CN107063275B - Intelligent vehicle map fusion system and method based on road side equipment - Google Patents
Intelligent vehicle map fusion system and method based on road side equipment Download PDFInfo
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Abstract
本发明请求保护一种基于路侧设备的智能车辆地图融合系统及方法，系统包括车载设备和路侧设备。车载设备包括车辆定位、ADAS地图接口、局部地图生成、DSRC通信和地图转换模块，路侧设备包括DSRC通信和地图融合模块。车载设备车辆定位模块检测主车位置及姿态；ADAS地图接口模块提供道路Id信息；局部地图生成模块生成主车当前位置局部地图；DSRC通信模块实现车辆与路侧设备交互；地图转换模块将融合地图转换到主车坐标系。路侧设备地图融合模块将DSRC通信模块接收的各车辆局部地图转换到路侧设备坐标系并进行融合。本发明实现多车辆感知能力共享来扩展环境感知范围，能提高智能车辆辅助驾驶/自动驾驶性能。
The present invention claims to protect an intelligent vehicle map fusion system and method based on roadside equipment, the system includes vehicle-mounted equipment and roadside equipment. Vehicle-mounted equipment includes vehicle positioning, ADAS map interface, local map generation, DSRC communication and map conversion modules, and roadside equipment includes DSRC communication and map fusion modules. The vehicle positioning module of the on-board equipment detects the position and attitude of the main vehicle; the ADAS map interface module provides road ID information; the local map generation module generates a local map of the current position of the main vehicle; the DSRC communication module realizes the interaction between the vehicle and the roadside equipment; the map conversion module will integrate the map Convert to the host vehicle coordinate system. The roadside equipment map fusion module converts the local maps of each vehicle received by the DSRC communication module to the roadside equipment coordinate system and fuses them. The invention realizes the sharing of perception capabilities of multiple vehicles to expand the range of environmental perception, and can improve the assisted driving/automatic driving performance of intelligent vehicles.
Description
Technical Field
The invention belongs to the technical field of automation, communication and computers, and particularly relates to an intelligent vehicle map fusion system and method based on road side equipment.
Background
Environmental perception and map generation are one of key technologies of intelligent vehicles, in order to improve the performance of intelligent vehicle auxiliary driving safety early warning and automatic driving path planning, the intelligent vehicle needs to have an environmental perception range as large as possible, but in the traditional method, the intelligent vehicle generally only depends on a vehicle-mounted sensor of the vehicle, so that the perception capability of the vehicle is extremely limited.
The Chinese patent application: an intelligent navigation system (application number: CN200710064151.3) discloses a method for sending real-time traffic information to a vehicle client by using a server to plan a route for a user, and the method uses a network to obtain a traffic live to plan the route without involving multi-vehicle real-time map fusion. The Chinese patent application: a vehicle-mounted virtual road state display system (application number: CN201610034923.8) based on vehicle-road cooperation technology discloses a method for acquiring vehicle information and road conditions near a vehicle by using an information interaction system and displaying the information by using the vehicle-mounted virtual display system. The Chinese patent application: an ADAS-based driving assistance system (application number: CN201511008743.4) discloses a safety map generated by using environmental information acquired by cloud-side acquisition vehicle-mounted equipment, which does not relate to multi-vehicle real-time map fusion and does not distinguish different roads. The Chinese patent application: an ADASIS extended information output device and method (application number: CN201510496628.X) based on a safe driving map discloses information extension of the safe driving map by using ADASIS extended information. The Chinese patent application: an ADAS-based driving assistance system (application number: CN201511010294.7) discloses an ADAS-based driving assistance system, which realizes sensor information interaction among different vehicles through a workshop communication technology and solves the problem that the safety early warning range of the vehicles is limited by the detection distance of a vehicle-mounted sensor. The system does not distinguish the relevance of the vehicle and does not consider cooperation with the roadside apparatus.
The invention provides an intelligent vehicle map fusion system and method based on road side equipment, aiming at the problems that the existing intelligent vehicle is limited in environment perception capability and relevance of vehicles is not distinguished during multi-vehicle information fusion. In the system, the roadside device receives local map information of a plurality of vehicles in a communication range through the DSRC, classifies and fuses the vehicles according to the roads to which the vehicles belong, generates a fusion map of each road and feeds the fusion map back to each vehicle, so that the environment perception range of the intelligent vehicle is expanded, and the auxiliary driving/automatic driving performance of the intelligent vehicle is improved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent vehicle map fusion system and method based on road side equipment to effectively expand the environment perception capability of an intelligent vehicle and improve the auxiliary driving/automatic driving performance of the intelligent vehicle, aiming at solving the problems that the environment perception capability of the prior intelligent vehicle is limited by a vehicle-mounted sensor and the relevance of the vehicle is not distinguished during the fusion of multi-vehicle information.
The technical scheme of the invention is as follows:
an intelligent vehicle map fusion system based on roadside equipment, comprising: the vehicle-mounted equipment and the roadside equipment. The vehicle-mounted equipment comprises a vehicle positioning module, an ADAS (Advanced Driver Assistance Systems) map interface module, a local map generation module, a vehicle DSRC (Dedicated short range Communications) communication module and a map conversion module, and the roadside equipment comprises a roadside DSRC communication module and a map fusion module.
Wherein the in-vehicle apparatus section: the vehicle positioning module is used for acquiring the position and posture information of the main vehicle under a geographic coordinate system through satellite positioning equipment; the ADAS map interface module is used for acquiring a road Id number of the current position of the main vehicle from the ADAS map database according to the vehicle position given by the vehicle positioning module; the local map generation module is used for detecting the surrounding environment of the main vehicle through a vehicle-mounted sensor and generating a local map corresponding to the current position of the main vehicle according to the measurement data of the sensor; the vehicle DSRC communication module is used for issuing the current time position and the posture of the main vehicle, the current road Id of the vehicle and a local map, and receiving the position and the posture of the roadside device issued by the roadside device and a fusion map consistent with the current road Id of the main vehicle; and the map conversion module is used for converting the fusion map into a main vehicle coordinate system.
A roadside apparatus section: the roadside DSRC communication module is used for receiving the vehicle position, the attitude, the road Id and the corresponding local map issued by each vehicle in the surrounding communication range of the roadside equipment, and issuing a fusion map obtained by fusing the current position, the attitude and the map of the roadside equipment with the local map of each vehicle by the map fusion module; the map fusion module is used for converting the local maps of the vehicles received by the roadside DSRC communication module into a roadside device coordinate system, classifying the local maps according to the road Id, and fusing the local maps with the same road Id to obtain a fusion map on each road.
Further, the vehicle positioning module collects and calculates the position and the posture of the main vehicle under the geographic coordinate system through satellite positioning equipment.
Further, the local map format generated by the vehicle-mounted device local map generation module is a grid map. The local map takes the current position of the vehicle as an origin, the direction of the vehicle head is the positive direction of the y axis, each grid of the map is represented by a vector, and the local map is represented as a matrix taking grid vectors as elements.
Further, in the vehicle-mounted device local map generation module, a vehicle-mounted sensor detects and acquires position and size information of obstacles (vehicles, pedestrians and other obstacles) in the surrounding environment of the host vehicle, a grid area covered by each obstacle is calculated in a host vehicle grid map coordinate system, a grid which is not covered with one grid is also calculated as a grid which is covered with one grid, and the grid state of the covered grid area is set to be an occupied state.
Further, the fusion map format of the road side equipment map fusion module is a grid map. The fused map is represented by taking the position of the road side equipment as an origin, taking the normal direction of the road as the positive direction of the y axis, each grid of the map is represented by a vector, and the fused map is represented by a matrix taking the grid vector as an element.
A road side equipment intelligent vehicle map fusion method based on the system comprises the following steps:
(1) detecting the position and the posture of the main vehicle: at the current moment k, a vehicle positioning module of the vehicular equipment of the main vehicle acquires and calculates the position and the posture of the main vehicle under a geographic coordinate system at the moment k through satellite positioning equipment;
(2) determining the current road of the host vehicle: the on-board equipment ADAS map interface module obtains the road Id number Id of the current position of the main vehicle from the ADAS map database according to the position of the main vehicle provided by the vehicle positioning modulek h；
(3) And local map generation: a vehicle-mounted sensor collects observation data of surrounding environment information of the main vehicle and generates a local grid map of the main vehicle at the time k;
(4) and (3) main vehicle information release: the vehicle-mounted DSRC communication module issues the current time position, the posture, the road Id number and the local grid map of the main vehicle;
(5) receiving information of the road side equipment: the roadside DSRC communication module receives the position, the posture, the road Id number and the local grid map issued by each vehicle;
(6) map fusion: the roadside device map fusion module converts the local map of each vehicle received by the roadside DSRC communication module into a local map under a coordinate system of the roadside device; classifying roads according to the Id numbers, classifying local maps with the same road Id numbers, and fusing each type of local map respectively to obtain fused maps on the roads;
(7) releasing a fusion map: the road side DSRC communication module issues the position and the posture of the current road side equipment, the Id number of each road and a corresponding fusion map;
(8) receiving vehicle-mounted equipment information: the vehicle-mounted DSRC communication module receives the position of the current roadside equipment and a fusion map with the same ID number as the current road of the main vehicle;
(9) converting the main vehicle map: and the vehicle-mounted equipment map conversion module converts the fusion map into a main vehicle coordinate system to obtain a main vehicle fusion map.
Further, the map fusion of step (6) is as follows:
(1) local map coordinate transformation: converting the local map of each vehicle received by the roadside DSRC communication module into a local map under a roadside device coordinate system;
(2) local map classification: classifying the roads according to the Id numbers, and classifying the local maps with the same road Id numbers according to the road classification;
(3) map fusion: and respectively fusing each type of local map to obtain fused maps on different roads, wherein the fusion rule is as follows: and performing grid fusion processing on the overlapped region according to OR, and performing splicing processing on the non-overlapped region.
The invention has the following advantages and beneficial effects:
the invention provides an intelligent vehicle map fusion system and method based on road side equipment. The map fusion system provided by the invention receives local map information of a plurality of vehicles in a communication range through a DSRC communication device by using roadside equipment, and feeds the map information back to each vehicle after fusion, so that the sensing capability is shared among the vehicles, and the environment sensing range of the intelligent vehicle is expanded; secondly, vehicles are classified according to the roads and then respectively fused to generate a fusion map of each road, so that the efficiency and the accuracy of map fusion are improved; thirdly, local maps of all vehicles are merged and released through the road side equipment, the vehicles only need to provide the local maps without a map merging module, and requirements of vehicle-mounted equipment are lowered. Through the innovation and the improvement, the invention realizes the sharing of the perception capability of multiple vehicles, effectively expands the perception range of the environment of the intelligent vehicle and has important significance and use value for improving the auxiliary driving/automatic driving performance of the intelligent vehicle.
Drawings
FIG. 1 is a general architecture of an intelligent vehicle map fusion system based on road side equipment according to a preferred embodiment of the invention;
FIG. 2 illustrates the format and coordinate system definition of a local map of an intelligent vehicle according to the present invention;
FIG. 3 illustrates the format and coordinate system definition of the road side device fusion map of the present invention;
FIG. 4 is a flowchart of an intelligent vehicle map fusion method based on road side equipment according to the present invention;
FIG. 5 is a flowchart of a road side device map fusion method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail and clearly with reference to the accompanying drawings. The described embodiments are only some of the embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
fig. 1 shows a general architecture of an intelligent vehicle map fusion system based on roadside devices according to the present invention. The system can be divided into an on-board device and a roadside device, and communication is carried out through the DSRC.
The vehicle-mounted equipment comprises a vehicle positioning module, an ADAS map interface module, a local map generation module, a vehicle DSRC communication module and a map conversion module; the roadside device comprises a roadside DSRC communication module and a map fusion module.
An in-vehicle apparatus section: the vehicle positioning module is used for acquiring the position and the posture information of the main vehicle under a geographic coordinate system through satellite positioning equipment; the ADAS map interface module is used for acquiring a road Id number of the current position of the main vehicle from the ADAS map database according to the vehicle position given by the vehicle positioning module; the local map generation module is used for detecting the surrounding environment of the main vehicle through a vehicle-mounted sensor and generating a local map corresponding to the current position of the main vehicle according to the measurement data of the sensor; the vehicle DSRC communication module is used for publishing the current time position and the posture of the main vehicle, the current road Id of the vehicle and a local map, and receiving the position and the posture of the roadside device published by the roadside device and a fusion map consistent with the current road Id of the main vehicle; the map conversion module is used for converting the fusion map into a main vehicle coordinate system.
A roadside apparatus section: the roadside DSRC communication module is used for receiving the vehicle position, attitude, road Id and corresponding local map issued by each vehicle in the surrounding communication range of the roadside equipment, and issuing the current position, attitude of the roadside equipment and a fusion map obtained by fusing the local maps of each vehicle by the map fusion module; the map fusion module is used for converting the local maps of the vehicles received by the roadside DSRC communication module into a roadside device coordinate system, classifying the local maps according to the road Id, and fusing the local maps with the same road Id to obtain a fusion map on each road.
2. Fig. 2 shows a format and a coordinate system definition of a local map of an intelligent vehicle-mounted device adopted by the invention. The local map is represented as a rectangular area with the current position of the vehicle as the origin, the direction of the vehicle head as the positive direction of the y axis, the length of the rectangular area being L and the width of the rectangular area being W. Selecting a unit grid with the specification of R to discretize the local map into n m (n is L/R, m is W/R) grids, wherein each grid is represented by a vector
The partial map is represented as a grid vector
Is a matrix of elements
Wherein
Is the coordinate of the center of the grid, takes an integer,
in the state of the grid, the grid is in a state,
in the occupied state, indicating an obstacle at the grid,
in an unoccupied state.
When the vehicle-mounted device local map is generated, the vehicle-mounted sensor detects and acquires the position and size information of obstacles (vehicles, pedestrians and other obstacles) in the surrounding environment of the host vehicle, calculates the grid area covered by each obstacle in the grid map coordinate system of the host vehicle, calculates the grid area covered by each obstacle when one grid is not covered, and sets the grid state of the covered grid area to be an occupied state,
the generated local grid map is
3. Fig. 3 shows the format and coordinate system definition of the roadside apparatus fusion map according to the present invention. The fusion map format of the road side equipment map fusion module is a grid map. The fusion map takes the position of road side equipment as an origin, the normal direction of a road is the positive direction of a y axis, the dimension specification of the map grids is R, and each grid is expressed as R by using a vector
Fusion map representation as grid vectors
Is a matrix of elements
Wherein n 'and m' are the number of the longitudinal and transverse grids,
is the coordinate of the center of the grid,
in the state of the grid, the grid is in a state,
in the occupied state, indicating an obstacle at the grid,
in an unoccupied state.
4. Fig. 4 shows a flowchart of an intelligent vehicle map fusion method based on roadside devices, which includes the following steps:
(1) detecting the position and the posture of the main vehicle: at the current moment k, a vehicle positioning module of the vehicular equipment of the main vehicle acquires and calculates the position of the main vehicle at the moment k in a geographic coordinate system through satellite positioning equipment
And posture
Wherein the attitude is defined as an included angle between the vehicle running direction and the true north direction of the geographic coordinate system;
(2) determining the current road of the host vehicle: the ADAS map interface module of the vehicle-mounted equipment acquires the road Id number of the current position of the main vehicle from the ADAS map database according to the position of the main vehicle provided by the vehicle positioning module
(3) Local mapGenerating: the vehicle-mounted sensor collects the observation data of the surrounding environment information of the main vehicle and generates a local grid map of the main vehicle at the time of k
(4) And (3) main vehicle information release: vehicle-mounted DSRC communication module issues current time position of main vehicle
Posture
Road Id number
And a local grid map
(5) Receiving information of the road side equipment: the roadside DSRC communication module receives the position issued by each vehicle
Posture
Road Id number
And a local grid map
(6) Map fusion: the roadside equipment map fusion module receives local maps of all vehicles received by the roadside DSRC communication module
Local map converted into coordinate system of road side equipment
Numbering roads by Id
Id class into Ngg(j) J is more than or equal to 1 and less than or equal to Ng, and local maps with the same road Id number
According to Idg(j) Dividing into Ng types, fusing each type of local map respectively to obtain fused maps on each road
(7) Releasing a fusion map: method for publishing current position L of roadside DSRC communication modulegPosture PgAnd each road Id number Idg(j) And corresponding fusion map
1≤j≤Ng；
(8) Receiving vehicle-mounted equipment information: the vehicle-mounted DSRC communication module receives the current position L of the roadside devicegPosture PgAnd the current road Id number of the host vehicle
Consistent Idg(j) And corresponding fusion map
Is marked as
(9) Converting the main vehicle map: the map conversion module of the vehicle-mounted equipment is used for fusing maps
Converting the coordinate system of the main vehicle into a coordinate system of the main vehicle to obtain a main vehicle fusion map
5. Fig. 5 is a flowchart of a road side device map fusion method according to the present invention, which includes the following steps:
(1) local map coordinate transformation: local map of each vehicle received by roadside DSRC communication module
Local map converted into coordinate system of road side equipment
a. Calculating transformation parameters of a vehicle coordinate system and a roadside device coordinate system: according to the position of vehicle i
Posture
And location L of roadside equipmentgPosture PgCalculating coordinate transformation parameters between the vehicle coordinate system and the roadside apparatus coordinate system, including rotation parameters θ (i) and translation parameters Δ x, regardless of the z-axisk(i)、Δy(i)：
b. Transforming the vehicle i local grid map into a roadside device coordinate system: according to the rotation parameter theta (i) and the translation parameter delta xk(i) Δ y (i), map the local grid of vehicle i
Transforming into a coordinate system of road side equipment to obtain
Wherein
Is the coordinate of the center of the grid, takes an integer,
for the grid state, the transformation relationship is:
(2) local map classification: numbering roads by Id
Id class into Ngg(j) J is more than or equal to 0 and less than or equal to Ng, and local maps with the same road Id number
According to Idg(j) Classifying into corresponding Ng classes;
(3) map fusion: respectively fusing each type of local map to obtain fused maps on Ng roads
J is more than or equal to 0 and less than or equal to Ng, and the fusion process is as follows:
a. let j (j is more than or equal to 0 and less than or equal to Ng) to-be-fused local map set
In (1) contains njA local map, an order
b. For local map
And
and fusion, wherein the fusion rule is as follows: to pair
And
the grid fusion processing is carried out on the overlapped area according to OR, and the splicing processing is carried out on the non-overlapped area. To pair
Middle Gridr,j(i) Each component of
The following algorithms (b1) - (b3) were performed for fusion:
(b1) judging an overlapping area: if present
Middle Gridg,jComponent (b) of
Satisfies the conditions
And
then
The represented grid belongs to an overlapping region, otherwise, belongs to a non-overlapping region;
(b2) and (3) fusion of overlapping regions: to the overlapping area
Performing grid fusion processing and updating according to OR
Upper corresponding grid state:
(b3) splicing non-overlapping areas: for non-overlapping region
Supplement it to
Grid ofg,jThe method comprises the following steps:
c. repeating the step b until n is pairedjAll the target vehicles are fused to obtain a fusion map on the road side equipment
The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (5)
1. A fusion method of an intelligent vehicle map fusion system based on road side equipment is disclosed, the intelligent vehicle map fusion system of the road side equipment comprises: the system comprises vehicle-mounted equipment and roadside equipment, wherein the vehicle-mounted equipment comprises a vehicle positioning module, an ADAS advanced driver assistance system map interface module, a local map generation module, a vehicle DSRC special short-range wireless communication module and a map conversion module, and the roadside equipment comprises a roadside DSRC communication module and a map fusion module;
wherein the in-vehicle apparatus section: the vehicle positioning module is used for acquiring the position and posture information of the main vehicle under a geographic coordinate system through satellite positioning equipment; the ADAS map interface module is used for acquiring a road Id number of the current position of the main vehicle from the ADAS map database according to the vehicle position given by the vehicle positioning module; the local map generation module is used for detecting the surrounding environment of the main vehicle through a vehicle-mounted sensor and generating a local map corresponding to the current position of the main vehicle according to the measurement data of the sensor; the vehicle DSRC communication module is used for issuing the current time position and the posture of the main vehicle, the current road Id of the vehicle and a local map, and receiving the position and the posture of the roadside device issued by the roadside device and a fusion map consistent with the current road Id of the main vehicle; the map conversion module is used for converting the fusion map into a main vehicle coordinate system;
a roadside apparatus section: the roadside DSRC communication module is used for receiving the vehicle position, the attitude, the road Id and the corresponding local map issued by each vehicle in the surrounding communication range of the roadside equipment, and issuing a fusion map obtained by fusing the current position, the attitude and the map of the roadside equipment with the local map of each vehicle by the map fusion module; the map fusion module is used for converting the local maps of the vehicles received by the roadside DSRC communication module into a roadside device coordinate system, classifying the local maps according to the road Id, and fusing the local maps with the same road Id to obtain a fusion map on each road; the method is characterized by comprising the following steps:
(1) detecting the position and the posture of the main vehicle: at the current moment k, a vehicle positioning module of the vehicular equipment of the main vehicle collects and calculates the position L of the main vehicle under the geographic coordinate system at the moment k through the satellite positioning equipmentk h＝(xk h,yk h,zk h) And attitude Pk hWherein the attitude is defined as an included angle between the driving direction of the vehicle and the true north direction of the geographic coordinate system;
(2) determining the current road of the host vehicle: the on-board equipment ADAS map interface module obtains the road Id number Id of the current position of the main vehicle from the ADAS map database according to the position of the main vehicle provided by the vehicle positioning modulek h；
(3) And local map generation: the vehicle-mounted sensor collects the observation data of the surrounding environment information of the main vehicle to generate a local grid Map of the main vehicle at the time of Kk h＝{L，W，Gridh}; l is the length of the local grid map, and W is the width of the local grid map; gridhIs expressed as a grid vector sj hIs a matrix of elements;
(4) and (3) main vehicle information release: vehicle-mounted DSRC communication module issues current time position L of main vehiclek hPosture Pk hRoad Id number Idk hAnd a local grid Mapk h；
(5) Receiving information of the road side equipment: the roadside DSRC communication module receives the position L issued by each vehiclek h(i) Posture Pk h(i) Road Id number Idk h(i) And a local grid Mapk h(i)；
(6) Map fusion: the roadside equipment Map fusion module receives the local Map of each vehicle received by the roadside DSRC communication modulek h(i) Local Map converted into road side equipment coordinate systemk r(i) (ii) a Numbering roads by Idk h(i) Id class into Ngg(j) J is more than or equal to 1 and less than or equal to Ng, and local maps Map with the same road Id numberk r(i) According to Idg(j) Dividing into Ng types, fusing each type of local Map respectively to obtain fused Map maps on each roadk g(j)；
(7) Releasing a fusion map: method for publishing current position L of roadside DSRC communication modulegPosture PgAnd each road Id number Idg(j) And corresponding fusion Mapk g(j)，1≤j≤Ng；
(8) Receiving vehicle-mounted equipment information: the vehicle-mounted DSRC communication module receives the current position L of the roadside devicegPosture PgAnd the host vehicle current road Id number Idk hConsistent Idg(j) And corresponding fusion Mapk g(j) Is denoted as Mapk g；
(9) Converting the main vehicle map: map conversion module of vehicle-mounted equipment is used for fusing Mapk gTransforming the coordinate system of the main vehicle to obtain a main vehicle fusionMapk g-h。
2. The fusion method of the roadside device-based intelligent vehicle map fusion system according to claim 1, wherein the local map format generated by the vehicle-mounted device local map generation module is a grid map, the local map takes the current position of the vehicle as an origin, the direction of the vehicle head is a y-axis forward direction, each grid of the map is represented by a vector as sj h＝(xj h,yj h,fj h)TThe local map is represented as a grid vector sj hMatrix Grid of elementsh＝[sj h]1,n*mWherein n and m are the number of the vertical and horizontal grids, xj h、yj hAs the grid center coordinate, fj hIn a grid state, fj h1 is occupied state, indicating that there is an obstacle at the grid, fj h0 is in an unoccupied state.
3. The fusion method of the road side equipment based intelligent vehicle map fusion system as claimed in claim 1, wherein the fusion map format of the road side equipment map fusion module is a grid map, the fusion map is represented by taking the position of the road side equipment as an origin, the normal direction of the road is a positive direction of a y axis, each grid of the map is represented by a vector as sj g＝(xj g,yj g,fj g)TThe fusion map is represented as a grid vector sj gMatrix Grid of elementsg＝[sj g]1,n’*m’Wherein n 'and m' are the number of longitudinal and transverse grids, xj g、yj gAs the grid center coordinate, fj gIn a grid state, fj g1 is occupied state, indicating that there is an obstacle at the grid, fj g0 is in an unoccupied state.
4. The fusion method of the roadside device based intelligent vehicle map fusion system of claim 1, wherein the map fusion module converts each vehicle local map received by the roadside DSRC communication module into a roadside device coordinate system and performs fusion, and the method comprises the following steps:
(1) local map coordinate transformation: local Map of each vehicle received by roadside DSRC communication modulek h(i) Local Map converted into road side equipment coordinate systemk r(i)；
(2) Local map classification: numbering roads by Idk h(i) Id class into Ngg(j) J is more than or equal to 0 and less than or equal to Ng, and local maps Map with the same road Id numberk r(i) According to Idg(j) Classifying into corresponding Ng classes;
(3) map fusion: respectively fusing each type of local Map to obtain fused maps Map on Ng roadsk g,j，0≤j≤Ng。
5. The fusion method of the intelligent vehicle map fusion system based on the roadside device as claimed in claim 4, wherein the step (3) of fusing each type of local map respectively to obtain fusion maps on Ng roads comprises the steps of:
(1) let j class, j is more than or equal to 0 and less than or equal to Ng to be fused with local Map set Mapk r,j(i) In (1) contains njA local Map, let Mapk g,j＝Mapk r,j(i)；
(2) For local Mapk r,j(i) And Mapk g,jAnd fusion, wherein the fusion rule is as follows: for Mapk r,j(i) And Mapk g,jThe overlapping area is subjected to grid fusion processing according to OR, and splicing processing is carried out on the non-overlapping area;
(3) repeating the step (2) until n is pairedjAll the target vehicles are fused to obtain a fusion Map on the road side equipmentk g,j。
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