CN106934107A - Traffic trip scenario building method, device, equipment and storage medium - Google Patents
Traffic trip scenario building method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN106934107A CN106934107A CN201710089333.XA CN201710089333A CN106934107A CN 106934107 A CN106934107 A CN 106934107A CN 201710089333 A CN201710089333 A CN 201710089333A CN 106934107 A CN106934107 A CN 106934107A
- Authority
- CN
- China
- Prior art keywords
- traffic trip
- traffic
- vehicle
- trip
- regions
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The invention discloses traffic trip scenario building method, device, equipment and storage medium, wherein method includes:Obtain real city road network data;Obtain real traffic trip sample data;Traffic trip sample data according to getting determines traffic trip model;According to city road network data and traffic trip model, required traffic trip scene is simulated.Using scheme of the present invention, the traffic trip scene for meeting truth can be constructed.
Description
【Technical field】
The present invention relates to Computer Applied Technology, more particularly to traffic trip scenario building method, device, equipment and storage
Medium.
【Background technology】
Modern Urban Development speed is more and more faster, and incident traffic problems are also increasingly severe, population and vehicle number
Amount is constantly soaring, but city space and finite capacity, it is impossible to the newly-built road and means of transportation of no maximum, traffic congestion into
It is the significant problem of urban development.
Therefore, it is necessary to consider in the case of not newly-built road and means of transportation, how to mitigate friendship otherwise
Logical congestion problems, that is, consider that new and potential communications and transportation solution is inevitable development trend.
Such as, automatic driving vehicle is introduced, but because automatic driving vehicle is emerging technology in recent years, is introduced into
After in traffic trip scene, for influenceing or unknown for traffic, so it is preferred that needing based on simulation (structure
Build) the traffic trip scene that goes out is estimated in advance.
In the prior art, generally all it is to travel rule according to some rules such as road conditions and vehicle of artificial setting
To simulate traffic trip scene, generally there is very big deviation with real traffic trip scene, subsequently commented so as to have impact on
Estimate the accuracy of result.
【The content of the invention】
In view of this, the invention provides traffic trip scenario building method, device, equipment and storage medium, being capable of structure
Build out the traffic trip scene for meeting truth.
Concrete technical scheme is as follows:
A kind of traffic trip scenario building method, including:
Obtain real city road network data;
Obtain real traffic trip sample data;
Traffic trip sample data according to getting determines traffic trip model;
According to the city road network data and the traffic trip model, required traffic trip scene is simulated.
A kind of traffic trip scenario building device, including:First acquisition unit, second acquisition unit and analogue unit;
The first acquisition unit, for obtaining real city road network data, is sent to the analogue unit;
The second acquisition unit, for obtaining real traffic trip sample data, and goes out according to the traffic for getting
Row sample data determines traffic trip model, is sent to the analogue unit;
The analogue unit, needed for for according to the city road network data and the traffic trip model, simulating
Traffic trip scene.
A kind of computer equipment, including memory, processor and storage are on the memory and can be in the processor
The computer program of upper operation, realizes method as described above during the computing device described program.
A kind of computer-readable recording medium, is stored thereon with computer program, and described program is when executed by reality
Existing method as described above.
Be can be seen that using scheme of the present invention based on above-mentioned introduction, can according to real city road network data and
According to the traffic trip model that real traffic trip sample data is determined, required traffic trip scene is simulated, so that
Compared to prior art, can more be met the traffic trip scene of truth.
【Brief description of the drawings】
Fig. 1 is the flow chart of traffic trip scenario building embodiment of the method for the present invention.
Fig. 2 is the composition structural representation of traffic trip scenario building device embodiment of the present invention.
Fig. 3 shows the block diagram for being suitable to the exemplary computer system/server 12 for realizing embodiment of the present invention.
【Specific embodiment】
In order that technical scheme is clearer, clear, develop simultaneously embodiment referring to the drawings, to institute of the present invention
The scheme of stating is described in further detail.
Fig. 1 is the flow chart of traffic trip scenario building embodiment of the method for the present invention, as shown in figure 1, including following
Specific implementation.
In 101, real city road network data are obtained.
In scheme of the present invention, the simulation for traffic all uses real city road network data, including height
Speed, major trunk roads, gateway, small internal road etc., in addition, in addition it is also necessary to including various traffic key elements, as urban transportation includes
Traffic sign, traffic lights, restricted driving, speed limit etc. are consistent with real scene.
How real city road network data are obtained for prior art.
In 102, real traffic trip sample data is obtained.
Traffic trip sample data, typically refers to the traffic trip sample data of vehicle.
How obtaining traffic trip sample data can be decided according to the actual requirements, such as, can be obtained from taxi company
The traffic trip sample data of taxi, or, the traffic trip sample of taxi and private car etc. is obtained by Baidu map
Notebook data.
Be may include in every traffic trip sample data:Travel time, starting point, terminal, path etc..
Whole urban area can be divided into M sub-regions in advance, M is the positive integer more than, and specific value can basis
Depending on being actually needed, how dividing all subregion can equally be decided according to the actual requirements.
Correspondingly, the corresponding traffic trip sample data of every sub-regions can respectively be obtained.
Such as, for a sub-regions a, can obtain in nearest one day, go to other subregions from the subregion
Traffic trip sample data, the starting point in the corresponding traffic trip sample datas of subregion a needs to be located in subregion a.
So, the corresponding traffic trip sample data of subregion a can be:Taxi b (is located in the * * times from * *
In subregion a) set out, in the * * times with reaching * * (be located at subregion c in), path is * *.
Traffic trip sample data is the data from the sample survey of true traffic trip data, traffic trip sample data with it is true
The ratio of traffic trip data can not differ too greatly different, and the otherwise sampling would become hard to represent the feature of entirety, traffic trip sample
The particular number of data can be decided according to the actual requirements.
In 103, traffic trip model is determined according to the traffic trip sample data for getting.
The traffic trip demand occurred in every sub-regions can be regarded as a Poisson process, can be according to every sub-regions
Corresponding traffic trip sample data, determines the traffic trip event that every sub-regions occur in different time sections respectively
Number, will determine traffic trip need assessment result of the result as every sub-regions in different time sections.
Regard the traffic trip demand occurred in different subregions as a Poisson process, in time interval [t, t+ τ]
The probability distribution of the number of the traffic trip event of generation is:
Can be according to prior art, by the traffic trip sample data of the corresponding different time sections of every sub-regions, difference
Determine that every sub-regions correspond to the parameter lambda of different time sections, the specific duration τ of each time period can according to actual needs and
It is fixed.
Such as, can be according to subregion a corresponding late 6:00~6:The traffic trip sample data of 30 this time period, that is, go out
The hair time is located at 6:00~6:The traffic trip sample data of 30 this time period, determines that subregion a corresponds to evening 6:00~
6:The parameter lambda of 30 this time period, and then according to above-mentioned probability distribution formula subregion a can be determined in evening 6:00~6:30
The number of the traffic trip event occurred in this time period, and result can will be determined as subregion a in evening 6:00~6:30
Traffic trip need assessment result in this time period.
In the manner described above, traffic trip need assessment knot of every sub-regions in different time sections can be respectively obtained
Really.
Also, for each traffic trip need assessment result, can further discriminate between out and wherein go to different subregions
Trip requirements number.
Such as, subregion a corresponding late 6:00~6:The traffic trip sample data of 30 this time period has four, its
In two go to subregion c, two other goes to subregion d, both ratios be 1:1, then then it is believed that subregion a is in evening
6:00~6:It is identical with the trip requirements number for going to subregion d that subregion c is gone in 30 this time period.
In addition, above-mentioned traffic trip need assessment result is determined according to the traffic trip sample data of sampling, it is
Make it closer to truth, each traffic trip demand can also be commented according to the traffic flow information of the key crossing for getting
Estimate result to be modified.
Specifically, can be regarded by being arranged on the magnitude of traffic flow of the different time sections that the camera of each key crossing is photographed
Frequently, the traffic flow information of each key crossing is analyzed.
Such as, determined in evening 6 by analysis:00~6:Pass through under international trade bridge in 30 this time period, from east to west
The vehicle number of traveling is 100, and according to the traffic trip sample data for getting, is analyzed in evening 6:00~6:30 this time
Pass through under international trade bridge in section, the vehicle number for travelling from east to west is 20, so as to understand that true analysis result is sample analysis knot
5 times of fruit;Similarly, be can determine that in evening 6 by analysis:00~6:Pass through under the bridge of Xue Zhi in 30 this time period, from east
The vehicle number for westwards travelling is 90, and according to the traffic trip sample data for getting, is analyzed in evening 6:00~6:30 this
Pass through under the bridge of Xue Zhi in time period, the vehicle number for travelling from east to west is 15, so as to understand that true analysis result is sample point
6 times of analysis result;…;After the corresponding multiple of each key crossing is respectively obtained, can be averaging, according to calculating
Average to all subregion evening 6:00~6:Traffic trip need assessment result in 30 this time period is modified, that is, use
Traffic trip need assessment result is multiplied by the average for calculating, correspondingly, can also be in each traffic trip need assessment result
Trip requirements number toward different subregions is modified.
Certainly, the above mode by way of example only, the technical scheme being not intended to limit the invention, except aforesaid way
Outward, can also use those skilled in the art it is conceivable that other any-modes, as long as traffic trip need assessment can be made
Result is consistent as much as possible with truth.
In 104, according to city road network data and traffic trip model, required traffic trip scene is simulated.
After by the treatment in 101~103, you can according to city road network data and revised each traffic trip need
Assessment result etc. is sought, required traffic trip scene is simulated.
Introduction based on before understands, according to revised each traffic trip need assessment result etc., it is to be understood that different
Traffic trip conditions of demand in time period, different subregions, i.e. how many vehicle need wherefrom where etc., accordingly
Ground, can according to the actual requirements, and region and time segment information if desired for simulation etc. simulate required traffic trip scene.
Such as, international trade Region in Late 6 is simulated:00~6:30 traffic trip scene, how to be simulated is prior art.
As can be seen that using scheme of the present invention, can be according to real city road network data and according to real friendship
The traffic trip model that pass-out row sample data is determined, simulates required traffic trip scene, so as to compared to existing skill
Art can more be met the traffic trip scene of truth.
On this basis, vehicle to be assessed can be also added in the traffic trip scene for simulating, and then evaluates and treat
Influence of the assessment vehicle to traffic.
Vehicle to be assessed can be automatic driving vehicle.
In future, if automatic driving vehicle is added in real traffic trip scene, there can be various advantages, than
Such as:
Automatic driving vehicle can be as mass transportation facilities, and the efficiency of its positioning and scheduling is far above taxi, can be with
Effectively solve the problems, such as public trip;
Automatic driving vehicle, beneficial to shared trip, is easy to scheduling as mass transportation facilities, and road surface car can be greatly decreased
Quantity, and improve ride quality;
After passenger is sent into specified location, with automatic parking to position farther out, or carrying can be continued, it is adaptable to down town
The less gold area in parking stall;
Automatic driving vehicle can avoid the traffic accident produced because of mistake, so as to accident rate can be reduced, reduce
The congestion produced by accident;
Automatic driving vehicle is observant of traffic rules, and the traffic caused because of not observing traffic rules and regulations can be avoided to gather around
It is stifled.
In actual applications, automatic driving vehicle can be added to the traffic trip for simulating according to Different Strategies respectively
Jing Zhong, so as to evaluate influence of the automatic driving vehicle to traffic under Different Strategies respectively.
Such as, the random part renting car picked out in traffic trip scene can be replaced with automatic driving vehicle, nobody
Vehicle is driven after passenger is sent into specified location, its automatic parking of schedulable to position farther out, or continuation carrying etc., evaluate
Replace the influence to traffic.
For another example, thus it is possible to vary add (replace as described above) to the quantity of the automatic driving vehicle in traffic trip scene,
And influence of the varying number to traffic is evaluated respectively.
In a word, being added to automatic driving vehicle using which kind of strategy can be according to actual test need in traffic trip scene
Depending on asking.
The traffic trip scene for simulating can be directed to, compares traffic index and the addition added before automatic driving vehicle
Traffic index after automatic driving vehicle, so as to obtain improvement situation of the automatic driving vehicle for traffic.
Improve situation according to corresponding traffic is distinguished under Different Strategies, it is known that being driven using nobody in which way
Vehicle is sailed, the advantage of automatic driving vehicle can be preferably played, this tool that puts into effect for follow-up automatic driving vehicle
There is important meaning.
Above is the introduction on embodiment of the method, below by way of device embodiment, enters to advance to scheme of the present invention
One step explanation.
Fig. 2 is the composition structural representation of traffic trip scenario building device embodiment of the present invention, as shown in Fig. 2
Including:First acquisition unit 201, second acquisition unit 202 and analogue unit 203.
First acquisition unit 201, for obtaining real city road network data, is sent to analogue unit 203;
Second acquisition unit 202, for obtaining real traffic trip sample data, and according to the traffic trip for getting
Sample data determines traffic trip model, is sent to analogue unit 203;
Analogue unit 203, for according to city road network data and traffic trip model, simulating required traffic trip
Scene.
Second acquisition unit 201 can respectively obtain the corresponding traffic trip sample data of every sub-regions, wherein, in advance will
Whole urban area is divided into M sub-regions, and M is the positive integer more than.
The traffic trip demand occurred in every sub-regions can be regarded as a Poisson process by second acquisition unit 202,
According to the corresponding traffic trip sample data of every sub-regions, determine what every sub-regions occurred in different time sections respectively
The number of traffic trip event, will determine traffic trip need assessment knot of the result as every sub-regions in different time sections
Really.
For each traffic trip need assessment result, the trip for wherein going to different subregions can be also further discriminated between out
Demand number.
In addition, above-mentioned traffic trip need assessment result is determined according to the traffic trip sample data of sampling, it is
Make it closer to truth, each traffic trip demand can also be commented according to the traffic flow information of the key crossing for getting
Estimate result to be modified.
I.e. second acquisition unit 202 can be further used for, according to the traffic flow information of the key crossing for getting, point
It is other that each traffic trip need assessment result is modified.
Correspondingly, analogue unit 203 can be according to city road network data and revised each traffic trip need assessment knot
Really, required traffic trip scene is simulated.
On this basis, can also be added to vehicle to be assessed in traffic trip scene by analogue unit 203, evaluate to be evaluated
Estimate influence of the vehicle to traffic.
Vehicle to be assessed can be automatic driving vehicle.
In actual applications, vehicle to be assessed can be added to traffic trip by analogue unit 203 according to Different Strategies respectively
In scene, influence of the vehicle to be assessed to traffic under Different Strategies is evaluated respectively.
The specific workflow of Fig. 2 shown device embodiments refer to the respective description in preceding method embodiment, herein
Repeat no more.
Fig. 3 shows the block diagram for being suitable to the exemplary computer system/server 12 for realizing embodiment of the present invention.
The computer system/server 12 that Fig. 3 shows is only an example, to the function of the embodiment of the present invention and should not use scope
Bring any limitation.
As shown in figure 3, computer system/server 12 is showed in the form of universal computing device.Computer system/service
The component of device 12 can be included but is not limited to:One or more processor (processing unit) 16, memory 28 connects not homology
The bus 18 of system component (including memory 28 and processor 16).
Bus 18 represents one or more in a few class bus structures, including memory bus or Memory Controller,
Peripheral bus, AGP, processor or the local bus using any bus structures in various bus structures.Lift
For example, these architectures include but is not limited to industry standard architecture (ISA) bus, MCA (MAC)
Bus, enhanced isa bus, VESA's (VESA) local bus and periphery component interconnection (PCI) bus.
Computer system/server 12 typically comprises various computing systems computer-readable recording medium.These media can be appointed
What usable medium that can be accessed by computer system/server 12, including volatibility and non-volatile media, it is moveable and
Immovable medium.
Memory 28 can include the computer system readable media of form of volatile memory, such as random access memory
Device (RAM) 30 and/or cache memory 32.Computer system/server 12 may further include that other are removable/no
Movably, volatile/non-volatile computer system storage medium.Only as an example, storage system 34 can be used for read-write
Immovable, non-volatile magnetic media (Fig. 3 do not show, commonly referred to " hard disk drive ").Although not shown in Fig. 3, can
To provide for the disc driver to may move non-volatile magnetic disk (such as " floppy disk ") read-write, and to removable non-volatile
Property CD (such as CD-ROM, DVD-ROM or other optical mediums) read-write CD drive.In these cases, each drive
Dynamic device can be connected by one or more data media interfaces with bus 18.Memory 28 can include at least one program
Product, the program product has one group of (for example, at least one) program module, and these program modules are configured to perform the present invention
The function of each embodiment.
With one group of program/utility 40 of (at least one) program module 42, can store in such as memory 28
In, such program module 42 includes --- but being not limited to --- operating system, one or more application program, other programs
Module and routine data, potentially include the realization of network environment in each or certain combination in these examples.Program mould
Block 42 generally performs the function and/or method in embodiment described in the invention.
Computer system/server 12 can also be with one or more external equipments 14 (such as keyboard, sensing equipment, aobvious
Show device 24 etc.) communication, can also be logical with the equipment that one or more enable a user to be interacted with the computer system/server 12
Letter, and/or any set with enable the computer system/server 12 to be communicated with one or more of the other computing device
Standby (such as network interface card, modem etc.) communication.This communication can be carried out by input/output (I/O) interface 22.And
And, computer system/server 12 can also be by network adapter 20 and one or more network (such as LAN
(LAN), wide area network (WAN) and/or public network, such as internet) communication.As shown in figure 3, network adapter 20 passes through bus
18 communicate with other modules of computer system/server 12.It should be understood that although not shown in computer can be combined
Systems/servers 12 use other hardware and/or software module, including but not limited to:At microcode, device driver, redundancy
Reason unit, external disk drive array, RAID system, tape drive and data backup storage system etc..
Program of the processor 16 by operation storage in memory 28, so as to perform at various function application and data
Reason, for example, realize the method in embodiment illustrated in fig. 1, that is, obtain real city road network data, obtains real traffic trip
Sample data, traffic trip model is determined according to the traffic trip sample data for getting, according to city road network data and
Traffic trip model, simulates required traffic trip scene.
In addition, also vehicle to be assessed can be added in traffic trip scene, vehicle to be assessed is evaluated to traffic
Influence.
Such as, vehicle to be assessed can be added in the traffic trip scene according to Different Strategies respectively, be assessed respectively
Go out influence of the vehicle to be assessed to traffic under Different Strategies.
It is preferred that vehicle to be assessed is automatic driving vehicle.
The present invention discloses a kind of computer-readable recording medium, computer program is stored thereon with, the program quilt
The method in embodiment as shown in Figure 1 will be realized during computing device.
Can be using any combination of one or more computer-readable media.Computer-readable medium can be calculated
Machine readable signal medium or computer-readable recording medium.Computer-readable recording medium for example can be --- but do not limit
In --- the system of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, device or device, or it is any more than combination.Calculate
The more specifically example (non exhaustive list) of machine readable storage medium storing program for executing includes:Electrical connection with one or more wires, just
Take formula computer disk, hard disk, random access memory (RAM), read-only storage (ROM), erasable type and may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In this document, computer-readable recording medium can be it is any comprising or storage journey
The tangible medium of sequence, the program can be commanded execution system, device or device and use or in connection.
Computer-readable signal media can include the data-signal propagated in a base band or as a carrier wave part,
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 beyond computer-readable recording medium, the computer-readable medium can send, propagate or
Transmit for being used or program in connection by instruction execution system, device or device.
The program code included on computer-readable medium can be transmitted with any appropriate medium, including --- but do not limit
In --- wireless, electric wire, optical cable, RF etc., or above-mentioned any appropriate combination.
Computer for performing present invention operation can be write with one or more programming language or its combination
Program code, described program design language includes object oriented program language-such as Java, Smalltalk, C++,
Also include conventional procedural programming language-such as " C " language or similar programming language.Program code can be with
Fully perform on the user computer, partly perform on the user computer, performed as an independent software kit, portion
Part on the user computer is divided to perform on the remote computer or performed on remote computer or server completely.
Be related in the situation of remote computer, remote computer can be by the network of any kind --- including LAN (LAN) or
Wide area network (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (is for example carried using Internet service
Come by Internet connection for business).
In several embodiments provided by the present invention, it should be understood that disclosed apparatus and method etc., can pass through
Other modes are realized.For example, device embodiment described above is only schematical, for example, the division of the unit,
It is only a kind of division of logic function, there can be other dividing mode when actually realizing.
The unit that is illustrated as separating component can be or may not be it is physically separate, it is aobvious as unit
The part for showing can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be according to the actual needs selected to realize the mesh of this embodiment scheme
's.
In addition, during each functional unit in each embodiment of the invention can be integrated in a processing unit, it is also possible to
It is that unit is individually physically present, it is also possible to which two or more units are integrated in a unit.Above-mentioned integrated list
Unit can both be realized in the form of hardware, it would however also be possible to employ hardware adds the form of SFU software functional unit to realize.
The above-mentioned integrated unit realized in the form of SFU software functional unit, can store and be deposited in an embodied on computer readable
In storage media.Above-mentioned SFU software functional unit storage is in a storage medium, including some instructions are used to so that a computer
Equipment (can be personal computer, server, or network equipment etc.) or processor (processor) perform the present invention each
The part steps of embodiment methods described.And foregoing storage medium includes:USB flash disk, mobile hard disk, read-only storage (ROM), with
Machine access memory (RAM), magnetic disc or CD etc. are various can be with the medium of store program codes.
Presently preferred embodiments of the present invention is the foregoing is only, is not intended to limit the invention, it is all in essence of the invention
Within god and principle, any modification, equivalent substitution and improvements done etc. should be included within the scope of protection of the invention.
Claims (14)
1. a kind of traffic trip scenario building method, it is characterised in that including:
Obtain real city road network data;
Obtain real traffic trip sample data;
Traffic trip sample data according to getting determines traffic trip model;
According to the city road network data and the traffic trip model, required traffic trip scene is simulated.
2. method according to claim 1, it is characterised in that
The method is further included:
Vehicle to be assessed is added in the traffic trip scene, shadow of the vehicle to be assessed to traffic is evaluated
Ring.
3. method according to claim 2, it is characterised in that
It is described that vehicle to be assessed is added in the traffic trip scene, the vehicle to be assessed is evaluated to traffic
Influence includes:
The vehicle to be assessed is added in the traffic trip scene according to Different Strategies respectively, different plans are evaluated respectively
Influence of the vehicle to be assessed to traffic under slightly.
4. method according to claim 2, it is characterised in that
The vehicle to be assessed includes:Automatic driving vehicle.
5. method according to claim 1, it is characterised in that
The real traffic trip sample data of acquisition includes:
Whole urban area is divided into M sub-regions, M is the positive integer more than;
Obtain respectively per the corresponding traffic trip sample data of sub-regions;
The traffic trip sample data that the basis gets constructs traffic trip model to be included:
The traffic trip demand occurred in every sub-regions is regarded as a Poisson process;
According to the corresponding traffic trip sample data of every sub-regions, determine that every sub-regions are sent out in different time sections respectively
The number of raw traffic trip event, will determine that traffic trip demand of the result as every sub-regions in different time sections is commented
Estimate result.
6. method according to claim 5, it is characterised in that
It is described will determine traffic trip need assessment result of the result as every sub-regions in different time sections after, enter one
Step includes:
According to the traffic flow information of the key crossing for getting, each traffic trip need assessment result is modified respectively;
It is described according to the city road network data and the traffic trip model, simulate required traffic trip scene bag
Include:
According to the city road network data and revised each traffic trip need assessment result, the traffic needed for simulating goes out
Row scene.
7. a kind of traffic trip scenario building device, it is characterised in that including:First acquisition unit, second acquisition unit and
Analogue unit;
The first acquisition unit, for obtaining real city road network data, is sent to the analogue unit;
The second acquisition unit, for obtaining real traffic trip sample data, and according to the traffic trip sample for getting
Notebook data determines traffic trip model, is sent to the analogue unit;
The analogue unit, for according to the city road network data and the traffic trip model, simulating required friendship
Pass-out row scene.
8. device according to claim 7, it is characterised in that
The analogue unit is further used for,
Vehicle to be assessed is added in the traffic trip scene, shadow of the vehicle to be assessed to traffic is evaluated
Ring.
9. device according to claim 8, it is characterised in that
Be added to the vehicle to be assessed in the traffic trip scene according to Different Strategies respectively by the analogue unit, respectively
Evaluate influence of the vehicle to be assessed to traffic under Different Strategies.
10. device according to claim 8, it is characterised in that
The vehicle to be assessed includes:Automatic driving vehicle.
11. devices stated according to claim 7, it is characterised in that
The second acquisition unit obtains the corresponding traffic trip sample data of every sub-regions respectively, wherein, in advance will be whole
Urban area is divided into M sub-regions, and M is the positive integer more than;
The traffic trip demand occurred in every sub-regions is regarded as a Poisson process by the second acquisition unit, according to every
The corresponding traffic trip sample data of sub-regions, determines that the traffic that every sub-regions occur in different time sections goes out respectively
The number of part is acted, traffic trip need assessment result of the result as every sub-regions in different time sections will be determined.
12. devices according to claim 11, it is characterised in that
The second acquisition unit is further used for, according to the traffic flow information of the key crossing for getting, respectively to each friendship
Pass-out row need assessment result is modified;
The analogue unit is simulated according to the city road network data and revised each traffic trip need assessment result
Required traffic trip scene.
A kind of 13. computer equipments, including memory, processor and storage are on the memory and can be on the processor
The computer program of operation, it is characterised in that any in realization such as claim 1~6 during the computing device described program
Method described in.
A kind of 14. computer-readable recording mediums, are stored thereon with computer program, it is characterised in that described program is processed
The method as any one of claim 1~6 is realized when device is performed.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710089333.XA CN106934107A (en) | 2017-02-20 | 2017-02-20 | Traffic trip scenario building method, device, equipment and storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710089333.XA CN106934107A (en) | 2017-02-20 | 2017-02-20 | Traffic trip scenario building method, device, equipment and storage medium |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106934107A true CN106934107A (en) | 2017-07-07 |
Family
ID=59423368
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710089333.XA Pending CN106934107A (en) | 2017-02-20 | 2017-02-20 | Traffic trip scenario building method, device, equipment and storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106934107A (en) |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107909180A (en) * | 2017-09-30 | 2018-04-13 | 百度在线网络技术(北京)有限公司 | Processing method, equipment and the computer-readable recording medium of transit trip used time |
CN110378502A (en) * | 2018-09-13 | 2019-10-25 | 北京京东尚科信息技术有限公司 | The method and apparatus that auxiliary unmanned vehicle determines path |
CN110995548A (en) * | 2020-03-04 | 2020-04-10 | 杭州云动智能汽车技术有限公司 | Method for testing validity of V2X protocol under boundary working condition |
CN111091581A (en) * | 2018-10-24 | 2020-05-01 | 百度在线网络技术(北京)有限公司 | Pedestrian trajectory simulation method and device based on generation of countermeasure network and storage medium |
CN111091156A (en) * | 2019-12-20 | 2020-05-01 | 斑马网络技术有限公司 | Intersection passing time estimation method and device and electronic equipment |
WO2020224462A1 (en) * | 2019-05-09 | 2020-11-12 | 腾讯科技(深圳)有限公司 | Processing method and apparatus for driving simulation scene, and storage medium |
CN114066001A (en) * | 2021-09-25 | 2022-02-18 | 苏州智能交通信息科技股份有限公司 | Travel intrinsic based traffic service optimization method, system, terminal and medium |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102881173A (en) * | 2012-09-24 | 2013-01-16 | 青岛海信网络科技股份有限公司 | Traffic demand control method and system |
CN103412975A (en) * | 2013-07-11 | 2013-11-27 | 吴建平 | Dynamic traffic simulation platform and simulation method thereof |
CN103593535A (en) * | 2013-11-22 | 2014-02-19 | 南京洛普股份有限公司 | Urban traffic complex self-adaptive network parallel simulation system and method based on multi-scale integration |
CN106153352A (en) * | 2016-07-04 | 2016-11-23 | 江苏大学 | A kind of automatic driving vehicle test and verification platform and method of testing thereof |
-
2017
- 2017-02-20 CN CN201710089333.XA patent/CN106934107A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102881173A (en) * | 2012-09-24 | 2013-01-16 | 青岛海信网络科技股份有限公司 | Traffic demand control method and system |
CN103412975A (en) * | 2013-07-11 | 2013-11-27 | 吴建平 | Dynamic traffic simulation platform and simulation method thereof |
CN103593535A (en) * | 2013-11-22 | 2014-02-19 | 南京洛普股份有限公司 | Urban traffic complex self-adaptive network parallel simulation system and method based on multi-scale integration |
CN106153352A (en) * | 2016-07-04 | 2016-11-23 | 江苏大学 | A kind of automatic driving vehicle test and verification platform and method of testing thereof |
Non-Patent Citations (3)
Title |
---|
于雷等: "《城市交通流理论》", 31 August 2016, 北京交通大学出版社 * |
王春: "基于VR_GIS一体化城市微观交通虚拟仿真系统的研究与应用", 《中国博士学位论文全文数据库工程科技Ⅱ辑(月刊)》 * |
高志强: "基于浮动车数据的社会车辆出行仿真场景构建", 《中国学位论文全文数据库》 * |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107909180A (en) * | 2017-09-30 | 2018-04-13 | 百度在线网络技术(北京)有限公司 | Processing method, equipment and the computer-readable recording medium of transit trip used time |
CN107909180B (en) * | 2017-09-30 | 2022-03-25 | 百度在线网络技术(北京)有限公司 | Processing method, equipment and readable medium for public transport travel |
CN110378502A (en) * | 2018-09-13 | 2019-10-25 | 北京京东尚科信息技术有限公司 | The method and apparatus that auxiliary unmanned vehicle determines path |
CN111091581A (en) * | 2018-10-24 | 2020-05-01 | 百度在线网络技术(北京)有限公司 | Pedestrian trajectory simulation method and device based on generation of countermeasure network and storage medium |
WO2020224462A1 (en) * | 2019-05-09 | 2020-11-12 | 腾讯科技(深圳)有限公司 | Processing method and apparatus for driving simulation scene, and storage medium |
CN111091156A (en) * | 2019-12-20 | 2020-05-01 | 斑马网络技术有限公司 | Intersection passing time estimation method and device and electronic equipment |
CN111091156B (en) * | 2019-12-20 | 2023-06-23 | 斑马网络技术有限公司 | Intersection passing time estimation method and device and electronic equipment |
CN110995548A (en) * | 2020-03-04 | 2020-04-10 | 杭州云动智能汽车技术有限公司 | Method for testing validity of V2X protocol under boundary working condition |
CN110995548B (en) * | 2020-03-04 | 2020-06-16 | 杭州云动智能汽车技术有限公司 | Method for testing validity of V2X protocol under boundary working condition |
CN114066001A (en) * | 2021-09-25 | 2022-02-18 | 苏州智能交通信息科技股份有限公司 | Travel intrinsic based traffic service optimization method, system, terminal and medium |
CN114066001B (en) * | 2021-09-25 | 2024-03-19 | 苏州智能交通信息科技股份有限公司 | Traffic service optimization method, system, terminal and medium based on travel intrinsic |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106934107A (en) | Traffic trip scenario building method, device, equipment and storage medium | |
WO2022121510A1 (en) | Stochastic policy gradient-based traffic signal control method and system, and electronic device | |
CN104683405B (en) | The method and apparatus of cluster server distribution map matching task in car networking | |
CN106897919A (en) | With the foundation of car type prediction model, information providing method and device | |
CN106951627A (en) | Emulation test method, device, equipment and the computer-readable recording medium of Vehicular automatic driving | |
CN106960219A (en) | Image identification method and device, computer equipment and computer-readable medium | |
CN106920038A (en) | The dispatching method of automatic driving vehicle, device, equipment and storage medium | |
CN107844886A (en) | Vehicle dispatching method, device, equipment and storage medium | |
CN106875670B (en) | Taxi allocation method based on GPS data under Spark platform | |
CN106843219A (en) | Automatic driving vehicle selects method, device, equipment and the storage medium of dock point | |
CN115100848B (en) | Ground traffic jam travel tracing method and system | |
CN106919908A (en) | Obstacle recognition method and device, computer equipment and computer-readable recording medium | |
CN109118787A (en) | A kind of car speed prediction technique based on deep neural network | |
JP2021514883A (en) | Systems and methods for determining travel routes in autonomous driving | |
CN109406166A (en) | Stage division, device, equipment, storage medium and the vehicle of unmanned vehicle | |
CN108615190A (en) | Air control model verification method, device, equipment and storage medium | |
CN107727108A (en) | The recommendation method, apparatus and computer-readable medium of transit trip route | |
Xu et al. | Spatial ensemble prediction of hourly PM2. 5 concentrations around Beijing railway station in China | |
CN114005297B (en) | Vehicle team coordinated driving method based on Internet of vehicles | |
Liu et al. | Heuristic approach for the multiobjective optimization of the customized bus scheduling problem | |
CN113947948A (en) | Vehicle passing control method and device | |
Araldo et al. | Implementation & policy applications of AMOD in multi-modal activity-driven agent-based urban simulator simmobility | |
US20220340146A1 (en) | Apparatus and method for calculating ratio of negligence based on 3d simulator | |
US20220237529A1 (en) | Method, electronic device and storage medium for determining status of trajectory point | |
CN116109188A (en) | Safety evaluation method for automatic driving vehicle, storage medium and electronic equipment |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170707 |
|
RJ01 | Rejection of invention patent application after publication |