CN104596534B - A kind of method for calculating optimal planning driving path - Google Patents
A kind of method for calculating optimal planning driving path Download PDFInfo
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- 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
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Abstract
The invention discloses a kind of method for calculating optimal planning driving path, run-length data of each vehicle intelligent terminal in current entry is collected by information centre first, starting point is inputted on intelligent terminal before user's traveling, terminal, plan arrival time, by intelligent terminal internal database or the database lookup at recalls information center, and call satisfactory planning driving path data, automatic adaptation planning driving path, minimum and closest to the target travel time the factor of itself absolute value in the range of the travel period that intelligent terminal needs on the day of being filtered out by internal calculation, as final goal data；Arranged from big to small according to running time value, and preferred path is shown according to ranking on vehicle intelligent terminal, final screening is done by user.This method makes intelligent terminal possess from record, from the characteristics of computing, based on own resource, supplemented by internet data, it is not necessary to real-time interconnection, signal interference is excluded, the problems such as network traffics.
Description
Technical field
The invention belongs to road traffic navigation field, and in particular to one kind calculates optimal roadway automatically on onboard system
The method in footpath.
Background technology
As social automobile purchase power and resident trip are ridden the growing day by day of demand, urban traffic road conditions face increasingly tight
High challenge；Same fixed section has very big difference in the throughput of whole day different time vehicle, especially on city
Come off duty peak time, carrying out Path selection by single stroke length can not meet masses to driving efficiency, trip body
The demand tested, and old-fashioned distance computational methods, current user's request is not applied to.
Chinese invention patent " the vehicle optimal path air navigation aid based on car networking " (publication number 102708698A), passes through
Setting dynamic contact matrix, traffic surveillance and control center passes through according to OD information and dynamic contact matrix to indicate road network connection state
The optimal path that improved ant colony optimization for solving vehicle travels in road network, enables the vehicle to real-time response emergency situations, reaches and carry
Height navigation levels of precision and the purpose for improving vehicle operational efficiency.The backstage that this invention calculates around internet as data, and
Rely on internet to upload download in real time to be operated, using most short traveling distance as the unique conditional for judging selection, but going out
, it is necessary to which real-time interconnection, which downloads road conditions jam situation, can just avoid congestion peak during existing path congestion, and can not be voluntarily in car
Stream peak period judges, evades congested link, but real-time interconnection does not only exist signal interference, the problems such as network traffics, flow velocity,
And download road conditions jam situation on the net and certain hysteresis quality be present, it is impossible to ensure that the road conditions real-time embodying of previous second is being downloaded
In road conditions, not accomplish really in real time.
Chinese invention patent " intelligent algorithm of urban optimal path navigation " (publication number 103134504A), is by city
Road is divided into different weights by far and near distance and the unobstructed situation of traffic in city, is then that distance is preferential also according to the selection of user
Be traffic it is unobstructed it is preferential considered after provide the user optimal path navigation scheme；Simultaneously in order to avoid due to similar
Navigation scheme cause new road congestion, to every selection road record, paid the utmost attention to when forming guidance path
The few road of the road or access times that were not recorded.The algorithm is according to " navigation road far and near distance ", " the unobstructed feelings of traffic
Two factors of condition ", two-dimensional function is combined into, it is preferred to carry out path.Having one section in original text, " motorist is from departure place X to purpose
Ground Y has that four bar navigation path A, B, C, D are optional, and wherein path A, B, D road was not used, and weight is 1, path C road
It has been previously used " it can be understood as two kinds of implications：
1. connecting network, the road for getting A, B, D was not used, the used information of C；
2. being arrived according to itself conventional travelling data record queries, new in the past road A, B, D were not used, and C is usual row
The road sailed；
Understand that analysis is according to thinking 1：Each use is required for connecting network, and acquisition approach records, and internet data
With ageing, it is impossible to ensure that same section of distance is consistent with initial internet hunt road conditions after certain time is travelled, therefore easily
It is not optimal to cause navigation results；
Then optimal planning driving path may might not be met due to untapped road according to thinking 2, cause to calculate path
Inaccurately.
To sum up, there is heavy dependence internet data in current airmanship, lack independent navigation ability, and algorithm has office
It is sex-limited to cause Path selection inaccurate, and user does not select for running time, such as when client prepares to go to fulfill an appointment on time, and
Do not require to arrive at as early as possible, and be desirable to reaching on the time, current navigation system is not carried out this personalized customization work(
Can, so, there is an urgent need to one kind in market that running time, operating range effectively can be arranged in pairs or groups for existing navigation, can more adduction
Reason calculates traffic path, realizes the new vehicle-mounted navigation computational method of lower oil consumption.
The content of the invention
The technical problems to be solved by the invention are to provide a kind of method for calculating optimal planning driving path, and this method is with inside
From collection, calculate certainly based on planning driving path data, internet is uploaded supplemented by data；Using running time as optimal selection, traveling
Distance realizes planning driving path most preferably as campaigning item.
A kind of method for calculating optimal planning driving path of the present invention, it comprises the following steps：
A kind of method for calculating optimal planning driving path, it is characterised in that comprise the following steps：
1) the start of a run A that each vehicle intelligent terminal records in routine use collects in the information centre of navigation information system
B data to terminal, wherein each trip period of 24 hours in one day is defined as into α；Determined according to different traffic routes
Traveling distance β, filter out specific starting point to the link travel time of terminal, gather within more days repeatedly, and collect and try to achieve difference and go out
The average running time γ of row period；
2) the trip period α in step 1) one day 24 hours, traveling distance β, average running time γ are arranged as one
Individual three-dimensional matrice M=[α, beta, gamma]；
M=M 1. [α, beta, gamma]=M [α, (beta, gamma)]
Wherein α represents the period in 24 hours 1 day, and β, γ can also form another due to the implication of its own
Two-dimensional matrix N, and represent as follows：
Then combine formula 2., following relational expression can be derived：
M=M 3. [α, beta, gamma]=M [α, N (beta, gamma)]
Above-mentioned matrix M and its back-end data of representative are inputted in each vehicle intelligent terminal by wirelessly or non-wirelessly mode
Portion's database；
3) user is before traveling, first when input driving starting point, terminal, plan arrive on vehicle intelligent terminal
Between, then internal database lookup carried out by vehicle intelligent terminal, and call satisfactory planning driving path data three-dimensional matrix M；
Such as the not no three-dimensional matrice M of internal database, then satisfactory planning driving path data of the database lookup at recalls information center,
Three-dimensional matrice M is synthesized after download；
4) after vehicle intelligent terminal obtains planning driving path data three-dimensional matrix M, automatic adaptation planning driving path, travel period ɑ
To add up within more days average running time γ in this period between distance β and objective by being travelled between two objectives during steady state value
Two-dimensional function matrix N is formed,
5) vehicle intelligent terminal filters out in the range of the travel period that needs of the same day itself absolute value most by internal calculation
The factor small and closest to the target travel time, as final goal data；Simultaneously according to different roads in national legal requirements
Speed limit selected path is screened, arranged from big to small according to running time value, and pressed on vehicle intelligent terminal
Phototypesetting name shows preferred path, and final screening is done by user.
Above-mentioned steps 3) in, the satisfactory planning driving path number of database lookup at vehicle intelligent terminal recalls information center
According to three-dimensional matrice M and download detailed process be：
3.1) first, current vehicle intelligent terminal voluntarily decomposes planning driving path, and it is continuous that planning driving path is decomposed into several
Roadway；
3.2) through own database search comparison, when the present period for finding wherein several roadways has record, and
Remaining roadway no record；
3.3) current vehicle intelligent terminal calls the traveling record that own database has；
3.4) current vehicle intelligent terminal sends travelling data of the no record roadway in present period to information centre
Request；
3.5) information centre's heart database search in the information；
3.6) when having current in the history driving recording uploaded before information centre searches other vehicle intelligent terminals
The no record roadway data of section, go to step 3.11 if not searching data；
3.7) this data is called, return to current vehicle intelligent terminal；
3.8) current vehicle-mounted intelligent terminal for reception data；
3.9) current vehicle intelligent terminal carries out internal synthesis, realizes the total travel travelling data after present period collects
Record；
3.10) planning driving path data three-dimensional matrix M is calculated to obtain after integrating；
3.11) searched for when information centre and complete to find driving needed for current intelligent terminal and other intelligent terminals all no users
Record data, then information centre connect internet automatically, carry out dynamic map download and correlation data calculation, repeat step 2),
Carry out Path selection.
Above-mentioned steps 4) in N detailed meanings annotate it is as follows：
β travels distance；The average running times of γ, such as above formula 2.
Set the γ 1=a11 of β 1；The γ 1=a21 of β 2；γ 2=a12 ... the β Q γ P=aQP of β 1；
Equation below can be drawn：
Transformational relation is between wherein β P γ Q and aPQ
Setting:Representated by β ----traveling distance is converted into the absolute value x with " kilometer " for unit；
Representated by γ ----averagely running time is converted into the absolute value y with " minute " for unit；
Derive equation below：
5. N (β, γ)=(γ 1 ... the β P γ Q of β 1 γ 1, β 1 γ 2, β 2)=(x1+y1, x1+y2, x2+y1 ... xP+yQ)=
(a11,a12,a21…aPQ)P,Q∈(1,2,3…∞)
Then also just it is deduced formula 6.
6. xP+yQ=aPQ P, Q ∈ (1,2,3 ... ∞).
Above-mentioned steps 5) detailed process be：Vehicle intelligent terminal is filtered out by internal calculation in above-mentioned array, when
Its period α m, m ∈ (1,2,3 ... ∞) for travelling of needs, in the range of itself absolute value it is minimum and closest to the target travel time
Factor aij, asd, i therein, j, s, d belong to P, Q array, while calls the aij marked under the α m periods, representated by asd
Travelling data, specific traffic route is converted to from the background, embody as follows：
Aij=xi+yj=β i γ j；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)
Wherein β i γ j must simultaneously meet under the conditions of Metzler matrix period α m 7., 8. two conditions：
7. xi+yj≤xP+yQ, aij≤aQP, β i γ j≤β P γ Q
The permanent β P γ Q values being less than or equal in any one N matrix of β i γ j wherein under the α m periods；
8. simultaneously when there is the factor equal with aij results in Metzler matrix, yj is certain permanent less than time factor turn in this group factor
The absolute value of chemical conversion；
The wherein calculation formula of target travel time：TUser's plan arrives at the time―TUser's actual time of departure=∣ △ T ∣=TMarkWhen mutatis mutandis
9. asd=xs+yd=β s γ d s, d ∈ (1,2,3 ... ∞)
10. Qi Zhong ∣ △ T ∣=T of yd=∣ △ T ∣ or Jie Jin Yu ∣ △ T ∣,User's plan arrives at the time―TUser's actual time of departure=TThe standard used time
In addition, it must not exceed 120 kilometers/hour according to national legal requirements highway flank speed；National highway, provincial highway highest
Speed must not exceed 60 kilometers/hour, while must be fulfilled at following 2 points：
(1) fastlink screening must is fulfilled for：∣x/y∣<2 units：Kilometer/minute
(2) national highway, provincial highway screening must are fulfilled for：∣x/y∣<1 unit：Kilometer/minute.
By aij, path representated by asd is screened, and is arranged from big to small according to y values, and pressed on vehicle intelligent terminal
Phototypesetting name shows preferred path, and final screening is done by user.
Beneficial effects of the present invention：
The present invention using " time " * " distance "=" optimal path " and algorithm, abandon it is single by shortest path calculate row
The old-fashioned method of bus or train route line, comprehensive origin to all distances between objective, according to one gathered certainly in driving conditions
Different periods (including the congestion period on and off duty), the average running time of corresponding distance are carried out preferred and integrated ordered in it, this
One method makes intelligent vehicle mounted terminal possess from record, from the characteristics of computing, can be interacted with internet but independent of interconnection
Net, gather the gathered data between different mobile units, different target section, by network timing upload information center, vehicle-mounted
During self information base resource deficiency, also internal resource matching, optimal road can be carried out in real time by the Internet download latest data storehouse
Footpath selects.Because internet is uploaded supplemented by data, it is not necessary to real-time interconnection, signal interference is excluded, the problems such as network traffics.
Compared with " intelligent algorithm of urban optimal path navigation " (publication number 103134504A), two inventions have
One important factor N actual travel distance, " intelligent algorithm of urban optimal path navigation " rely on M average vehicle flows and N
Distance carries out two-dimentional balance exclusive method；The present invention uses three-dimensional " travel period α ", " traveling distance β ", " average running time γ "
Three-dimensional matrice screening method is carried out, with reference to the method for finally leaving hommization selection space, optimal route is screened, since it is considered that more
Weight factor, operation matrix is also changing into three-dimensional, and eliminate from calculate that vehicle flowrate M can change with the time it is unstable because
Element, this method using verification user wish duration (user perhaps wishes that running time is slightly long sometimes, this method can with hommization,
Control, folding and unfolding running time) after again by travel period distinguish, be weighted distance, the control methods of time, rather than simple weighted
From road occupation weight and road distance is calculated, the method is simpler, reliable, rigorous.
Brief description of the drawings
Fig. 1 is embodiment middle rolling car route map,
Fig. 2 is the flow chart of the present invention,
Fig. 3 is the satisfactory planning driving path data flow of vehicle intelligent terminal recalls information centre data library lookup of the present invention
Cheng Tu.
Embodiment
With reference to Fig. 1, the invention will be further described.
Existing invention calculates optimal path and uses one-dimensional standard short line optimum seeking method more；Illustrate：Such as Fig. 1, starting point a
There are three paths between b to terminal：Acb, adb, ab；Wherein ab sections of road distance is less than acb sections, i.e. xab<Xacb, but
It is in a certain special time, running time yab>Yacb, such as continues to use present invention, and navigation still can select ab sections as optimal
Recommend, it is clear that this method in car peak period of being expert at does not apply to simultaneously.And this method uses three-dimensional standard M [α, beta, gamma], to lane
Road is counted, wherein each trip period of 24 hours in one day is defined as into α；The row determined according to different traffic routes
Distance β is sailed, filters out specific starting point to the link travel time of terminal, is gathered within more days repeatedly, and is collected when trying to achieve different trips
The average running time γ of section；.Usage factor yab is as main traffic route screening criteria, and its cofactor is as assisting sifting
Standard, this makes it possible to more accurately calculate optimal planning driving path, the older invention of this method more saves, time saving and holding
Without connection network in real time, path can be selected according to the real needs hommization of 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
T represents the specifically used time of traveling
Conclusion：The 18 of every day:00-19:00 this period
Average running time=(t1+t4+t7+ ...+t (n-2))/n=y1 of distance acb；Travel distance x1；
Average running time=(t2+t5+t8+ ...+t (n-1))/n=y2 of distance adb；Travel distance x2；
Average running time=(t3+t6+t9+ ...+the tn)/n=y3 of distance ab；Travel distance x3；
Wherein (y1, y2, y3) belongs to gamma matrix；(x1, x2, x3) belongs to β matrix categories；
Screened using α travel periods, the result of γ and β weighting, it is minimum and closest to the target travel time to choose absolute value
's
Combinations of factors is finally carried out according to itself hobby hommization selection as preferred path by user.
From reasoning above, the trip period in one day, traveling distance, averagely traveling Time alignment can be turned into one
Three-dimensional matrice M=[α, beta, gamma]；
M=M 1. [α, beta, gamma]=M [α, (beta, gamma)]
User is before traveling, first when input driving starting point, terminal, plan arrive on vehicle intelligent terminal
Between, then internal database lookup carried out by vehicle intelligent terminal, and call satisfactory planning driving path data three-dimensional matrix M；
Such as the not no three-dimensional matrice M of internal database, then satisfactory planning driving path data of the database lookup at recalls information center,
Three-dimensional matrice M is synthesized after download；
After vehicle intelligent terminal obtains planning driving path data three-dimensional matrix M, automatic adaptation planning driving path, by two objectives
Between between running distance factor-beta and objective at more days of this period accumulative average running time γ composition two-dimensional function matrix Ns,
Its detailed meanings is annotated as follows：
Set the γ 1=a11 of β 1；The γ 1=a21 of β 2；γ 2=a12 ... the β Q γ P=aQP of β 1；
Draw equation below：
Transformational relation is between wherein β P γ Q and aPQ：
Setting:Representated by β ----traveling distance is converted into the absolute value x with " kilometer " for unit；
Representated by γ ----averagely running time is converted into the absolute value y with " minute " for unit；
Derive equation below：
5. N (β, γ)=(γ 1 ... the β P γ Q of β 1 γ 1, β 1 γ 2, β 2)=(x1+y1, x1+y2, x2+y1 ... xP+yQ)=
(a11,a12,a21…aPQ)P,Q∈(1,2,3…∞)
Then also just it is deduced formula 6.
6. xP+yQ=aPQ P, Q ∈ (1,2,3 ... ∞)
Vehicle intelligent terminal is filtered out by internal calculation in above-mentioned array, and the same day needs period α m, the m ∈ travelled
(1,2,3 ... ∞), in the range of itself absolute value it is minimum and closest to the target travel time the factor aij, asd (i, j therein,
S, d belong to P, Q array), while the aij marked under the α m periods is called, the travelling data representated by asd, be converted to from the background specific
Traffic route, embody as follows：
Aij=xi+yj=β i γ j；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)
Wherein β i γ j must simultaneously meet under the conditions of Metzler matrix period α m 7., 8. two conditions：
7. xi+yj≤xP+yQ, aij≤aQP, β i γ j≤β P γ Q
The permanent β P γ Q values being less than or equal in any one N matrix of β i γ j wherein under the α m periods；
8. simultaneously when there is the factor equal with aij results in Metzler matrix, yj is certain permanent less than time factor turn in this group factor
The absolute value of chemical conversion；
The wherein calculation formula of target travel time：TUser's plan arrives at the time―TUser's actual time of departure=∣ △ T ∣=TThe standard used time
9. asd=xs+yd=β s γ d s, d ∈ (1,2,3 ... ∞)
10. Qi Zhong ∣ △ T ∣=T of yd=∣ △ T ∣ or Jie Jin Yu ∣ △ T ∣,User's plan arrives at the time―TUser's actual time of departure=TThe standard used time
In addition, it must not exceed 120 kilometers/hour according to national legal requirements highway flank speed；National highway, provincial highway highest
Speed must not exceed 60 kilometers/hour, while must be fulfilled at following 2 points：
(1) fastlink screening must is fulfilled for：∣x/y∣<2 units：Kilometer/minute
(2) national highway, provincial highway screening must are fulfilled for：∣x/y∣<1 unit：Kilometer/minute
By aij, path representated by asd is screened, and is arranged from big to small according to y values, and pressed on vehicle intelligent terminal
Phototypesetting name shows preferred path, and final screening is done by user.
The satisfactory planning driving path data three-dimensional matrix M of database lookup at vehicle intelligent terminal recalls information center is simultaneously
The detailed process of download is：
3.1) first, current vehicle intelligent terminal voluntarily decomposes planning driving path, and it is continuous that planning driving path is decomposed into several
Roadway；
3.2) through own database search comparison, when the present period for finding wherein several roadways has record, and
Remaining roadway no record；
3.3) current vehicle intelligent terminal calls the traveling record that own database has；
3.4) current vehicle intelligent terminal sends travelling data of the no record roadway in present period to information centre
Request；
3.5) information centre's heart database search in the information；
3.6) when having current in the history driving recording uploaded before information centre searches other vehicle intelligent terminals
The no record roadway data of section, go to step 3.11 if not searching data；
3.7) this data is called, returns to current vehicle intelligent terminal；
3.8) current vehicle-mounted intelligent terminal for reception data；
3.9) current vehicle intelligent terminal carries out internal synthesis, realizes the total travel travelling data after present period collects
Record；
3.10) planning driving path data three-dimensional matrix M is calculated to obtain after integrating；
3.11) searched for when information centre and complete to find driving needed for current intelligent terminal and other intelligent terminals all no users
Record data, then information centre connect internet automatically, carry out dynamic map download and correlation data calculation, repeat step 2),
Carry out Path selection.
Wherein such as Fig. 3, intelligent terminal B, intelligent terminal C can also coordinate with information centre, use above logical method pair
Driving demand without historical record is called, designed.
It is as follows according to Fig. 3 relational expressions that can be in contact：It is daily 24 hours fixed periods wherein to scheme upper α, above figure table
The functional relation revealed is：
1. xA-b-B=xAb+xB；
2. xb-c-C=xbc+xC；
3. xc-A-a=xcA+xA；
Wherein x is traveling distance β, and average running time γ calling is finer, and calling is analyzed as follows：
As 1. section AbB is decomposed into two sections of distances of Ab, B by formula, user's intelligent vehicle mounted terminal is by being calculated, in α
M, m ∈ (1,2,3 ... the ∞) periods, travel in Ab sections, and when user drives to B sections, the α n in Metzler matrix, n
∈ (1,2,3 ... the ∞) periods, then the yAb values of segment record when running time γ calculating needs to call α m in AbB system-wide journeys, and
The yB values of segment record during α n, so simply can not be represented with calculation formula above.Then from figure 3, it can be seen that selecting
During the AbB of path, incidental correlation factor has α m in α, a α n periods, xAb, xB in the β factors, in the γ factors under the α m periods
YAb, yB values under the α n periods；
1. it can be derived from formula：When driving, the conventional path of recorder self record can apply from
It is empirically internal to extrapolate a new driving path on the path do not crossed.
In addition, there is also a kind of situation, when information centre can not search related data, system can spontaneous connection it is mutual
Networking Google Maps, as shown in Fig. 2 carrying out route searching, then wanted according still further to period, traveling distance, running time three
Plain Integrated Selection, it is that user selects optimal path according to above-named formula.
Concrete application approach of the present invention is a lot, and described above is only the preferred embodiment of the present invention, it is noted that for
For those skilled in the art, under the premise without departing from the principles of the invention, some improvement can also be made, this
A little improve also should be regarded as protection scope of the present invention.
Claims (4)
- A kind of 1. method for calculating optimal planning driving path, it is characterised in that comprise the following steps：1) start of a run A that each vehicle intelligent terminal records in routine use collects to end in the information centre of navigation information system Point B data, wherein each trip period of 24 hours in one day is defined as into α；The row determined according to different traffic routes Distance β is sailed, filters out specific starting point to the link travel time of terminal, is gathered within more days repeatedly, and is collected when trying to achieve different trips The average running time γ of section；2) the trip period α in step 1) one day 24 hours, traveling distance β, average running time γ are arranged as one three Tie up matrix M=[α, beta, gamma]；M=M 1. [α, beta, gamma]=M [α, (beta, gamma)]Wherein α represents the period in 24 hours 1 day, and β, γ can also form another two dimension due to the implication of its own Matrix N, and represent as follows：②Then combine formula 2., following relational expression can be derived：M=M 3. [α, beta, gamma]=M [α, N (beta, gamma)]Above-mentioned matrix M and its back-end data of representative are inputted to the inside number of each vehicle intelligent terminal by wirelessly or non-wirelessly mode According to storehouse；3) user is before traveling, first on vehicle intelligent terminal input driving starting point, terminal, plan arrive at the time, Internal database lookup is carried out by vehicle intelligent terminal again, and calls satisfactory planning driving path data three-dimensional matrix M；As in The not no three-dimensional matrice M of portion's database, then the satisfactory planning driving path data of the database lookup at recalls information center, are downloaded Three-dimensional matrice M is synthesized afterwards；4) after vehicle intelligent terminal obtains planning driving path data three-dimensional matrix M, automatic adaptation planning driving path, travel period ɑ is perseverance By being travelled between two objectives between distance β and objective in the more days accumulative average running time average rows of this period during definite value Time γ composition two-dimensional function matrix Ns are sailed,5) vehicle intelligent terminal by internal calculation filter out itself absolute value in the range of the travel period that needs of the same day it is minimum and Closest to the factor of target travel time, as final goal data；Simultaneously according to the speed of different roads in national legal requirements The degree upper limit is screened to selected path, is arranged from big to small according to running time value, and according to row on vehicle intelligent terminal Name shows preferred path, and final screening is done by user.
- 2. a kind of method for calculating optimal planning driving path according to claim 1, it is characterised in that vehicle-mounted in step 3) The satisfactory planning driving path data three-dimensional matrix M of database lookup at intelligent terminal recalls information center and the specific mistake downloaded Cheng Wei：3.1) first, current vehicle intelligent terminal voluntarily decomposes planning driving path, and planning driving path is decomposed into several continuous rows Bus or train route section；3.2) through own database search comparison, when the present period for finding wherein several roadways has a record, and remaining Roadway no record；3.3) current vehicle intelligent terminal calls the traveling record that own database has；3.4) current vehicle intelligent terminal sends no record roadway to information centre and asked in the travelling data of present period；3.5) information centre's heart database search in the information；3.6) present period be present in the history driving recording uploaded before information centre searches other vehicle intelligent terminals No record roadway data, go to step 3.11 if not searching data；3.7) this data is called, returns to current vehicle intelligent terminal；3.8) current vehicle-mounted intelligent terminal for reception data；3.9) current vehicle intelligent terminal carries out internal synthesis, realizes that the total travel travelling data after present period collects is remembered Record；3.10) planning driving path data three-dimensional matrix M is calculated to obtain after integrating；3.11) searched for when information centre and complete to find driving recording needed for current intelligent terminal and other intelligent terminals all no users Data, then information centre connect internet automatically, carry out dynamic map download and correlation data calculation, repeat step 2), carry out Path selection.
- A kind of 3. method for calculating optimal planning driving path according to claim 1 or 2, it is characterised in that N in step 4) Detailed meanings are annotated as follows：β travels distance；The average running times of γ, such as above formula 2.②Set the γ 1=a11 of β 1；The γ 1=a21 of β 2；γ 2=a12 ... the β Q γ P=aQP of β 1；Equation below can be drawn：④Transformational relation is between wherein β P γ Q and aPQSetting:Representated by β ----traveling distance is converted into the absolute value x with " kilometer " for unit；Representated by γ ----averagely running time is converted into the absolute value y with " minute " for unit；Derive equation below：5. N (β, γ)=(γ 1 ... the β P γ Q of β 1 γ 1, β 1 γ 2, β 2)=(x1+y1, x1+y2, x2+y1 ... xP+yQ)=(a11, a12,a21…aPQ)P,Q∈(1,2,3…∞)Then also just it is deduced formula 6.6. xP+yQ=aPQ P, Q ∈ (1,2,3 ... ∞).
- A kind of 4. method for calculating optimal planning driving path according to claim 3, it is characterised in that the specific mistake of step 5) Cheng Wei：Vehicle intelligent terminal is filtered out by internal calculation in above-mentioned array, period α m, m ∈ that the same day needs to travel (1, 2,3 ... ∞), in the range of itself absolute value is minimum and factor aij, asd closest to the target travel time, i therein, j, s, d Belong to P, Q array, while call the aij marked under the α m periods, the travelling data representated by asd, be converted to specific driving from the background Route, embody as follows：Aij=xi+yj=β i γ j；i,j∈(1,2,3…∞)；s,d∈(1,2,3…∞)Wherein β i γ j must simultaneously meet under the conditions of Metzler matrix period α m 7., 8. two conditions：7. xi+yj≤xP+yQ, aij≤aQP, β i γ j≤β P γ QThe permanent β P γ Q values being less than or equal in any one N matrix of β i γ j wherein under the α m periods；8. simultaneously when there is the factor equal with aij results in Metzler matrix, the certain perseverances of yj are less than time factor in this group factor and changed into Absolute value；The wherein calculation formula of target travel time：TUser's plan arrives at the time―TUser's actual time of departure=∣ △ T ∣=TThe standard used time9. asd=xs+yd=β s γ d s, d ∈ (1,2,3 ... ∞)10. yd=∣ △ T ∣Or closest toQi Zhong ∣ △ T ∣=T of ∣ △ T ∣,User's plan arrives at the time―TUser's actual time of departure=TThe standard used timeIn addition, it must not exceed 120 kilometers/hour according to national legal requirements highway flank speed；National highway, provincial highway flank speed 60 kilometers/hour are must not exceed, while must is fulfilled at following 2 points：(1) fastlink screening must is fulfilled for：∣x/y∣<2 units：Kilometer/minute(2) national highway, provincial highway screening must are fulfilled for：∣x/y∣<1 unit：Kilometer/minute；By aij, path representated by asd is screened, and is arranged from big to small according to y values, and according to row on vehicle intelligent terminal Name shows preferred path, and final screening is done by user.
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