CN101656021A - Method and system for judging road conditions and traffic information processing system - Google Patents

Abstract

The invention belongs to the technical field of traffic information, and provides a method and a system for judging road conditions and a traffic information processing system. In the invention, aiming at the traffic information data of one acquisition cycle and through map matching, the traffic information data after the map matching is classified according to a plurality of time slices; aiming at the speed in the traffic information data of each time slice under each road link, a fusion speed is calculated; and the traffic condition in the time slices of the current road link is judged according to the fusion speed to further judge the overall traffic conditions of M road links in the acquisition cycle. Thus, each road link in one acquisition cycle has more acquisition point data used for judging the traffic conditions, and through the fusion of speed data, abnormal speed data has small influence on the result of the judgment of the overall traffic road conditions, namely the resultof the judgment of the road conditions is more accurate.

Description

A kind of method of discrimination of road conditions, system and traffic information processing system

Technical field

The invention belongs to the transport information technical field, relate in particular to a kind of method of discrimination, system and traffic information processing system of road conditions.

Background technology

Along with socioeconomic fast development, the road traffic demand sharply increases, and the growth of road progressively tends towards stability, and the road traffic demand more and more is difficult to satisfy, thus phenomenons such as crowding often appears in road traffic, obstruction.

And along with the progress at full speed of infotech, a kind of computing machine of application of advanced, communication and sensor technology, (Advanced TrafficManagement Systems ATMS) is subjected to paying close attention to widely the traffic control system that vehicle, road and traffic administration are combined together.ATMS be a kind of can realize to traffic flow monitor in real time, the system of the active management of functional control.ATMS by the various transport information in the Traffic Net are gathered in real time, transmission and analyzing and processing, obtain road traffic condition and failure message, for the traveler and the participant of road traffic provides decision support, incur loss through delay thereby reduce the travel time that causes by congested in traffic and traffic hazard to greatest extent, thus the security and the operational efficiency of raising road traffic.

Traffic information collection equipment commonly used mainly contains two classes, and a class is the fixed monitor, as inductive coil, video monitor, microwave monitor etc.; Another kind of is the mobile model monitor, as be mounted with GPS (Global Positioning System, GPS) and the Floating Car of Wireless Telecom Equipment.Characteristics such as the mobile model monitor drops into owing to it is low, height covers, can expand become the general data source that road conditions are judged.

Use the existing road conditions method of discrimination need be at each Floating Car, the data in each highway section be handled.Simultaneously, the speed that is adopted is the average velocity of same continuous two the gps time points of car.And in a collection period, because may there be abnormal conditions such as vehicle damage, parking carrying in some Floating Car, at this moment, the traffic information data that these Floating Car collect is inaccurate, thereby can cause the differentiation of transport information not accurate enough.And when corresponding road section only collected less data, the traffic information data that unusual mobile model monitor collects was bigger to the differentiation influence in whole highway section.

Summary of the invention

The purpose of the embodiment of the invention is to provide a kind of method of discrimination of road conditions, is intended to solve traffic information data that unusual Floating Car gathers when inaccurate, utilizes prior art to differentiate the inaccurate problem of differentiation result that traffic occurs easily.

The embodiment of the invention is achieved in that a kind of method of discrimination of road conditions, said method comprising the steps of:

Receive the traffic information data of a collection period;

By map match, described traffic information data is referred in the corresponding M road chain;

Collection period is divided into a plurality of timeslices,, the traffic information data of described road chain correspondence is referred in the corresponding timeslice at each road chain;

Each timeslice in each road chain reads the speed data in the traffic information data, and calculates a fusion speed according to described speed data;

Differentiate traffic in current road chain, the timeslice according to described fusion speed, and then differentiate the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

Another purpose of the embodiment of the invention is to provide a kind of judgement system of road conditions, and described system comprises:

Data reception module is used to receive the traffic information data of a collection period;

Map-matching module is used for by map match, and described traffic information data is referred in the corresponding M road chain;

The data classifying module is used for collection period is divided into a plurality of timeslices, at each road chain, the traffic information data of described road chain correspondence is referred in the corresponding timeslice;

Merge speed calculation module, be used for each timeslice, read the speed data in the traffic information data, and calculate a fusion speed according to described speed data at each road chain;

The road conditions discrimination module is used for differentiating traffic in current road chain, the timeslice according to described fusion speed, and then differentiates the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

Another purpose of the embodiment of the invention is to provide a kind of traffic information processing system, described traffic information processing system comprises raw data base, the traffic information distributing device, and described traffic information processing system also comprises the judgement system of road conditions, it is characterized in that described judgement system comprises:

Data reception module is used to receive the traffic information data of a collection period;

Map-matching module is used for by map match, and described traffic information data is referred in the corresponding M road chain;

The data classifying module is used for collection period is divided into a plurality of timeslices, at each road chain, the traffic information data of described road chain correspondence is referred in the corresponding timeslice;

Merge speed calculation module, be used for each timeslice, read the speed data in the traffic information data, and calculate a fusion speed according to described speed data at each road chain;

The road conditions discrimination module is used for differentiating traffic in current road chain, the timeslice according to described fusion speed, and then differentiates the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

In an embodiment of the present invention, traffic information data at a collection period, pass through map match, and classify according to the traffic information data of a plurality of timeslices after to map match, at the speed in the traffic information data of each timeslice under each road chain, calculate a fusion speed, and judge traffic in current road chain, the timeslice, and then differentiate the whole traffic of M road chain in collection period according to this fusion speed.Like this, for each road chain of a collection period, can be used to judge that the collection point data of traffic are just more, merge by speed data, make abnormal data less to whole traffic discrimination result influence, more accurate even road conditions are differentiated the result.

Description of drawings

Fig. 1 is the implementing procedure figure of the method for discrimination of the road conditions that provide of the embodiment of the invention;

Fig. 2 is the implementing procedure figure of the computing method of the fusion speed that provides of the embodiment of the invention;

Fig. 3 is the implementing procedure figure according to fusion speed differentiation traffic behavior that the embodiment of the invention provides;

Fig. 4 is the process flow diagram according to the whole traffic of traffic state judging road chain in the cycle of current road each timeslice of chain that the embodiment of the invention provides;

Fig. 5 is the structural representation of the traffic information processing system that provides of the embodiment of the invention;

Fig. 6 is the structural representation of the fusion speed calculation module that provides of the embodiment of the invention.

Embodiment

In order to make purpose of the present invention, technical scheme and advantage clearer,, the present invention is further elaborated below in conjunction with drawings and Examples.Should be appreciated that specific embodiment described herein only in order to explanation the present invention, and be not used in qualification the present invention.

In an embodiment of the present invention, traffic information data at a collection period, pass through map match, and classify according to the traffic information data of a plurality of timeslices after to map match, at the speed in the traffic information data of each timeslice under each road chain, calculate a fusion speed, and judge traffic in current road chain, the timeslice, and then differentiate the whole traffic of M road chain in collection period according to this fusion speed.Like this, for each road chain of a collection period, can be used to judge that the collection point data of traffic are just more, merge by speed data, make abnormal data less to whole traffic discrimination result influence, more accurate even road conditions are differentiated the result.

Fig. 1 shows the implementing procedure of the method for discrimination of the road conditions that the embodiment of the invention provides, and details are as follows:

In step S101, receive the traffic information data in the collection period.This traffic information data can comprise current place longitude and latitude, speed, time, information such as direction.

Floating Car is gathered traffic information data on road, and every predetermined period T, with regard to utilizing wireless communication mode the traffic information data that collects is sent.Should predetermined period T be collection period.For the Floating Car that is mounted with GPS equipment, a GPS point of its collection is a traffic information data.Certainly, after receiving all data, can also reject some wrong data, for example speed is the traffic information data of negative value.

In step S102, by map match, this traffic information data is referred in the corresponding M road chain, wherein M is the road chain number that road comprised that needs to judge road conditions on the electronic chart.

Each road chain for road on the electronic chart all has the longitude and latitude scope, when the latitude and longitude information in certain bar traffic information data is in the longitude and latitude scope of a certain road chain, this traffic information data is referred in this road chain, and promptly this traffic information data is about this road chain.

Through after the map match, as embodiments of the invention, can revise some traffic information datas devious, for example, the speed limit of certain bar road chain is 80km/h, can make the speed data that surpasses 80km/h on this road chain into 80km/h.

In step S103, collection period is divided into N timeslice, at each road chain, the traffic information data that it is corresponding is referred in the corresponding timeslice.

As embodiments of the invention, collection period T can be equally divided into N timeslice: t ₁, t ₂..., t _N-1, t _NAt all traffic information datas of each road chain correspondence, according to the time in the traffic information data, gather in the sheet between at a time when certain bar traffic information data, then this traffic information data is referred in this timeslice.Certainly, also can adopt non-average mode to come the time division sheet.

In step S104, read i road chain, the speed data in all traffic information datas in j timeslice.

Wherein, i, the initial value of j is 1, and promptly from the 1st road chain, the speed data in all traffic information datas in the 1st timeslice begins to read.

In step S105, calculate the fusion speed that to represent the average travel speed of this road chain according to these all speed datas that read.

For making the differentiation result more accurate, need reduce the abnormal speed data to merging the influence of speed as far as possible, make data as far as possible near average travel speed.As embodiments of the invention, can give n speed data configuration a weighted value respectively, the weighted value that makes the abnormal speed data is less than 1/n, and wherein, n is the number of the speed data of current road chain, timeslice.At this moment, fusion speed is the sum of seizing the opportunity of n speed data and its respective weights value.Suppose that in current link, timeslice, all speed datas are: V ₁, V ₂..., V _i..., V _N-1, V _n, its corresponding weighted value is: ω ₁, ω ₂..., ω _i..., ω _n, ω ₁+ ω ₂+ ... + ω _n=1, fusion speed so is: V ₁ω ₁+ V ₂ω ₂+ ... + V _iω _i+ ... + V _nω _n

Usually, in current road chain, timeslice, it is unusual having only the minority speed data.Therefore, for normal speed data, most speed datas differ less in itself and other data, it is the support that normal speed data can access most speed datas in other data, and for unusual speed data, most speed datas differ bigger in itself and other data, and promptly unusual speed data can not get the support of most speed datas in other data.Therefore, as embodiments of the invention, can be subjected to the support situation of other speed data according to each speed data, the support situation that the size of configure weights value, speed data obtain other speed data is high more, gives this speed data configuration big more weighted value.

When calculating fusion speed, do not distinguish the source vehicle of speed data, but regard current road chain, all speed datas of timeslice as one group of data that contain noise, and utilize this group data computation to obtain fusion speed.Owing to adopted the data of all vehicles, the Data Source that is used to calculate fusion speed has obtained abundant, and the fusion speed that calculates is just more accurate.

In step S106, differentiate traffic in current road chain, the timeslice according to this fusion speed.Traffic comprises: unimpeded, crowded, stop up three kinds.

In step S107, the value of j increases by 1.

In step S108, whether the value of judging j is greater than N.Because N is the number of the timeslice in the one-period, if the value of j is not more than N, illustrating has still At All Other Times under the chain of current road that the speed data of sheet does not read, and then returns execution in step S104; If the value of j, illustrates then that the speed data of all timeslices under the chain of current road all reads greater than N and finishes, direct execution in step S109 then.

In step S109, according to traffic state judging this road chain the whole traffic collection period in of this road chain in each timeslice.

In step S110, the value of i increases by 1.

In step S111, whether the value of judging i is greater than M.Because M is the number of road road chain, if the value of i is not more than M, illustrating still has the speed data of road chain not read, and then returns execution in step S104; If the value of i, illustrates then that the speed data of all road chains all reads greater than M and finishes, then finish whole flow process.

Fig. 2 shows the implementing procedure of the computing method of the fusion speed that the embodiment of the invention provides, and details are as follows:

In step S1051,, calculate each speed data of reflection matrix X=[x of the degree of support mutually according to n speed data ₁, x ₂..., x _n] ^T

Suppose that in current link, timeslice all speed datas are V ₁, V ₂..., V _i..., V _N-1, V _n, matrix X=[x ₁, x ₂..., x _n] ^TComputing method be:

d _ij＝|v _i-v _j|，i，j＝1，2，…，n；

$r_{\mathrm{ij}}=\frac{{-d}_{\mathrm{ij}}}{\max \left\{d_{\mathrm{ij}}\right\}}+1,(d_{\mathrm{ij}}>0);$

$R=\left|\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ ...& ...& ...& ...\\ r_{n1}& r_{n2}& ...& r_{\mathrm{nn}}\end{array}\right|,$ Calculate the maximum norm eigenvectors matrix of R (n*n) at last, promptly obtain X=[x ₁, x ₂..., x _n] ^TWherein, d _IjThe absolute value of representing the difference of i speed data and j speed data, the i.e. relative distance of an i and j speed data.Max{d _IjRepresent all d _IjIn maximal value, i.e. maximal value in two speed relative distance.R degree of expressing support for matrix.

Because d _IjThe relative distance of representing an i and j speed data, therefore, the degree that can support mutually with this n of matrix representation speed data of a n*n, and, introduce r for the ease of the calculating of the maximum norm eigenvectors matrix of the matrix of n*n _Ij, i.e. r _IjUse the degree of support that has showed i speed data and j speed data less than 1 numerical value.

In step S1052, calculate weight matrix W=[ω according to X ₁, ω ₂..., ω _n]] ^T, wherein, ω _i=[x _i/ (x ₁+ x ₂+ ... + x _n)].

In step S1054, calculate fusion speed v=ω according to weight matrix W ₁v ₁+ ω ₂v ₂+ ... + ω _nv _n

Certainly, except that the computing method of above-mentioned fusion speed, also can adopt other method to calculate fusion speed, the algorithm that only needs to be adopted reduces the abnormal speed data to merging the influence of speed as far as possible, makes fusion speed as far as possible near average travel speed.

Fig. 3 shows the implementing procedure according to fusion speed differentiation traffic behavior that the embodiment of the invention provides, and details are as follows:

In step S1061, judge whether fusion speed is not less than unimpeded speed threshold values.

Preestablish a unimpeded speed threshold values, contrast the fusion speed and the unimpeded speed threshold values that calculate, when fusion speed during more than or equal to unimpeded threshold values, execution in step S1062, otherwise, execution in step S1063.As embodiments of the invention, can be with the initial set value of this unimpeded speed threshold values be the maximum limit speed in highway section.

In step S1062, make the value of unimpeded number of times increase by 1, and the unimpeded velocity amplitude that adds up.With unimpeded number of times of reference record and unimpeded velocity amplitude, whenever fusion speed during greater than unimpeded speed threshold values, the parameter that writes down unimpeded number of times increases by 1, and will merge velocity amplitude and be added in the parameter that writes down unimpeded velocity amplitude.

In step S1063, judge whether fusion speed is not less than crowded speed threshold values.Preestablish a crowded speed threshold values, when fusion speed during, contrast fusion speed and crowded speed threshold values less than unimpeded speed threshold values, when fusion speed when crowding threshold values, execution in step S1064, otherwise, execution in step S1065.

In step S1064, make the value of crowded number of times increase by 1, and the crowded velocity amplitude that adds up.With crowded number of times of reference record and crowded velocity amplitude, whenever fusion speed less than unimpeded speed threshold values, and during more than or equal to crowded speed threshold values, the value of the parameter of the crowded number of times of record increases by 1, and will merge velocity amplitude and be added in the parameter that writes down the velocity amplitude that crowds.

In step S1065, make the value of stopping up number of times increase by 1, and the obstruction velocity amplitude that adds up.Stop up number of times and stop up velocity amplitude with reference record, whenever fusion speed during less than crowded speed threshold values, the value that record stops up the parameter of number of times increases by 1, and current fusion velocity amplitude is increased in the parameter that writes down the obstruction velocity amplitude.

The flow process that Fig. 4 shows that the embodiment of the invention provides according to the whole traffic of traffic state judging road chain in the cycle of current road each timeslice of chain, details are as follows:

In step S1091, more unimpeded number of times, crowded number of times, the size of obstruction number of times.When the value of unimpeded number of times is maximum, execution in step S1092; When the value of crowded number of times is maximum, execution in step S1093; When the value of stopping up number of times is maximum, execution in step S1094.

In step S1092, calculate average unimpeded speed, unimpeded degree, confidence level.

Wherein, the unimpeded speed/unimpeded number of times of average unimpeded speed=after adding up.

Unimpeded degree=(average unimpeded speed-unimpeded speed threshold values)/(link limiting velocity-unimpeded speed threshold values), the maximum speed limit * correction factor of link limiting velocity=road, correction factor can be got a value in 1.3～1.5, and the maximum speed limit of road is known.The unimpeded degree of road chain is high more, and this road is just unimpeded more.

Confidence level=unimpeded number of times/effective time sheet number.Wherein, effective time, the sheet number was meant the timeslice that has 1 speed data at least, and effective time, sheet can come out.This unimpeded confidence level is high more, and unimpeded possibility is big more, and promptly unimpeded conclusion is credible more.

In step S1093, calculate average crowded speed, crowding, confidence level.

Wherein, the crowded speed/crowded number of times of on average crowded speed=after adding up.

Crowding=(unimpeded speed threshold values-on average crowded speed)/(unimpeded speed threshold values-crowded speed threshold values).Crowding is high more, and the road chain is just crowded more.

Confidence level=unimpeded number of times/effective time sheet number.Confidence level that should be crowded is high more, and crowded possibility is big more, and promptly Yong Ji conclusion is credible more.

In step S1094, calculate average obstruction speed, congestion degree, confidence level.

Wherein, on average stop up the obstruction speed/obstruction number of times of speed=after adding up.

Crowding=(crowded speed threshold values-on average stop up speed)/crowded speed threshold values, crowding is high more, and the road chain is just crowded more.

Confidence level=obstruction number of times/effective time sheet number.The confidence level of this obstruction is high more, and possibility of jamming is big more, and promptly the conclusion of Du Saiing is credible more.

Fig. 5 shows the structure of the traffic information processing system that the embodiment of the invention provides, and this traffic information processing system comprises the judgement system of road conditions, raw data base and traffic information distributing device.

In the concrete process of implementing, the judgement system of road conditions comprises: data aggregation and pretreatment system, judgement system.Data aggregation and pretreatment system comprise: raw data parsing module 301, misdata are rejected module 302, map-matching module 303, deviation data correcting module 304 and packing data sending module 305.And judgement system comprises data resolution module 306, data classifying module 307, merges speed calculation module 308, road conditions discrimination module 309 and road conditions fusion treatment module 310.

The raw data that Floating Car collects is kept in the raw data base, the raw data parsing module 301 of data aggregation and pretreatment system obtains the raw data of a collection period from raw data base, misdata is rejected module 302 and is deleted the irrational data of data attribute, for example, current time is 2008, the data time attribute is 2007, and obviously the attribute of data is unreasonable.Map-matching module 303 is referred to the traffic information data in this cycle in the corresponding M road chain by map match.Deviation data correcting module 304 is revised some data devious, for example surpasses the speed data of the speed threshold values in highway section.Packing data sending module 305 sends to judgement system with pretreated data, has made things convenient for data aggregation and pretreatment system, and judgement system transmits data by ICP/IP protocol.Packing data by 306 pairs of Network Transmission of data resolution module of judgement system is resolved.Data qualification module 307 is divided into a plurality of timeslices to collection period, at each road chain, the traffic information data of this road chain correspondence is referred in the corresponding timeslice.For the various situation of data source type, come grouped data according to type of vehicle (bus, taxi, logistics car etc.) earlier.Speed Fusion Module 308 reads the speed data in the traffic information data at each timeslice in each road chain, and calculates a fusion speed according to this speed data.Road conditions discrimination module 309 is differentiated traffic in current road chain, the timeslice according to this fusion speed, and then differentiates the whole traffic of M road chain in collection period, and wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.Road conditions fusion treatment module 310 receives the local traffic information that transmits such as Department of Communications, Traffic Announcement radio station, and makes fusion treatment with the traffic of road conditions discrimination module output, obtains the final road conditions evaluation result of link.After final road conditions evaluation result is kept at the road condition data storehouse, just can realize text by the traffic information distributing device, picture, map sketch, the transport information issue of various ways such as voice.

In said process, data aggregation and pretreatment system are responsible for obtaining in real time the raw data that Floating Car is gathered from database, through after the pre-service, form effective normal data, directly send judgement system to by the TCP/IP mode at last.Judgement system receives the normal data that data aggregation and pretreatment system send, and obtains road conditions result based on link by processing, and the traffic information data that merges other again obtains the road conditions result of final link.Result after the processing is saved in the road condition data storehouse, uses for the traffic information distributing device.The traffic information distributing device extracts road condition data from original road condition data storehouse, after data are processed, and with text, the map sketch, picture, multiple mode such as voice is issued.

Fig. 6 shows the structure of the fusion speed calculation module that the embodiment of the invention provides, and this fusion speed calculation module 308 comprises weight allocation module 3082 and computing module 3083.

Weight allocation module 3082 disposes a weighted value respectively for n speed data, and the weighted value that makes the abnormal speed data is less than 1/n, and to make n weighted value sum be 1.Computing module 3083 is according to v=ω ₁v ₁+ ω ₂v ₂+ ... + ω _nv _nCalculate fusion speed, wherein, n is the number of the speed data of current road chain, timeslice, and in current link, the timeslice, all speed datas are V ₁, V ₂..., V _i..., V _N-1, V _n, its corresponding weighted value is ω ₁, ω ₂..., ω _i..., ω _N-1, ω _nAs embodiments of the invention, merge speed calculation module and also comprise weight matrix computing module 3081, this weight matrix computing module 3081 calculates the matrix X=[x as weight configuration foundation ₁, x ₂..., x _n] ^T, be weight allocation module 3081 and assign weight and provide foundation, described ω _i=[x _i/ (x ₁+ x ₂+ ... + x _n)], this matrix X=[x ₁, x ₂..., x _n] ^TBe the maximum norm eigenvectors matrix of matrix R, the computing method of this matrix R are:

d _ij＝|v _i-v _j|，i，j＝1，2，…，n；

$r_{\mathrm{ij}}=\frac{{-d}_{\mathrm{ij}}}{\max \left\{d_{\mathrm{ij}}\right\}}+1,(d_{\mathrm{ij}}>0);$

$R=\left|\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ ...& ...& ...& ...\\ r_{n1}& r_{n2}& ...& r_{\mathrm{nn}}\end{array}\right|;$

Wherein, V _iBe i speed, V _jBe j speed, ω _iBe V _iCorresponding weighted value, d _IjThe relative distance of representing an i and j speed data, max{d _IjRepresent all d _IjMiddle maximal value.

In sum, traffic information data at a collection period, pass through map match, and classify according to the traffic information data of a plurality of timeslices after to map match, at the speed in the traffic information data of each timeslice under each road chain, calculate a fusion speed, and judge traffic in current road chain, the timeslice, and then differentiate the whole traffic of M road chain in collection period according to this fusion speed.Like this, for each road chain of a collection period, can be used to judge that the collection point data of traffic are just more, merge by speed data, make abnormal data less to whole traffic discrimination result influence, more accurate even road conditions are differentiated the result.

The above only is preferred embodiment of the present invention, not in order to restriction the present invention, all any modifications of being done within the spirit and principles in the present invention, is equal to and replaces and improvement etc., all should be included within protection scope of the present invention.

Claims (9)

1, a kind of method of discrimination of road conditions is characterized in that, said method comprising the steps of:

Receive the traffic information data of a collection period;

By map match, described traffic information data is referred in the corresponding M road chain;

Collection period is divided into a plurality of timeslices,, the traffic information data of described road chain correspondence is referred in the corresponding timeslice at each road chain;

Each timeslice in each road chain reads the speed data in the traffic information data, and calculates a fusion speed according to described speed data;

Differentiate traffic in current road chain, the timeslice according to described fusion speed, and then differentiate the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

2, the method for claim 1 is characterized in that, describedly reads the speed data in the traffic information data at each timeslice in each road chain, and calculates a step that merges speed according to described speed data and specifically comprise:

Dispose a weighted value respectively for n speed data, the weighted value that makes the abnormal speed data is less than 1/n, and to make n weighted value sum be 1;

According to v=ω ₁v ₁+ ω ₂v ₂+ ...+ω _nv _nCalculate fusion speed,

Wherein, n is the number of the speed data of current road chain, timeslice, and in current link, the timeslice, all speed datas are V ₁, V ₂..., V _i..., V _N-1, V _n, its corresponding weighted value is ω ₁, ω ₂..., ω _i..., ω _N-1, ω _n

3, method as claimed in claim 2 is characterized in that, disposes a weighted value respectively for n speed data described, and the weighted value that makes the abnormal speed data is less than 1/n, and to make n weighted value sum be that 1 step also comprises before:

Calculating is as the matrix X=[x of weight configuration foundation ₁, x ₂..., x _n] ^T, described ω _i=[x _i/ (x ₁+ x ₂+ ...+x _n)],

Described matrix X=[x ₁, x ₂..., x _n] ^TBe the maximum norm eigenvectors matrix of matrix R, the computing method of described matrix R are:

d _ij＝|v _i-v _j|，i，j＝1，2，...，n；

$r_{\mathrm{ij}}=\frac{-d_{\mathrm{ij}}}{\max \left\{d_{\mathrm{ij}}\right\}}+1,(d_{\mathrm{ij}}>0);$

$R=\left|\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ ...& ...& ...& ...\\ r_{n1}& r_{n2}& ...& r_{\mathrm{nn}}\end{array}\right|;$

Wherein, V _iBe i speed, V _jBe j speed, ω _iBe V _iCorresponding weighted value, d _IjThe relative distance of representing an i and j speed data, max{d _IjRepresent all d _IjMiddle maximal value.

4, a kind of judgement system of road conditions is characterized in that, described system comprises:

Data reception module is used to receive the traffic information data of a collection period;

Map-matching module is used for by map match, and described traffic information data is referred in the corresponding M road chain;

The data classifying module is used for collection period is divided into a plurality of timeslices, at each road chain, the traffic information data of described road chain correspondence is referred in the corresponding timeslice;

Merge speed calculation module, be used for each timeslice, read the speed data in the traffic information data, and calculate a fusion speed according to described speed data at each road chain;

The road conditions discrimination module is used for differentiating traffic in current road chain, the timeslice according to described fusion speed, and then differentiates the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

5, system as claimed in claim 4 is characterized in that, described fusion speed calculation module comprises:

The weight allocation module is used for disposing a weighted value respectively to n speed data, and the weighted value that makes the abnormal speed data is less than 1/n, and to make n weighted value sum be 1;

Computing module is used for the ω according to v= ₁v ₁+ ω ₂v ₂+ ...+ω _nv _nCalculate fusion speed,

Wherein, n is the number of the speed data of current road chain, timeslice, and in current link, the timeslice, all speed datas are V ₁, V ₂..., V _i..., V _N-1, V _n, its corresponding weighted value is ω ₁, ω ₂..., ω _i..., ω _N-1, ω _n

6, system as claimed in claim 4 is characterized in that, described fusion speed calculation module also comprises:

The weight matrix computing module is used to calculate the matrix X=[x as weight configuration foundation ₁, x ₂..., x _n] ^T, described ω _i=[x _i/ (x ₁+ x ₂+ ...+x _n)],

Described matrix X=[x ₁, x ₂..., x _n] ^TBe the maximum norm eigenvectors matrix of matrix R, the computing method of described matrix R are:

d _ij＝|v _i-v _j|，i，j＝1，2，...，n；

$r_{\mathrm{ij}}=\frac{-d_{\mathrm{ij}}}{\max \left\{d_{\mathrm{ij}}\right\}}+1,(d_{\mathrm{ij}}>0);$

$R=\left|\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ ...& ...& ...& ...\\ r_{n1}& r_{n2}& ...& r_{\mathrm{nn}}\end{array}\right|;$

Wherein, V _iBe i speed, V _jBe j speed, ω _iBe V _iCorresponding weighted value, d _IjThe relative distance of representing an i and j speed data, max{d _IjRepresent all d _IjMiddle maximal value.

7, a kind of traffic information processing system, described traffic information processing system comprises raw data base, and the traffic information distributing device is characterized in that, and described traffic information processing system also comprises the judgement system of road conditions, it is characterized in that, and described judgement system comprises:

Data reception module is used to receive the traffic information data of a collection period;

Map-matching module is used for by map match, and described traffic information data is referred in the corresponding M road chain;

The data classifying module is used for collection period is divided into a plurality of timeslices, at each road chain, the traffic information data of described road chain correspondence is referred in the corresponding timeslice;

Merge speed calculation module, be used for each timeslice, read the speed data in the traffic information data, and calculate a fusion speed according to described speed data at each road chain;

The road conditions discrimination module is used for differentiating traffic in current road chain, the timeslice according to described fusion speed, and then differentiates the whole traffic of M road chain in collection period,

Wherein, M is the road chain number that road comprised that needs to differentiate road conditions on the electronic chart.

8, traffic information processing system as claimed in claim 7 is characterized in that, described fusion speed calculation module comprises:

The weight allocation module is used for disposing a weighted value respectively to n speed data, and the weighted value that makes the abnormal speed data is less than 1/n, and to make n weighted value sum be 1;

Computing module is used for the ω according to v= ₁v ₁+ ω ₂v ₂+ ...+ω _nv _nCalculate fusion speed,

Wherein, n is the number of the speed data of current road chain, timeslice, and in current link, the timeslice, all speed datas are V ₁, V ₂..., V _i..., V _N-1, V _n, its corresponding weighted value is ω ₁, ω ₂..., ω _i..., ω _N-1, ω _n

9, traffic information processing system as claimed in claim 7 is characterized in that, described fusion speed calculation module also comprises:

The weight matrix computing module is used to calculate the matrix X=[x as weight configuration foundation ₁, x ₂..., x _n] ^T, described ω _i=[x _i/ (x ₁+ x ₂+ ...+x _n)],

Described matrix X=[x ₁, x ₂..., x _n] ^TBe the maximum norm eigenvectors matrix of matrix R, the computing method of described matrix R are:

d _ij＝|v _i-v _j|，i，j＝1，2，...，n；

$r_{\mathrm{ij}}=\frac{-d_{\mathrm{ij}}}{\max \left\{d_{\mathrm{ij}}\right\}}+1,(d_{\mathrm{ij}}>0);$

$R=\left|\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ ...& ...& ...& ...\\ r_{n1}& r_{n2}& ...& r_{\mathrm{nn}}\end{array}\right|;$

Wherein, V _iBe i speed, V _jBe j speed, ω _iBe V _iCorresponding weighted value, d _IjThe relative distance of representing an i and j speed data, max{d _IjRepresent all d _IjMiddle maximal value.

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