CN106197455A - A kind of urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method - Google Patents

Abstract

The invention discloses a kind of urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method, utilize road itself on route impact produce preference value and vehicle run time influence each other produce value at cost combine formed comprehensive assessment index value of utility, the quality of path navigation scheme is estimated by the size utilizing value of utility, and use the value of utility of quantum calculation parallel computation all path navigations scheme, use quantum searching effective search to go out satisfactory path navigation scheme.The present invention has taken into full account the various factors affecting the coast is clear, and quantifies finally to integrate to the influence degree of traffic by various factors and obtain value of utility, uses value of utility accurately to judge the quality of path navigation scheme.Quantum calculation and quantum searching are simultaneously introduced it so that the result of calculation of value of utility can be obtained in real time, and thus obtain suitable path navigation scheme, on the premise of meeting each driver's individual interest so that the traffic congestion of whole city road network is obviously improved.

Description

A kind of urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method

Technical field

The invention belongs to computer science and intelligent transportation system technical field, be specifically related to a kind of urban road network real Time dynamic multipath mouth path navigation quantum searching method.

Background technology

Big and medium-sized cities traffic network blocks up day by day, and the time cost, management cost and the Financial cost that produce because blocking up more are come The biggest, traffic congestion adds the resident trip time, have impact on work efficiency and the quality of life of people, constrains city and send out Exhibition, adds energy resource consumption and exhaust emissions, exacerbates environmental pollution, solves the congestion problems of urban road network and benefits the nation profit The people.But urban road network general layout is difficult to change, path resource is limited, efficient path navigation and rational path resource Distribution becomes the main path that solution city road network blocks up.

Path navigation can be divided into static path navigation and dynamic route to navigate, and static path navigation refers to physically The conditions such as reason information and traffic rules be constraint to seek shortest path, dynamic route navigation be static path navigation basis On, in conjunction with real-time transport information, the optimum traffic route planned in advance is carried out in good time adjustment until arriving at Obtain optimal path eventually.At present, the ripe path guiding system of the application that puts goods on the market is mostly based on the path navigation of static state, mainly There are dijkstra's algorithm, Lee algorithm, Floyd algorithm, blind search, A* heuritic approach etc., but in the face of there is numerous shakiness The traffic reality of determining cause element, user is also not content with existing system.Although static path navigation can quickly find single The optimal path of vehicle, but coordinate between vehicle to be difficult to avoid road local to block up relative with other Local resources not busy owing to lacking Put, and when there is vehicle accident and traffic jam, static path navigation can not change route in real time in time according to traffic information. Therefore the path navigation providing Real-time and Dynamic for vehicle is most important to alleviating road traffic congestion.Vehicle dynamic path navigation base In history, current traffic information data, future traffic flow is predicted, and is used for adjusting in time and updating optimal row Bus or train route line, thus effectively reduce road block and vehicle accident.In dynamic route navigation, the importance of traffic forecast gradually highlights, Increasing researchers apply kalman filter method, Time Series Method, neural network, Markov prediction and ash Traffic information predicting is conducted in-depth research by color prediction theory etc..Although flourish along with network, provide real for vehicle Time path navigation information be not difficult to accomplish, but simple dynamic realtime prediction flow model limits the accurate of real-time prediction model Property, cause the disposal ability to real-time traffic emergency poor, and the dynamic realtime forecast model Consideration of complexity is many Many, computation complexity increases with road network scale and exponentially increases, and the most current dynamic route navigation is the most immature, Duo Shuoting Stay theory stage.The accuracy of dynamic realtime forecast model and the contradiction of complexity limit the development of dynamic route navigation.

Summary of the invention

In order to solve above-mentioned technical problem, the invention provides a kind of urban road network Real-time and Dynamic Multiple Intersections path and lead Boat quantum searching method, by considering the various factors affecting traffic and quantifying these factors and assess path navigation side with this Case obtains effectively alleviating the navigation scheme of traffic congestion, and urban road network path resource utilization rate is maximized.

The technical solution adopted in the present invention is: a kind of urban road network Real-time and Dynamic Multiple Intersections path navigation quantum is searched Suo Fangfa, is mapped to illustraton of model R (B, E) by true road network, and wherein B represents junction node set, B_i(i=1,2 ..., r) table Showing single junction node, r is total crossing number, and E represents the section set in band direction；Assume this road network has n car, either car W has current starting point P_sWith destination terminal P_d, then certain feasible path continuous adjacent junction node of this car is expressed as {P_s,...,P_i,...,P_d}；Each car all selects a feasible path, and the driving path of all cars forms a feasible path collection Close FPS_n, i.e. one path navigation scheme；

It is characterized in that, said method comprising the steps of:

Step 1: according to vehicle number n, terminal information and the optional path of each car, initializes vehicle collection { v₁,v₂,..., v_nAnd optional path collectionWherein v_iRepresent i-th car,Represent an optional path of i-th car；

Step 2: to vehicle and optional path 0,1 thereof ..., b_iCarry out quantum coding | 0 >, | 1 > ..., | 2^n×h-1 > }, Determine that quantum state can completely represent all of path navigation scheme；Wherein b_iRepresenting the optional number of path of i-th car, h represents right The minimum number of bits that optional path code needs；

Step 3: determine the independent multiplication factor α of each influence factor according to traffic information_i,β_j, determine that value of utility calculates function U(x)；Wherein every kind of path navigation scheme correspondence independent variable x value；

Step 4: for preparing path navigation scheme waits power superposition state | x >, calculate the effectiveness that each path navigation scheme x is corresponding Value | U (x) |, obtain value of utility function waits power superposition state | U (x) >；

Step 5: determine the empirical value k of value of utility, waits power superposition state to value of utility function | U (x) > carry out quantum searching, Search out the value of utility meeting requirement | U_s>；

Step 6: output meets the value of utility U required_sAnd the path navigation scheme of correspondence, each car is carried out path and leads Boat.

As preferably, value of utility function U (x) described in step 3 is:

U (x)=Fr (x) × (α 1 × Rs (x)+α, 2 × Sl (x)+α, 3 × Ls (x)+α, 4 × Os (x)+α, 5 × Fd (x))-(β 1 ×Ta(x)+β2×Tc(x)+β3×De(x)+β4×Oc(x)+β5×Tl(x))

Wherein Fr (x) represent section whether can arrive at, take 1 expression up to, take 0 expression unreachable；Rs (x) represents section shape Condition, value [0,1]；Sl (x) represents that speed limits, value [0,1]；Ls (x) represents section illuminating position, value [0,1]；Os X () represents driver's obedient extent to system recommendation, value [0,1]；Fd (x) represents driver's familiarity to section, value [0,1]；Ta (x) represents the road impact that vehicle accident or the temporary control etc. of burst bring, value [0,1]；Tc (x) represents institute The time cost that routing footpath is expended, value [0, ∞]；De (x) represents the distance cost that selected path is expended, value [0, ∞]；Oc X () represents the oil mass cost that selected path is expended, value [0, ∞]；Tl (x) represents the impact of traffic lights, value [0,1]；α_i(i =1,2 ..., 5), β_i(i=1,2 ..., 5) represent the independent multiplication factor that each influence factor is corresponding respectively.

As preferably, implementing of step 4 includes following sub-step:

Step 4.1: the quantum etc. utilizing Hadamard gate to prepare initial argument's path navigation scheme weighs superposition stateWherein N represents quantum state sum；

Step 4.2: the unitary transformation circuit U that design function is corresponding_U(x)And can be used for realizing the auxiliary quantum that function calculates Bit | z >；

Step 4.3: superposition state is weighed in waiting of input path navigation scheme, parallel computation function U (x):

$U_{U\left(x\right)}|x>|z>=|x>|z\⊕U\left(x\right)>;$

Step 4.4: obtain value of utility function waits power superposition state | U (x) >.

As preferably, implementing of step 5 includes following sub-step:

Step 5.1: be given and instruct function f (y) for determine target state, and the quantum wire of correspondence is set；

$f\left(y\right)=\{\begin{array}{cc}1,& \begin{array}{cc}if& y\≥k\end{array}\\ 0,& else\end{array};$

Value of utility function etc. power superposition state | U (x) > after instruct criteria function, functional value f (x) is that the state of 1 is Target state；

Step 5.2: target state added up, draws target state number m and calculates aggreggate utility value target state | U_a>；

$|U_a>=\frac{1}{\sqrt{m}}\underset{i=0}{\overset{m-1}{\Σ}}|a_i>;$

Wherein, a_iRepresent target state, | a_i> represent target state quantum form；

Step 5.3: according to | U_a> determine and instruct inquiry O, determine that O converts；

O=I-2 | U_a><U_a|；

Wherein I represents and | U_a>quantum figure place identical wait power superposition state,<U_a| expression | U_a> conjugate vector；

Step 5.4: according to waiting power superposition stateDetermine that D converts；

Wherein,It is that waiting of all basic status weighs superposition state,H represents that Hadamard converts, and is used for making Standby grade weighs superposition state,Represent that preparing waiting of n × h position weighs superposition state；N represents quantum state sum, | i > represent i-th quantum State；

Step 5.5: determined that a G converts G=DO by O conversion and D conversion；

Step 5.6: value of utility function is waited power superposition state | U (x) > carry outSecondary G conversion, round table Show immediate integer；

Step 5.7: the value of utility state of observation output | U_out> and corresponding path navigation scheme | x_out>, within the time limit Search out the value of utility meeting requirement | U_s>；

Step 5.8: output value of utility state | U_s> corresponding path navigation scheme x_sIn the guidance path chosen for each car.

As preferably, implementing of step 5.7 includes following sub-step:

Step 5.7.1: the output after having converted G is observed, obtains value of utility U_outWith current search used time t_s；

Step 5.7.2: if t_s<t_max, then following step 5.7.3, wherein t are performed_maxRepresent and can guarantee that path navigation is real The maximum navigation time interval of time property；Otherwise, following step 5.7.5 is performed；

Step 5.7.3: if U_out< k, then t_s=t_s+t_c, and turn round execution described step 5.7.2, wherein t_cRepresent and perform Time required for RGQS method；Otherwise, following step 5.7.4 is performed；

Step 5.7.4: if fruit U_out<k_m, then k=U_out, t_s=t_s+t_c, and turn round execution described step 5.7.2, wherein k_m Represent the preferable value of utility rule of thumb set；Otherwise, following step 5.7.5 is performed；

Step 5.7.5:U_s=U_out, export U_s。

The present invention constructs the Real-time and Dynamic Multiple Intersections traffic model of a urban road network, various by urban transportation Influence factor is integrated into value of utility for assessing the quality of path navigation scheme；Introduce quantum calculation and quantum searching solves effectiveness Calculating in real time and search problem of value, after initial road conditions determines, the algorithm using the present invention to provide can be carried out in real time Calculate and search obtains suitable value of utility and corresponding suitably path navigation scheme, provide path to lead for all vehicles Boat so that the traffic in whole city is effectively alleviated and urban highway traffic resource utilization is maximized.

Accompanying drawing explanation

Fig. 1 is true road network and the model mapping graph of the embodiment of the present invention.

Fig. 2 is the RGQS method flow diagram of the embodiment of the present invention.

Fig. 3 is the UVCQC algorithm flow chart of the embodiment of the present invention.

Fig. 4 is that the UVCQC algorithm quantum parallelism of the embodiment of the present invention calculates process schematic.

Fig. 5 is the RNUQS algorithm schematic diagram of the embodiment of the present invention.

Fig. 6 be the embodiment of the present invention RNUQS algorithm in G conversion andThe geometric representation of secondary G conversion.

Detailed description of the invention

Understand and implement the present invention for the ease of those of ordinary skill in the art, below in conjunction with the accompanying drawings and embodiment is to this Bright it is described in further detail, it will be appreciated that enforcement example described herein is merely to illustrate and explains the present invention, not For limiting the present invention.

In order to effectively alleviate traffic congestion, providing real-time path navigation for driving vehicle, the present invention proposes one simultaneously Urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method.The method is for Multiple Intersections big in city road network Amount vehicle carries out the calculating of path value of utility, needs the factor considered the most, not only includes driver's objective attribute to road And subjective preferences, in addition it is also necessary in view of the Expenses Cost that route selection is corresponding, and the accident etc. being likely to occur on road Uncertain factor.Use quantum calculation and quantum searching that influence factor and path navigation scheme are calculated in real time and searched for, Obtain the path navigation scheme of suitable value of utility and correspondence, while meeting driving vehicle individual interests, it is achieved whole city The maximization of city's road network path resource utilization rate.

True road network (such as Fig. 1 (a)) is mapped to illustraton of model R (B, E) (such as Fig. 1 (b)) by the present invention, and B is node, and E is joint The vector arrows in band direction between point, the figure that R is made up of B and E.Crossing in Fig. 1 (a) is mapped as the node in Fig. 1 (b) successively B₁,B₂,...,B₁₂, section in Fig. 1 (a) is mapped as the vector arrows in Fig. 1 (b) band direction, and the true road network in Fig. 1 (a) reflects Penetrate as the figure R in Fig. 1 (b).Each node B represents a crossing in Fig. 1 (a), node B_i(i=1,2 ..., r) represent i-th Individual crossing, wherein r is total crossing number, and each vector arrows E represents a section.Assume this road network has n car, either car W has current starting point P_sWith destination terminal P_d, then certain feasible path of this car can be expressed as with continuous adjacent crossing {P_s,...,P_i,...,P_d}.Each car all selects a feasible path, and the driving path of all cars forms a feasible path collection Close FPS_n, i.e. one path navigation scheme.Owing to vehicle number and each car feasible path number are all a lot, therefore path navigation scheme Enormous amount, the present invention need solve problem can be converted into search optimal path, i.e. obtain optimal FPS_n.Truly Road network in be continually changing due to road conditions, therefore the search procedure of path navigation scheme must in certain period of time the most more Newly, the effectiveness of guarantee path navigation scheme, it is therefore necessary to ensure to search out optimal path reality within the limited time Time ground update.

The present invention with value of utility U evaluate path navigation scheme quality, affect value of utility size because have many, both wrapped Include invariant factor, as number of track-lines, the restriction of section speed, traffic lights duration, driver to recommend navigation scheme obedient extent etc., also Including the factor being continually changing in time, such as the distance in optional path, time-consuming, road conditions etc., the constant factor present invention is integrated into Preference value P, the factor of change is integrated into value at cost C, shown in the computing formula of value of utility such as formula (1).

U=P-C (1)

Value of utility U is to evaluate the important indicator that path navigation scheme is good and bad, and i.e. when path navigation scheme determines, U value is also Determining that, and U value is the biggest, path navigation scheme is the best.Being known by formula (1), U value depends on preference value P and value at cost C, The influence factor of preference value is as shown in table 1, and the influence factor of value at cost is as shown in table 2, when path navigation scheme determines, and U value Determined by the factor in Tables 1 and 2.

The influence factor of table 1 preference value P and parameter definition

The influence factor of table 2 value at cost C and parameter definition

In Tables 1 and 2, various factors is different for the influence degree of value of utility U, during therefore calculating U value, Every kind of factor will give corresponding weights according to city size and path navigation target.The factor of determining that property of preference value P, table 1 Defining the factor affecting preference value, after arbitrary vehicle determines starting point and destination, preference value determines that.Thus, certain Shown in the preference value P computing formula such as formula (2) in section.

P=Fr × (α 1 × Rs+ α 2 × Sl+ α 3 × Ls+ α 4 × Os+ α 5 × Fd) (2)

Wherein α_i(i=1,2 ..., 5) it is independent multiplication factor corresponding to each influence factor respectively, its value is advised with city Mould, decision objective setting relevant, multiplication factor numerical value is the biggest, and this factor is the most important, and the impact on value of utility U is the biggest, with In one traffic network, all of factor values determines that.In the optional path of any bar, the preference value in each section is cumulative to be The preference value in this path, preference value is the biggest, represents that this path is the most excellent.

For every road, the size of preference value P determines that, the size of value at cost C not only with select path Itself is relevant, it is also contemplated that influencing each other between vehicle, table 2 define the influence factor of value at cost.Determine at a car After path, the value of Ta, De and Tl can calculate accordingly, but oil mass cost Oc is by time cost Tc, distance costs De and row Sail speed comprehensively to determine, and the value of time cost Tc is not readily available and calculates, owing to the time spent is not only by path length Degree impact, also the congestion level impact in path Zhong Ge section, the vehicle number on section has directly with the coefficient that blocks up of road Relation, the average overall travel speed of block up coefficient and the road of road is inverse correlation.For certain specific section, can pass through The number of vehicles being currently running estimates the average overall travel speed by this section, and present invention traffic congestion coefficient gamma represents The congestion on road, vehicle average overall travel speed on road is closely bound up with traffic congestion coefficient, section actual vehicle number For n, threshold capacity is H, and the capacity that blocks up is L, then shown in the calculating of coefficient gamma of blocking up such as formula (3).

$\mathrm{\&gamma;}=\left\{\begin{array}{cc}1,& n<H\\ \frac{n}{H},& H\&le;n<L\\ \frac{L}{H}+e^{\frac{n}{L}},& n\&GreaterEqual;L\end{array}\right.---\left(3\right)$

After time cost Tc determines, oil mass cost Oc and value at cost C also can be calculated.When all vehicles can walking along the street After footpath determines, the value at cost C in any bar path can be calculated such as formula (4).

C=β₁×Ta+β₂×Tc+β₃×De+β₄×Oc+β₅×Tl (4)

Wherein, β_i(i=1,2 ..., 5) it is the independent multiplication factor of each influence factor affecting value at cost C, its value and city City's scale, decision objective set relevant, and their size represents each influence factor influence degree to value at cost C respectively, also Represent its importance degree.When certain path cost value C is the least, and this path is the most excellent, the value at cost of all vehicles is cumulative to be The value at cost of this whole path navigation scheme.

Value of utility U can weigh the quality of a path navigation scheme, and high usage value is also that a traffic system is well transported The key character of row.When the driving path (i.e. a kind of path navigation scheme) of all vehicles determines, its effectiveness i.e. can be calculated Value, the average utility value of vehicle represents the quality of vehicle route navigation scheme, and value of utility is the highest, and navigation scheme is the best, traffic Situation is the best.When likely navigation scheme value of utility U obtain after, select optimum utility value U_maxPath navigation scheme Carry out vehicle guidance, it is achieved that optimal communication navigation.But for a large size city road network, all possible path is led Boat scheme number is huge, when using common computer to carry out calculating search, owing to calculating speed and the restriction of search speed, The real-time of whole road network vehicle scheduling cannot be realized.In finite time, search out optimal navigation scheme just there is actual application It is worth.Therefore, the present invention proposes a kind of urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method RGQS, as Shown in Fig. 2, RGQS method flow asks for an interview table 3；RGQS method is by UVCQC algorithm and RUNQS Algorithm constitution.Quantum computer is also The search capability of row ability and quantum search algorithm breaches calculating speed and the restriction of search speed, it is achieved that whole road network The real-time of path navigation.

Table 3 RGQS method flow

If being total to n car in road network, numbering is respectively V₁,V₂,...,V_n, either car V_iAll there is the beginning and end of self, Between beginning and end, optional path has one or some, and it is that the driver that meets that driver selects wants that these paths are system The path asked, if the optional number of path of this n car is respectively b₁,b₂,...,b_n, path crossing set expression, V_i,jRepresent i-th The j-th strip path of car, a path navigation scheme is exactly to extract the set of a paths for each car, such as set(wherein, a_i(i=1,2 ..., n) represent the optional path of any bar in i-th car) it is a kind of road Footpath navigation scheme.

Path navigation scheme and its value of utility one_to_one corresponding, path navigation scheme is independent variable x, and value of utility U is function, its Functional relationship represents as shown in formula (5).

U (x)=P (x)-C (x) (5)；

Wherein, independent variable x span isX form bit 0 and 1 in a computer represents, each x Value uniquely represent a path navigation scheme, for apparent expression, the binary digit of path navigation scheme x need represent Go out the path selected by each car, then the optional path of each car is both needed to the binary digit of some and represents, take to meet and be somebody's turn to do Formula max{b₁,b₂,...,b_n}≤2^hX is encoded by minimum h value, and the number of path of each car needs h position binary representation, altogether Need n × h position binary system to represent path navigation scheme number, if vehicle number scale is 1000, the path of each car with 3 codings, Then needing 3000 to represent a kind of path navigation scheme, the space that storing these schemes needs is 2³⁰⁰⁰Individual bit.Classic computer Cannot store, more cannot calculate.And quantum computer has the performance of brilliance in data storage and concurrent operation, due to folded Add the existence of state, the data theory that 3000 quantum bits can store is 2³⁰⁰⁰Bit, for classic computer, amount The storage capacity of sub-computer, almost without the upper limit, therefore can solve the storage problem of path navigation scheme, and quantum calculation The superior performance of machine is (to operate continuous variable parallel computation truly to all independent variables simultaneously, run one Secondary obtain all functional values).Therefore the parallel computation problem of value of utility can be solved.

In quantum computer, the ultimate unit of storage is state, in classic computer only 0 and 1 two kind of state, and at quantum meter There is superposition state in calculation machine, i.e. exist can the most non-zero superposition state of the most non-1, therefore in classic computer one 3000 Binary system is only capable of representing a kind of path navigation scheme x_i, and 3000 quantum bits can represent 2 in quantum computer³⁰⁰⁰Plant road Footpath navigation scheme, as long as this quantum state is not observed, it is believed that these are 2 years old³⁰⁰⁰Plant path navigation scheme to be stored, quantum meter simultaneously Calculation machine is especially suitable for the storage to these continuous variables, and every kind of path navigation scheme all exists with same probability, this Probability represents with probability amplitude σ in quantum mechanics, square σ of certain path navigation scheme probability amplitude²Equal to this path navigation side The probability (at the probability that outfan is observed) that case can be output.

Present invention independent variable x represents path navigation scheme, and function U (x) represents the value of utility of this navigation scheme, at quantum In computer, both of which quantum state represents, respectively with two depositor storages, independent variable x initializes as shown in formula (6).

$|x>=\frac{1}{\sqrt{2^{n\&times;h}}}\left(\right|0>+|1>+|2>+...+|2^{n\&times;h}-1>)---\left(6\right)$

As it is shown on figure 3, path navigation scheme is determined by the starting and terminal point information of vehicle number n and vehicle, binary system can be used Coding schedule illustrates all path navigation schemes, and the sum of navigation scheme is less than or equal to 2^n×h, make S=2^n×h, therefore with S quantum State can completely represent all of path navigation scheme.Independent variable x etc. power superposition state (the most all of path navigation scheme) be The input of quantum calculation, in formula (6)Represent probability amplitude σ (its square of σ that path navigation scheme exists²Represent respective path The probability of navigation scheme), S state represents N number of path navigation scheme x value, wherein S=N respectively, and all path navigation schemes exist Existence probability in superposition state isQuantum state in formula (6) is shorthand, such as state | 0 > reallyAll states Total bit be n × h position, n represents vehicle number, and wherein the selectable path of each car is all with h position binary representation, such as i-th Individual h position full 0 represents that the path selected by i-th car is Article 1 (numbered 0), and this S quantum state illustrates all of road comprehensively Footpath navigation scheme, storage and the input of path navigation scheme all can effectively solve.The calculating of function U (x) in UVCQC algorithm As shown in formula (7).

$\begin{array}{c}U\left(x\right)=Fr\left(x\right)\&times;(\mathrm{\&alpha;}1\&times;Rs(x)+\mathrm{\&alpha;}2\&times;S1(x)+\mathrm{\&alpha;}3\&times;Ls(x)+\mathrm{\&alpha;}4\&times;Os(x)+\mathrm{\&alpha;}5\&times;Fd(x\left)\right)-\\ (\mathrm{\&beta;}1\&times;Ta(x)+\mathrm{\&beta;}2\&times;Tc(x)+\mathrm{\&beta;}3\&times;De(x)+\mathrm{\&beta;}4\&times;Oc(x)+\mathrm{\&beta;}5\&times;T1(x\left)\right)\end{array}---\left(7\right)$

Carrying out different quantum calculations and need different quantum wires, quantum wire need to determine according to function, at quantum meter Calculation machine must use during operation function unitary transformation U_f, subscript f refers to certain function, and different unitary transformations uses different Quantum wire, also needs to by an auxiliary quantum bit in quantum computer | z > and realize unitary transformation and obtain function, tool Body calculates shown in process such as formula (8).

$U_f|x>|z>=|x>|z\&CirclePlus;f\left(x\right)>---\left(8\right)$

In this converts, for a specific output, input is unique.

As shown in Figure 3, it is determined that after value of utility function U (x), suitable quantum wire and auxiliary quantity need to be set according to U (x) Sub-bit realizes unitary transformation, and corresponding utility function value U (x) of the i.e. independent variable x of each state, all of independent variable performs simultaneously Same operation, completes the calculating of value of utility parallel, quantum-mechanical character can obtain its calculating process such as formula (9) institute Show.

$U_{U\left(x\right)}|x>|z>=|x>|z\&CirclePlus;U\left(x\right)>---\left(9\right);$

The specific circuit of quantum calculation runs shown in the such as formula of result once (10).Fig. 4 be UVCQC algorithm quantum also Row calculates process once.

$\frac{1}{\sqrt{S}}\left(\right|0>\left|U\right(0)>+|1>\left|U\right(1)>+...+|S-1>\left|U\right(S-1)>)---\left(10\right);$

All of U value is stored in another depositor, it is assumed that observe in independent variable one end | i >, then storage U value Depositor also collapse is | U (i) >, after observing i, the value that the depositor of storage U value observes be the probability of U (i) be 1, anti-mistake Also as being.Analyzed by above, UVCQC algorithm flow can be obtained as shown in table 4.

Table 4 UVCQC algorithm

The aforementioned acquisition solving each influence factor of value of utility U and calculating, although but quantum computer can carry out also Row calculates, but the extraction of result is but not easy to, and must be single output, i.e. quantum computer can calculate all The value of utility of navigation scheme, but collapse it is bound to when outfan is observed, and the value of utility that may finally obtain output only has one Individual.And city road network path navigation problem is had only to obtain a kind of optimal path navigation scheme, therefore have only to obtain A corresponding value of utility (optimum utility value).Aforementioned obtain the value of utility that magnanimity is unordered, and quantum meter at present Calculation machine has scanned for efficient algorithm, i.e. quantum search algorithm to the data that magnanimity is unordered.But quantum search algorithm The feelings of (target state refers to need the state of search, the state that referred to optimum utility value is corresponding) can only be solved it has been determined that target state Condition, and cannot absolutely search for successfully, in order to adapt to the solution of practical problem, the present invention proposes a kind of road network value of utility amount Sub-searching algorithm RNUQS, it is therefore an objective to from the quantum superposition state of the aforementioned value of utility function obtained | U (x) > search and conform to The value of utility asked, and obtain the path navigation scheme of correspondence.

Superposition state is weighed in waiting of aforementioned acquisition value of utility, and path navigation problem is converted into an optimal result search problem, searches The collection of rope be combined into { | U > }=| U (0) >, | U (1) > ..., | U (N-1) > }, the number of value of utility state is S, and target state (i.e. needs The state of output) it is U_max(maximum value of utility), target state is unknown, therefore can not directly be obtained by quantum search algorithm Maximum value of utility and corresponding path navigation scheme, the present invention proposes a kind of RNUQS algorithm.In true road network, no The minimum value of utility blocked up can be produced and may be considered a fixing empirical value k, then more than the value of utility of empirical value k To export as result, it is assumed that the value of utility number more than empirical value k is m, then any one in this m is satisfied by output bars Part.

Target state number is to be used in m, RNUQS algorithm determining that the function of target state is referred to as instructing function, makes y=U (x), What RNUQS used instructs shown in function such as formula (11).

$f\left(y\right)=\left\{\begin{array}{cc}1,& \begin{array}{cc}if& y\&GreaterEqual;k\end{array}\\ 0,& else\end{array}\right.---\left(11\right)$

Value of utility function state | U (x) > after instruct criteria function, functional value f (x) be the state of 1 be target state, m Target state is locked therewith, and whether RNUQS algorithm is 1 to judge whether this state is target state by functional value corresponding to state, RNUQS Algorithm can obtain correct output by promoting target probability of state width.

In search procedure with instruct function check each value of utility whether be target state, then by Grover conversion expand Big target probability of state width improves the probability of target value of utility state output, as it is shown in figure 5, G represents that Grover converts in figure, below Elaboration in be called for short G conversion, carry out G conversion and be i.e. by once specific Quantum Iteration, convert through the G of certain algebraically After, target value of utility probability of state rises to a certain degree, finally with close to 1 probability output, thus obtain suitable target Value of utility state.

Wherein, G=DO, O represent and instruct inquiry, it is assumed that | U_a> it is target state, unitary will be performed after instructing inquiry and become Change I-2 | U_a><U_a|, this operation will not be performed if non-targeted state, so shown in the calculating of O such as formula (12).

O=I-2 | U_a><U_a| (12)

Shown in the calculating of D such as formula (13).

WhereinIt is that waiting of all basic status weighs superposition state,H represents that Hadamard conversion (is used Hadamard gate realizes), it is used for power superposition states such as preparing,Represent that preparing waiting of n × h position weighs superposition state.Initial waits power Superposition state every time through G convert after target value of utility probability of state width increase a bit, non-targeted value of utility state then reduces a bit, warp After crossing the G conversion of certain iterations, the output probability of target value of utility state, close to 1, now can be observed at outfan, obtain Suitably value of utility.

In order to be more fully understood that a G converts role, a G conversion can regard the quantum state amount at two-dimensional space as Son conversion, is divided into two steps, is O conversion and D conversion respectively.If Fig. 6 (a) is the geometric representation of G conversion, Fig. 6 (b) be into OKThe geometric representation of secondary G conversion, | U_a> it is target state, this superposition state of current superposition state projective representation in target state The output probability width of middle target state, often converts through a G, and original state rotates 2 θ angles to target state, as shown in Fig. 6 (a),Shown in process such as Fig. 6 (b) of secondary G conversion, in Fig. 6 (a), angle [alpha] is any acute angle, Fig. 6 (a) and the angle, θ phase of 6 (b) Deng ()。

In Fig. 6 (a),It is that superposition state is weighed in initial waiting, | U_t> representing the most current state, all of G conversion is all right | U_t> Convert, | U_a> representing the sum of all of target state, it calculates shown in process such as formula (14).

$|U_a>=\frac{1}{\sqrt{m}}\underset{i=0}{\overset{m-1}{\&Sigma;}}|a_i>---\left(14\right)$

a_iRepresent target state,Represent | U_a> orthogonal state, with | U_a> vertical, | U_t> withAngle be set to α,WithAngle be θ, wait power superposition stateIn target state | U_aProjection (probability amplitude) on > is Meaning is to wait Observe that target probability of state is sin under power superposition state²θ=m/N, current state is | U_t>, converting through a G, current state converts For O | U_t>, | U_t> and O | U_t> aboutSymmetry, O | U_t> convert through a D again, it is transformed to G | U_t>, O | U_t> and G | U_t> close InSymmetry, is not difficult to calculate according to angular relationship, G | U_t> with | U_t> angle be 2 θ, unrelated with α, often convert through G, when Front state rotated counterclockwise by angle 2 θ.

Due to value of utility state | U > the power superposition state such as it is initially in, after i G converts, withAngle become (2i+ 1) θ, in order to make target state with close to 1 probability output, (2i+1) θ ≈ 1 should be made, wherein CalculateRound represents immediate integer, and the most only need to carry out i conversion can search Suitably target value of utility, required time complexity is only

From the calculating of i value it can be seen that due to i can only round numbers, finally can obtain target probability of state and simply connect very much Nearly 1, therefore there is the possibility made mistakes, in actual path navigation, mistake is not allowed to.For this problem, this Invention proposes a kind of quantum error detection strategy (Quantum Error Detection Strategy, QEDS), QEDS strategic process As shown in table 5.Empirical value k only can guarantee that an appropriate output, but output cannot ensure enough to optimize, at practical situation In can set a preferable empirical value k_m, repeatedly search for, meeting the maximum time limit t of real-time_maxOn the premise of, Search the most repeatedly, if used time of search is t_c, having spent the time is t_s(being initially 0).

Table 5 QEDS strategy

Thus, the RNUQS algorithm flow that the present invention proposes is as shown in table 6.

Table 6 RNUQS algorithm

It should be appreciated that the part that this specification does not elaborates belongs to prior art.

It should be appreciated that the above-mentioned description for preferred embodiment is more detailed, can not therefore be considered this The restriction of invention patent protection scope, those of ordinary skill in the art, under the enlightenment of the present invention, is weighing without departing from the present invention Profit requires under the ambit protected, it is also possible to make replacement or deformation, within each falling within protection scope of the present invention, this The bright scope that is claimed should be as the criterion with claims.

Claims (5)

1. a urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method, is mapped to model by true road network Figure R (B, E), wherein B represents junction node set, B_i(i=1,2 ..., r) representing single junction node, r is total crossing number, E Represent the section set in band direction；Assume this road network has n car, either car w have current starting point P_sWith destination eventually Point P_d, then certain feasible path continuous adjacent junction node of this car is expressed as { P_s,...,P_i,...,P_d}；Each car all selects Selecting a feasible path, the driving path of all cars forms a feasible path set FPS_n, i.e. one path navigation scheme；

It is characterized in that, said method comprising the steps of:

Step 1: according to vehicle number n, terminal information and the optional path of each car, initializes vehicle collection { v₁,v₂,...,v_n} And optional path collectionWherein v_iRepresent i-th car,Represent in all optional path of i-th car；

Step 2: to vehicle and optional path 0,1 thereof ..., b_iCarry out quantum coding | 0 >, | 1 > ..., 2 |^n×h-1 > }, determine Quantum state can completely represent all of path navigation scheme；Wherein b_iRepresenting the optional number of path of i-th car, h represents optional The minimum number of bits that path code needs；

Step 3: determine the independent multiplication factor α of each influence factor according to traffic information_i, β_j, determine that value of utility calculates function U (x)；Wherein every kind of path navigation scheme correspondence independent variable x value；

Step 4: for preparing path navigation scheme waits power superposition state | x >, calculate the value of utility that each path navigation scheme x is corresponding | U (x) |, obtain value of utility function waits power superposition state | U (x) >；

Step 5: determine the empirical value k of value of utility, waits power superposition state to value of utility function | U (x) > carry out quantum searching, and search Go out and meet the value of utility required | U_s>；

Step 6: output meets the value of utility U required_sAnd the path navigation scheme of correspondence, each car is carried out path navigation.

Urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method the most according to claim 1, it is special Levy and be, the U of value of utility function described in step 3_(x)For:

U (x)=Fr (x) × (α 1 × Rs (x)+α, 2 × Sl (x)+α, 3 × Ls (x)+α, 4 × Os (x)+α, 5 × Fd (x))-

(β1×Ta(x)+β2×Tc(x)+β3×De(x)+β4×Oc(x)+β5×Tl(x))

Wherein Fr (x) represent section whether can arrive at, take 1 expression up to, take 0 expression unreachable；Rs (x) represents section situation, Value [0,1]；Sl (x) represents that speed limits, value [0,1]；Ls (x) represents section illuminating position, value [0,1]；Os (x) table Show driver's obedient extent to system recommendation, value [0,1]；Fd (x) represents driver's familiarity to section, value [0,1]； Ta (x) represents the road impact that vehicle accident or the temporary control etc. of burst bring, value [0,1]；Tc (x) represents selected path The time cost expended, value [0, ∞]；De (x) represents the distance cost that selected path is expended, value [0, ∞]；Oc (x) table Show the oil mass cost expended in selected path, value [0, ∞]；Tl (x) represents the impact of traffic lights, value [0,1]；α_i(i=1, 2,...,5)、β_i(i=1,2 ..., 5) represent the independent multiplication factor that each influence factor is corresponding respectively.

Urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method the most according to claim 1, it is special Levying and be, implementing of step 4 includes following sub-step:

Step 4.1: the quantum etc. utilizing Hadamard gate to prepare initial argument's path navigation scheme weighs superposition stateWherein N represents quantum state sum；

Step 4.2: the unitary transformation circuit U that design function is corresponding_U(x)And can be used for realizing the auxiliary quantum bit that function calculates | z >；

Step 4.3: superposition state is weighed in waiting of input path navigation scheme, parallel computation function U (x):

U_U(x)| x > | z >=| x > | z U (x) >；

Step 4.4: obtain value of utility function waits power superposition state | U (x) >.

Urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method the most according to claim 1, it is special Levying and be, implementing of step 5 includes following sub-step:

Step 5.1: be given and instruct function f (y) for determine target state, and the quantum wire of correspondence is set；

$f\left(y\right)=\left\{\begin{array}{cc}1,& ify\&GreaterEqual;k\\ 0,& else\end{array}\right.;$

Value of utility function etc. power superposition state | U (x) > after instruct criteria function, functional value f (x) be the state of 1 be target State；

Step 5.2: target state added up, draws target state number m and calculates aggreggate utility value target state | U_a>；

$|U_a>=\frac{1}{\sqrt{m}}\underset{i=0}{\overset{m-1}{\&Sigma;}}|a_i>;$

Wherein, a_iRepresent target state, | a_i> represent i-th target state quantum form, m represent target state sum；

Step 5.3: according to | U_a> determine and instruct inquiry O, determine that O converts；

O=I-2 | U_a><U_a|；

Wherein I represents and | U_a>quantum figure place identical wait power superposition state,<U_a| expression | U_a> conjugate vector；

Step 5.4: according to waiting power superposition stateDetermine that D converts；

Wherein,It is that waiting of all basic status weighs superposition state,H represents that Hadamard converts, and is used for preparing Power superposition state,Represent that preparing waiting of n × h position weighs superposition state；N represents quantum state sum, | i > represent i-th quantum state；

Step 5.5: determined that a G converts G=DO by O conversion and D conversion；

Step 5.6: value of utility function is waited power superposition state | U (x) > carry outSecondary G conversion, round represents Close integer；

Step 5.7: the value of utility state of observation output | U_out> and corresponding path navigation scheme | x_out>, search within the time limit Go out and meet the value of utility required | U_s>；

Step 5.8: output value of utility state | U_s> corresponding path navigation scheme x_sIn the guidance path chosen for each car.

Urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method the most according to claim 4, it is special Levying and be, implementing of step 5.7 includes following sub-step:

Step 5.7.1: the output after having converted G is observed, obtains value of utility U_outWith current search used time t_s；

Step 5.7.2: if t_s<t_max, then following step 5.7.3, wherein t are performed_maxRepresent and can guarantee that path navigation real-time Maximum navigation time interval；Otherwise, following step 5.7.5 is performed；

Step 5.7.3: if U_out＜ k, then t_s=t_s+t_c, and turn round execution described step 5.7.2, wherein t_cRepresent and perform once Time required for described urban road network Real-time and Dynamic Multiple Intersections path navigation quantum searching method；Otherwise, perform following Step 5.7.4；

Step 5.7.4: if fruit U_out＜ k_m, then k=U_out, t_s=t_s+t_c, and turn round execution described step 5.7.2, wherein k_mRepresent The preferable value of utility rule of thumb set；Otherwise, following step 5.7.5 is performed；

Step 5.7.5:U_s=U_out, export U_s。