CN106779159A - Method and controller for determining stop probability of the object in road network - Google Patents
Method and controller for determining stop probability of the object in road network Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
Abstract
The present invention relates to one kind for determining the method (600) that stops probability of the object (100) in the road network (106) with least one fork position (200), at least one first sub- sections (202) and the second sub- section (204) are separated from the fork position.Method (600) is including determining step (610), that is, it is determined that representing at least one first probable values of stop probability of the object (100) on the first sub- section (202) and representing at least one second probable values of stop probability of the object (100) on the second sub- section (204).Method (600) also includes scale step (630), scale at least is carried out to the first probable value and the second probable value, so that the summation of the second probable value of the first probable value of scale and scale is more than probable value of the object (100) on the sub- section before fork position (200), to determine stop probability of the object (100) in road network (106).
Description
Technical field
The present invention relates to the apparatus and method of the type according to independent claims.Object of the invention is also computer journey
Sequence.
Background technology
Position of the object in numerical map for example can be determined by means of so-called particle filter.
The content of the invention
In this context, by the scheme for herein proposing, according to main claim, it is proposed that for determining object in road network
In stop probability method, it is also proposed that using the controller of the method, and finally propose corresponding computer program.
The device for illustrating in the independent claim can be advantageously improved and improved by the measure enumerated in the dependent claims.
Scheme described herein provides a kind of method for determining stop probability of the object in road network, and road network has
At least one fork position, at least one first sub- sections and the second sub- section are separated from the fork position, wherein, method includes
Following steps：
Step is determined, it is determined that representing at least one first probable values and the generation of stop probability of the object on the first sub- section
At least one second probable values of stop probability of the table object on the second sub- section；With
Scale step, at least carries out scale to the first probable value and the second probable value so that the first probable value of scale and
The summation of the second probable value of scale is more than probable value of the object on the sub- section before the position of fork, to determine that object exists
Stop probability in road network.
Stop probability and be understood to the probability that the place of determination of the object in road network stops.Road network is understood to by object
The net of the mulitpath composition that can be used or use.Fork position is understood to the point in road network, and the section of road network is at this point
It is divided at least two sub- sections.Object is for example understood to vehicle, mobile phone, automobile, chest, packet etc..
Probable value for example can be regarded as representing the probability number for stopping probability.
Scheme described herein is based on the recognition：Can determine that object in road network by using multiverse algorithm
Position, road network is for example stored in numerical map.The advantage of such localization method is, object is calculated by means of multiverse algorithm
The stop probability that goes out is provided and point-device meets very much actual value.Therefore, even if only little or bad sensor
Data stop probability available for the reasonability or amendment for checking stop probability, can also ensure reliable positioning.
According to an advantageous embodiment, in scale step, probability higher in the first probable value or the second probable value
Value can obtain the probable value of scale, the probable value on its sub- section equivalent to object before the position of fork.By this way
It is capable of achieving to improve stop probability of the ground determination object in road network.
It is also possible to consider a kind of implementation method of the scheme for herein proposing, wherein, such scale first in scale step
Probable value and the second probable value, i.e. the probability with representative more than 100% of the first probable value and the second probable value, and/or first
Probable value or the second probable value represent 100% probability.It is same by this way to be capable of achieving to determine object in road network with improving
Stop probability.
Scheme described herein additionally provides a kind of method for determining stop probability of the object in road network, road network tool
Have：At least one first forks position, at least one first sub- sections and the second sub- section are separated from the first fork position；With
At least one is located at the second fork position in the first sub- section, and at least one the 3rd sub- sections are separated from the second fork position
With the 4th sub- section, wherein, method is comprised the following steps：
Step is determined, when object is located on the first sub- section, it is determined that it is general to represent stop of the object on the 3rd sub- section
At least one first probable values of rate, when object is on the first sub- section, it is determined that representing object stopping on the 4th sub- section
At least one second probable values of probability are stayed, and determines at least one the 3rd probable values, it represents object in the second sub- section
Stop probability upper or on another sub- section separated from another fork position that can be reached by the second sub- section；
Step is added, the first probable value, the second probable value is added with the 3rd probable value, to obtain instrumental value；With
Scale step, at least to the first probable value, the second probable value and the 3rd probable value in the case of using instrumental value
Scale is carried out, to determine stop probability of the object in road network.
Instrumental value is especially understood to the value for representing the probability more than 100%.
In scale step, three probable values for example refer to 100% or 1 reference probability carry out scale so that three marks
The summation of the probable value of degree is equivalent to 100% or 1 probability.
According to a kind of implementation method, instrumental value represents the probability more than 100%.Herein can be in scale step so to the
Three probable values, the 4th probable value and the second probable value carry out scale, i.e. after scale, the 3rd probable value, the 4th probable value and
The summation of the second probable value represents 100% probability.It is achieved in determining with gearing to actual circumstances as far as possible to be closed from different sub- sections
The stop probability of connection.
Furthermore it is advantageous that it is determined that in step, if object is on the first sub- section or the 4th sub- section or the second sub- road
In section or other sub- sections, determine object can be by the first sub- road in the case of using the 4th probable value and the second probable value
The stop probability on the 5th sub- section that section and the second sub- section reach.Here, the 5th sub- section for example can be by including first
First path in sub- section and the 4th sub- section is reached by the alternate path including the second sub- section and other sub- sections.This
Outward, the 4th sub- section or other sub- sections can be led in the 5th sub- section.Can determine that object or vehicle exist by the implementation method
By the position combined on the section for obtaining in two or more sub- sections.Thus can enter in the object or vehicle in positioning road network
One step improves precision.
According to another implementation method, it is determined that in step, if the second probable value is represented, the probable values of Bi tetra- are smaller to stop
Probability is stayed, the stop probability of object or vehicle on the 5th sub- section can be equivalent to the 4th probable value.Alternatively, if the 4th is general
Rate value represents the stop probability smaller than the second probable value, and stopping probability can be equivalent to the second probable value.Therefore, with the 5th sub- road
The stop probability of Duan Guanlian particularly simple can be determined by deleting the probable value of the stop probability for representing accordingly smaller.Thus
Can reduce to calculate when it is determined that stopping probability and spend.
Additionally, method is settable amendment step, wherein, according to implementation method, using by object or vehicle
The 3rd probable value, the 4th probable value or the second probability are corrected in the case of the sensing data that at least one sensor is provided
Value.Sensor for example can be the environmental sensor of object or vehicle.Additionally or alternatively, relevant probable value can also be in amendment
Corrected in the case where navigation data is used in step.
Furthermore it is advantageous that it is determined that determining at least one additional probable value in step, it is represented works as object or vehicle
When on the second sub- section, object or vehicle are at least one stop from the additional sub- section that other fork positions separate
Probability.Correspondingly, at least can be by the 3rd probable value, the 4th probable value, the second probable value and additional probability in step is added
Value is added, to obtain instrumental value, wherein, in scale step, can using in the case of instrumental value at least to the 3rd probable value,
4th probable value, the second probable value and additional probable value carry out scale.Thus can reliably and precisely determine very much object or
Stop probability of the vehicle in the sub- section multiple different, especially independent of each other of road network.
The method for example for example can in the controller be performed with the mixed form of software or hardware or software and hardware.
The scheme for herein proposing further relates to a kind of controller, and it is configured to be performed in corresponding device, manipulated or realized
The step of modification of the method for herein proposing.Can also by the embodiment modification of the form in controller of the invention it is quick and
Efficiently realize purpose proposed by the present invention.
Here, controller is understood to electrical equipment, it processes sensor signal and is exported according to sensor signal and controls
Signal processed and/or data-signal.Controller can have interface, and it can be formed in the way of hardware and/or software.In hardware type
In structural scheme, interface for example can be a part for the so-called ASIC systems containing controller various functions.However, equally may be used
Capable, interface is the integrated circuit of oneself or is made up of discrete structural detail at least in part.In the construction side of software type
In case, interface can be software module, and it is for example with other software module and is present in microcontroller with depositing.
Also advantageously computer program product or the computer program with program code, it is storable in machine can
On the carrier or storage medium (such as semiconductor memory, harddisk memory or optical memory) of reading, and especially work as program
When product or program are implemented on computer or device, the program product or program be used to performing, realize and/or manipulate according to
The step of stating a kind of method in implementation method.
Brief description of the drawings
Embodiments of the invention are shown in the drawings, and it is described in detail in subsequent explanation.Wherein：
Fig. 1 shows the schematic diagram of the vehicle with controller according to embodiment；
Fig. 2 shows the schematic diagram of the section of road network for being used together with controller according to embodiment；
Fig. 3 shows the schematic diagram of the section of road network for being used together with controller according to embodiment；
Fig. 4 A show the schematic diagram of the section of road network for being used together with controller according to embodiment；
Fig. 4 B show the schematic diagram for the section using the road network in embodiment；
Fig. 4 C show the schematic diagram for the section using the road network in embodiment；
Fig. 4 D show the schematic diagram for the section using the road network in embodiment；
Fig. 4 E show the schematic diagram for the section using the road network in embodiment；
Fig. 5 shows the schematic diagram of the section of road network for being used together with controller according to embodiment；
Fig. 6 shows the flow chart of the method according to embodiment；And
Fig. 7 shows the block diagram as controller of embodiments of the invention.
Specific embodiment
Below to the explanation of advantageous embodiment of the present invention in, for it is showing in different drawings and act on it is similar
Element uses same or analogous reference, wherein, eliminate the repeat specification to these elements.
Fig. 1 shows the schematic diagram of the vehicle 100 with controller 102 according to embodiment.Vehicle 100 is in track 104
Upper traveling, the track is a part for road network 106 and is divided into many sub- sections in multiple fork positions.Controller 102 is constructed
Into the place that determination of the vehicle 100 in road network 106 is determined in the case where the multiverse algorithm being detailed below is used
The probability of stop, wherein, stop probability of the vehicle 100 on two sub- sections with common fork position as starting point exists
Determined in the case of with the stop probability of stop on the sub- section of the two sub- section independences using vehicle 100.Alternatively, control
Device processed 102 is coupled with the environmentally sensitive mechanism 108 of vehicle 100, and environmentally sensitive mechanism is configured to obtain vehicle on track 104
Position and the position is sent to controller 102, be used for for the sensing data of environmentally sensitive mechanism 108 to check by controller
The reasonability of the result of multiverse algorithm or the result of amendment multiverse algorithm.
Position of the object in numerical map can be for example determined by means of so-called particle filter.Here, in numeral
A large amount of points (being also known as particle) are given in map.Each particle represents the real stop place of object with certain probability.
Particle should be located on certain predetermined region (such as road) in map.
In the movement step of corresponding localization method, the corresponding motion of object is for example by means of so-called dead reckoning
Algorithm is determined.For example pass through odometer, pedometer, gyro in the case where GLONASS (guide number SS) is used
The measurement that instrument, acceleration transducer or wireless fingerprint are moved.
As measurement result, the displacement vector that object has been moved is determined.Because sensor with errors works, displacement
Vector is probability distribution.Mainly show normal distribution.
Displacement vector is added on each particle now.Because not strictly speaking being to be related to vector, but it is related to distribution, institute
Cloned with to particle, and different sample elements are added respectively from the distribution of displacement vector.Thus produced from a particle
Raw multiple seed.Here, the probability of father's particle is according in the probability distribution of children's particle to children's particle.And then father is deleted
Particle.
Particle is moved in numerical map.Multiple in the new children's particle for producing can be abandoned, if they are moved at it
Aspect has crossed the forbidden zone of numerical map.Therefore, particle can leave wall or depart from road in the case of vehicle.It is all such
Particle can localization method prune step off in deleted because the motion is forbidden.Can make a reservation for can verify that particle is credible
Other boundary conditions of degree.Therefore, the dead reckoning algorithm for referring to for example also provides object in addition to displacement vector and can be located at
Wherein, the global area for example in the stop ellipse calculated by navigational satellite system, wherein, it is all outside the region
Particle can be deleted.
For example pruned off by being multiplied with so-called emission probability, be maintained at by this way after very short time only
Little particle is there remains, by its approximate actual location for determining object in numerical map.
By being multiplied with emission probability and delete incredible particle, the summation no longer phase of the probability on all particles
When in numerical value 1.Therefore, in normalization step again, the probability of all particles to leaving carries out scale, makes it in summation
On again be 1.
This particle filter can have relatively large global error scope, and particle should rest on the global error scope
In, such as because the WLAN of the masking in navigational satellite system or interruption is connected.Additionally, motion vector can be very weak, i.e. operation
Vector only illustrates shift length, but without direction, is nearly similar to pedometer.Additionally, there are generally only by lines
The digital network of composition, object can be moved in the digital network.
Fig. 2 shows the schematic diagram of the section of road network 106 for being used together with controller according to embodiment.Road network
106 is, for example, the road network illustrated by Fig. 1.Track 104 is shown, it is divided into the first sub- section in the first fork position 200
202nd, the second sub- section 204 and the 3rd sub- section 206.Travel direction of the vehicle in road network 106 has been marked with arrow.
Fig. 3 shows the schematic diagram of the section of road network 106 for being used together with controller according to embodiment.It is different
In Fig. 2, there is the second fork position 300 on the first sub- section 202, the 3rd sub- section 206 is separated from the second fork position
With the 4th sub- section 302.
Fig. 4 A show the schematic diagram of the section of road network 106 for being used together with controller according to embodiment.No
Fig. 3 is same as, road network 106 has another fork position 400 on the second sub- section 204, according to the embodiment, from another fork
Position separates another sub- section 402 and additional sub- section 404.Here, the 4th sub- section 302 and another sub- section 402 lead to
To in the 5th common sub- section 406, the 5th sub- section is for example between the 3rd sub- section 206 and additional sub- section 404
Extend.
Fig. 5 shows the schematic diagram of the section of road network 106 for being used together with controller according to embodiment.It is different
In the road network illustrated by Fig. 2 to Fig. 4 A to Fig. 4 E, figure 5 illustrates road network 106 be shown as capillatus road network.Track 104 exists
First fork position 200 is divided into the first sub- section 202 and the second sub- section 204.Track 104 is on the first sub- section 202
The second fork position 300 be divided into the 3rd sub- section 206 and the 4th sub- section 302.As can be found out in Figure 5, track
104 are also divided into the 6th sub- section 502 and the 7th sub- section 504 in the junctions position 500 on the 3rd sub- section 206.
Track 104 is divided into the 8th sub- section 506 and the 9th sub- section again in the 4th fork position 505 on the 6th sub- section 502
508.5th fork position 510 is located on the 8th sub- section 506.The tenth sub- section 512 and are separated from the 5th fork position 510
11 sub- sections 514.Sub- section 204,302,504,508,514 be, for example, lie, its from track 104 by sub- section 202,
206th, 502,506,512 A-roads for being formed are separated.
Fig. 2 and Fig. 3 show the example of triradius, that is to say, that be respectively equipped with three equalitys for an intersection
Outlet.As seen from Figure 2, after by intersection, respectively with 33% probability cross petition section 202,204,
The road of 206 forms, i.e. probability is uniformly distributed in all of outlet.
Fig. 3 is shown similar to such intersection in Fig. 2, but difference is that intersection deforms simultaneously a little herein
And be made up of two intersection sequences.It is general in Fig. 3 when using in the particle filter for preceding referring to determine probability distribution
Rate distribution differs markedly from the probability distribution in Fig. 2.In the first crossing intersection part of the form in the first fork position 200, one
To right travel, second half particle is travelled half particle to the left.Particle in travel direction to the right now leads in the second trouble
Next intersection of the form of mouthful position 300 and it is divided into identical part again.Therefore, instead of determine in fig. 2 1/
3rd, 1/3,1/3 probability distribution obtains 1/4,1/4,1/2 probability distribution, that is to say, that between two intersections
How small unrelated distance is.
For the example for showing in Figure 4 A of road network 106, track 104 is divided into two tracks 202,204, and it is then proceeded to
Divide and assembled in middle lane 406.Therefore, vehicle can determine to travel whichaway twice.As a result, all three
The probability in track 206,404,406 is identical.Therefore, it is contemplated that probability assignments be 1/3,1/3,1/3.However, from particle filter
From the perspective of, the particle of half is travelled to the left in the first fork position 200, wherein, second half particle is to right travel.So
Afterwards, particle sub-distribution and is merged for middle lane 406 again.Therefore, finally given according to particle filter
Be assigned as 1/4,1/2,1/4.
Capillatus road network is schematically illustrated in Figure 5.Sweep of turning left is separated at regular intervals from straight lane herein,
Can be turned to this with 50% probability respectively in turning left sweep.As a result, from from the perspective of vehicle, all roads or branch road probability
It is identical.And from from the perspective of particle filter, vehicle is finally only also travelled straight with 1/32 probability, because at each fork
During the particle of half sails branch road at position.
It is determined that error during probability distribution can carry out overcompensation by means of dead reckoning algorithm.And by means of subsequent
The multiverse algorithm of the scheme that describe in detail, basis is herein proposed can meet required precision.
The principle of particle filter is based on a large amount of possible positions of Parallel Tracking.Therefore, it is not that single object is determined
Position, but strictly speaking multiple objects or particle are positioned, such as multiple vehicles, it is independent and drives towards friendship independently of each other
The cross road mouthful, wherein, self ground of corresponding driver and determine only according to randomly assigne to be turned round towards which road independently of each other.
Consider from this angle, the distribution as particle filter is calculated seems quite accurate.
But the most likely location of single object is should determine that now.It is applicable herein, each object can not be determined together
When to the left and to the right.That is to say, basic thought is that object can only determine a paths in each crossing intersection part.It is different from
The method of particle filter, single object can not divide in crossing intersection part.In a kind of actuality, can only determine to the left, and
In another actuality, can only determine to the right.But two kinds of actuality can not be present simultaneously.It can be said that being related to alternative universe.
In one universe, object turns round to the right, and in another universe, object turns round to the left.Importantly, particle filter is different from,
In bifurcated, object is not separated by, but the new alternative world additionally occurs.
Therefore, alternative universe should not regard children's generation in the original universe existed before fork as.But be relative to original
The new parallel universe of the complete equality in beginning universe.Once these universe are produced, there is no interaction between these universe.
New universe is produced by cloning original universe.Hereafter, object turns round to the right and another in a universe
Turned round to the left in universe, wherein, additionally produce universe, i.e. be not to be divided into multiple filial generations from parent.But there is new adding
Universe born of the same parents, wherein, in universe born of the same parents each obtain by the transition probability in crossing intersection part and by intersection it
Probability derived from preceding probability.
Due to clone, until exist all universe in rather than standardization again only in universe born of the same parents it
Before, the summation of probability is more than 1.
It is presently not the probability for using particle, but use the general of universe to determine the most possible position of object
Rate.If there is different universe, middle object is at same location in these different universe, then it is object to stop probability
The maximum in all universe of the position is located at wherein.
Instead of parallel universe, it is also contemplated that from the alternative path of the home position of object to current location.If this road
Footpath is led on fork, then figuratively, there is the additional path from home position to the fork.Now, a path is towards a side
To turn, and another path uses alternative.
Multiverse algorithm can be similar to the algorithm of particle filter.Difference is, in particle filter, particle
Seed or children's particle are split into, and in multiverse algorithm, compatriot is produced in generation instead of children.Multiverse algorithm can be same
Particle filter equally includes probability authenticity examination and again standardized step.
It is on the process for producing universe born of the same parents, such as claimed below suitable for multiverse algorithm.
When clone and probability are redistributed on compatriot, any one in compatriot should not have than before clone
Universe probability higher.Otherwise, the transition probability from " before intersection " to " after intersection " is more than 100%.
Due to clone, until before standardizing again, may occur in which probability higher.However, should not have probability in clone
Disappear, that is to say, that the summation of the probability in universe born of the same parents should at least be equal to the probability before fork.
Additionally, directly the probability proportion after clone between universe born of the same parents should be equivalent to the probability in crossing intersection part
Predetermined ratio, for example：" main roads are followed with 90% probability and are only transferred in blind alley with 10% probability ".Accordingly
Ground, universe born of the same parents should also have 90 to 10 probability proportion.
Particle filter forms a kind of limiting case, and old probability is distributed on all of compatriot completely wherein, and
Do not have to produce new probability during clone.This is fully allocated to its children generation corresponding to the comparing for illustrating, the accordingly probability of parent, its
In, parent itself disappears.
Another limiting case is to produce the new probability of maximum quantity wherein.In this case, in compatriot
Fork is crossed in the case where its probability (untill only up to standardizing again certainly) is not changed.Every other basis born of the same parents
Distribution at fork is than obtaining probability that is equally big or diminishing.
Multiverse algorithm is this limiting case.There is any many calculations in theory between both limiting cases
Method.Both limiting cases can be summarized as follows.Particle filter illustrates distribution of multiple objects in a universe；It is polynary
Distribution of the single object in multiple parallel universe of universe algorithmic descriptions.There is algorithm between both limiting cases can
The complete continuity in the interstage of energy.
Multiverse algorithm can be expressed as follows.
It is given that there is n outlet and Probability p is left1…pnIntersection.The summation of probability is 1.Limited without general
In the case of system, p1≥p2≥…≥pn。
In particle filter, the probability of father's particle is transmitted to children's generation, wherein, the probability and p of parent1、p2…pnIt is multiplied.
Then, father's particle disappears.
The situation in multiverse algorithm is that the father's particle for just considering is in fact particle born of the same parents and does not change now
Live on becoming.It moves to most possible subsequent traveling p1Position at.Additionally there is new compatriot, it has original
Beginning probability and factor pk/p1The additional probability of multiplication.This is the process for parallel universe or parallel path occur.Therefore, additional probability
By original probability and (p2+…+pn)/p1It is multiplied and produces.
If particle reaches the same position in different universe, it is likely that the bigger universe of property survives.Less may be used
The universe of energy is deleted.The process is also referred to as the merging in universe.
In carrying out again standardized step in all parallel universe for existing, to all at the end of filter updates
The summation of the probability in particle or universe is standardized into 1.
The action principle of multiverse algorithm is expanded on further with the example in Fig. 2 to Fig. 5 of preceding explanation below.
In fig. 2, be characterised by a point particle drive towards the first fork position 200 and tackle three outlet 202,
204th, in 206 makes decision.There are two additional compatriot, wherein, probability is respectively 1.After standardizing again
Obtain 1/3,1/3,1/3 probability distribution.
In figure 3, occur two universe after the first fork position 200, wherein, in the posterior probability point of standardization again
Wei 50%.In a universe, particle drives towards the second fork position 300, so as to two new universe occur.In universe
In one, particle turns round to the left at the second fork position 300, and particle in another universe at the second fork position 300
Turn round to the right.Because transition probability is identical, two universe born of the same parents are respectively with 50% probability.Therefore three spaces are obtained
Cosmos, wherein, probability is respectively 50%.1/3,1/3,1/3 desired result is finally given after standardizing again.
In Figure 4 A, occur two universe after the first fork position 200, wherein, probability is respectively 50%.In the second trouble
After mouth position 300, each universe splits into two sub- universe with each 50% probability.There is difference after standardizing again
Four universe with 25% probability.In two in four universe, particle directly overlaps each other simultaneously when continuing and travelling
And therefore can combination with one another.Because two universe probability are identical, in universe is deleted.After standardizing again
To three universe, wherein, probability is respectively 33%.
Fig. 4 B show the schematic diagram for the section using the road network in embodiment, wherein, it is that sub- section is assigned
Probability.
It is generable in particle filter to be, after movement step, on section that not only can be before fork but also
There is particle on section that can be after fork.Different turned by what topology obtained on the section being transferred to after fork
Move probability (for example：User is walked with 66% probability along main roads, and only with 33% probability along minor road row
Walk).Now, therefrom show that particle had 100% probability before fork, particle has on the main roads after fork
66% probability, and particle has 33% probability (certainly, probability should also and then root on the minor road after fork
According to the draft norm or scale for herein proposing).In this case, particle always had than after fork before fork
Probability higher.In extreme circumstances, matching algorithm is waited at the position before fork during this period, until all of particle
It is moved across fork.
According to the diagram of Fig. 4 B, the particle before the position of fork always has higher than particle after the position of fork
Probability.
Fig. 4 C show the schematic diagram for the section using the road network in embodiment, wherein, according to what is herein proposed
New scheme is that sub- section is assigned scale or standardized probability：Some particles after the position of fork have and in trouble
Particle identical probability before mouthful.
In the scheme for herein proposing, after fork, the particle in the segmentation with highest with respect to transition probability
With and particle identical probability before fork.Therefore, the position in road network for being determined by matching algorithm can be more
Corresponding to physical location.
If there is such case, i.e. at a heavy bifurcation mouth, all particles are moved across fork, then and traditionally make
There is no difference with particle filter.Only when running over more than one fork position in movement step or particle is present in fork
When before position and afterwards, the new scheme for herein proposing is favourable.
Fig. 4 D show the schematic diagram for the section using the road network in the embodiment that there is the second fork position, its
In, it is that sub- section is assigned probability.Three feasible paths are obtained, wherein, in this example, branch line to the right always obtains 2/
3 probability, and branch line to the left accordingly obtains 1/3 probability.It is general that absolute stop described herein is obtained according to the conventional method
Rate.
Fig. 4 E show the schematic diagram for the section using the road network in embodiment, wherein, it is that sub- section is associated with
Scale or standardized probability.Method according to herein proposing obtains definitely stopping for the explanation for exemplarily being shown in Fig. 4 E
Stay probability.
In Figure 5, the new universe with probability born of the same parents is produced in each fork position.The first fork position 200 it
Two compatriot that probability is respectively 50% are produced afterwards.After the second fork position 300, a generation probability in two universe is
50% another universe.Therefore, three universe that probability is respectively 33% are obtained after standardizing again.Another universe is at it
Next fork position produces new universe that probability is 33% etc. again.As a result, all of road equality in terms of probability.
Fig. 6 shows the flow chart of a kind of method 600 according to embodiment.Method 600 can be for example combined above by Fig. 1
Performed to the controller of Fig. 5 explanations.Method 600 is used to determine object stopping in the road network with least one fork position
Probability is stayed, at least one first sub- sections and the second sub- section are separated from least one fork position.
Here, determining to represent at least one of stop probability of the object 100 on the first sub- section 202 in step 610
First probable value and at least one second probable values for representing stop probability of the object 100 on the second sub- section 204.
Finally scale at least can be carried out to the first probable value and the second probable value in scale step 630, so that scale
The summation of the second probable value of the first probable value and scale is more than probable value of the object on the sub- section before the position of fork, with
Determine stop probability of the object in road network.
It is also possible to consider such embodiment of the invention, have at least one also in road network wherein and be located at the first sub- road
The second fork position in section, at least one the 3rd sub- sections and the 4th sub- section are separated from the second fork position.It is determined that
In step 610, when object is located on the 3rd sub- section, it is determined that representing at least one the 3rd probability of the stop probability of object
Value, and when object is located on the 4th sub- section, it is determined that representing at least the one of stop probability of the object on the 4th sub- section
Individual 4th probable value.In step 620 is added, at least the second probable value, the 3rd probable value are added with the 4th probable value, so as to
Obtain instrumental value.Finally, in scale step 630, at least to the second probable value, the 3rd probability in the case of using instrumental value
Value and the 4th probable value carry out scale, to determine stop probability of the object in road network.
According to an embodiment, herein can such three probable values of scale, i.e. offspring of three summations of probable value in scale
The probability of table 100% or 1.
According in another embodiment, in step 620, thereby determining that combines with each other the first sub- section and the second sub- section
The 5th sub- section (such as middle lane) probable value, i.e. the representative for deleting the first sub- section and the second sub- section is smaller
The probable value of probability is stopped, wherein, the 5th sub- section is associated with remaining probable value.
Step 610,620,630 can continue to implement.
Fig. 7 shows the block diagram of the controller 104 according to an embodiment of the present invention.Controller 104 is included for determining
Equipment 710, its at least one first probable values and generation for being used to determining to represent stop probability of the object on the first sub- section
At least one second probable values of stop probability of the table object on the second sub- section.Controller also includes the equipment for scale
730, it is used at least probable value of scale first and the second probable value so that the first probable value of scale and the second probability of scale
The summation of value is more than probable value of the object on the sub- section before the position of fork, general to determine stop of the object in road network
Rate.
It is also possible to consider such embodiment of the invention, it is configured to for the equipment 710 for determining wherein, when object position
When on the 3rd sub- section, it is determined that at least one the 3rd probable values of the stop probability of object are represented, and when object is located at the
When on four sub- sections, it is determined that representing at least one the 4th probable values of stop probability of the object on the 4th sub- section.It is being used for
In the equipment 720 of addition, the second probable value, the 3rd probable value is at least set to be added with the 4th probable value, to obtain instrumental value.Finally
It is at least general to the second probable value, the 3rd probable value and the 4th in the case of using instrumental value in the equipment 730 for scale
Rate value carries out scale, to determine stop probability of the object in road network.
If embodiment is included in the "and/or" relation between fisrt feature and second feature, this can so understand,
That is, the embodiment includes fisrt feature and second feature according to an implementation method, and has according to another implementation method or only
There is fisrt feature, or only there is second feature.
Claims (12)
1. a kind of for determining stop probability of the object (100) in the road network (106) with least one fork position (200)
Method (600), separate at least one first sub- sections (202) and the second sub- section (204) from least one fork position,
Wherein, methods described (600) is comprised the following steps：
Step (610) is determined, it is determined that representing stop probability of the object (100) on the described first sub- section (202) extremely
Lack first probable value and represent stop probability at least one of the object (100) on the described second sub- section (204)
Individual second probable value；With
Scale step (630), at least carries out scale to the first probable value and the second probable value so that the first probable value of scale and
The summation of the second probable value of scale is more than probable value of the object (100) on the sub- section before fork position (200),
To determine stop probability of the object (100) in the road network (106).
2. method (600) according to claim 1, it is characterised in that in the scale step (630), the first probability
Probable value higher obtains the probable value of scale in value or the second probable value, and the probable value of the scale is equivalent to the object
(100) probable value on the sub- section before fork position (200).
3. method (600) according to any one of the claims, it is characterised in that the first probable value and the second probability
The summation of value represents the probability more than 100%, and/or first probable value or the second probable value represent 100% probability.
4. the method according to any one of the claims, wherein, in road network (106) having at least one is located at institute
The second fork position (300) on the first sub- section (202) is stated, at least one the 3rd sub- sections are separated from the second fork position
And the 4th sub- section (302) (206), it is characterised in that
It is determined that in step (610), when the object (100) is on the described 3rd sub- section (202), it is determined that representing described
At least one the 3rd probable values of the stop probability of object (100), and when the object (100) is positioned at the 4th sub- section
(302) when on, it is determined that representing at least one the of stop probability of the object (100) on the described 4th sub- section (302)
Four probable values, wherein,
Addition step (620) is provided with, second probable value, the 3rd probable value is added with the 4th probable value, to obtain
Instrumental value, and
It is at least general to the second probable value, the 3rd probable value and the 4th in the case of using instrumental value in scale step (630)
Rate value carries out scale, to determine stop probability of the object (100) in the road network (106).
5. method (600) according to claim 4, it is characterised in that obtain instrumental value in step is added, the instrumental value
The probability more than 100% is represented, wherein, in scale step (630), to the 3rd probable value, the 4th probable value and second
Probable value carries out scale so that the summation of the 3rd probable value, the 4th probable value and the second probable value is represented after scale
100% probability.
6. method (600) according to claim 4 or 5, it is characterised in that it is determined that in step (610), when the object
(100) in the described first sub- section (202) or the 4th sub- section (302) or the second sub- section (204) or other sons
When on section (402), determine that the object (100) can pass through institute in the case where the 4th probable value and the second probable value is used
State the stop probability on the 5th sub- section (406) that the first sub- section (202) and the second sub- section (204) reach.
7. method (600) according to claim 6, it is characterised in that it is determined that in step (610), if described second
Probable value represents the stop probability less than the 4th probable value, stop of the object (100) on the described 5th sub- section (406)
Probability equivalent to the 4th probable value, or if the 4th probable value represent less than the second probable value stop probability, it is described
Stop probability of the object (100) on the described 5th sub- section (406) is equivalent to the second probable value.
8. method (600) according to any one of the claims 4 to 7, it is characterised in that be provided with amendment step,
Described the is corrected in the case that the sensing data provided by least one sensor (108) of the object (100) is provided
Three probable values, the 4th probable value and/or the second probable value.
9. method (600) according to any one of the claims 4 to 8, it is characterised in that it is determined that step (610)
In, determine at least one additional probable value, if the object (100) is on the described second sub- section (204), this is added
Probable value represent the object (100) at least one additional sub- section separated from other fork positions (400)
(404) the stop probability on, wherein, in step (620) is added, at least make the 3rd probable value, the 4th probable value, the second probability
It is worth and is added with additional probable value, to obtain instrumental value, wherein, in scale step (630), in the case of using instrumental value
Scale at least is carried out to the 3rd probable value, the 4th probable value, the second probable value and additional probable value.
10. a kind of controller (102), with unit (710,720,730), the unit is configured to implement and/or manipulate basis
The step of method (600) any one of the claims.
A kind of 11. computer programs, are configured to implement and/or manipulate method according to any one of claim 1 to 9
(600)。
A kind of 12. storage mediums of machine readable, be stored with computer according to claim 11 on the storage medium
Program.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102015222944.0 | 2015-11-20 | ||
| DE102015222944.0A DE102015222944A1 (en) | 2015-11-20 | 2015-11-20 | Method for determining a probability of residence of an object in a road network and control device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106779159A true CN106779159A (en) | 2017-05-31 |
| CN106779159B CN106779159B (en) | 2021-03-12 |
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ID=58693959
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611028993.9A Active CN106779159B (en) | 2015-11-20 | 2016-11-18 | Method and controller for determining the probability of a stay of an object in a road network |
Country Status (4)
| Country | Link |
|---|---|
| CN (1) | CN106779159B (en) |
| DE (1) | DE102015222944A1 (en) |
| FR (1) | FR3044127B1 (en) |
| IT (1) | IT201600115018A1 (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102235870A (en) * | 2010-04-15 | 2011-11-09 | 罗伯特·博世有限公司 | Method and navigation device determining a maximum possible speed of a vehicle within a remaining region of a speed measurement section |
| DE102014204364A1 (en) * | 2014-03-10 | 2015-09-10 | Robert Bosch Gmbh | Method for determining a position of an object |
-
2015
- 2015-11-20 DE DE102015222944.0A patent/DE102015222944A1/en active Pending
-
2016
- 2016-11-15 IT IT102016000115018A patent/IT201600115018A1/en unknown
- 2016-11-16 FR FR1661091A patent/FR3044127B1/en active Active
- 2016-11-18 CN CN201611028993.9A patent/CN106779159B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102235870A (en) * | 2010-04-15 | 2011-11-09 | 罗伯特·博世有限公司 | Method and navigation device determining a maximum possible speed of a vehicle within a remaining region of a speed measurement section |
| DE102014204364A1 (en) * | 2014-03-10 | 2015-09-10 | Robert Bosch Gmbh | Method for determining a position of an object |
Also Published As
| Publication number | Publication date |
|---|---|
| FR3044127A1 (en) | 2017-05-26 |
| IT201600115018A1 (en) | 2018-05-15 |
| CN106779159B (en) | 2021-03-12 |
| FR3044127B1 (en) | 2021-12-03 |
| DE102015222944A1 (en) | 2017-05-24 |
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