CN106969779A - Intelligent vehicle map emerging system and method based on DSRC - Google Patents

Intelligent vehicle map emerging system and method based on DSRC Download PDF

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CN106969779A
CN106969779A CN201710161021.5A CN201710161021A CN106969779A CN 106969779 A CN106969779 A CN 106969779A CN 201710161021 A CN201710161021 A CN 201710161021A CN 106969779 A CN106969779 A CN 106969779A
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map
main car
target vehicle
local
vehicle
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CN106969779B (en
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岑明
赵文旋
曾素华
田甄
任凡
喻佩
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Chongqing University of Post and Telecommunications
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/3453Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29Geographical information databases
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/025Services making use of location information using location based information parameters
    • H04W4/026Services making use of location information using location based information parameters using orientation information, e.g. compass

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Abstract

A kind of intelligent vehicle map emerging system based on DSRC and method is claimed in the present invention, and the system includes vehicle location, local map generation, DSRC communications, the screening of ADAS map interfaces, target vehicle and map Fusion Module.Vehicle localization module is used to obtain main truck position and posture;Local map generation module generates the corresponding local map in main car current location according to onboard sensor data;DSRC communication modules are used to receive the position, posture and local cartographic information that target vehicle is issued in communication range, while sending main car self-position, posture and local map;ADAS map interfaces module provides the agreement and interface for accessing ADAS maps;Target vehicle screening module screens the target vehicle that same road is in main car;Map Fusion Module merges the local map of main car and the target vehicle filtered out, generates the extension local map of main car.The present invention realizes that many vehicle perceptions are shared to extend environment sensing range, is favorably improved intelligent vehicle auxiliary driving/automatic Pilot performance.

Description

Intelligent vehicle map emerging system and method based on DSRC
Technical field
The invention belongs to automate, Communications And Computer technical field, and in particular to one kind be based on DSRC (Dedicated Short Range Communications, special short-distance wireless communication) intelligent vehicle map emerging system and method.
Background technology
Environment sensing is one of key technology of intelligent vehicle with map generation, and peace is driven in order to improve intelligent vehicle auxiliary Full early warning and the performance of automatic Pilot path planning, intelligent vehicle are needed with environment sensing scope as big as possible, but tradition Typically the onboard sensor of vehicle in itself is relied only in method so that the perception of vehicle is extremely limited.
Chinese patent application:Vehicular navigation system and automobile navigation method (application number:CN201010110837.3 it is) open A kind of onboard navigation system and automobile navigation method, the system are believed before vehicle sets out according to the real-time road of collection and map Breath planning vehicle makes evasive jam road and can not travel from the optimal global driving path of origin-to-destination.The party Method is a kind of macro approach, does not possess real-time safe early warning and local paths planning ability.Chinese patent application:One kind is based on The multilasered optical radar grating map emerging system (application number of pilotless automobile:CN201410252993.1 a kind of base) is disclosed In the multilasered optical radar grating map emerging system of pilotless automobile, the system is multiple installed in the different positions of vehicle by merging The laser radar data generation vehicle-periphery grating map put, solves the problem of intelligent vehicle collides with barrier. But this method is only the fusion of multisensor on same vehicle, the onboard sensor of vehicle in itself is substantially also to rely on, is felt Know that ability is equally limited.Chinese patent application:ADASIS extension information output apparatus and method (Shen based on safe driving map Please number:CN201510496628.X a kind of ADASIS extension information output apparatus based on safe driving map and side) are disclosed Road information, vehicle position information and the traffic route of track level are sent to wagon control application module by method, the system, are improved The perception of vehicle and control performance, the system are not directed to interaction and Multi-sensor Fusion between vehicle.Chinese patent application:Base In ADAS drive assist system (application number:CN201511010294.7 a kind of driving auxiliary system based on ADAS) is disclosed System, the system realizes that the sensor information between different vehicle is interacted by inter-vehicle communication technology, solves vehicle safety early warning model Enclose the problem of being limited by onboard sensor detection range.The system does not carry out Effective selection to interactive vehicle, have impact on interaction The effectiveness of information.Chinese patent application:Vehicle mobile terminals and its communication means (application number based on DSRC: CN201410397940.9), the system realizes the information between car and exterior vehicle and base station by the DSRC communication technologys Interaction, mainly including vehicle location, running status and traffic information, strengthens understanding of the vehicle driver to traffic information.This is Unite also without Effective selection is carried out to interactive vehicle to distinguish the validity of interactive information.
The present invention does not distinguish interactive information when being directed to existing intelligent vehicle environment sensing limited ability, vehicle information interaction Validity the problem of, it is proposed that a kind of intelligent vehicle map emerging system and method based on DSRC.Within the system, main car Local map information sharing with multiple target vehicles in communication range is realized by DSRC, according to each target vehicle position and ADAS cartographic informations screen effective target vehicle, and its local map is merged with main car local map, generation extension local map, So as to extend main car environment sensing scope, intelligent vehicle auxiliary driving/automatic Pilot performance is favorably improved.
The content of the invention
The deficiency of the present invention existing invention for more than, is passed to solve existing intelligent vehicle environment sensing ability by vehicle-mounted A kind of the problem of failing Effective selection interactive vehicle when the limitation of sensor, vehicle information interaction, it is proposed that intelligence based on DSRC Energy vehicle map emerging system and method effectively to extend intelligent vehicle environment sensing ability and auxiliary driving/automatic Pilot Energy.
Technical scheme is as follows:
A kind of intelligent vehicle map emerging system based on DSRC, it includes vehicle localization module, local map generation mould Block, DSRC communication modules, ADAS map interfaces module, target vehicle screening module and map Fusion Module, wherein:
Vehicle localization module is used for position and the attitude information that main car is obtained by mobile satellite location equipment;Local map is generated Module is used to detect main car surrounding environment by onboard sensor, according to sensor measurement data, generates main car current location pair The local map answered;DSRC communication modules are used to issue position of main car current time, posture and local cartographic information, receive simultaneously Target vehicle is issued in communication range self-position, posture and local cartographic information;ADAS map interfaces module is used to provide Access the agreement and interface of ADAS maps;Target vehicle screening module is used to pass through ADAS map interfaces according to main car current location Obtain main car and be currently located road Id numberings, numbered further according to road Id and filter out the target carriage that same road is in main car ;Map Fusion Module is used to, according to the position of main car and the target vehicle filtered out, posture and local cartographic information, carry out ground Figure fusion, generates the extension local map of main car.
Further, the vehicle localization module is gathered by mobile satellite location equipment and calculates main car in geographic coordinate system Under position Lk h=(xk h,yk h,zk h) and posture Pk h, wherein to be defined as vehicle heading just northern with geographic coordinate system for posture To angle;
Further, the form of the local map of the main car of the local map generation module generation and target vehicle is grid Lattice map.Local map is expressed as using current vehicle position as origin, and headstock direction is that y-axis is positive, a length of L, a width of W rectangle Region.Choose element grid of the specification for R*R and turn to n*m (n=L/R, m=W/R) individual grid, each grid by local map is discrete Lattice are s with a vector representationj h=(xj h,yj h,fj h)T, local map is expressed as with lattice vector sj hFor the matrix of element Gridh=[sj h]1,n*m, wherein xj h、yj hFor grid centre coordinate, fj hFor trellis states could, fj h=1 is occupies state, and representing should There are barrier, f at gridj h=0 is not occupy state.
Further, in the local map generation module, onboard sensor, which is detected and obtained in main car surrounding environment, to be hindered Hinder position and the dimension information of thing (vehicle, pedestrian and other barriers), each barrier is calculated in main car grating map coordinate system Hinder the grid region that thing is covered, a completely grid is not covered by one raster symbol-base of covering yet, and the grid zone that will be capped The trellis states could in domain is set to occupy state, sh i,j=1.The local grid map of generation is Mapk h={ L, W, Gridh}。
Further, the function of the DSRC communication modules includes transmission with receiving two parts, when the main car of transmission is current Carve position Lk h, posture Pk hWith local grid map Mapk h, while the self-position that target vehicle is issued in reception communication range, Posture and local grid map information, including target vehicle position lk o(i)=(xk o(i),yk o(i),zk o(i)), posture pk o(i) And local grid map mapk o(i)={ L, W, Grido(i)}。
Further, the target vehicle screening module passes through ADAS map interfaces according to main car and target vehicle position Module obtains main car and target vehicle is currently located road Id numberings, filters out the target vehicle that same road is in main car, Step includes:
(1) present road Id is inquired about:According to position L of main car current timek h, main car is obtained by ADAS map interfaces module It is currently located road Id numberings Idk h
(2) target vehicle is screened:To all target vehicles, according to target vehicle i current time position lk o(i), pass through ADAS map interfaces module obtains target vehicle i and is currently located road Id numberings idk o(i), if meeting idk o(i)=Idk h, then Retain vehicle i information, finally filter out the target vehicle that same road is in main car.
Further, the map Fusion Module merges the target vehicle local map filtered out with main car local map The step of generation extension local map, includes:
(1) according to each target vehicle position, posture and main truck position, posture, respectively calculate target vehicle coordinate system with Coordinate conversion parameter between main car coordinate system, including rotation parameter and translation parameters, by the local grid map of target vehicle Transform in main car coordinate system;
(2) based on main car current time local map, melt respectively with the target vehicle local grid map after conversion The extension local grid map for obtaining main car is closed, fusion rule is:Map overlapping region is carried out at grid fusion according to "or" Reason, splicing is carried out to Non-overlapping Domain.
A kind of intelligent vehicle map amalgamation method based on the system, it comprises the following steps:
(1) main truck position and attitude detection:In current time k, main car vehicle localization module is adopted by mobile satellite location equipment Collect and calculate position L of the k moment main car under geographic coordinate systemk h=(xk h,yk h,zk h) and posture Pk h, wherein posture definition For vehicle heading and geographic coordinate system direct north angle;
(2) local map is generated:Onboard sensor gathers the observation data of main car ambient condition information, when generating main car k The local grid map Map at quarterk h={ L, W, Gridh};
(3) DSRC module informations are sent with receiving:DSRC communication modules send position L of main car current timek h, posture Pk h With local grid map Mapk h, while with receiving the self-position of target vehicle issue in communication range, posture and local grid Figure information, if i-th of target vehicle position lk o(i)=(xk o(i),yk o(i),zk o(i)), posture is pk o(i), local grid Scheme mapk o(i)={ L, W, Grido(i) }, i ∈ [0, nk], nkFor target vehicle number in current time main car communication range;
(4) target vehicle is screened:Target vehicle screening module is first according to position L of main car current timek hBy ADAS Figure interface module obtains main car and is currently located road Id numberings Idk h, further according to each target vehicle i position lk o(i) pass through ADAS map interface modules obtain the target vehicle and are currently located road Id numberings idk o(i), if idk o(i)=Idk hThen retain Target vehicle i information, is otherwise deleted, until filtering out NkThe individual target vehicle that same road is in main car, wherein Nk≤ nk
(5) local grid map is merged:Map Fusion Module is with main car current time local grid map Mapk hBased on, By the N filtered outkThe local grid map map of individual target vehiclek o(i) main car coordinate system and and Map are transformed tok hFusion, generation The extension local grid map Map of main cark h_extern
Advantages of the present invention and have the beneficial effect that:
The present invention proposes a kind of intelligent vehicle map emerging system and method based on DSRC.On the one hand, this method passes through DSRC communicators issue main car self-position, posture and local cartographic information, receive target vehicle position, posture and partly Figure information and the local map for merging generation extension so that the shared of perception is realized between multiple vehicles, intelligence is extended Vehicle environmental sensing range;On the other hand, it is effective to what is merged according to each target vehicle position and the screening of ADAS cartographic informations Target vehicle, improves map fusion efficiencies.By the innovation and improvement in terms of two above, the present invention realizes many vehicle senses Know that ability is shared, effectively extend intelligent vehicle environment sensing scope, to improving intelligent vehicle auxiliary driving/automatic Pilot performance Significant and use value.
Brief description of the drawings
Fig. 1 is that the present invention provides intelligent vehicle map emerging system overall framework of the preferred embodiment based on DSRC;
Form and the coordinate system definition of Fig. 2 intelligent vehicle local maps of the present invention;
Intelligent vehicle map amalgamation method flow chart of Fig. 3 present invention based on DSRC;
Fig. 4 target vehicle screening technique flow charts of the present invention;
Fig. 5 map amalgamation method flow charts of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, detailed Carefully describe.Described embodiment is only a part of embodiment of the present invention.
The present invention solve above-mentioned technical problem technical scheme be:
The present invention proposes a kind of intelligent vehicle map emerging system and method based on DSRC, and the system and method pass through The DSRC communication technologys, realize effectively shared local map between main car and target vehicle, extend intelligent vehicle environment sensing model Enclose, and the effective target vehicle to merge is screened by ADAS cartographic informations, improve map fusion efficiencies.
The embodiment of the present invention is described below in conjunction with accompanying drawing and instantiation.
1st, it is as shown in Figure 1 a kind of overall frame of the intelligent vehicle map emerging system based on DSRC proposed by the present invention Frame.The system is by vehicle localization module, local map generation module, DSRC communication modules, ADAS map interfaces module, target carriage Screening module and map Fusion Module, wherein:
Vehicle localization module is used to obtain position of the main car under geographic coordinate system and posture letter by mobile satellite location equipment Breath;Local map generation module is used to detect main car surrounding environment by onboard sensor, according to sensor measurement data, generation The corresponding local map in main car current location;DSRC communication modules are used to issue position of main car current time, posture and partly Figure information, while receiving the self-position of target vehicle issue in communication range, posture and local cartographic information;ADAS maps connect Mouth mold block is used to provide the agreement and interface that access ADAS maps;Target vehicle screening module is used for logical according to main car current location Cross the main car of ADAS map interfaces acquisition and be currently located road Id numberings, filter out and be in together with main car further according to road Id numberings The target vehicle of one road;Map Fusion Module is used for position, posture and part according to main car and the target vehicle filtered out Cartographic information, carries out map fusion, generates the extension local map of main car.
2nd, form and the coordinate system definition of the intelligent vehicle local map that the present invention is used are illustrated in figure 2.Main car and mesh The form for marking the local map of vehicle is grating map.Local map is expressed as using current vehicle position as origin, headstock side To for y-axis it is positive, a length of L, a width of W rectangular area.Choose element grid of the specification for R*R and turn to n* by local map is discrete M (n=L/R, m=W/R) individual grid, each grid is s with a vector representationj h=(xj h,yj h,fj h)T, local map represents For with lattice vector sj hFor the matrix Grid of elementh=[sj h]1,n*m, wherein xj h、yj hFor the coordinate at grid center, round numbers, fj hFor trellis states could, fj h=1, to occupy state, represents there is barrier, f at the gridj h=0 is not occupy state.
3rd, a kind of intelligent vehicle map amalgamation method flow based on DSRC proposed by the present invention, the party are illustrated in figure 3 Method comprises the following steps:
(1) main truck position and attitude detection:In current time k, main car vehicle localization module is adopted by mobile satellite location equipment Collect and calculate position L of the k moment main car under geographic coordinate systemk h=(xk h,yk h,zk h) and posture Pk h, wherein posture definition For vehicle heading and geographic coordinate system direct north angle;
(2) local map is generated:Onboard sensor gathers the observation data of main car ambient condition information, when generating main car k The local grid map Map at quarterk h={ L, W, Gridh, wherein L is local map length, and W is local map width, Gridh= [sj h]1,n*mRepresent trellis states could;
(3) DSRC module informations are sent with receiving:DSRC communication modules send position L of main car current timek h, posture Pk h With local grid map Mapk h, while with receiving the self-position of target vehicle issue in communication range, posture and local grid Figure information, if i-th of target vehicle position lk o(i)=(xk o(i),yk o(i),zk o(i)), posture is pk o(i), local grid Scheme mapk o(i)={ L, W, Grido(i) }, i ∈ [0, nk], nkFor target vehicle number in current time main car communication range, Grido(i)=[sj o(i)]1,n*m, sj o(i)=(xj o(i),yj o(i),fj o(i))T, wherein xj o(i)、yj o(i) it is grid center Coordinate, fj o(i) it is trellis states could, fj o(i)=1 to occupy state, represent there is barrier, f at the gridj o(i)=0 it is not account for According to state.
(4) target vehicle is screened:Target vehicle screening module is first according to position L of main car current timek hBy ADAS Figure interface module obtains main car and is currently located road Id numberings Idk h, further according to each target vehicle i position lk o(i) pass through ADAS map interface modules obtain the target vehicle and are currently located road Id numberings idk o(i), if idk o(i)=Idk hThen retain Target vehicle i information, is otherwise deleted, until filtering out NkThe individual target vehicle that same road is in main car, wherein Nk≤ nk
(5) local grid map is merged:Map Fusion Module is with main car current time local grid map Mapk hBased on, By the N filtered outkThe local grid map map of individual target vehiclek o(i) main car coordinate system and and Map are transformed tok hFusion, generation The extension local grid map Map of main cark h_extern
4th, target vehicle screening technique flow of the present invention is illustrated in figure 4, is passed through according to main car and target vehicle position ADAS map interfaces module obtains main car and target vehicle is currently located road Id numberings, filters out and is in same road with main car Target vehicle, its step includes:
(1) obtain main car and be currently located road Id numberings:According to position L of main car current timek h, pass through ADAS map interfaces Module obtains main car and is currently located road Id numberings Idk h
(2) obtain target vehicle i and be currently located road Id numberings:According to target vehicle i current time position lk o(i), Target vehicle i is obtained by ADAS map interfaces module and is currently located road Id numberings idk o(i);
(3) target vehicle is screened:To target vehicle i, if meeting idk o(i)=Idk h, then target vehicle i letter is retained Breath, is otherwise deleted;
(4) repeat step (2)-(3), until to nkIndividual target vehicle is all screened, and obtains NkIt is individual to be in together with main car The target vehicle of one road, wherein Nk≤nk
5th, map amalgamation method flow of the present invention is illustrated in figure 5, the target vehicle local map filtered out is transformed into Main car coordinate system carries out map fusion, generates main car extension local map, and its step includes:
(1) target vehicle is calculated with main car coordinate conversion parameter:To target vehicle i, according to its position lk o(i)=(xk o (i),yk o(i),zk o(i)), posture pk o(i) and main car position Lk h=(xk h,yk h,zk h), posture Pk h, do not consider z-axis, calculate Coordinate conversion parameter between i coordinate system and main car coordinate system, including rotation parameter θ (i) and translation parameters Δ xk(i)、Δy (i):
(2) target vehicle local grid map transforms to main car coordinate system:According to rotation parameter θ (i) and translation parameters Δ xk(i), Δ y (i), by target vehicle i local grid map mapk o(i) transform in main car coordinate system, obtain mapk o-h(i) ={ L, W, Grido-h(i) }, wherein Grido-h(i)=[sj o-h(i)]1,n*m, sj o-h(i)=(xj o-h(i),yj o-h(i),fj o-h (i))T, xj o-h(i)、yj o-h(i) it is grid centre coordinate, round numbers, fj o(i) it is trellis states could, transformation relation is:
(3) main car is merged with target vehicle local map:With main car current time local map Mapk hBased on, with mapk o-h(i) merge, fusion rule is:Grid fusion treatment is carried out according to "or" to map overlapping region, to Non-overlapping Domain Carry out splicing.Merging flow is:To mapk o-h(i) Grid ino-h(i) each component sj o-h(i),
A. overlapping region judges:If there is Mapk hMiddle GridhComponent sl hMeet condition xj o-h(i)=xl hAnd yj o-h (i)=yl h, then sj o-h(i) grid represented belongs to overlapping region, otherwise belongs to Non-overlapping Domain;
B. overlapping region is merged:To overlapping region sj o-h(i) grid fusion treatment, is carried out according to "or", Map is updatedk hOn Corresponding trellis states could:
fl h=fl h fj o-h(i) (3)
C. Non-overlapping Domain is spliced:To Non-overlapping Domain sj o-h(i), it is appended to Mapk hGridhIn:
Gridh=[Gridh,sj o-h(i)] (3)
(4) repeat step (1)-(3), until to NkIndividual target vehicle is all merged, and the extension for obtaining main car is local Grating map Mapk h_extern
The above embodiment is interpreted as being merely to illustrate the present invention rather than limited the scope of the invention. After the content for the record for having read the present invention, technical staff can make various changes or modifications to the present invention, these equivalent changes Change and modification equally falls into the scope of the claims in the present invention.

Claims (5)

1. a kind of intelligent vehicle map emerging system based on DSRC, it is characterised in that including vehicle localization module, local map The special short-range wireless communication module of generation module, DSRC, ADAS Senior Officer's accessory system map interfaces module, target vehicle Screening module and map Fusion Module, wherein:The vehicle localization module, for obtaining main car on ground by mobile satellite location equipment Manage the position under coordinate system and attitude information;The local map generation module, for detecting main car week by onboard sensor Collarette border, according to sensor measurement data, generates the corresponding local map in main car current location;The DSRC communication modules, are used In issuing position of main car current time, posture and local cartographic information, at the same receive target vehicle issue in communication range from Body position, posture and local cartographic information;The ADAS map interfaces module, the agreement of ADAS maps is accessed for providing with connecing Mouthful;The target vehicle screening module, is currently located for obtaining main car by ADAS map interfaces according to main car current location Road Id is numbered, and is numbered further according to road Id and is filtered out the target vehicle that same road is in main car;The map fusion Module, for the position according to main car and the target vehicle filtered out, posture and local cartographic information, carries out map fusion, raw Into the extension local map of main car.
2. the intelligent vehicle map emerging system according to claim 1 based on DSRC, it is characterised in that it is described partly The main car and the form of the local map of target vehicle that figure generation module is generated are grating map, and local map is expressed as with vehicle Current location is origin, and headstock direction is that y-axis is positive, a length of L, a width of W rectangular area.Choose the unit grid that specification is R*R Lattice turn to n*m grid by local map is discrete, and n=L/R, m=W/R, each grid are s with a vector representationj h=(xj h, yj h,fj h)T, local map is expressed as with lattice vector sj hFor the matrix Grid of elementh=[sj h]1,n*m, wherein xj h、yj hFor grid Lattice centre coordinate, fj hFor trellis states could, fj h=1, to occupy state, represents there is barrier, f at the gridj h=0 is not occupy shape State.
3. a kind of intelligent vehicle map amalgamation method based on DSRC based on system described in claim 1 or 2, its feature exists In comprising the following steps:
(1) main truck position and attitude detection:In current time k, main car vehicle localization module is gathered simultaneously by mobile satellite location equipment Calculate position L of the k moment main car under geographic coordinate systemk h=(xk h,yk h,zk h) and posture Pk h, wherein posture is defined as car Travel direction and geographic coordinate system direct north angle;
(2) local map is generated:Onboard sensor gathers the observation data of main car ambient condition information, generates the main car k moment Local grid map Mapk h={ L, W, Gridh};
(3) DSRC module informations are sent with receiving:DSRC communication modules send position L of main car current timek h, posture Pk hAnd part Grating map Mapk h, while self-position, posture and the local grid map information of target vehicle issue in communication range are received, If i-th of target vehicle position lk o(i)=(xk o(i),yk o(i),zk o(i)), posture is pk o(i), local grid map mapk o (i)={ L, W, Grido(i) }, i ∈ [0, nk], nkFor target vehicle number in current time main car communication range;
(4) target vehicle is screened:Target vehicle screening module is first according to position L of main car current timek hConnect by ADAS maps Mouth mold block obtains main car and is currently located road Id numberings Idk h, further according to each target vehicle i position lk o(i) by ADAS Figure interface module obtains the target vehicle and is currently located road Id numberings idk o(i), if idk o(i)=Idk hThen retain target carriage I information, is otherwise deleted, until filtering out NkThe individual target vehicle that same road is in main car, wherein Nk≤nk
(5) local grid map is merged:Map Fusion Module is with main car current time local grid map Mapk hBased on, it will sieve The N selectedkThe local grid map map of individual target vehiclek o(i) main car coordinate system and and Map are transformed tok hFusion, generates main car Extension local grid map Mapk h_extern
4. the intelligent vehicle map amalgamation method according to claim 3 based on DSRC, it is characterised in that the target carriage Screening module passes through ADAS map interfaces module according to main car and target vehicle position and obtains main car and the current institute of target vehicle In road Id numberings, the target vehicle that same road is in main car is filtered out, its step includes:
(1) obtain main car and be currently located road Id numberings:According to position L of main car current timek h, pass through ADAS map interface modules Obtain main car and be currently located road Id numberings Idk h
(2) obtain target vehicle i and be currently located road Id numberings:According to target vehicle i current time position lk o(i), pass through ADAS map interfaces module obtains target vehicle i and is currently located road Id numberings idk o(i);
(3) target vehicle is screened:To target vehicle i, if meeting idk o(i)=Idk h, then retain target vehicle i information, it is no Then delete;
(4) repeat step (2)-(3), until to nkIndividual target vehicle is all screened, and obtains NkIt is individual to be in main car with along with The target vehicle on road, wherein Nk≤nk
5. the intelligent vehicle map amalgamation method according to claim 3 based on DSRC, it is characterised in that the map melts The target vehicle local map filtered out is transformed into main car coordinate system by matched moulds block, carries out map fusion, generates main car extension office Portion's map, its step includes:
(1) target vehicle is calculated with main car coordinate conversion parameter:To target vehicle i, according to its position lk o(i)=(xk o(i),yk o (i),zk o(i)), posture pk o(i) and main car position Lk h=(xk h,yk h,zk h), posture Pk h, do not consider z-axis, calculate i coordinate Coordinate conversion parameter between system and main car coordinate system, including rotation parameter θ (i) and translation parameters Δ xk(i)、Δy(i);
(2) target vehicle local grid map transforms to main car coordinate system:According to rotation parameter θ (i) and translation parameters Δ xk(i)、 Δ y (i), by target vehicle i local grid map mapk o(i) transform in main car coordinate system, obtain mapk o-h(i);
(3) main car is merged with target vehicle local map:With main car current time local map Mapk hBased on, with mapk o-h (i) merge, fusion rule is:Grid fusion treatment is carried out according to "or" to map overlapping region, Non-overlapping Domain is spelled Connect processing;
(4) repeat step (1)-(3), until to NkIndividual target vehicle is all merged, with obtaining the local grid of extension of main car Scheme Mapk h_extern
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Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108284838A (en) * 2018-03-27 2018-07-17 杭州欧镭激光技术有限公司 A kind of detecting system and detection method for detecting outside vehicle environmental information
CN108646752A (en) * 2018-06-22 2018-10-12 奇瑞汽车股份有限公司 The control method and device of automated driving system
CN108680176A (en) * 2018-05-16 2018-10-19 电子科技大学 A kind of generation method of blind man navigation avoidance map
CN109278752A (en) * 2018-09-26 2019-01-29 郑州轻工业学院 Plug-in hybrid-power automobile energy optimal control method based on cooperative sensing
CN109781129A (en) * 2019-01-28 2019-05-21 重庆邮电大学 A kind of road surface safety detection system and method based on inter-vehicular communication
CN109900490A (en) * 2017-12-11 2019-06-18 上海交通大学 State of motion of vehicle detection method and system based on autonomous type and cooperating type sensor
CN109993813A (en) * 2017-12-29 2019-07-09 长城汽车股份有限公司 Create method, apparatus, vehicle and the readable storage medium storing program for executing of map
CN110263607A (en) * 2018-12-07 2019-09-20 电子科技大学 A kind of for unpiloted road grade global context drawing generating method
CN110736474A (en) * 2018-07-18 2020-01-31 郑州宇通客车股份有限公司 Map information acquisition method and device for vehicles
CN110796852A (en) * 2019-11-07 2020-02-14 中南大学 Vehicle queue map building method and self-adaptive following distance calculation method thereof
CN110827541A (en) * 2019-11-08 2020-02-21 腾讯科技(深圳)有限公司 Information acquisition method, device, equipment and storage medium
CN110851545A (en) * 2018-07-27 2020-02-28 比亚迪股份有限公司 Map drawing method, device and equipment
CN111024095A (en) * 2018-10-09 2020-04-17 罗伯特·博世有限公司 Method for locating a vehicle
CN111160420A (en) * 2019-12-13 2020-05-15 北京三快在线科技有限公司 Map-based fault diagnosis method and device, electronic equipment and storage medium
CN111486853A (en) * 2019-01-28 2020-08-04 阿里巴巴集团控股有限公司 Electronic horizon generation method, device and related system
CN112344956A (en) * 2020-11-05 2021-02-09 腾讯科技(深圳)有限公司 Map display method and device
CN112414416A (en) * 2020-10-26 2021-02-26 高深智图(广州)科技有限公司 ADAS map data system based on four-level automatic driving high precision
WO2021168841A1 (en) * 2020-02-28 2021-09-02 华为技术有限公司 Positioning method and apparatus
CN113947937A (en) * 2021-10-29 2022-01-18 沈阳世纪高通科技有限公司 Road danger prompting technology based on vehicle sensor and dynamic traffic fusion
CN114018240A (en) * 2021-10-29 2022-02-08 广州小鹏自动驾驶科技有限公司 Map data processing method and device
US11313695B2 (en) * 2018-09-27 2022-04-26 Phiar Technologies, Inc. Augmented reality navigational indicator
US11448518B2 (en) 2018-09-27 2022-09-20 Phiar Technologies, Inc. Augmented reality navigational overlay

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102354449A (en) * 2011-10-09 2012-02-15 昆山市工业技术研究院有限责任公司 Internet of vehicles-based method for realizing image information sharing and device and system thereof
US20140136108A1 (en) * 2010-03-04 2014-05-15 Navteq B.V. Navigating on Images
CN105701479A (en) * 2016-02-26 2016-06-22 重庆邮电大学 Intelligent vehicle multi-laser radar fusion recognition method based on target features
CN105741546A (en) * 2016-03-18 2016-07-06 重庆邮电大学 Intelligent vehicle target tracking system through integration of road side equipment and vehicle sensor and method thereof
CN106485949A (en) * 2015-07-20 2017-03-08 德韧营运有限责任公司 The sensor fusion of the video camera for vehicle and V2V data

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140136108A1 (en) * 2010-03-04 2014-05-15 Navteq B.V. Navigating on Images
CN102354449A (en) * 2011-10-09 2012-02-15 昆山市工业技术研究院有限责任公司 Internet of vehicles-based method for realizing image information sharing and device and system thereof
CN106485949A (en) * 2015-07-20 2017-03-08 德韧营运有限责任公司 The sensor fusion of the video camera for vehicle and V2V data
CN105701479A (en) * 2016-02-26 2016-06-22 重庆邮电大学 Intelligent vehicle multi-laser radar fusion recognition method based on target features
CN105741546A (en) * 2016-03-18 2016-07-06 重庆邮电大学 Intelligent vehicle target tracking system through integration of road side equipment and vehicle sensor and method thereof

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
祝继华 等: "基于图像配准的栅格地图拼接方法", 《自动化学报》 *

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