CN104596534A - Method for calculating optimum driving path - Google Patents
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Abstract
The invention discloses a method for calculating an optimum driving path. The method comprises the following steps: firstly collecting stroke data of current entry of each vehicle-mounted intelligent terminal by virtue of an information centre; inputting a starting point, a finishing point and a scheduled arrival time on the intelligent terminal by a user before driving; searching from an internal database of the intelligent terminal or transferring the database of the information center and transferring the driving path data meeting the requirement; automatically adapting the driving path; screening factors with the absolute values which are minimal and are closest to a target driving time in a driving time range required by that day by the intelligent terminal by virtue of internal calculation as the final target data; and arranging in a descending manner according to the driving time and displaying the preferable path on the vehicle-mounted intelligent terminal according to rankings and finally screening by the user. According to the method, the intelligent terminal has the characteristics of self-record and self-calculation. Based on self resources assisted by Internet data, real-time networking is not required, and the problems of removing signal interference and network flow are solved.
Description
Technical field
The invention belongs to road traffic navigation field, be specifically related to a kind of method automatically calculating optimum driving path on onboard system.
Background technology
Along with social automobile purchase power and resident trip are ridden growing with each passing day of demand, urban traffic road conditions face increasingly serious challenge; Same fixing section has very large difference at the throughput of whole day different time vehicle, especially the peak time on and off duty in city, rely on single stroke length to carry out routing and can not meet the popular demand that driving efficiency, trip are experienced, and old-fashioned distance computing method, inapplicable current user's request.
Chinese invention patent " the vehicle optimal path air navigation aid based on car networking " (publication number 102708698A), by arranging dynamic contact matrix in order to indicate road network connection state, the optimal path that traffic surveillance and control center is travelled by the ant colony optimization for solving vehicle improved according to OD information and dynamic contact matrix in road network, make vehicle energy real-time response emergency situations, reach the object improving navigation levels of precision and improve vehicle operating efficiency.This invents around internet as the backstage that data calculate, and rely on internet to upload download in real time to carry out work, using the shortest traveling distance as the unique conditional judging to select, but when there is path congestion, need real-time interconnection to download road conditions jam situation and just can avoid the peak that blocks up, and can not judge peak period in wagon flow voluntarily, evade congested link, but not only there is signal disturbing in real-time interconnection, network traffics, the problems such as flow velocity, and download road conditions jam situation there is certain hysteresis quality online, can not ensure that the road conditions real-time embodying of last second is in download road conditions, not accomplish real real-time.
Chinese invention patent " intelligent algorithm of urban optimal path navigation " (publication number 103134504A), that road in city is divided into different weights by far and near distance and the unobstructed situation of traffic, be then far and near preferential according to the selection of user or traffic is unobstructed preferentially consider after provide best path navigation scheme for user; Simultaneously in order to avoid causing new road congestion due to similar navigation scheme, record being carried out to the road that every bar is selected, paying the utmost attention to the road be not recorded or the few road of access times when forming guidance path.This algorithm, according to " navigation road far and near distance ", " the unobstructed situation of traffic " two factors, is combined into two-dimensional function, and it is preferred to carry out path.One section " motorist has four bar navigation path A, B, C, D optional from departure place X to destination Y, wherein the road of path A, B, D did not use, and weight is 1, and the road of path C has been previously used " is had to can be understood as two kinds of implications in original text:
1. interconnection network, the road getting A, B, D did not use, the used information of C;
2. according to self in the past travelling data record queries arrive, new in the past road A, B, D did not use, and C is the usual road travelled;
Understanding analysis according to thinking 1 is: each use all needs interconnection network, acquisition approach record, and internet data has ageing, can not ensure that same section of distance is consistent with initial internet hunt road conditions after traveling certain hour, therefore easily cause navigation results not to be optimum;
May might not meet optimum driving path due to untapped road according to thinking 2, cause calculating path out of true.
To sum up, there is heavy dependence internet data in current airmanship, lack independent navigation ability, there is limitation and cause routing out of true in algorithm, and user does not select for running time, such as when client prepares to go to fulfill an appointment on time, do not require to arrive destination as early as possible, but wish reaching on the time, current navigational system does not realize this personalized customization function, so, existing navigation market can to running time in the urgent need to one, operating range is effectively arranged in pairs or groups, can reasonable computation traffic path more, realize the new vehicle mounted guidance computing method of lower oil consumption.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of method calculating optimum driving path, and the method is based on inside from gathering, certainly calculating driving path data, and internet uploading data is auxiliary; Using running time as optimal selection, travel distance as campaigning item, realize driving path most preferably.
A kind of method calculating optimum driving path of the present invention, it comprises the following steps:
Calculate the method in optimum driving path, it is characterized in that comprising the following steps:
1) data of start of a run A that each vehicle intelligent terminal records in routine use B are to terminal collected by the information center of navigation information system, wherein each trip period of 24 hours in one day are defined as α; The traveling distance β determined according to different traffic route, filters out the link travel time of specific starting point to terminal, repeatedly within many days, gathers, and gathers the average running time γ trying to achieve the different trip periods;
2) by step 1) one day trip period α in 24 hours, travel distance β, average running time γ is arranged as a three-dimensional matrice M=[α, beta, gamma];
①M＝M[α，β，γ]＝M[α，(β，γ)]
Wherein α represents the period in 1 day 24 hours, and β, γ are due to the implication of himself, can also form another two-dimensional matrix N, and is expressed as follows:
So in conjunction with formula 2., following relational expression can be derived:
③M＝M[α，β，γ]＝M[α,N(β,γ)]
By wireless or wired mode, the back-end data of above-mentioned array M and representative thereof is inputted the internal database of each vehicle intelligent terminal;
3) user is before traveling, and first on vehicle intelligent terminal, input driving starting point, terminal, plan arrive destination time, then carry out internal database lookup by vehicle intelligent terminal, and call satisfactory driving path data three-dimensional matrix M; As internal database not this three-dimensional matrice M, the then satisfactory driving path data of the database lookup at recalls information center, synthesis three-dimensional matrice M after downloading;
4) after vehicle intelligent terminal obtains driving path data three-dimensional matrix M, automatic adaptation driving path, on average travel time factor γ by the many days accumulated weights travelling section at this moment between distance β and objective between two objectives when travel period ɑ is steady state value and form two-dimensional function matrix N
5) filtered out self absolute value within the scope of the travel period that needed the same day by internal calculation minimum and closest to the factor of target running time for vehicle intelligent terminal, as final goal data; According to the speed limit of road different in constitutional law provisioning request, selected path is screened simultaneously, arrange from big to small according to running time value, and according to rank display preferred path on vehicle intelligent terminal, do final screening by user.
Above-mentioned steps 3) in, the detailed process that the database lookup satisfactory driving path data three-dimensional matrix M at vehicle intelligent terminal recalls information center is also downloaded is:
3.1) first, current vehicle intelligent terminal disintegrate driving path, is decomposed into several continuous print roadways by driving path;
3.2) through its data library searching comparison, when finding that the present period of wherein several roadways has record, and all the other roadway no records;
3.3) current vehicle intelligent terminal calls the traveling record that its data storehouse has;
3.4) current vehicle intelligent terminal sends the travelling data request of no record roadway at present period to information center;
3.5) information center's heart database search in the information;
3.6) there are the no record roadway data of present period in the history driving recording that information center uploads before searching other vehicle intelligent terminals, then going to step 3.11 as do not searched data;
3.7) call these data, return to current vehicle intelligent terminal;
3.8) current these data of vehicle-mounted intelligent terminal for reception;
3.9) current vehicle intelligent terminal carries out inside synthesis, realizes the total travel travelling data record after present period gathers;
3.10) driving path data three-dimensional matrix M is calculated after integrating;
3.11) when the current intelligent terminal of discovery and other intelligent terminals all driving recording data needed for no user have been searched for by information center, the then automatic connecting Internet of information center, carry out dynamic map download and correlation data calculation, repeat step 2), carry out routing.
Above-mentioned steps 4) in N detailed meanings annotate as follows:
β travels distance; The average running time of γ, as above formula 2.
Setting β 1 γ 1=a11; β 2 γ 1=a21; β 1 γ 2=a12 ... β Q γ P=aQP;
Following formula can be drawn:
Wherein between β P γ Q and aPQ, transformational relation is
Setting: representated by β---the absolute value x that it is unit that-traveling distance is converted into " kilometer ";
Representated by γ---the absolute value y that it is unit that-average running time is converted into " minute ";
Derive following formula:
⑤N(β,γ)＝(β1γ1,β1γ2,β2γ1…βPγQ)＝(x1+y1,x1+y2,x2+y1…xP+yQ)＝(a11,a12,a21…aPQ)P,Q∈(1,2,3…∞)
So be also just deduced formula 6.
⑥xP+yQ＝aPQ P,Q∈(1,2,3…∞)。
Above-mentioned steps 5) detailed process be: vehicle intelligent terminal is filtered out in above-mentioned array by internal calculation, the same day need travel time period α m, m ∈ (1,2,3 ... ∞), self absolute value is minimum and closest to factor aij, the asd of target running time in scope, i wherein, j, s, d belong to P, Q array, the aij marked under simultaneously calling the α m period, travelling data representated by asd, backstage is converted to concrete traffic route, embodies as follows:
aij＝xi+yj＝βiγj；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)
Wherein β i γ j must meet 7. under Metzler matrix period α m condition simultaneously, 8. two conditions:
⑦xi+yj≤xP+yQ，aij≤aQP，βiγj≤βPγQ
β i γ j perseverance wherein under the α m period is less than or equal to the β P γ Q value in any one N matrix;
8., simultaneously when there being the factor equal with aij result in Metzler matrix, the certain perseverance of yj is less than the absolute value that in this group factor, time factor changes into;
The wherein computing formula of target running time: T
user plans to arrive destination time-T
user's actual time of departure=∣ △ T ∣=T
marktime mutatis mutandis
⑨asd＝xs+yd＝βsγd s,d∈(1,2,3…∞)
10. yd=∣ △ T ∣
or closest to∣
△t ∣, Qi Zhong ∣ △ T ∣=T
user plans to arrive destination time-T
user is actual departure time=T
the standard used time
Separately, must not more than 120 kilometers/hour according to constitutional law provisioning request highway flank speed; National highway, provincial highway flank speed more than 60 kilometers/hour, must not must meet following 2 points simultaneously:
(1) fastlink screening must meet: ∣ x/y ∣ <1 unit: kilometer/minute
(2) national highway, provincial highway screening must meet: ∣ x/y ∣ <2 unit: kilometer/minute.
Path representated by aij, asd is screened, arranges from big to small according to y value, and according to rank display preferred path on vehicle intelligent terminal, do final screening by user.
Beneficial effect of the present invention:
The present invention adopt " time " * " distance "=" optimal path " and algorithm, abandon the old-fashioned method that single dependence shortest path calculates traffic route, all distances between comprehensive origin to objective, certainly Different periods (comprising on and off duty blocking up the period) in a day that gathers in foundation driving conditions, the average running time of corresponding distance carries out preferably, and it is integrated ordered, this method makes intelligent vehicle mounted terminal possess from record, from the feature of computing, can be mutual but do not rely on internet with internet, gather different mobile unit, image data between different target section, by network timing information upload center, when vehicle-mounted self information base resource is not enough, also the Internet download latest data storehouse can be passed through in real time, carry out internal resource coupling, optimal route selection.Because internet uploading data is auxiliary, do not need real-time interconnection, get rid of signal disturbing, the problems such as network traffics.
Compared with " intelligent algorithm of urban optimal path navigation " (publication number 103134504A), two inventions have an important factor N actual travel distance, and " intelligent algorithm of urban optimal path navigation " relies on M average vehicle flow and N distance to carry out two-dimentional balance exclusive method, the present invention uses three-dimensional " travel period α ", " travel distance β ", " average running time γ " carries out three-dimensional matrice screening method, in conjunction with the method finally leaving hommization selection space, screening optimal route, because consider multiple factors, operation matrix is also changing into three-dimensional, and eliminate can vicissitudinous labile factor in time from calculating vehicle flowrate M, this method adopts to be checked user and wishes duration (user perhaps wishes that running time is slightly long sometimes, this method can hommization, control, folding and unfolding running time) after press again travel period distinguish, be weighted distance, the control methods of time, instead of simple weighted is from calculating road occupation weight and road distance, the method is simpler, reliably, rigorous.
Accompanying drawing explanation
Fig. 1 is embodiment middle rolling car route map,
Fig. 2 is process flow diagram of the present invention,
Fig. 3 is vehicle intelligent terminal recalls information centre data library lookup of the present invention satisfactory driving path data flowchart.
Embodiment
Below in conjunction with Fig. 1, the invention will be further described.
Existing invention calculates optimal path many employings one dimension standard short line optimum seeking method; Illustrate: as Fig. 1, starting point a has three paths to terminal between b: acb, adb, ab; Wherein ab sections of road distance is less than acb section, i.e. xab<xacb, but at a certain special time, running time yab>yacb, as continued to use present invention, navigation still can select ab section to recommend as optimum, and this method in car peak period of being obviously expert at is also inapplicable.And this method adopts three-dimensional standard M [α, beta, gamma], driving route is added up, wherein each trip period of 24 hours in one day is defined as α; The traveling distance β determined according to different traffic route, filters out the link travel time of specific starting point to terminal, repeatedly within many days, gathers, and gathers the average running time γ trying to achieve the different trip periods; .Usage factor yab is as main traffic route screening criteria, its complementary divisor is as assisting sifting standard, this makes it possible to calculate more accurately optimum driving path, this method more always invent more energy-conservation, save time and keep need not in real time interconnection network, can according to the real needs hommization selecting paths of end user.
Such as: departure times: 18:00-19:00 period 1Day, 2Day, 3Day ... nDay
Running time: Day1:t1, t2, t3
Day2:t4,t5,t6
Day3:t7,t8,t9
……
Day n:t(n-2),t(n-1),tn
The concrete service time that t representative travels
Conclusion: in this period of the 18:00-19:00 of every day
Distance acb average running time=(t1+t4+t7+ ... + t (n ?2))/n=y1; Travel distance x1;
Distance adb average running time=(t2+t5+t8+ ... + t (n ?1))/n=y2; Travel distance x2;
Distance ab average running time=(t3+t6+t9+ ... + tn)/n=y3; Travel distance x3;
Wherein (y1, y2, y3) belongs to gamma matrix; (x1, x2, x3) belongs to β matrix category;
Adopt the screening of α travel period, the result of γ and β weighting, choose absolute value minimum and closest to the combinations of factors of target running time as preferred path, and finally to be undertaken according to self hobby hommization selection by user.
From reasoning above, the trip period in one day, traveling distance, the average Time alignment that travels can be become a three-dimensional matrice M=[α, beta, gamma];
①M＝M[α，β，γ]＝M[α，(β，γ)]
User is before traveling, and first on vehicle intelligent terminal, input driving starting point, terminal, plan arrive destination time, then carry out internal database lookup by vehicle intelligent terminal, and call satisfactory driving path data three-dimensional matrix M; As internal database not this three-dimensional matrice M, the then satisfactory driving path data of the database lookup at recalls information center, synthesis three-dimensional matrice M after downloading;
After vehicle intelligent terminal obtains driving path data three-dimensional matrix M, automatic adaptation driving path, by between two objectives between running distance factor-beta and objective at this moment many days accumulated weights of section on average travel time factor γ and form two-dimensional function matrix N, its detailed meanings is annotated as follows:
Setting β 1 γ 1=a11; β 2 γ 1=a21; β 1 γ 2=a12 ... β Q γ P=aQP;
Draw following formula:
Wherein between β P γ Q and aPQ, transformational relation is:
Setting: representated by β---the absolute value x that it is unit that-traveling distance is converted into " kilometer ";
Representated by γ---the absolute value y that it is unit that-average running time is converted into " minute ";
Derive following formula:
⑤N(β,γ)＝(β1γ1,β1γ2,β2γ1…βPγQ)＝(x1+y1,x1+y2,x2+y1…xP+yQ)＝(a11,a12,a21…aPQ)P,Q∈(1,2,3…∞)
So be also just deduced formula 6.
⑥xP+yQ＝aPQ P,Q∈(1,2,3…∞)
Vehicle intelligent terminal is filtered out in above-mentioned array by internal calculation, needs the time period α m travelled the same day, m ∈ (1,2,3 ... ∞), self absolute value is minimum and closest to the factor aij of target running time in scope, asd (i wherein, j, s, d belongs to P, Q array,), the aij marked under simultaneously calling the α m period, the travelling data representated by asd, backstage is converted to concrete traffic route, embodies as follows:
aij＝xi+yj＝βiγj；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)
Wherein β i γ j must meet 7. under Metzler matrix period α m condition simultaneously, 8. two conditions:
⑦xi+yj≤xP+yQ，aij≤aQP，βiγj≤βPγQ
β i γ j perseverance wherein under the α m period is less than or equal to the β P γ Q value in any one N matrix;
8., simultaneously when there being the factor equal with aij result in Metzler matrix, the certain perseverance of yj is less than the absolute value that in this group factor, time factor changes into;
The wherein computing formula of target running time: T
user plans to arrive destination time-T
user's actual time of departure=∣ △ T ∣=T
marktime mutatis mutandis
⑨asd＝xs+yd＝βsγd s,d∈(1,2,3…∞)
10. yd=∣ △ T ∣
or closest to∣
△t ∣, Qi Zhong ∣ △ T ∣=T
user plans to arrive destination time-T
user is actual departure time=T
the standard used time
Separately, must not more than 120 kilometers/hour according to constitutional law provisioning request highway flank speed; National highway, provincial highway flank speed more than 60 kilometers/hour, must not must meet following 2 points simultaneously:
(1) fastlink screening must meet: ∣ x/y ∣ <1 unit: kilometer/minute
(2) national highway, provincial highway screening must meet: ∣ x/y ∣ <2 unit: kilometer/minute
Path representated by aij, asd is screened, arranges from big to small according to y value, and according to rank display preferred path on vehicle intelligent terminal, do final screening by user.
The detailed process that the database lookup satisfactory driving path data three-dimensional matrix M at vehicle intelligent terminal recalls information center is also downloaded is:
3.1) first, current vehicle intelligent terminal disintegrate driving path, is decomposed into several continuous print roadways by driving path;
3.2) through its data library searching comparison, when finding that the present period of wherein several roadways has record, and all the other roadway no records;
3.3) current vehicle intelligent terminal calls the traveling record that its data storehouse has;
3.4) current vehicle intelligent terminal sends the travelling data request of no record roadway at present period to information center;
3.5) information center's heart database search in the information;
3.6) there are the no record roadway data of present period in the history driving recording that information center uploads before searching other vehicle intelligent terminals, then going to step 3.11 as do not searched data;
3.7) call these data, return to current vehicle intelligent terminal;
3.8) current these data of vehicle-mounted intelligent terminal for reception;
3.9) current vehicle intelligent terminal carries out inside synthesis, realizes the total travel travelling data record after present period gathers;
3.10) driving path data three-dimensional matrix M is calculated after integrating;
3.11) when the current intelligent terminal of discovery and other intelligent terminals all driving recording data needed for no user have been searched for by information center, the then automatic connecting Internet of information center, carry out dynamic map download and correlation data calculation, repeat step 2), carry out routing.
Wherein as Fig. 3, intelligent terminal B, intelligent terminal C can also coordinate with information center, use above logical method to call the driving demand without historical record, design.
As follows according to Fig. 3 relational expression that can contact: wherein the upper α of figure is 24 hours every days fixing period, and the functional relation that above graphical representation goes out is:
①xA‐b‐B＝xAb+xB；
②xb‐c‐C＝xbc+xC；
③xc‐A‐a＝xcA+xA；
Wherein x is for travelling distance β, and calling of average running time γ is meticulousr, calls and is analyzed as follows:
As 1. section AbB is decomposed into Ab, B two sections of distances by formula, user's intelligent vehicle mounted terminal is through calculating, at α m, m ∈ (1,2,3 ... ∞) the period, travel in Ab section, and when user drives to B section, be in the α n in Metzler matrix, n ∈ (1,2,3 ... ∞) the period, then the yAb value of segment record when the calculating of running time γ needs to call α m in AbB system-wide journey, with the yB value of segment record during α n, so can not represent by computing formula above simply.So as can be seen from Figure 3, when selecting paths AbB, incidental correlation factor has α m in α, α n period, xAb, xB in the β factor, yB value under yAb, α n period in the γ factor under the α m period;
1. can derive from formula: when driving, the conventional path of registering instrument self record can be applied on the path never crossed, empirically innerly extrapolates a new driving path.
In addition, also there will be a kind of situation, when information center cannot search related data, system can spontaneous connecting Internet Google Maps, as shown in Figure 2, carry out route searching, and then according to time period, traveling distance, running time three elements Integrated Selection, according to above-named formula for user selects optimal path.
Embody rule approach of the present invention is a lot, and the above is only the preferred embodiment of the present invention, should be understood that; for those skilled in the art; under the premise without departing from the principles of the invention, can also make some improvement, these improvement also should be considered as protection scope of the present invention.
Claims (4)
1. calculate the method in optimum driving path, it is characterized in that comprising the following steps:
1) data of start of a run A that each vehicle intelligent terminal records in routine use B are to terminal collected by the information center of navigation information system, wherein each trip period of 24 hours in one day are defined as α; The traveling distance β determined according to different traffic route, filters out the link travel time of specific starting point to terminal, repeatedly within many days, gathers, and gathers the average running time γ trying to achieve the different trip periods;
2) by step 1) one day trip period α in 24 hours, travel distance β, average running time γ is arranged as a three-dimensional matrice M=[α, beta, gamma];
①M＝M[α，β，γ]＝M[α，(β，γ)]
Wherein α represents the period in 1 day 24 hours, and β, γ are due to the implication of himself, can also form another two-dimensional matrix N, and is expressed as follows:
So in conjunction with formula 2., following relational expression can be derived:
③M＝M[α，β，γ]＝M[α,N(β,γ)]
By wireless or wired mode, the back-end data of above-mentioned array M and representative thereof is inputted the internal database of each vehicle intelligent terminal;
3) user is before traveling, and first on vehicle intelligent terminal, input driving starting point, terminal, plan arrive destination time, then carry out internal database lookup by vehicle intelligent terminal, and call satisfactory driving path data three-dimensional matrix M; As internal database not this three-dimensional matrice M, the then satisfactory driving path data of the database lookup at recalls information center, synthesis three-dimensional matrice M after downloading;
4) after vehicle intelligent terminal obtains driving path data three-dimensional matrix M, automatic adaptation driving path, on average travels time factor γ by the many days accumulated weights travelling section at this moment between distance β and objective between two objectives when travel period ɑ is steady state value and forms two-dimensional function matrix N;
5) filtered out self absolute value within the scope of the travel period that needed the same day by internal calculation minimum and closest to the factor of target running time for vehicle intelligent terminal, as final goal data; According to the speed limit of road different in constitutional law provisioning request, selected path is screened simultaneously, arrange from big to small according to running time value, and according to rank display preferred path on vehicle intelligent terminal, do final screening by user.
2. a kind of method calculating optimum driving path according to claim 1, is characterized in that, step 3) in, the detailed process that the database lookup satisfactory driving path data three-dimensional matrix M at vehicle intelligent terminal recalls information center is also downloaded is:
3.1) first, current vehicle intelligent terminal disintegrate driving path, is decomposed into several continuous print roadways by driving path;
3.2) through its data library searching comparison, when finding that the present period of wherein several roadways has record, and all the other roadway no records;
3.3) current vehicle intelligent terminal calls the traveling record that its data storehouse has;
3.4) current vehicle intelligent terminal sends the travelling data request of no record roadway at present period to information center;
3.5) information center's heart database search in the information;
3.6) there are the no record roadway data of present period in the history driving recording that information center uploads before searching other vehicle intelligent terminals, then going to step 3.11 as do not searched data;
3.7) call these data, return to current vehicle intelligent terminal;
3.8) current these data of vehicle-mounted intelligent terminal for reception;
3.9) current vehicle intelligent terminal carries out inside synthesis, realizes the total travel travelling data record after present period gathers;
3.10) driving path data three-dimensional matrix M is calculated after integrating;
3.11) when the current intelligent terminal of discovery and other intelligent terminals all driving recording data needed for no user have been searched for by information center, the then automatic connecting Internet of information center, carry out dynamic map download and correlation data calculation, repeat step 2), carry out routing.
3. a kind of method calculating optimum driving path according to claim 1 and 2, is characterized in that, step 4) in the detailed meanings of N annotate as follows:
β travels distance; The average running time of γ, as above formula 2.
Setting β 1 γ 1=a11; β 2 γ 1=a21; β 1 γ 2=a12 ... β Q γ P=aQP;
Following formula can be drawn:
Wherein between β P γ Q and aPQ, transformational relation is
Setting: representated by β---the absolute value x that it is unit that-traveling distance is converted into " kilometer ";
Representated by γ---the absolute value y that it is unit that-average running time is converted into " minute ";
Derive following formula:
⑤N(β,γ)＝(β1γ1,β1γ2,β2γ1…βPγQ)＝(x1+y1,x1+y2,x2+y1…xP+yQ)＝(a11,a12,a21…aPQ)P,Q∈(1,2,3…∞)
So be also just deduced formula 6.
⑥xP+yQ＝aPQ P,Q∈(1,2,3…∞)。
4. a kind of method calculating optimum driving path according to claim 3, it is characterized in that, step 5) detailed process be: vehicle intelligent terminal is filtered out in above-mentioned array by internal calculation, needed the time period α m travelled the same day, m ∈ (1,2,3 ... ∞), self absolute value is minimum and closest to factor aij, the asd of target running time in scope, i wherein, j, s, d belong to P, Q array, the aij marked under simultaneously calling the α m period, travelling data representated by asd, backstage is converted to concrete traffic route, embodies as follows:
aij＝xi+yj＝βiγj；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)
Wherein β i γ j must meet 7. under Metzler matrix period α m condition simultaneously, 8. two conditions:
⑦xi+yj≤xP+yQ，aij≤aQP，βiγj≤βPγQ
β i γ j perseverance wherein under the α m period is less than or equal to the β P γ Q value in any one N matrix;
8., simultaneously when there being the factor equal with aij result in Metzler matrix, the certain perseverance of yj is less than the absolute value that in this group factor, time factor changes into;
The wherein computing formula of target running time: T
user plans to arrive destination time-T
user's actual time of departure=∣ △ T ∣=T
mark time mutatis mutandis
⑨asd＝xs+yd＝βsγd s,d∈(1,2,3…∞)
10. yd=∣ △ T ∣ or most Jie Jin Yu ∣ △ T ∣, Qi Zhong ∣ △ T ∣=T
user plans to arrive destination time-T
user is actual departure time=T
the standard used time
Separately, must not more than 120 kilometers/hour according to constitutional law provisioning request highway flank speed; National highway, provincial highway flank speed more than 60 kilometers/hour, must not must meet following 2 points simultaneously:
(1) fastlink screening must meet: ∣ x/y ∣ <1 unit: kilometer/minute;
(2) national highway, provincial highway screening must meet: ∣ x/y ∣ <2 unit: kilometer/minute;
Path representated by aij, asd is screened, arranges from big to small according to y value, and according to rank display preferred path on vehicle intelligent terminal, do final screening by user.
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