CN103761430A - Method for identifying peak periods of road networks on basis of floating cars - Google Patents

Abstract

The invention relates to a method for identifying peak periods of road networks on the basis of floating cars. The method includes steps of computing speeds of single vehicle samples of road sections by the aid of GPS (global positioning system) data of the floating cars; extracting average travel speeds of the road sections; computing periodic traffic congestion indexes TCI; extracting morning and evening peak hour starting and ending time points. Compared with the prior art, the method has the advantages that the shortcoming of deficiency of a method for identifying peak periods of road networks on the basis of a floating car technology at present can be overcome; time-varying traffic laws of the road networks can be analyzed via the existing floating car technology and an urban road congestion analysis system, so that the peak periods of the road networks can be extracted.

Description

A kind of road network recognition methods peak period based on Floating Car

Technical field

The present invention relates to traffic planninng technical field, is a kind of road network recognition methods peak period based on Floating Car specifically.

Background technology

Floating car technology is a kind of technology of obtaining road situation according to pavement of road operational vehicle dynamic location information, utilization can Real-time Collection vehicle with the Floating Car (taxi or bus) of GPS information displacement information, seasonal effect in time series vehicle location coordinate is mated with map, can obtain the speed data of unsteady vehicle.Floating car technology can store the data that gather a year in database into, utilizes cycle section velocity information to obtain cycle link flow information.

The annual day magnitude of traffic flow of AADT(road, annual average daily traffic) be the very important parameter of traffic model and management decision, in research fields such as traffic programme, highway layout, traffic safety, transport need analysis, traffic controls, there is crucial effect.Existing AADT calculates and does not recycle traditional manual counts, and also by the road-section average speed of utilizing floating car technology to obtain, the intellectuality that realizes road AADT by a series of models calculating is accurately estimated.The demand data that has met traffic programme, traffic design, traffic administration, has improved work efficiency.

Refer to the section in rush hour road traffic morning and evening causing due to the traffic of travelling frequently peak period (peak hours).The morning peak period is generally: 7:00-9:00, and evening peak is generally 17:00-19:00, and when concrete, discontinuous point there are differences with the difference in region, category of roads, section.Peak period, algorithm for estimating can be realized calculating peak period in city road network and region, for road conditions issuing service provides basic data source, in traffic administration and traffic-information service, played an important role.Utilizing floating car technology to calculate in the process of AADT, when calculating hour magnitude of traffic flow, the judgement of its peak period is according to the road traffic of setting forth in < < urban road traffic congestion assessment indicator system > > (exposure draft) peak period standard sooner or later.But the peak period in each city is all not identical, if utilize unified standard variant actual peak period obvious and each city, thereby affect the intelligent estimation precision of AADT.How developing a kind of recognition methods that can carry out based on floating car technology road network peak period for different cities has become and has been badly in need of the technical matters that solves.

Summary of the invention

To the object of the invention is the defect that there is no road network recognition methods peak period based on floating car technology in prior art in order solving, to provide a kind of road network recognition methods peak period based on Floating Car to solve the problems referred to above.

To achieve these goals, technical scheme of the present invention is as follows:

Road network recognition methods peak period based on Floating Car, comprises the following steps:

Utilize Floating Car gps data to calculate section bicycle sample speed;

Extract road-section average travel speed;

Computation period traffic congestion index TCI;

Extract beginning and ending time peak hour point sooner or later.

The described Floating Car gps data calculating section bicycle sample speed of utilizing comprises the following steps:

By Floating Car gps data obtain sample vehicle j the routing information { P of adjacent 2 of front and back of process _i, i=1,2, L, n};

By path Δ d _jwith mistiming Δ t _jobtain the Average Travel Speed in this section of path

If approach section number only have one or kilometer/hour time, will be assigned to section P ₁; Otherwise, the instantaneous velocity v by four kinds of traffic behavior principles in conjunction with starting point ₁instantaneous velocity v with terminal ₂, to each section speed of approach assignment respectively.

The determination methods of four kinds of described traffic behavior principles is as follows:

Deceleration regime, meets

time, initial section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

Acceleration mode, meets

time, termination section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

First slow down and accelerate afterwards, initial section velocity amplitude is composed as v ₁, stop section velocity amplitude and compose as v ₂, middle section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

First accelerate to slow down afterwards, approach section velocity amplitude is composed and is

Described extraction road-section average travel speed computing formula is

$V_i=\left\{\begin{array}{cc}{V}_i=\frac{l_i}{t_i}=\frac{l_i}{\left(\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{l_i}{v_j}\right)/n}=\frac{n}{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{v_j}},& \mathrm{if}{n}_i\&NotEqual;0\\ V_i=\stackrel{\&OverBar;}{V_i},& \mathrm{if}{n}_i=0\end{array}\right.$

Wherein, V _ifor segmental arc P _iaverage velocity, l _ifor segmental arc P _ilength, t _ijbe j car segmental arc P in path _ion travel time, n _ifor segmental arc P _ithe number of vehicles that upper participation is calculated.

Described computation period traffic congestion index TCI comprises the following steps:

Based on road-section average travel speed V _icarry out congestion status identification, judge the section that blocks up;

Calculate the section mileage ratio RCR that blocks up, calculate respectively through street mileage ratio RCRf, trunk roads mileage ratio RCRa, secondary distributor road mileage ratio RCRm and the branch road mileage ratio RCRl that blocks up that blocks up that blocks up that blocks up, computing formula is as follows:

RCR=RCRf*ω ₁+RCRa*ω ₂+RCRm*ω ₃+RCRl*ω ₄；

Wherein,

L (i) is the length of section i, the length that Lc (i) is the section i that gets congestion,

N _f: the total number in section, through street,

N _a: the total number in trunk roads section,

N _m: the total number in secondary distributor road section,

N _l: the total number in branch road section,

W1, w2, w3, w4 represents respectively the weight of each grade road,

Calculate the road grid traffic index TCI that blocks up, computing formula is as follows:

$\mathrm{TCI}=\left\{\begin{array}{c}\frac{a}{2}(0\&le;a\&le;4)\\ 2+\frac{a-4}{2}(4<a\&le;8)\\ 4+\frac{(a-8)\&times;2}{3}(8<a\&le;11)\\ 6+\frac{(a-11)\&times;2}{3}(11<a\&le;14)\\ 8+\frac{a-14}{5}(14<a\&le;24)\\ 10(a\&GreaterEqual;24)\end{array}\right.$

Wherein: a=RCR*100.

Described extraction sooner or later beginning and ending time peak hour point comprises the following steps:

Judge in one day 24 hours whether Normal Distribution of TCI curve, if Normal Distribution enters next step, calculate, if disobey normal distribution, represent traffic abnormity on the same day, reject data and also reselect data;

Set confidence value c, c is the error range that estimated value and population parameter allow;

According to 24 hours TCI changing values, maximal value and the minimum value of getting TCI,

Take 0 o'clock to 12 o'clock as dividing, TCI maximal value is max_a, the number of cycles that wherein a is 1-288, and the cycle is 5 minutes; The anterior minimum value of TCI is min_t1, and wherein t1 is periodicity corresponding to minimum value; TCI rear portion minimum value min_t2, wherein t2 is periodicity corresponding to minimum value;

Take 12 o'clock to 24 o'clock as dividing, TCI maximal value max_p, wherein p is the number of cycles of 1-288, the cycle is 5 minutes; The anterior minimum value min_t3 of TCI, wherein t3 is periodicity corresponding to minimum value; TCI rear portion minimum value min_t4, wherein t4 is periodicity corresponding to minimum value;

Zoning total area S1, S2, S3, S4,

$S_1=\underset{t1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_1)i\&Element;[t_1,a],$

$S_2=\underset{a}{\overset{t2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_2)i\&Element;[a,t_2],$

$S_3=\underset{t3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_3)i\&Element;[t_3,p],$

$S_4=\underset{p}{\overset{t4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_4)i\&Element;[p,t_4];$

Calculate variance area S ₁', S ₂', S ₃', S ₄',

${S^{\text{'}}}_1=\underset{j_1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_1-\min \_t_1)j\&Element;[t_1,a],$

$S_2^{\text{'}}=\underset{a}{\overset{j_2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_2-\min \_t_2)j\&Element;[a,t_2],$

$S_3^{\text{'}}=\underset{j_3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_3-\min \_t_3)j\&Element;[t_3,p],$

$S_4^{\text{'}}=\underset{p}{\overset{j_4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_4-\min \_t_4)j\&Element;[p,t_4];$

By S1, S2, S3, S4 and S ₁', S ₂', S ₃', S ₄' substitution formula c=S corresponding to difference _i'/S _isolve, by solving, obtain respectively j1, j2, j3, j4, wherein, i=1,2,3,4, S _i' be variance area, S _iit is interval area;

Determine that the morning peak period is T1 to T2, determine that the evening peak period is T3 to T4, wherein T1, T2, T3, the T4 difference start time in cycle of corresponding j1, j2, j3, j4 successively.

Described judge TCI curve whether the formula of Normal Distribution be:

$0.9<\frac{M}{\stackrel{\&OverBar;}{x}}<1.1$ And $\stackrel{\&OverBar;}{x}>3s,$

Wherein: be arithmetic mean, M is median, and s is standard deviation.

Beneficial effect

A kind of road network recognition methods peak period based on Floating Car of the present invention, compared with prior art can pass through existing floating car technology and urban road congestion analysis system, becomes rule while therefrom analyzing road grid traffic, extracts road network peak period.Obtain the most serious period of road grid traffic load, for traffic administration person and traffic programme person provide Data support, improve the intelligent estimation precision of AADT.

Accompanying drawing explanation

Fig. 1 is method flow diagram of the present invention

Fig. 2 is TCI24 hour curvilinear motion figure and relevant parameter mark figure

Embodiment

For making that architectural feature of the present invention and the effect reached are had a better understanding and awareness, in order to preferred embodiment and accompanying drawing, coordinate detailed explanation, be described as follows:

As shown in Figure 1, a kind of road network recognition methods peak period based on Floating Car of the present invention, comprises the following steps:

The first step, utilizes Floating Car gps data to calculate section bicycle sample speed.

Utilize Floating Car gps data to calculate bicycle sample mean travelling speed in the measurement period in section, first, by Floating Car gps data obtain sample vehicle j the routing information { P of adjacent 2 of front and back of process _i, i=1,2, L, n}.Secondly, based on gps data, can pass through path Δ d _jwith mistiming Δ t _jobtain the Average Travel Speed in this section of path

again, when approach section number only have one represent do not cross over crossing or

while kilometer/hour being unimpeded state, will be assigned to section P ₁; Otherwise, by the instantaneous velocity v in conjunction with starting point ₁instantaneous velocity v with terminal ₂, point four kinds of traffic behaviors are to each section speed of approach assignment respectively.

When Floating Car is in deceleration regime, meet

time, initial section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed, then speed is assigned to section P ₁.

When Floating Car is in acceleration mode, meet

time, termination section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed, then speed is assigned to section P ₁.

When Floating Car is in first slowing down and accelerate afterwards, initial section velocity amplitude is composed as v ₁, stop section velocity amplitude and compose as v ₂, middle section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed, then speed is assigned to section P ₁.

When Floating Car deceleration after first accelerating, approach section velocity amplitude is composed and is

again will

be assigned to section P ₁.

Second step, extracts road-section average travel speed.

Extracting road-section average travel speed computing formula is

$V_i=\left\{\begin{array}{cc}{V}_i=\frac{l_i}{t_i}=\frac{l_i}{\left(\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{l_i}{v_j}\right)/n}=\frac{n}{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{v_j}},& \mathrm{if}{n}_i\&NotEqual;0\\ V_i=\stackrel{\&OverBar;}{V_i},& \mathrm{if}{n}_i=0\end{array}\right.$

Wherein, V _ifor segmental arc P _iaverage velocity, l _ifor segmental arc P _ilength, t _ijbe j car segmental arc P in path _ion travel time, n _ifor segmental arc P _ithe number of vehicles that upper participation is calculated.Here, work as n _iequal 0, while there is no data cover on this section, we supplement by the historical average speeds of one week different time sections of historical accumulation; Work as n _ibe not equal at 0 o'clock, road-section average travel speed is the harmonic average speed of multiple samples.

The 3rd step, computation period traffic congestion index TCI.

Cycle traffic congestion index refers in a measurement period (normally 5 minutes), describes the level of blocking up of current region road network with the numerical value of one 0～10, is the quantizating index of describing the degree of blocking up.Calculation procedure is as follows:

First, based on road-section average travel speed V _icarry out congestion status identification, judge the section that blocks up.

According to the speed interval table in table 1, judge current section and whether belong to congestion status, the section data for congestion status are put forward for next step processing.Threshold value table Data Source in table 1 is according to stipulating in the < < urban traffic management assessment indicator system > > of announcement in 2010, the corresponding threshold value of motor vehicle average travel speed in city thoroughfare, and according to Hefei City's actual traffic characteristic, carried out that fine setting obtains.While using in different cities, can adapt to fine setting according to local actual traffic characteristic.

The road condition of table 1 based on road-section average travelling speed divided speed interval table

Classification	1 grade: Free-flow	2 grades: unimpeded	3 grades: jogging	4 grades: crowded	5 grades: block up
						Through street	More than 65km/h	65-40km/h	40-30km/h	30-15km/h	Below 15km/h
Major trunk roads	More than 50km/h	50-30km/h	30-22km/h	22-12km/h	Below 12km/h
						Subsidiary road	More than 40km/h	40-25km/h	25-18km/h	18-10km/h	Below 10km/h
Branch road	More than 35km/h	35-23km/h	23-16km/h	16-8km/h	Below 8km/h

Secondly, calculate the section mileage ratio RCR that blocks up.

Calculate respectively through street mileage ratio RCRf, trunk roads mileage ratio RCRa, secondary distributor road mileage ratio RCRm and the branch road mileage ratio RCRl that blocks up that blocks up that blocks up that blocks up, computing formula is as follows:

RCR=RCRf*ω ₁+RCRa*ω ₂+RCRm*ω ₃+RCRl*ω ₄；

Wherein,

L (i) is the length of section i, the length that Lc (i) is the section i that gets congestion,

N _f: the total number in section, through street,

N _a: the total number in trunk roads section,

N _m: the total number in secondary distributor road section,

N _l: the total number in branch road section,

W1, w2, w3, w4 represents respectively the weight of each grade road,

W1, w2, w3, w4 represent respectively the weight of each grade road, from the total current mileage historical data statistical study of each grade road of road network vehicle, draw.In table 2, have respectively working day weights recommendation tables and festivals or holidays weights recommendation tables, in practice, also can with reference to provincial standard carry out w1, w2, w3, w4 appointment calculate.

Table 2 < < urban road traffic congestion assessment indicator system > > Beijing provincial standard

Working day	Through street	Trunk roads	Secondary distributor road	Branch road	Add up to
						Peak period	0.19	0.43	0.15	0.23	1.00
Full-time average	0.20	0.41	0.16	0.23	1.00
						Festivals or holidays	Through street	Trunk roads	Secondary distributor road	Branch road	Add up to
Full-time average	0.20	0.41	0.16	0.23	1.00

Finally, calculate the road grid traffic index TCI that blocks up.

Computing formula is as follows:

$\mathrm{TCI}=\left\{\begin{array}{c}\frac{a}{2}(0\&le;a\&le;4)\\ 2+\frac{a-4}{2}(4<a\&le;8)\\ 4+\frac{(a-8)\&times;2}{3}(8<a\&le;11)\\ 6+\frac{(a-11)\&times;2}{3}(11<a\&le;14)\\ 8+\frac{a-14}{5}(14<a\&le;24)\\ 10(a\&GreaterEqual;24)\end{array}\right.$

Wherein: a=RCR*100, according to the value difference of a, selects corresponding computing formula.

The 4th step, extracts beginning and ending time peak hour point sooner or later.

Comprise the steps:

(1) as shown in Figure 2, first judge in one day 24 hours whether Normal Distribution of TCI curve, if Normal Distribution enters next step, calculate, if disobey normal distribution, represent traffic abnormity on the same day, have emergency situations to occur.Data are difficult for, as with reference to computational data, therefore rejecting data and reselecting data.Differentiate the TCI curve method whether Normal Distribution adopts, it is one of existing statistics the inside normal distribution-test method, to judge by the ratio of sample median M and arithmetic mean and the relation of arithmetic mean and standard deviation, reflection peak shape and kurtosis, formula is as follows:

$0.9<\frac{M}{\stackrel{\&OverBar;}{x}}<1.1$ And $\stackrel{\&OverBar;}{x}>3s,$

Wherein:

be arithmetic mean, M is median, and s is standard deviation.

(2) set confidence value c, c is the error range that estimated value and population parameter allow.Confidence value is the estimated value of judgement, can specify according to city and decision maker's actual needs, in general, in order to guarantee larger confidence level, generally gets confidence value and is greater than 90.

(3) according to 24 hours TCI changing values, maximal value and the minimum value of getting TCI.

Take 0 o'clock to 12 o'clock as dividing, TCI maximal value is max_a, the number of cycles that wherein a is 1-288, and the cycle is 5 minutes, 288 is to divide and get take 5 minutes as a cycle according to 24 hours.The anterior minimum value of TCI is min_t1, and wherein t1 is periodicity corresponding to minimum value.TCI rear portion minimum value min_t2, wherein t2 is periodicity corresponding to minimum value.

Take 12 o'clock to 24 o'clock as dividing, TCI maximal value max_p, wherein p is the number of cycles of 1-288, the cycle is 5 minutes.The anterior minimum value min_t3 of TCI, wherein t3 is periodicity corresponding to minimum value.TCI rear portion minimum value min_t4, wherein t4 is periodicity corresponding to minimum value.

(4) zoning total area S1, S2, S3, S4, its computing formula is as follows:

$S_1=\underset{t1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_1)i\&Element;[t_1,a],$

$S_2=\underset{a}{\overset{t2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_2)i\&Element;[a,t_2],$

$S_3=\underset{t3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_3)i\&Element;[t_3,p],$

$S_4=\underset{p}{\overset{t4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_4)i\&Element;[p,t_4].$

(5) calculate variance area S ₁', S ₂', S ₃', S ₄', its computing formula is as follows:

${S^{\text{'}}}_1=\underset{j_1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_1-\min \_t_1)j\&Element;[t_1,a],$

$S_2^{\text{'}}=\underset{a}{\overset{j_2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_2-\min \_t_2)j\&Element;[a,t_2],$

$S_3^{\text{'}}=\underset{j_3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_3-\min \_t_3)j\&Element;[t_3,p],$

$S_4^{\text{'}}=\underset{p}{\overset{j_4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_4-\min \_t_4)j\&Element;[p,t_4].$

(6) by S1, S2, S3, S4 and S ₁', S ₂', S ₃', S ₄' substitution formula c=S corresponding to difference _i'/S _isolve, by solving, obtain respectively j1, j2, j3, j4, wherein, i=1,2,3,4, S _i' be variance area, S _iit is interval area.

(7) determine that the morning peak period is T1 to T2, determine that the evening peak period is T3 to T4, wherein T1, T2, T3, the T4 difference start time in cycle of corresponding j1, j2, j3, j4 successively.Because j1, j2, j3, j4 this representative are, by 24 hours take 5 minutes 288 periodicities as the cycle, by j1, j2, j3, the concrete time point T1 of j4 representative, T2, T3, T4, thereby just can judge the morning peak period, be that T1-T2, evening peak period are T3-T4.

More than show and described ultimate principle of the present invention, principal character and advantage of the present invention.The technician of the industry should understand; the present invention is not restricted to the described embodiments; what in above-described embodiment and instructions, describe is principle of the present invention; the present invention also has various changes and modifications without departing from the spirit and scope of the present invention, and these changes and improvements all fall in claimed scope of the present invention.The protection domain that the present invention requires is defined by appending claims and equivalent thereof.

Claims (7)

1. road network recognition methods peak period based on Floating Car, is characterized in that, comprises the following steps:

1) utilize Floating Car gps data to calculate section bicycle sample speed;

2) extract road-section average travel speed;

3) computation period traffic congestion index TCI;

4) extract beginning and ending time peak hour point sooner or later.

2. a kind of road network recognition methods peak period based on Floating Car according to claim 1, is characterized in that: the described Floating Car gps data calculating section bicycle sample speed of utilizing comprises the following steps:

21) by Floating Car gps data obtain sample vehicle j the routing information { P of adjacent 2 of front and back of process _i, i=1,2, L, n};

22) by path Δ d _jwith mistiming Δ t _jobtain the Average Travel Speed in this section of path $\stackrel{\&OverBar;}{v}=\mathrm{\&Delta;}{d}_j/\mathrm{\&Delta;}{t}_j;$

23) if approach section number only have one or

kilometer/hour time, will

be assigned to section P ₁; Otherwise, the instantaneous velocity v by four kinds of traffic behavior principles in conjunction with starting point ₁instantaneous velocity v with terminal ₂, to each section speed of approach assignment respectively.

3. a kind of road network recognition methods peak period based on Floating Car according to claim 2, is characterized in that, the determination methods of four kinds of described traffic behavior principles is as follows:

31) deceleration regime, meets time, initial section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

32) acceleration mode, meets

time, termination section velocity amplitude is composed and is

other section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

33) first slow down and accelerate afterwards, initial section velocity amplitude is composed as v ₁, stop section velocity amplitude and compose as v ₂, middle section velocity amplitude is total travel time Δ t _jdeduct the travel time in initial section, then by distance, divided by this time, obtain speed;

34) first accelerate to slow down afterwards, approach section velocity amplitude is composed and is

4. a kind of road network recognition methods peak period based on Floating Car according to claim 1, is characterized in that: described extraction road-section average travel speed computing formula is

$V_i=\left\{\begin{array}{cc}{V}_i=\frac{l_i}{t_i}=\frac{l_i}{\left(\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{l_i}{v_j}\right)/n}=\frac{n}{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{v_j}},& \mathrm{if}{n}_i\&NotEqual;0\\ V_i=\stackrel{\&OverBar;}{V_i},& \mathrm{if}{n}_i=0\end{array}\right.$

Wherein, V _ifor segmental arc P _iaverage velocity, l _ifor segmental arc P _ilength, t _ijbe j car segmental arc P in path _ion travel time, n _ifor segmental arc P _ithe number of vehicles that upper participation is calculated.

5. a kind of road network recognition methods peak period based on Floating Car according to claim 1, is characterized in that, described computation period traffic congestion index TCI comprises the following steps:

51) based on road-section average travel speed V _icarry out congestion status identification, judge the section that blocks up;

52) calculate the section mileage ratio RCR that blocks up, calculate respectively through street mileage ratio RCRf, trunk roads mileage ratio RCRa, secondary distributor road mileage ratio RCRm and the branch road mileage ratio RCRl that blocks up that blocks up that blocks up that blocks up, computing formula is as follows:

RCR=RCRf*ω ₁+RCRa*ω ₂+RCRm*ω ₃+RCRl*ω ₄；

Wherein,

L (i) is the length of section i, the length that Lc (i) is the section i that gets congestion,

N _f: the total number in section, through street,

N _a: the total number in trunk roads section,

N _m: the total number in secondary distributor road section,

N _l: the total number in branch road section,

W1, w2, w3, w4 represents respectively the weight of each grade road,

53) calculate the road grid traffic index TCI that blocks up, computing formula is as follows:

$\mathrm{TCI}=\left\{\begin{array}{c}\frac{a}{2}(0\&le;a\&le;4)\\ 2+\frac{a-4}{2}(4<a\&le;8)\\ 4+\frac{(a-8)\&times;2}{3}(8<a\&le;11)\\ 6+\frac{(a-11)\&times;2}{3}(11<a\&le;14)\\ 8+\frac{a-14}{5}(14<a\&le;24)\\ 10(a\&GreaterEqual;24)\end{array}\right.$

Wherein: a=RCR*100.

6. a kind of road network recognition methods peak period based on Floating Car according to claim 1, is characterized in that, described extraction sooner or later beginning and ending time peak hour point comprises the following steps:

61) judge in one day 24 hours whether Normal Distribution of TCI curve, if Normal Distribution enters next step, calculate, if disobey normal distribution, represent traffic abnormity on the same day, reject data and also reselect data;

62) set confidence value c, c is the error range that estimated value and population parameter allow;

63) according to 24 hours TCI changing values, maximal value and the minimum value of getting TCI,

Take 0 o'clock to 12 o'clock as dividing, TCI maximal value is max_a, the number of cycles that wherein a is 1-288, and the cycle is 5 minutes; The anterior minimum value of TCI is min_t1, and wherein t1 is periodicity corresponding to minimum value; TCI rear portion minimum value min_t2, wherein t2 is periodicity corresponding to minimum value;

Take 12 o'clock to 24 o'clock as dividing, TCI maximal value max_p, wherein p is the number of cycles of 1-288, the cycle is 5 minutes; The anterior minimum value min_t3 of TCI, wherein t3 is periodicity corresponding to minimum value; TCI rear portion minimum value min_t4, wherein t4 is periodicity corresponding to minimum value;

64) zoning total area S1, S2, S3, S4,

$S_1=\underset{t1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_1)i\&Element;[t_1,a],$

$S_2=\underset{a}{\overset{t2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_2)i\&Element;[a,t_2],$

$S_3=\underset{t3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_3)i\&Element;[t_3,p],$

$S_4=\underset{p}{\overset{t4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_i-\min \_t_4)i\&Element;[p,t_4];$

65) calculate variance area S ₁', S ₂', S ₃', S ₄',

${S^{\text{'}}}_1=\underset{j_1}{\overset{a}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_1-\min \_t_1)j\&Element;[t_1,a],$

$S_2^{\text{'}}=\underset{a}{\overset{j_2}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_2-\min \_t_2)j\&Element;[a,t_2],$

$S_3^{\text{'}}=\underset{j_3}{\overset{p}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_3-\min \_t_3)j\&Element;[t_3,p],$

$S_4^{\text{'}}=\underset{p}{\overset{j_4}{\mathrm{\&Sigma;}}}(\mathrm{TCI}\_j_4-\min \_t_4)j\&Element;[p,t_4];$

66) by S1, S2, S3, S4 and S ₁', S ₂', S ₃', S ₄' substitution formula c=S corresponding to difference _i'/S _isolve, by solving, obtain respectively j1, j2, j3, j4, wherein, i=1,2,3,4, S _i' be variance area, S _iit is interval area;

67) determine that the morning peak period is T1 to T2, determine that the evening peak period is T3 to T4, wherein T1, T2, T3, the T4 difference start time in cycle of corresponding j1, j2, j3, j4 successively.

7. a kind of road network recognition methods peak period based on Floating Car according to claim 6, is characterized in that, described judge TCI curve whether the formula of Normal Distribution be:

$0.9<\frac{M}{\stackrel{\&OverBar;}{x}}<1.1$ And $\stackrel{\&OverBar;}{x}>3s,$

Wherein:

be arithmetic mean, M is median, and s is standard deviation.

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