CN109215372A - Road network information update method, device and equipment - Google Patents
Road network information update method, device and equipment Download PDFInfo
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- CN109215372A CN109215372A CN201811196662.5A CN201811196662A CN109215372A CN 109215372 A CN109215372 A CN 109215372A CN 201811196662 A CN201811196662 A CN 201811196662A CN 109215372 A CN109215372 A CN 109215372A
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- 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
- G08G1/096844—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route where the complete route is dynamically recomputed based on new data
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
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Abstract
This application discloses a kind of road network information update method, device and equipment, and wherein method includes: to determine current corresponding first tensor of target road section according to the driving trace of multiple vehicles of acquisition；According to the corresponding road net data of target road section, corresponding second tensor of target road section is determined；First tensor and the second tensor are inputted into preset network model, to determine whether the first tensor matches with the second tensor；If the first tensor does not match with the second tensor, according to the first tensor, processing is updated to the road net data of target road section.The application realizes the wheelpath by acquiring vehicle, it is detected automatically to whether road network information changes, and when road network information changes, automatically changed part is updated, so as to improve the update efficiency of road network information and can be shortened the period, convenience is brought for the trip of user.
Description
Technical field
This application involves technical field of information processing, in particular to a kind of road network information update method, device and equipment.
Background technique
With the progress of urbanization and the fast development of economy, road network information renewal rate is gradually increased.Currently, satisfying the need
When net information is updated, data are usually changed according to the road network of reporting of user to complete, due to the effect of reporting of user data
Rate is low, the period is long, so that road network information update be caused always not catch up with real road network change, influences user's trip.
Summary of the invention
The application provides a kind of road network information update method, device and equipment, believes in the related technology road network for solving
When breath is updated, since the low efficiency of reporting of user data, period are long, so that making road network information update does not always catch up with reality
Road network variation, influences the problem of user goes on a journey.
The application one side embodiment provides a kind of road network information update method, this method comprises: according to the multiple of acquisition
The driving trace of vehicle determines current corresponding first tensor of target road section；According to the corresponding road net data of the target road section,
Determine corresponding second tensor of the target road section；First tensor and second tensor are inputted into preset network mould
Whether type is matched with determination first tensor with second tensor；If first tensor and second tensor are not
Match, then according to first tensor, processing is updated to the road net data of the target road section.
The application another aspect embodiment provides a kind of road network information updating device, which includes: the first determining module,
For the driving trace according to multiple vehicles of acquisition, current corresponding first tensor of target road section is determined；Second determining module,
For determining corresponding second tensor of the target road section according to the corresponding road net data of the target road section；Judgment module is used
In first tensor and second tensor are inputted preset network model, with determination first tensor and described second
Whether tensor matches；Update module, if not matched for first tensor with second tensor, according to described first
Amount, is updated processing to the road net data of the target road section.
The another aspect embodiment of the application provides a kind of computer equipment, which includes: including memory, place
The computer program managing device and storage on a memory and can running on a processor, when the processor executes described program,
To realize road network information update method described in first aspect embodiment.
The computer readable storage medium of the application another further aspect embodiment, is stored thereon with computer program, the calculating
When machine program is executed by processor, to realize road network information update method described in first aspect embodiment.
The computer program of the application another further aspect embodiment, when the computer program is executed by processor, with reality
Road network information update method described in existing first aspect embodiment.
Technical solution disclosed in the present application, has the following beneficial effects:
First according to the driving trace of multiple vehicles of acquisition, current corresponding first tensor of target road section, and root are determined
According to the corresponding road net data of target road section, corresponding second tensor of target road section is determined, then by the first tensor and the second tensor
Input in preset network model, to determine whether the first tensor matches with the second tensor, when the first tensor and the second tensor not
Matching, then be updated processing according to road net data of first tensor to target road section.Hereby it is achieved that passing through acquisition vehicle
Wheelpath is detected automatically to whether road network information changes, and when road network information changes, automatically to generation
The part of variation is updated, and is the trip band of user so as to improve the update efficiency of road network information and can be shortened the period
Convenience is carried out.
The additional aspect of the application and advantage will be set forth in part in the description, and will partially become from the following description
It obtains obviously, or recognized by the practice of the application.
Detailed description of the invention
The application is above-mentioned and/or additional aspect and advantage will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, wherein
Fig. 1 is the flow diagram according to the road network information update method shown in the application one embodiment；
Fig. 2 is the driving trace schematic diagram of the multiple vehicles of acquisition illustrated according to the application；
Fig. 3 is the flow diagram according to the preset network model of generation shown in the application one embodiment；
Fig. 4 is the flow diagram that another implements the preset network model of generation exemplified according to the application；
Fig. 5 is that another implements the flow diagram of the road network information update method exemplified according to the application；
Fig. 6 is the structural schematic diagram according to the road network information updating device shown in the application one embodiment；
Fig. 7 is that another implements the structural schematic diagram of the road network information updating device exemplified according to the application；
Fig. 8 is the structural schematic diagram according to the computer equipment shown in the application one embodiment；
Fig. 9 is that another implements the structural schematic diagram of the computer equipment exemplified according to the application.
Specific embodiment
Embodiments herein is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to for explaining the application, and should not be understood as the limitation to the application.
Each embodiment of the application is directed in the related technology, when being updated to road network information, due to reporting of user data
Low efficiency, period are long, so that making road network information update does not always catch up with real road network change, influence asking for user's trip
Topic, proposes a kind of road network information update method.
The embodiment of the present application determines target road section current corresponding first according to the driving trace of multiple vehicles of acquisition
Tensor, and according to the corresponding road net data of target road section, determines corresponding second tensor of target road section, then by the first tensor and
Second tensor inputs in preset network model, determines whether the first tensor matches with the second tensor, when the first tensor and second
When tensor mismatches, then according to the first tensor, processing is updated to the road net data of target road section.Hereby it is achieved that passing through
The wheelpath for acquiring vehicle, is detected to whether road network information changes, and automatically when road network information changes,
Automatically changed part is updated, so as to improve the update efficiency of road network information and can be shortened the period, for
The trip at family brings convenience.
Below with reference to the accompanying drawings road network information update method, device and the equipment for describing the embodiment of the present application carry out specifically
It is bright.
Firstly, road network information updating method in the application is specifically described in conjunction with Fig. 1.
Fig. 1 is the flow diagram according to the road network information update method shown in the application one embodiment.
As shown in Figure 1, the embodiment of the present application road network information update method may comprise steps of:
Step 101, according to the driving trace of multiple vehicles of acquisition, current corresponding first tensor of target road section is determined.
Wherein, road network information update method provided by the embodiments of the present application, can be by calculating provided by the embodiments of the present application
Machine equipment executes.Wherein, road network information updating device is provided in computer equipment, to realize that the update to road network information carries out
Control.The present embodiment computer equipment can be any hardware device having data processing function, such as car-mounted terminal, electricity
Brain, personal digital assistant, smart phone etc..
In the present embodiment, multiple vehicles refer within a preset time, with all vehicles travelled in a road section.Wherein,
Preset time can carry out adaptability setting according to actual needs, for example, the predetermined time can be set to a week, fortnight,
One month, three months etc., it is not especially limited herein.
Wherein, target road section can be any section in practical road network, be not construed as limiting herein to it.
In the present embodiment, can be by global positioning system (Global Positioning System, abbreviation GPS), north
It struggles against satellite navigation system (BeiDou Navigation Satellite System, abbreviation BDS), alternatively, GLONASS satellite
Navigation system (GLOBAL NAVIGATION SATELLITE SYSTEM, abbreviation GLONASS) etc., obtains the traveling of multiple vehicles
Track, referring specifically to Fig. 2.It may include track display control as shown in Fig. 2, obtaining in the driving trace interface of multiple vehicles
Device 21 and pickup coordinate and search result display module 22 wherein can also include roaming, link in track display controller 21
The units such as track, path locus, vector query obtain the different driving trace information of vehicle to facilitate.
Wherein, due to the driving trace of multiple vehicles of acquisition include it is a plurality of, there is the traveling of some vehicles among these
Track mutually conflicts with the driving trace of other most of vehicles.For example, being obtained in target road section 9 in the driving trace of 10 vehicles
The driving direction of vehicle is all to travel from left to right, and another 1 vehicle is to travel from right to left, then illustrates the traveling rail of the vehicle
Mark is noise data, then can be rejected.
In this regard, the present embodiment can be weighted averaging to the driving trace of multiple vehicles of acquisition, average row is obtained
Track is sailed, so that corresponding first tensor of target road section is determined, to can not only effectively reject using the driving trace that is averaged
Undesirable driving trace, moreover it is possible to improve treatment effeciency.
Further, since every driving trace is all made of a series of data coordinates point, and each data coordinates
Different dimensions can be respectively corresponded, therefore the present embodiment can pass through analysis after the driving trace for getting multiple vehicles
Then the driving trace of multiple vehicles is worked as with determining target road section current driving direction and travel speed according to target road section
Preceding driving direction and travel speed determines value of each characteristic point in multiple dimensions in target road section, and according to each characteristic point
Value in multiple dimensions constructs corresponding first tensor.
Wherein, multiple dimensions may include: crossing attribute, line properties etc..For example, crossing attribute can be with are as follows: turn left,
Right-hand rotation, T-type crossing, crossroad, T-shaped road junction etc.；Line properties can be with are as follows: the lane quantity that includes, the direction of route,
Velocity interval of restriction etc..
Step 102, according to the corresponding road net data of the target road section, determine that the target road section is second corresponding
Amount.
In the road network information of actual use, it may include the corresponding road net data of different sections of highway.In this regard, the present embodiment can root
According to the identification information of target road section, corresponding road net data is obtained in road network information, then passes through the road net data to acquisition
It is analyzed, determines corresponding second tensor of target road section.
Wherein, the identification information of target road section can be section title, section geographic location etc..
Step 103, first tensor and second tensor are inputted into preset network model, with determination described first
Whether tensor matches with second tensor, if mismatching, thens follow the steps 104, no to then follow the steps 105.
Optionally, after determining the first tensor and the second tensor, the present embodiment can be by the first tensor and the second tensor
As input data, it is input to preset network model, by the algorithm in preset network model, determines the first tensor and
Whether two tensors match.It should be noted that preset network model in the present embodiment, will carry out in detail in the following embodiments
It describes in detail bright, it is not repeated excessively herein.
In the present embodiment, determine whether the first tensor matches with the second tensor, it can be by determining the first tensor and second
The characteristic point being had differences in tensor, and calculate the quantity and the quantity of total characteristic point in the first tensor of the characteristic point having differences
Ratio, the ratio is compared with threshold value then, determines whether the first tensor matches with the second tensor.
Wherein, if above-mentioned ratio is greater than threshold value, illustrate that the first tensor and the second tensor mismatch；If above-mentioned ratio is less than
Or be equal to threshold value, then illustrate that the first tensor is matched with the second tensor.
Above-mentioned threshold value can be adapted to according to the quantity of total characteristic point in actually determined first tensor and the second tensor
Property setting.For example, can be set a threshold to if the quantity of total characteristic point is 100 in the first tensor and the second tensor
5%, 10% etc., it is not construed as limiting herein.
That is, determining whether the first tensor matches with the second tensor in the present embodiment, comprising:
Determine the characteristic point being had differences in first tensor and second tensor quantity and first tensor
Whether the ratio of the quantity of middle total characteristic point is greater than threshold value.
For example, if threshold value be 5%, then by the first tensor and the second tensor be input to preset network model it
Afterwards, if calculating the number of total characteristic point in the quantity and the first tensor for the characteristic point having differences in the first tensor and the second tensor
The ratio of amount is 7%, it is determined that the first tensor and the second tensor mismatch.
Step 104, if first tensor does not match with second tensor, according to first tensor, to described
The road net data of target road section is updated processing.
Optionally, when the first tensor does not match with the second tensor, then illustrate the corresponding road of target road section in road network information
Network data is different from the real data of target road section, to carry out navigation behaviour according to the road net data of target road section in road network information
When making, the data for being easier to occur practical section are not consistent with navigation data, influence the normal trip of user.
In this regard, in order to enable user actually use road network information navigate etc. operation when, it is available to more acurrate
Road net data, the present embodiment can carry out the more corresponding road net data of target road section in road network information according to the first tensor
New processing.
Step 105, terminate.
It is understood that the embodiment of the present application passes through the driving trace of multiple vehicles, first of target road section is determined
Amount, and corresponding second tensor of target road section is obtained from road network information, and pass through of analysis the first tensor and the first tensor
With degree, determine whether the corresponding road net data of target road section changes, when a change, according to the first tensor to target road
The corresponding road net data of section is updated, to improve the subsequent reliability and accuracy used.
Road network information update method provided by the embodiments of the present application, first according to the driving trace of multiple vehicles of acquisition,
It determines current corresponding first tensor of target road section, and according to the corresponding road net data of target road section, determines that target road section is corresponding
The second tensor, then the first tensor and the second tensor are inputted in preset network model, to determine the first tensor and second
Whether tensor matches, when the first tensor and the second tensor mismatch, then according to the first tensor to the road net data of target road section into
Row update processing.Hereby it is achieved that being examined automatically by the wheelpath of acquisition vehicle to whether road network information changes
It surveys, and when road network information changes, changed part is updated automatically, so as to improve road network information
It updates efficiency and can be shortened the period, bring convenience for the trip of user.
Below with reference to Fig. 3, in the embodiment of the present application, the generating process of preset network model is described in detail.
As shown in figure 3, the preset network model of the embodiment of the present application can train in the following manner generation:
Step 301, according to road network history more new data, training sample is obtained, wherein including basis in the training sample
The corresponding road network original data of road network and corresponding driving trace that history driving trace updates.
In practical application, more new data can be carried out when being updated operation to the road net data in road network information
Storage operates access, analysis of more new data etc. so as to subsequent.It wherein, more may include quilt in road network information in new data
The road network original data of update, corresponding driving trace, renewal time, updated data etc..Therefore, the present embodiment can be from
In the history of record more new data, training sample is obtained.
Step 302, according to the road network original data and corresponding driving trace, construct respectively third tensor to be processed and
4th tensor.
Wherein, can be distinguished after getting road network original data and corresponding driving trace according to road network history more new data
Construct third tensor and the 4th tensor to be processed.
It should be noted that constructing the process of third tensor and the 4th tensor to be processed in the present embodiment, can specifically join
See the mode that above-described embodiment is recorded, it is not repeated excessively herein.
Step 303, using the third tensor and the 4th tensor as training data, the third tensor and the 4th tensor
It does not match as training result, initial network model is trained, to generate the preset network model.
Optionally, by using third tensor and the 4th tensor as input data, being input to initial network model, and according to
Third tensor and the 4th tensor do not match as training result, are repeatedly trained to initial network model, constantly adjustment original net
The corresponding weighted value of each computation layer in network model, so that initial network model after training is in input third tensor and the 4th
After amount, until can accurately exporting third tensor and the 4th unmatched result of tensor.Thus will be initial after the training
Network model is as preset network model.
It further, further include the updated data of road network, then to first as shown in figure 4, in the present embodiment in training sample
Beginning network model is trained, when generating preset network model, can with the following steps are included:
Step 401, according to the updated data of the road network and the road network original data, the third tensor and institute are determined
Each characteristic point is stated in the 4th tensor in the different information of multiple dimensions.
Due to having differences between the updated data of road network and road network original data, the present embodiment can be according to road network
Updated data and road network original data determine that each characteristic point is in the difference of multiple dimensions in third tensor and the 4th tensor
Information.
For example, in third tensor and the 4th tensor include 10 characteristic points, and above-mentioned 10 characteristic points be respectively at it is multiple
In dimension, such as multiple dimensions difference crossing attribute, line properties etc., i.e., [crossing attribute, line properties], then can be according to the
In three tensors each characteristic point respectively with character pair point in the 4th tensor, to dimension be crossing attribute, line properties respectively into
Row matching operation.If character pair point is in crossing attribute difference in arbitrary characteristics point and third tensor in the 4th tensor, root
It is that crossing attribute is different according to above-mentioned dimension, determines the crossing different information of arbitrary characteristics point in third tensor and the 4th tensor.
Step 402, using the third tensor and the 4th tensor as training data, the third tensor and the 4th tensor
In each characteristic point multiple dimensions different information be training result, the initial network model is trained, with generate
The preset network model.
That is, the present embodiment constructs third by obtaining training sample from road network history more new data respectively
Amount and the 4th tensor, and according to third tensor and the 4th tensor be training data, third tensor does not match with the 4th tensor is instruction
Practice as a result, being trained to initial network model, to generate preset network model.Further, construction third tensor and
After 4th tensor, it can also be determined every in third tensor and the 4th tensor according to the updated data of road network and road network original data
A characteristic point multiple dimensions different information, using third tensor and the 4th tensor as training data, third tensor and the 4th
Each characteristic point is training result in the different information of multiple dimensions in amount, is trained to initial network model, pre- to generate
If network model so that in practical application, can fast and accurately be identified according to the preset network model of generation
Whether the currently practical data of target road section match with road net data, to determine the corresponding road network of target road section according to matching result
Whether data, which need, updates, and improves the detection accuracy and timeliness of road network information variation.
By above-mentioned analysis it is found that the embodiment of the present application, which passes through, determines corresponding first tensor of target road section and second
Amount determines whether the first tensor matches with the second tensor to utilize preset network model, when mismatching, according to first
Amount is updated processing to the road net data of target road section.
In actual use, when the first tensor of target road section and the second tensor mismatch, in order to target road section
Road net data is accurately and effectively updated, can be first before the present embodiment is updated processing to the road net data of target road section
Different information of each characteristic point in multiple dimensions in the first tensor and the second tensor is first determined, then further according to different information
It carries out targetedly updating operation, to improve the update accuracy of road net data.Below with reference to Fig. 5, to the road of the application
The net information updating method above process is described in detail.
Fig. 5 is the flow diagram according to the road network information update method shown in the application further embodiment.
As shown in figure 5, the embodiment of the present application road network information update method may comprise steps of:
Step 501, according to the driving trace of multiple vehicles of acquisition, current corresponding first tensor of target road section is determined.
Step 502, according to the corresponding road net data of the target road section, determine that the target road section is second corresponding
Amount.
Step 503, first tensor and second tensor are inputted into preset network model, with determination described first
Whether tensor matches with second tensor, thens follow the steps 504 if mismatching, no to then follow the steps 506.
Wherein, step 501 is identical to step 103 as step 101 in above-described embodiment to step 503, does not make to it herein
Excessively repeat.Specific implementation process is referring to above-described embodiment.
Step 504, it according to the output of the preset network model, determines in first tensor and second tensor
Different information of each characteristic point in multiple dimensions.
Optionally, preset network model in the present embodiment, can be to each characteristic point in the different tensors of input more
The different information of a dimension, therefore after the first tensor and the second tensor are inputted preset network model, preset network mould
Type can analyze the first tensor and the second tensor, and export according to preset computation layer and corresponding weighted value
Different information of each characteristic point in multiple dimensions in first tensor and the second tensor.
Step 505, existed according to each characteristic point in first tensor and first tensor and second tensor
Different information in multiple dimensions is updated processing to the road net data of the target road section.
In the present embodiment, when the difference for determining multiple dimensions of each characteristic point in the first tensor and the second tensor is believed
After breath, computer equipment can be according to the first tensor, to multiple dimensions of each characteristic point in the first tensor and the second tensor
Different information be updated, i.e., processing is updated to the corresponding road net data of target road section, so that target road section pair
The road net data answered matches with real data, thus when user calls the road section information of the target road section again, Ke Yigeng
Accurately and reliably help user.
Step 506, terminate.
Road network information update method provided by the embodiments of the present application, when determining that the first tensor and the second tensor mismatch,
According to the output of preset network model, difference of each characteristic point in multiple dimensions in the first tensor and the second tensor is determined
Information, and the different information according to each characteristic point in the first tensor and the first tensor and the second tensor in multiple dimensions,
Processing is updated to the road net data of target road section.Hereby it is achieved that road network number is recognized accurately according to default network model
Processing is updated to road net data according to the different information with real data, and according to the different information of real data, is not only mentioned
The high update accuracy of road net data, moreover it is possible to improve and update efficiency, bring convenience for the trip of user.
In order to realize above-described embodiment, the application also proposed a kind of road network information updating device.
Fig. 6 is the structural schematic diagram according to the road network information updating device shown in the application one embodiment.
As shown in fig. 6, the embodiment of the present application road network information updating device includes: that the first determining module 11, second determines mould
Block 12, judgment module 13 and update module 14.
Wherein, the first determining module 11 is used for the driving trace of multiple vehicles according to acquisition, determines that target road section is current
Corresponding first tensor；
Second determining module 12 is used to determine that the target road section is corresponding according to the corresponding road net data of the target road section
The second tensor；
Judgment module 13 is used to first tensor and second tensor inputting preset network model, to determine
State whether the first tensor matches with second tensor；
If update module 14 is not matched with second tensor for first tensor, according to first tensor,
Processing is updated to the road net data of the target road section.
As a kind of optional implementation of the application, the judgment module 13 is specifically used for:
Determine the characteristic point being had differences in first tensor and second tensor quantity and first tensor
Whether the ratio of the quantity of middle total characteristic point is greater than threshold value.
As a kind of optional implementation of the application, first determining module 11, comprising:
First determines subelement, for the driving trace according to multiple vehicles of acquisition, determines that the target road section is current
Driving direction and travel speed；
Second determines subelement, for the driving direction and travel speed current according to the target road section, determine described in
Value of each characteristic point in multiple dimensions in target road section.
As a kind of optional implementation of the application, road network information updating device further include: obtain module, construction mould
Block, training module.
Wherein, module is obtained, for training sample being obtained, wherein the training sample according to road network history more new data
In include according to history driving trace update the corresponding road network original data of road network and corresponding driving trace；
Constructing module, for constructing third to be processed respectively according to the road network original data and corresponding driving trace
Tensor and the 4th tensor；
Training module, for using the third tensor and the 4th tensor as training data, the third tensor and described the
Four tensors do not match as training result, are trained to initial network model, to generate the preset network model.
As a kind of optional implementation of the application, in the training sample further include: the road network is updated
Data；
The present embodiment road network information updating device, further includes: third determining module.
Wherein, third determining module, for determining institute according to the updated data of the road network and the road network original data
Each characteristic point is stated in third tensor and the 4th tensor in the different information of multiple dimensions；
The training module, is specifically used for:
Using the third tensor and the 4th tensor as each spy in training data, the third tensor and the 4th tensor
Sign point is training result in the different information of multiple dimensions, is trained to the initial network model.
It should be noted that the aforementioned explanation to road network information updating method embodiment is also applied for the embodiment
Road network information updating device, realization principle is similar, and details are not described herein again.
Road network information updating device provided by the embodiments of the present application, first according to the driving trace of multiple vehicles of acquisition,
It determines current corresponding first tensor of target road section, and according to the corresponding road net data of target road section, determines that target road section is corresponding
The second tensor, then the first tensor and the second tensor are inputted in preset network model, to determine the first tensor and second
Whether tensor matches, when the first tensor and the second tensor mismatch, then according to the first tensor to the road net data of target road section into
Row update processing.Hereby it is achieved that being examined automatically by the wheelpath of acquisition vehicle to whether road network information changes
It surveys, and when road network information changes, changed part is updated automatically, so as to improve road network information
It updates efficiency and can be shortened the period, bring convenience for the trip of user.
Fig. 7 is that another implements the structural schematic diagram of the road network information updating device exemplified according to the application.
Referring to Fig. 7, the road network information updating device of the embodiment of the present application includes: that the first determining module 11, second determines mould
Block 12, judgment module 13, update module 14 and the 4th determining module 15.
Wherein, the first determining module 11 is used for the driving trace of multiple vehicles according to acquisition, determines that target road section is current
Corresponding first tensor；
Second determining module 12 is used to determine that the target road section is corresponding according to the corresponding road net data of the target road section
The second tensor；
Judgment module 13 is used to first tensor and second tensor inputting preset network model, to determine
State whether the first tensor matches with second tensor；
If update module 14 is not matched with second tensor for first tensor, according to first tensor,
Processing is updated to the road net data of the target road section.
As a kind of optional implementation of the application, the 4th determining module 15, for according to the preset network
The output of model determines that difference of each characteristic point in first tensor and second tensor in multiple dimensions is believed
Breath；
The update module 14, is specifically used for:
According to each characteristic point in first tensor and first tensor and second tensor in multiple dimensions
In different information, processing is updated to the road net data of the target road section.
The multiple dimension, comprising: crossing attribute, line properties.
It should be noted that the implementation process and technical principle of the road network information updating device of the present embodiment are referring to aforementioned right
The explanation of the road network information update method of first aspect embodiment, details are not described herein again.
Road network information updating device provided by the embodiments of the present application, when determining that the first tensor and the second tensor mismatch,
According to the output of preset network model, difference of each characteristic point in multiple dimensions in the first tensor and the second tensor is determined
Information, and the different information according to each characteristic point in the first tensor and the first tensor and the second tensor in multiple dimensions,
Processing is updated to the road net data of target road section.Hereby it is achieved that road network number is recognized accurately according to default network model
Processing is updated to road net data according to the different information with real data, and according to the different information of real data, is not only mentioned
The high update accuracy of road net data, moreover it is possible to improve and update efficiency, bring convenience for the trip of user.
In order to realize above-described embodiment, the application also proposes a kind of computer equipment.
Fig. 8 is the structural schematic diagram according to the computer equipment shown in one exemplary embodiment of the application.The meter that Fig. 8 is shown
Calculating machine equipment is only an example, should not function to the embodiment of the present application and use scope bring any restrictions.
As shown in figure 8, above-mentioned computer equipment 200 includes: memory 210, processor 220 and is stored in memory 210
Computer program that is upper and can running on processor 220, when the processor 220 executes described program, with first aspect reality
Apply road network information update method described in example.
In a kind of optional way of realization, as shown in figure 9, the computer equipment 200 can also include: memory 210
And processor 220, the bus 230 of different components (including memory 210 and processor 220) is connected, memory 210 is stored with meter
Calculation machine program realizes road network information update method described in the embodiment of the present application when processor 220 executes described program.
Bus 230 indicates one of a few class bus structures or a variety of, including memory bus or Memory Controller,
Peripheral bus, graphics acceleration port, processor or the local bus using any bus structures in a variety of bus structures.It lifts
For example, these architectures include but is not limited to industry standard architecture (ISA) bus, microchannel architecture (MAC)
Bus, enhanced isa bus, Video Electronics Standards Association (VESA) local bus and peripheral component interconnection (PCI) bus.
Computer equipment 200 typically comprises a variety of computer equipment readable mediums.These media can be it is any can
The usable medium accessed by computer equipment 200, including volatile and non-volatile media, moveable and immovable Jie
Matter.
Memory 210 can also include the computer system readable media of form of volatile memory, such as arbitrary access
Memory (RAM) 240 and/or cache memory 250.Computer equipment 200 may further include that other are removable/no
Movably, volatile/non-volatile computer system storage medium.Only as an example, storage system 260 can be used for reading and writing
Immovable, non-volatile magnetic media (Fig. 9 do not show, commonly referred to as " hard disk drive ").It, can although being not shown in Fig. 9
To provide the disc driver for reading and writing to removable non-volatile magnetic disk (such as " floppy disk "), and it is non-volatile to moving
Property CD (such as CD-ROM, DVD-ROM or other optical mediums) read and write CD drive.In these cases, each drive
Dynamic device can be connected by one or more data media interfaces with bus 230.Memory 210 may include at least one journey
Sequence product, the program product have one group of (for example, at least one) program module, these program modules are configured to perform this Shen
Please each embodiment function.
Program/utility 280 with one group of (at least one) program module 270, can store in such as memory
In 210, such program module 270 include --- but being not limited to --- operating system, one or more application program, other
It may include the realization of network environment in program module and program data, each of these examples or certain combination.Journey
Sequence module 270 usually executes function and/or method in embodiments described herein.
Computer equipment 200 can also be with one or more external equipments 290 (such as keyboard, sensing equipment, display
291 etc.) it communicates, the equipment interacted with the computer equipment 200 communication can be also enabled a user to one or more, and/or
(such as network interface card is adjusted with enabling the computer equipment 200 and one or more other to calculate any equipment that equipment are communicated
Modulator-demodulator etc.) communication.This communication can be carried out by input/output (I/O) interface 292.Also, computer equipment
200 can also by network adapter 293 and one or more network (such as local area network (LAN), wide area network (WAN) and/or
Public network, such as internet) communication.As shown, network adapter 293 passes through its of bus 230 and computer equipment 200
He communicates module.It should be understood that although not shown in the drawings, other hardware and/or software can be used in conjunction with computer equipment 200
Module, including but not limited to: microcode, device driver, redundant processing unit, external disk drive array, RAID system, magnetic
Tape drive and data backup storage system etc..
It should be noted that the implementation process and technical principle of the computer equipment of the present embodiment are referring to aforementioned to first party
The explanation of the road network information update method of face embodiment, details are not described herein again.
Computer equipment provided by the embodiments of the present application determines mesh first according to the driving trace of multiple vehicles of acquisition
Current corresponding first tensor in section is marked, and according to the corresponding road net data of target road section, determines target road section corresponding second
Then tensor inputs the first tensor and the second tensor in preset network model, be with the second tensor with determining first tensor
No matching is then updated according to road net data of first tensor to target road section when the first tensor and the second tensor mismatch
Processing.Hereby it is achieved that detected automatically by the wheelpath of acquisition vehicle to whether road network information changes, and
When road network information changes, changed part is updated automatically, so as to improve the update of road network information
It efficiency and can be shortened the period, bring convenience for the trip of user.
To achieve the above object, the application also proposes a kind of computer readable storage medium.
The wherein computer readable storage medium, is stored thereon with computer program, when which is executed by processor, with
Realize road network information update method described in first aspect embodiment.
In a kind of optional way of realization, the present embodiment can be using any group of one or more computer-readable media
It closes.Computer-readable medium can be computer-readable signal media or computer readable storage medium.It is computer-readable to deposit
Storage media for example may be-but not limited to-system, device or the device of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor
Part, or any above combination.The more specific example (non exhaustive list) of computer readable storage medium includes: to have
The electrical connection of one or more conducting wires, portable computer diskette, hard disk, random access memory (RAM), read-only memory
(ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-
ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.In this document, computer-readable storage
Medium can be any tangible medium for including or store program, which can be commanded execution system, device or device
Using or it is in connection.
Computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including --- but
It is not limited to --- electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be
Any computer-readable medium other than computer readable storage medium, which can send, propagate or
Transmission is for by the use of instruction execution system, device or device or program in connection.
The program code for including on computer-readable medium can transmit with any suitable medium, including --- but it is unlimited
In --- wireless, electric wire, optical cable, RF etc. or above-mentioned any appropriate combination.
The computer for executing operation of the present invention can be write with one or more programming languages or combinations thereof
Program code, described program design language include object oriented program language-such as Java, Smalltalk, C++,
Further include conventional procedural programming language-such as " C " language or similar programming language.Program code can be with
It fully executes, partly execute on the user computer on the user computer, being executed as an independent software package, portion
Divide and partially executes or executed on a remote computer or server completely on the remote computer on the user computer.?
Be related in the situation of remote computer, remote computer can pass through the network of any kind --- including local area network (LAN) or
Wide area network (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (such as mentioned using Internet service
It is connected for quotient by internet).
To achieve the above object, the application also proposes a kind of computer program.Wherein when computer program is held by processor
When row, to realize road network information update method described in first aspect embodiment.
In this application unless specifically defined or limited otherwise, the terms such as term " setting ", " connection " should do broad sense reason
Solution, for example, it may be mechanical connection, is also possible to be electrically connected；It can be directly connected, the indirect phase of intermediary can also be passed through
Even, the connection inside two elements or the interaction relationship of two elements be can be, unless otherwise restricted clearly.For this
For the those of ordinary skill in field, the concrete meaning of above-mentioned term in this application can be understood as the case may be.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is contained at least one embodiment or example of the application.
In addition, term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the application includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, to execute function, this should be by the application
Embodiment person of ordinary skill in the field understood.
It should be appreciated that each section of the application can be realized with hardware, software, firmware or their combination.Above-mentioned
In embodiment, software that multiple steps or method can be executed in memory and by suitable instruction execution system with storage
Or firmware is realized.It, and in another embodiment, can be under well known in the art for example, if realized with hardware
Any one of column technology or their combination are realized: having a logic gates for realizing logic function to data-signal
Discrete logic, with suitable combinational logic gate circuit specific integrated circuit, programmable gate array (PGA), scene
Programmable gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
Storage medium mentioned above can be read-only memory, disk or CD etc..Although having been shown and retouching above
Embodiments herein is stated, it is to be understood that above-described embodiment is exemplary, and should not be understood as the limit to the application
System, those skilled in the art can be changed above-described embodiment, modify, replace and become within the scope of application
Type.
Claims (11)
1. a kind of road network information update method characterized by comprising
According to the driving trace of multiple vehicles of acquisition, current corresponding first tensor of target road section is determined；
According to the corresponding road net data of the target road section, corresponding second tensor of the target road section is determined；
First tensor and second tensor are inputted into preset network model, with determination first tensor and described the
Whether two tensors match；
If first tensor does not match with second tensor, according to first tensor, to the road of the target road section
Network data is updated processing.
2. the method as described in claim 1, which is characterized in that stating the first tensor and second tensor described in the determination is
No matching, comprising:
It determines total in the quantity and first tensor for the characteristic point being had differences in first tensor and second tensor
Whether the ratio of the quantity of characteristic point is greater than threshold value.
3. the method as described in claim 1, which is characterized in that the road net data to the target road section is updated place
Before reason, further includes:
According to the output of the preset network model, each characteristic point in first tensor and second tensor is determined
Different information in multiple dimensions；
The road net data to the target road section is updated processing, comprising:
According to each characteristic point in first tensor and first tensor and second tensor in multiple dimensions
Different information is updated processing to the road net data of the target road section.
4. method as claimed in claim 3, which is characterized in that the multiple dimension, comprising: crossing attribute, line properties.
5. the method as described in claim 1-4 is any, which is characterized in that the preset network model is in the following manner
What training generated, comprising:
According to road network history more new data, training sample is obtained, wherein including according to history driving trace in the training sample
The corresponding road network original data of the road network of update and corresponding driving trace；
According to the road network original data and corresponding driving trace, third tensor and the 4th tensor to be processed are constructed respectively；
It is trained for not matched as training data, the third tensor with the 4th tensor using the third tensor and the 4th tensor
As a result, being trained to initial network model, to generate the preset network model.
6. method as claimed in claim 5, which is characterized in that in the training sample further include: the road network is updated
Data；
It is described the initial network model is trained before, further includes:
According to the updated data of the road network and the road network original data, determine in the third tensor and the 4th tensor
Different information of each characteristic point in multiple dimensions；
It is described that the initial network model is trained, comprising:
Using the third tensor and the 4th tensor as each characteristic point in training data, the third tensor and the 4th tensor
It is training result in the different information of multiple dimensions, the initial network model is trained.
7. the method as described in claim 1-4 is any, which is characterized in that the traveling rail of multiple vehicles according to acquisition
Mark determines current corresponding first tensor of target road section, comprising:
According to the driving trace of multiple vehicles of acquisition, the target road section current driving direction and travel speed are determined；
According to the target road section current driving direction and travel speed, determine that each characteristic point is multiple in the target road section
Value in dimension.
8. a kind of road network information updating device characterized by comprising
First determining module determines target road section current corresponding first for the driving trace according to multiple vehicles of acquisition
Tensor；
Second determining module, for according to the corresponding road net data of the target road section, determining the target road section corresponding the
Two tensors；
Judgment module, for will first tensor and the preset network model of second tensor input, with determination described the
Whether one tensor matches with second tensor；
Update module, if not matched for first tensor with second tensor, according to first tensor, to described
The road net data of target road section is updated processing.
9. a kind of computer equipment, which is characterized in that on a memory and can be in processor including memory, processor and storage
The computer program of upper operation, when the processor executes described program, to realize road network as claimed in claim 1
Information updating method.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
When execution, to realize road network information update method as claimed in claim 1.
11. a kind of computer program, which is characterized in that when the computer program is executed by processor, to realize such as right
It is required that any road network information update method of 1-7.
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