pose module maps the step pixel points to a target parking space coordinate system to obtain step coordinate points, and obtains a vehicle outline of the target vehicle according to all the step coordinate points;
the vehicle relative pose module respectively acquires the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment according to the vehicle distance sensing data.
In a further embodiment, the vehicle relative pose module performs pose analysis according to the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose, and the vehicle relative pose comprises:
the vehicle relative pose module acquires coordinates of a vehicle tail positioning point, a right vehicle body positioning point, a left vehicle body positioning point and a vehicle head positioning point of the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point in a target parking space coordinate system according to the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment;
the vehicle relative pose module connects the coordinates of the vehicle tail positioning point and the vehicle head positioning point to obtain a vehicle body parallel vector, and connects the right vehicle body positioning point and the left vehicle body positioning point to obtain a vehicle body vertical vector;
the vehicle relative pose module acquires a vehicle relative pose according to the vehicle contour, the vehicle body parallel vector and the vehicle body vertical vector of the target vehicle.
In a further embodiment, the vehicle parking request is used for instructing the intelligent transportation cloud platform to perform parking space planning on the target vehicle so as to select a target parking space with the highest matching degree for the target vehicle, and the vehicle parking request includes a target parking area and a real-time position of the target vehicle. The target parking space is an idle parking space with the highest matching degree with the target vehicle in the target parking area. The target parking area is an area range where a vehicle driver of the target vehicle desires to park. The parking space live information comprises: the parking space number, the real-time parking space state and the parking space position. The parking space real-time state is used for indicating the real-time state of the corresponding parking space, and comprises an idle state or a use state. The parking space number is used for carrying out unique identification on the parking space. The parking space position is used for indicating the specific position of the parking space.
The parking auxiliary equipment is equipment with an image acquisition function, a distance sensing function and a data transmission function, and each parking auxiliary equipment corresponds to a unique parking space. The vehicle terminal is the intelligent equipment that has communication function and data transmission function that vehicle driver used, and it includes: smart phones, tablet computers, and smart watches.
According to the invention, the urban parking stall model is obtained by analyzing the real-time state of the parking stall of each parking stall in the whole city, and the parking stall planning model is obtained according to the urban parking stall model and the real-time position of the target vehicle, so that the target parking stall with the highest matching degree in the expected parking area of the driver is obtained, and the time for the driver to drive the vehicle to search the parking stall is saved.
In addition, the position and posture of the vehicle is analyzed through the vehicle position and posture image and the vehicle distance induction data to obtain the relative position and posture of the vehicle, and the parking path is planned according to the relative position and posture of the vehicle to obtain the parking planning path so as to assist a driver to accurately park the vehicle in a parking space.
Drawings
Fig. 1 is a block diagram illustrating a configuration of a smart transit parking management system based on a cloud platform according to an exemplary embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention.
Referring to fig. 1, in one embodiment, a cloud platform based intelligent transportation parking management system includes a parking assistance device, a vehicle terminal, and an intelligent transportation cloud platform having a communication connection with the parking assistance device and the vehicle terminal. Wisdom traffic cloud platform includes: the parking space model building system comprises a parking space model building module, a target parking space analyzing module, a vehicle relative pose module, a parking path planning module and a database, wherein communication connection is formed among the modules.
The intelligent traffic cloud platform receives parking space live information sent by each parking auxiliary device and a vehicle parking request sent by a vehicle terminal;
the parking space model building module builds an urban parking space model according to all parking space live information, the target parking space analysis module obtains vehicle coordinate points and parking space coordinate points in a target area according to the urban parking space model and a vehicle parking request, and the vehicle coordinate points are respectively connected with each parking space coordinate point in the target area to obtain a parking space mapping vector so as to obtain a parking space planning model;
the target parking space analysis module decomposes each parking space mapping vector in the parking space planning model into a plurality of parking space mapping sub-vectors according to the target road data to obtain the real-time distance between each parking space coordinate point and the vehicle coordinate point, obtains the matching degree between the target vehicle and each vacant parking space in the target parking area according to the real-time distance between each parking space coordinate point and the vehicle coordinate point, and then selects the vacant parking space with the highest matching degree in the target parking area as the target parking space;
when a target vehicle reaches a target parking space, the parking auxiliary equipment acquires a vehicle pose image and vehicle distance induction data of the target vehicle in real time and sends the vehicle pose image and the vehicle distance induction data to the intelligent traffic cloud platform;
the vehicle relative pose module carries out pose analysis according to the vehicle pose image and the vehicle distance induction data to obtain a vehicle relative pose;
and the parking path planning module carries out path planning according to the relative pose of the vehicle to obtain a parking planning path and sends a parking command generated according to the parking planning path to the corresponding vehicle terminal.
The urban parking space model is obtained by analyzing the real-time state of the parking space of each parking space in the whole city, and the parking space planning model is obtained according to the urban parking space model and the real-time position of the target vehicle, so that the target parking space with the highest matching degree in the expected parking area of the driver is obtained, and the time for driving the driver to find the parking space is saved.
For the purposes of promoting an understanding, the principles and operation of the present invention are described in detail below. Specifically, in one embodiment, the intelligent transportation parking management method may include the following steps:
and S1, the intelligent traffic cloud platform receives the real-time parking space information sent by each parking auxiliary device and the vehicle parking request sent by the vehicle terminal.
Optionally, the parking space live information includes: the parking space number, the real-time parking space state and the parking space position. The parking space real-time state is used for indicating the real-time state of the corresponding parking space and comprises an idle state or a use state, the parking space number is used for carrying out unique identification on the parking space, and the parking space position is used for indicating the specific position of the parking space. The vehicle parking request is used for indicating the intelligent traffic cloud platform to carry out parking space planning on the target vehicle so as to select a target parking space with the highest matching degree for the target vehicle, and the vehicle parking request comprises a target parking area and the real-time position of the target vehicle.
Optionally, the parking assistance device is a device having an image acquisition function, a distance sensing function, and a data transmission function, and each parking assistance device corresponds to a unique parking space. The vehicle terminal is the intelligent equipment that has communication function and data transmission function that vehicle driver used, and it includes: smart phones, tablet computers, and smart watches. The target parking space is the free parking space with the highest matching degree with the target vehicle in the target parking area. The target parking area is an area range where the vehicle driver of the target vehicle desires to park.
S2, the parking space model building module builds an urban parking space model according to all parking space live information, the target parking space analysis module obtains vehicle coordinate points and parking space coordinate points in the target area according to the urban parking space model and the vehicle parking request, and the vehicle coordinate points are respectively connected with each parking space coordinate point in the target area to obtain a parking space mapping vector so as to obtain a parking space planning model.
In one embodiment, the establishment of the urban parking space model by the parking space model establishment module according to the actual parking space information in the city comprises:
the parking place model building module builds an urban parking place coordinate system by taking the urban center as an origin of coordinates, and acquires the real-time parking place state of each parking place in the city according to the real-time parking place information of each parking place;
the parking space model building module generates an urban parking space state table according to the real-time parking space state of each parking space in the city; the vehicle is characterized in that the parking space state table comprises a plurality of urban parking space state items, and the urban parking space state items are used for expressing the mapping relation among parking space real-time states, parking space numbers and parking space positions;
the parking space model building module selects an urban parking space state item with a parking space real-time state being an idle state in the urban parking space state table to generate an urban idle parking space table; the city idle parking space table comprises a plurality of city parking space state items with parking spaces in idle states in real time;
the parking space model building module maps the parking space position of each free parking space in the urban free parking space table to an urban parking space coordinate system to obtain a parking space coordinate point of each free parking space in the urban parking space coordinate system, and marks a corresponding parking space number for each parking space coordinate point to obtain an urban parking space model; and each parking space coordinate point corresponds to a unique free parking space.
In one embodiment, the obtaining of the parking space planning model by the target parking space analysis module according to the urban parking space model and the vehicle parking request includes:
the target parking space analysis module acquires the real-time position of a target vehicle according to the vehicle parking request, and maps the real-time position of the target vehicle into an urban parking space coordinate system to obtain vehicle coordinate points of the target vehicle in the urban parking space coordinate system, wherein each vehicle coordinate point corresponds to a unique target vehicle;
the target parking space analysis module acquires a target parking area according to the vehicle parking request, acquires a plurality of area edge positions of the target parking area, maps the plurality of area edge positions of the target parking area to an urban parking space coordinate system to obtain a plurality of area edge coordinate points, and then connects the area edge coordinate points in the urban parking space coordinate system to obtain a target area in the urban parking space coordinate system;
the target parking space analysis module obtains parking space coordinate points in a target area in an urban parking space coordinate system, the vehicle coordinate points are respectively connected with all parking space coordinate points in the target area in the urban parking space coordinate system to obtain parking space mapping vectors corresponding to all parking space coordinate points in the target area, and then a parking space planning model is obtained according to all parking space mapping vectors.
S3, the target parking space analysis module decomposes each parking space mapping vector in the parking space planning model into a plurality of parking space mapping sub-vectors according to the target road data to obtain the real-time distance between each parking space coordinate point and the vehicle coordinate point, obtains the matching degree between the target vehicle and each vacant parking space in the target parking area according to the real-time distance between each parking space coordinate point and the vehicle coordinate point, and then selects the vacant parking space with the highest matching degree in the target parking area as the target parking space.
Optionally, the target parking space analysis module sends the target parking space information to a corresponding vehicle terminal, that is, a vehicle terminal corresponding to the target vehicle. The target parking space information comprises: the number of the target parking space, the position of the target parking space and the relative distance of the vehicle. The relative distance of the vehicle is the distance between the target parking space and the real-time position of the target vehicle. The target parking space is an idle parking space recommended by the intelligent traffic cloud platform and having the highest matching degree with the target vehicle.
In one embodiment, the obtaining, by the target parking space analysis module according to the parking space planning model, the matching degree between the target vehicle and each vacant parking space in the target parking area includes:
the target parking space analysis module acquires a parking space mapping vector corresponding to each parking space coordinate point in a target area in an urban parking space coordinate system according to the parking space planning model;
the target parking space analysis module acquires a city map of the location of a target vehicle from the database, acquires target road data in a target parking area according to the city map, and then decomposes each parking space mapping vector into a plurality of parking space mapping sub-vectors according to the target road data;
the target parking space analysis module acquires a plurality of parking space mapping sub-vectors of each parking space mapping vector, acquires a model of each parking space mapping sub-vector, and then acquires the real-time distance between each parking space coordinate point and a vehicle coordinate point according to the models of all parking space mapping sub-vectors of each parking space mapping vector;
the target parking space analysis module acquires target road data in a target parking area and analyzes the vehicle condition of each road to obtain the vehicle condition coefficient of each free parking space in the target parking area; the vehicle condition coefficient is used for indicating the road condition and the complexity of the vehicle condition from the target vehicle to the corresponding idle parking space;
and the target parking space analysis module acquires the matching degree of the target vehicle and each free parking space in the target parking area according to the matching degree function, the real-time distance between each parking space coordinate point and the vehicle condition coefficient of each free parking space.
In one real-time example, the match function is:
wherein P is the matching degree, s is the real-time distance, c is the vehicle condition coefficient, and e is the natural base number.
S4, when the target vehicle reaches the target parking space, the parking auxiliary equipment collects the vehicle pose image and the vehicle distance sensing data of the target vehicle in real time and sends the vehicle pose image and the vehicle distance sensing data to the intelligent traffic cloud platform; and the vehicle relative pose module analyzes the pose according to the vehicle pose image and the vehicle distance induction data to obtain the vehicle relative pose.
Optionally, the vehicle pose image is used for indicating a current position and a current posture of the target vehicle, and the vehicle distance sensing data is used for indicating a distance between the target vehicle and the target parking space. The vehicle relative pose is the relative position and posture of the target vehicle and the parking assistance apparatus.
In one embodiment, the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module establishes a target parking space coordinate system by taking the parking auxiliary equipment as a center, taking the length direction of the parking space as a longitudinal axis and taking the width direction of the parking space as a transverse axis;
the vehicle relative pose module acquires the change direction and the change amplitude of each pixel point in the vehicle pose image according to the vehicle pose image;
the vehicle relative pose module calculates a continuous weight coefficient of each pixel point according to the abscissa and the ordinate of each pixel point, and performs weighted average on each pixel point of the vehicle pose image according to the change direction, the change amplitude and the continuous weight coefficient of each pixel point to obtain a pixel change amplitude of each pixel point.
In one embodiment, the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module compares the pixel change amplitude of each pixel point with an amplitude threshold value, and takes the pixel points with the pixel change amplitudes larger than the amplitude threshold value as step pixel points.
The vehicle relative pose module maps the step pixel points to a target parking space coordinate system to obtain step coordinate points, and obtains a vehicle outline of the target vehicle according to all the step coordinate points;
the vehicle relative pose module respectively acquires the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment according to the vehicle distance sensing data.
In one embodiment, the vehicle relative pose module transforming the step pixel points to the target parking space coordinate system by using the direction rotation matrix and the translation vector comprises:
wherein, (x, y) is the coordinate of the step pixel point in the coordinate system of the target parking space, (x)s,ys) And the coordinates of the step pixel points in the image are shown, U is a direction rotation matrix, and V is a translation vector.
In one embodiment, the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module acquires coordinates of a vehicle tail positioning point, a right vehicle body positioning point, a left vehicle body positioning point and a vehicle head positioning point of the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point in a target parking space coordinate system according to the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment;
the vehicle relative pose module connects the coordinates of the vehicle tail positioning point and the vehicle head positioning point to obtain a vehicle body parallel vector, and connects the right vehicle body positioning point and the left vehicle body positioning point to obtain a vehicle body vertical vector;
the vehicle relative pose module acquires a vehicle relative pose according to the vehicle contour, the vehicle body parallel vector and the vehicle body vertical vector of the target vehicle.
And S5, the parking path planning module carries out path planning according to the relative pose of the vehicle to obtain a parking planning path, and sends a parking command generated according to the parking planning path to the corresponding vehicle terminal.
Optionally, the parking planning path is a specific parking path, and the parking command instruction is used to command the driver to park, including: straight, reverse, left turn and right turn.
In addition, functional units in the embodiments herein 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 storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium, which includes 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 invention, and the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The principles and embodiments of this document are explained herein using specific examples, which are presented only to aid in understanding the methods and their core concepts; meanwhile, for the general technical personnel in the field, according to the idea of this document, there may be changes in the concrete implementation and the application scope, in summary, this description should not be understood as the limitation of this document.
Claims (9)
1. The utility model provides a wisdom transportation parking management system based on cloud platform which characterized in that, it includes: the intelligent traffic cloud platform is in communication connection with the parking auxiliary equipment and the vehicle terminal; the intelligent traffic cloud platform comprises a parking space model building module, a target parking space analysis module, a vehicle relative pose module, a parking path planning module and a database;
the intelligent traffic cloud platform receives parking space live information sent by parking auxiliary equipment and a vehicle parking request sent by a vehicle terminal, wherein the vehicle parking request comprises a target parking area and a real-time position of a target vehicle;
the parking space model building module builds an urban parking space model according to all parking space live information, the target parking space analysis module obtains vehicle coordinate points and parking space coordinate points in a target area according to the urban parking space model and a vehicle parking request, and the vehicle coordinate points are respectively connected with each parking space coordinate point in the target area to obtain a parking space mapping vector so as to obtain a parking space planning model;
the target parking space analysis module decomposes each parking space mapping vector in the parking space planning model into a plurality of parking space mapping sub-vectors according to the target road data to obtain the real-time distance between each parking space coordinate point and the vehicle coordinate point, obtains the matching degree between the target vehicle and each vacant parking space in the target parking area according to the real-time distance between each parking space coordinate point and the vehicle coordinate point, and then selects the vacant parking space with the highest matching degree in the target parking area as the target parking space;
when a target vehicle reaches a target parking space, the parking auxiliary equipment acquires a vehicle pose image and vehicle distance induction data of the target vehicle in real time and sends the vehicle pose image and the vehicle distance induction data to the intelligent traffic cloud platform;
the vehicle relative pose module carries out pose analysis according to the vehicle pose image and the vehicle distance induction data to obtain a vehicle relative pose;
and the parking path planning module carries out path planning according to the relative pose of the vehicle to obtain a parking planning path and sends a parking command generated according to the parking planning path to the corresponding vehicle terminal.
2. The system of claim 1, wherein the parking space model building module building the urban parking space model according to the actual parking space information in the city comprises:
the parking place model building module builds an urban parking place coordinate system by taking the urban center as an origin of coordinates, and acquires the real-time parking place state of each parking place in the city according to the real-time parking place information of each parking place;
the parking space model building module generates an urban parking space state table according to the real-time parking space state of each parking space in the city; the vehicle is characterized in that the parking space state table comprises a plurality of urban parking space state items, and the urban parking space state items are used for expressing the mapping relation among parking space real-time states, parking space numbers and parking space positions;
the parking space model building module selects an urban parking space state item with a parking space real-time state being an idle state in the urban parking space state table to generate an urban idle parking space table; the city idle parking space table comprises a plurality of city parking space state items with parking spaces in idle states in real time;
the parking space model building module maps the parking space position of each free parking space in the urban free parking space table to an urban parking space coordinate system to obtain a parking space coordinate point of each free parking space in the urban parking space coordinate system, and marks a corresponding parking space number for each parking space coordinate point to obtain an urban parking space model; and each parking space coordinate point corresponds to a unique free parking space.
3. The system of claim 2, wherein the target parking space analysis module obtaining the parking space planning model according to the urban parking space model and the vehicle parking request comprises:
the target parking space analysis module acquires the real-time position of a target vehicle according to the vehicle parking request, and maps the real-time position of the target vehicle into an urban parking space coordinate system to obtain vehicle coordinate points of the target vehicle in the urban parking space coordinate system, wherein each vehicle coordinate point corresponds to a unique target vehicle;
the target parking space analysis module acquires a target parking area according to the vehicle parking request, acquires a plurality of area edge positions of the target parking area, maps the plurality of area edge positions of the target parking area to an urban parking space coordinate system to obtain a plurality of area edge coordinate points, and then connects the area edge coordinate points in the urban parking space coordinate system to obtain a target area in the urban parking space coordinate system;
the target parking space analysis module obtains parking space coordinate points in a target area in an urban parking space coordinate system, the vehicle coordinate points are respectively connected with all parking space coordinate points in the target area in the urban parking space coordinate system to obtain parking space mapping vectors corresponding to all parking space coordinate points in the target area, and then a parking space planning model is obtained according to all parking space mapping vectors.
4. The system of claim 3, wherein the obtaining, by the target parking space analysis module, the matching degree between the target vehicle and each free parking space in the target parking area according to the parking space planning model comprises:
the target parking space analysis module acquires a parking space mapping vector corresponding to each parking space coordinate point in a target area in an urban parking space coordinate system according to the parking space planning model;
the target parking space analysis module acquires a city map of the location of a target vehicle from the database, acquires target road data in a target parking area according to the city map, and then decomposes each parking space mapping vector into a plurality of parking space mapping sub-vectors according to the target road data;
the target parking space analysis module acquires a plurality of parking space mapping sub-vectors of each parking space mapping vector, acquires a model of each parking space mapping sub-vector, and then acquires the real-time distance between each parking space coordinate point and a vehicle coordinate point according to the models of all parking space mapping sub-vectors of each parking space mapping vector;
the target parking space analysis module acquires target road data in a target parking area and analyzes the vehicle condition of each road to obtain the vehicle condition coefficient of each free parking space in the target parking area; the vehicle condition coefficient is used for indicating the road condition and the complexity of the vehicle condition from the target vehicle to the corresponding idle parking space;
and the target parking space analysis module acquires the matching degree of the target vehicle and each free parking space in the target parking area according to the matching degree function, the real-time distance between each parking space coordinate point and the vehicle condition coefficient of each free parking space.
5. The system of claim 4, wherein the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module establishes a target parking space coordinate system by taking the parking auxiliary equipment as a center, taking the length direction of the parking space as a longitudinal axis and taking the width direction of the parking space as a transverse axis;
the vehicle relative pose module acquires the change direction and the change amplitude of each pixel point in the vehicle pose image according to the vehicle pose image;
the vehicle relative pose module calculates a continuous weight coefficient of each pixel point according to the abscissa and the ordinate of each pixel point, and performs weighted average on each pixel point of the vehicle pose image according to the change direction, the change amplitude and the continuous weight coefficient of each pixel point to obtain a pixel change amplitude of each pixel point.
6. The system of claim 5, wherein the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module compares the pixel change amplitude of each pixel point with an amplitude threshold value, and takes the pixel points with the pixel change amplitudes larger than the amplitude threshold value as step pixel points;
the vehicle relative pose module maps the step pixel points to a target parking space coordinate system to obtain step coordinate points, and obtains a vehicle outline of the target vehicle according to all the step coordinate points;
the vehicle relative pose module respectively acquires the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment according to the vehicle distance sensing data.
7. The system of claim 6, wherein the vehicle relative pose module performing pose analysis based on the vehicle pose image and the vehicle distance sensing data to obtain the vehicle relative pose comprises:
the vehicle relative pose module acquires coordinates of a vehicle tail positioning point, a right vehicle body positioning point, a left vehicle body positioning point and a vehicle head positioning point of the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point in a target parking space coordinate system according to the distances between the vehicle tail middle point, the vehicle body right middle point, the vehicle body left middle point and the vehicle head middle point and the parking auxiliary equipment;
the vehicle relative pose module connects the coordinates of the vehicle tail positioning point and the vehicle head positioning point to obtain a vehicle body parallel vector, and connects the right vehicle body positioning point and the left vehicle body positioning point to obtain a vehicle body vertical vector;
the vehicle relative pose module acquires a vehicle relative pose according to the vehicle contour, the vehicle body parallel vector and the vehicle body vertical vector of the target vehicle.
8. The system according to any one of claims 1 to 7, wherein the vehicle terminal is a smart device having a communication function and a data transmission function, which is used by a vehicle driver, and includes: smart phones, tablet computers, and smart watches.
9. The system of any one of claims 1 to 8, wherein the target parking area is an area range where a vehicle driver of a target vehicle desires to park, and the parking space real-time information includes a parking space number, a real-time parking space status and a parking space position, wherein the real-time parking space status is used for indicating a real-time status of a corresponding parking space, and the parking space number is used for uniquely identifying the parking space.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110092581.6A CN112885135B (en) | 2021-01-24 | 2021-01-24 | Intelligent traffic parking management system based on cloud platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110092581.6A CN112885135B (en) | 2021-01-24 | 2021-01-24 | Intelligent traffic parking management system based on cloud platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112885135A true CN112885135A (en) | 2021-06-01 |
| CN112885135B CN112885135B (en) | 2022-12-20 |
Family
ID=76050646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110092581.6A Active CN112885135B (en) | 2021-01-24 | 2021-01-24 | Intelligent traffic parking management system based on cloud platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112885135B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114179785A (en) * | 2021-11-22 | 2022-03-15 | 岚图汽车科技有限公司 | Service-oriented fusion parking control system, electronic equipment and vehicle |
| CN114512019A (en) * | 2021-12-30 | 2022-05-17 | 浙江创泰科技有限公司 | Intelligent parking identification group control method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104299448A (en) * | 2014-11-05 | 2015-01-21 | 重庆金融后援服务有限公司 | Urban intelligent parking management system and method based on cloud platform internet of vehicles |
| CN204440665U (en) * | 2015-03-12 | 2015-07-01 | 武汉泰通卫星技术发展有限责任公司 | A kind of regional traffic wisdom parking cloud platform |
| CN107993433A (en) * | 2017-11-29 | 2018-05-04 | 重庆文中科技有限公司 | Smart city public information service cloud platform |
| CN109559553A (en) * | 2018-12-12 | 2019-04-02 | 重庆邮电大学 | A kind of wisdom shutdown system and its parking management method |
| CN111462496A (en) * | 2020-05-09 | 2020-07-28 | 云南电网有限责任公司电力科学研究院 | Vehicle-mounted application system of smart city |
-
2021
- 2021-01-24 CN CN202110092581.6A patent/CN112885135B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104299448A (en) * | 2014-11-05 | 2015-01-21 | 重庆金融后援服务有限公司 | Urban intelligent parking management system and method based on cloud platform internet of vehicles |
| CN204440665U (en) * | 2015-03-12 | 2015-07-01 | 武汉泰通卫星技术发展有限责任公司 | A kind of regional traffic wisdom parking cloud platform |
| CN107993433A (en) * | 2017-11-29 | 2018-05-04 | 重庆文中科技有限公司 | Smart city public information service cloud platform |
| CN109559553A (en) * | 2018-12-12 | 2019-04-02 | 重庆邮电大学 | A kind of wisdom shutdown system and its parking management method |
| CN111462496A (en) * | 2020-05-09 | 2020-07-28 | 云南电网有限责任公司电力科学研究院 | Vehicle-mounted application system of smart city |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114179785A (en) * | 2021-11-22 | 2022-03-15 | 岚图汽车科技有限公司 | Service-oriented fusion parking control system, electronic equipment and vehicle |
| CN114179785B (en) * | 2021-11-22 | 2023-10-13 | 岚图汽车科技有限公司 | Service-oriented fusion parking control system, electronic equipment and vehicle |
| CN114512019A (en) * | 2021-12-30 | 2022-05-17 | 浙江创泰科技有限公司 | Intelligent parking identification group control method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112885135B (en) | 2022-12-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112885134B (en) | Smart city traffic management method based on big data | |
| US20220332348A1 (en) | Autonomous driving method, related device, and computer-readable storage medium | |
| CN108345822B (en) | Point cloud data processing method and device | |
| CN112885135B (en) | Intelligent traffic parking management system based on cloud platform | |
| CN110103953B (en) | Method, apparatus, medium, and system for assisting driving control of vehicle | |
| CN115222158B (en) | Smart city parking lot management method, system and device based on Internet of things | |
| CN112639882B (en) | Positioning method, device and system | |
| CN110930323B (en) | Method and device for removing reflection of image | |
| CN109783593A (en) | A kind of map updating system can be used for automatic Pilot and method | |
| CN113792566A (en) | Laser point cloud processing method and related equipment | |
| CN112789208B (en) | Apparatus and method for estimating vehicle position | |
| CN106920386B (en) | Method, robot and system for adjusting vehicle placement position | |
| CN114613193A (en) | Calculation force sharing-based parking space acquisition method, storage medium, system and vehicle | |
| CN106355935A (en) | Server subsystem for on-line management system of parking lot | |
| CN115205311B (en) | Image processing method, device, vehicle, medium and chip | |
| CN106448243A (en) | Parking lot on-line management method | |
| CN115311891A (en) | Roadside and parking lot free parking space sharing method and system and storage medium | |
| CN109147374A (en) | Parking lot management method, system, on board unit and background server | |
| CN115203457B (en) | Image retrieval method, device, vehicle, storage medium and chip | |
| CN114859942B (en) | Robot motion control method and device, electronic equipment and storage medium | |
| CN115100630B (en) | Obstacle detection method, obstacle detection device, vehicle, medium and chip | |
| CN112946603B (en) | Road maintenance detection system based on laser radar and detection method thereof | |
| CN114283397A (en) | Global relocation method, device, equipment and storage medium | |
| CN113282638A (en) | Urban construction vehicle identification method and device | |
| Chen et al. | Towards bio-inspired place recognition over multiple spatial scales |
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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20221205 Address after: 601-614, Building 18A, Shangxiyuan, No. 31, Xiangfu West Road, Tianxin District, Changsha, Hunan 410000 Applicant after: Changsha static transportation investment and Operation Co.,Ltd. Address before: No.4, 1st floor, building 8, 255 Da'an Road, Zhengxing street, Tianfu New District, Chengdu, Sichuan 610218 Applicant before: Chengdu smart enabling technology Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |