CN103258430B - Road traveling time calculating and traffic road condition judging method and road traveling time calculating and traffic road condition judging device - Google Patents

Road traveling time calculating and traffic road condition judging method and road traveling time calculating and traffic road condition judging device Download PDF

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Publication number
CN103258430B
CN103258430B CN201310150613.9A CN201310150613A CN103258430B CN 103258430 B CN103258430 B CN 103258430B CN 201310150613 A CN201310150613 A CN 201310150613A CN 103258430 B CN103258430 B CN 103258430B
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described
vehicle
section
sample
hourage
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CN201310150613.9A
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CN103258430A (en
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高林
王栋梁
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青岛海信网络科技股份有限公司
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Abstract

The invention discloses a road segment traveling time calculating and traffic road condition judging method and a road segment traveling time calculating and traffic road condition judging device. The road segment traveling time calculating and traffic road condition judging method includes the following steps. License plate data of small vehicles between an upstream intersection entrance road segment and a downstream intersection exit road segment of a road segment within a set time period before the current time are collected. License plate matching is performed on the license plate data collected from the upstream intersection and the downstream intersection of the road segment. Driving time and driving speeds of the vehicles which pass through the road segment and matched with the license plates are confirmed. Abnormal speed screening is performed based on confirmed driving speeds and sample vehicles are confirmed. According to driving time spent by the sample vehicles in passing through the road segment and by combining with a time period where the current time exists, traveling time statistics of the road segment are calculated out. According to the road segment traveling time calculating method and the road segment traveling time calculating and traffic road condition judging device, only license data of small vehicles are collected, license plate matching is performed on the license plate data and abnormal speed data screening is performed so that traveling time of a segment of an urban road can be calculated out accurately by combing with the time period where the current time exists.

Description

Road trip time statistics and traffic decision method and device

Technical field

The present invention relates to intelligent transportation field, particularly relate to a kind of road trip time statistics and traffic decision method and device.

Background technology

Along with the rapid propelling of urbanization process, living standards of the people improve day by day, and Urban vehicles poputation rapidly increases, and what bring is that urban road traffic congestion phenomenon is on the rise thereupon.Carry out automatically, timely judging to urban highway traffic road conditions, the information that urban road can be provided whether to block up for traveler, contributes to the smooth trip of traveler, and slows down urban traffic jam, improves urban highway traffic integrated management level.

At present, urban highway traffic road conditions mainly to carry out judging according to road section hourage: the average overall travel speed calculating this section according to road section hourage; Search urban highway traffic road condition division table according to the average overall travel speed in this section, determine the traffic in this section.

Publication number is that the patent of invention of CN1025924446 discloses a kind of method utilizing Floating Car locator data to calculate the intercity road travel time.The method arranges at least two threshold speeds, and intercity road chain is divided at least three kinds of road segment classification by described at least two threshold speeds; Gather the locator data of Floating Car in each data acquisition moment, comprise road speed and latitude and longitude coordinates; According to the locator data of Floating Car and threshold speed, segmentation is carried out to intercity road chain; And the hourage calculated according to the locator data of Floating Car and threshold speed on often kind of section.

The present inventor finds, when the method is applied to urban road, the road trip time calculated may be not accurate enough; Its reason is, the method carries out segmentation mainly for intercity road chain, and calculates the road trip time of intercity.If the method to be applied to the calculating of Urban road hourage, the method does not limit the type of vehicle gathering Floating Car locator data, can not get rid of the locator data of specific Floating Car, in the locator data of the bus of fixed station stop in such as city.Therefore, not accurate enough for hourage according to the Urban road that the method calculates, cause the judgement of city traffic road condition also not accurate enough.

Publication number is that the patent of invention of CN101017609 discloses a kind of intelligent analysis system for municipal traffic journey time.This system comprises candid photograph identification equipment, the Intelligent Service device at each crossing being arranged on urban traffic network, and each is captured identification equipment and connects Intelligent Service device; Intelligent Service device comprises urban traffic network topological structure module, vehicle snapshot identification module, road-section average running time computing module, discrimination module violating the regulations.Wherein, road-section average running time computing module is for calculating road-section average running time (or road trip time).

The present inventor finds, the method is also not accurate enough when carrying out road-section average running time and calculating; Its reason is, the method, using capturing the car plate data of the license plate number coupling arrived all as the car plate data calculating road-section average running time, does not carry out abnormal data screening to car plate data.If be included in the car plate data that the vehicle of of short duration parking or oiling is carried out in this section in the car plate data of capturing, then the road-section average running time that goes out of this system-computed is by not accurate enough, causes the judgement of city traffic road condition also not accurate enough.

In sum, for the road trip time computing method of urban road application prior art, the road trip time calculated is not accurate enough, causes the accuracy of the traffic determined according to road trip time also not high; Therefore, be necessary that the road trip time providing a kind of traffic that can more adequately determine calculates and traffic decision method.

Summary of the invention

The embodiment provides a kind of road trip time statistics and traffic decision method and device, in order to more adequately to calculate Urban road hourage, and more adequately judge the traffic of urban road according to road trip time.

According to an aspect of the present invention, provide a kind of road trip time statistical method, comprising:

Obtain the first data acquisition set and the second data acquisition set; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set;

For each car plate data in the second data acquisition set, if find the car plate data matched with it in the first data acquisition set, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted;

For each vehicle to be counted, determine the running time of this vehicle by described section, and determine the travel speed of this vehicle by described section according to the running time determined;

According to the travel speed of each vehicle to be counted by described section, carry out abnormal speed screening, from described vehicle to be counted, determine sample vehicle;

According to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, calculate statistical value hourage in described section.

Preferably, described according to the travel speed of each vehicle to be counted by described section, after carrying out abnormal speed screening, from described vehicle to be counted, determine that sample vehicle specifically comprises:

For each vehicle to be counted, the upper and lower limit of this vehicle to be counted by the travel speed in described section and the travel speed interval in described section is compared; If be greater than the upper limit in described travel speed interval, then this vehicle to be counted is defined as over-speed vehicles; If be less than the lower limit in described travel speed interval, then this vehicle to be counted is defined as idling car;

Statistics is defined as the quantity of over-speed vehicles, if the quantity of over-speed vehicles is less than the first proportion threshold value, then each over-speed vehicles is defined as vehicle to be screened out;

Statistics is defined as the quantity of idling car, if the quantity of idling car is less than the second proportion threshold value, then each idling car is defined as vehicle to be screened out;

Wait that the vehicle sieved than vehicles is described sample vehicle described in determining to remove in described vehicle to be counted.

Preferably, described setting-up time section is specially a sampling period; And the first car plate data that collect for current sample period of car plate data in data acquisition set and the second data acquisition set.

Preferably, described according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section specifically comprises:

After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is peak period, then:

After the sample state of described current sample period being set to disappearance, n before judgement 1whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 1the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 1for the round values preset.

Preferably, described according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:

After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is the flat peak phase, then:

After the sample state of described current sample period being set to disappearance, n before judgement 2whether the sample state in individual sampling period is disappearance; If the disappearance of being, by statistical value hourage in the section in sampling period residing for the time corresponding to described current time before m in historical data days, as statistical value hourage in the described section of described current sample period; Otherwise, calculate described n before 2the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 2, m is respectively the round values preset.

Preferably, described according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:

After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is low peak period, then:

Whether the traffic judging the last sampling period is unimpeded; If so, then hourage corresponding for the free flow velocity in described section is worth statistical value hourage as the described section of described current sample period; Otherwise, n before judgement 3whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 3the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 3for the round values preset, the traffic in described last sampling period be according to described current sample period before statistical value hourage in section in sampling period judge out.

Preferably, described according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:

If determine, the quantity of described sample vehicle is greater than the sample value upper limit, then according to the running time of each sample vehicle by described section, normal distribution criterion is adopted to calculate the hourage in described section after statistical value, do to optimize further to statistical value hourage calculated: by be less than calculate hourage statistical value, after each sample vehicle makes arithmetic mean by the running time in described section, the mean value obtained is as statistical value hourage after optimizing; Using after optimizing hourage statistical value as final statistical value hourage in described section;

If determine, the quantity of described sample vehicle is between described sample value upper and lower limit, then according to the running time of each sample vehicle by described section, adopt normal distribution criterion to calculate statistical value hourage in described section.

According to another aspect of the present invention, additionally provide a kind of traffic decision method, comprising:

Above-mentioned road trip time statistical method is adopted to calculate statistical value hourage in described section;

According to statistical value hourage calculated, calculate the travel speed statistical value in described section;

The traffic in described section is judged according to the speed statistical value calculated.

According to another aspect of the present invention, additionally provide a kind of road trip time statistic device, comprising:

Image data acquisition module, for obtaining the first data acquisition set and the second data acquisition set; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set;

Car plate matching module, for for each car plate data in the second data acquisition set, if find the car plate data matched with it in the first data acquisition set, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted;

Abnormal speed screening module, for for each vehicle to be counted, determines the running time of this vehicle by described section, and determines the travel speed of this vehicle by described section according to the running time determined; According to the travel speed of each vehicle to be counted by described section, carry out abnormal speed screening, from described vehicle to be counted, determine sample vehicle;

Hourage statistical module, for according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, calculate statistical value hourage in described section.

According to another aspect of the present invention, additionally provide a kind of traffic decision maker, comprising:

Each module in above-mentioned road trip time statistic device; And

Travel speed statistical module, for statistical value hourage according to the section that described hourage, statistical module calculated, calculates the travel speed statistical value in described section;

Traffic determination module, the travel speed statistical value for calculating according to described travel speed statistical module judges the traffic in described section.

In technical scheme of the present invention, the collection of the car plate data of Urban road hourage and traffic accurately can not be reflected owing to eliminating motorcycle, bus etc., only gather the car plate data of compact car vehicle, and car plate coupling and abnormal speed data screening have been carried out to the car plate data gathered, statistical value hourage in section has been calculated in conjunction with the time period (peak period, flat peak phase and low peak period) residing for current time; Thus more adequately can calculate statistical value hourage in section in urban road, the accuracy that the traffic carrying out section with statistical value hourage improved according to section judges, for traveler provide more accurately transport information to go on a journey smoothly.

Accompanying drawing explanation

Fig. 1 is the road trip time statistical method process flow diagram of the embodiment of the present invention;

Fig. 2 is the method flow diagram of the peak period calculating road trip time statistical value of the embodiment of the present invention;

Fig. 3 is the method flow diagram of the flat peak phase calculating road trip time statistical value of the embodiment of the present invention;

Fig. 4 is the method flow diagram of the low peak period calculating road trip time statistical value of the embodiment of the present invention;

Fig. 5 is the traffic decision method process flow diagram of the embodiment of the present invention;

Fig. 6 a is the inner structure block diagram of the road trip time statistic device of the embodiment of the present invention;

Fig. 6 b is the traffic decision maker inner structure block diagram of the device of the embodiment of the present invention.

Embodiment

For making object of the present invention, technical scheme and advantage clearly understand, enumerate preferred embodiment referring to accompanying drawing, the present invention is described in more detail.But it should be noted that, the many details listed in instructions are only used to make reader to have a thorough understanding, even if do not have these specific details also can realize these aspects of the present invention to one or more aspect of the present invention.

In technical scheme of the present invention, road trip time statistical method gets rid of the collection that motorcycle, bus etc. accurately can not reflect the car plate data of Urban road hourage and traffic, only gathers the car plate data of compact car vehicle; Car plate coupling and abnormal speed screening are carried out to the car plate data gathered; After using normal distribution criterion to get rid of small probability vehicle, in conjunction with the time period (peak period, flat peak phase and low peak period) residing for current time, statistical study is carried out to road trip time.Thus, improve the accuracy of Urban road calculating hourage, and then judge urban highway traffic road conditions more accurately.

The technical scheme of embodiments of the invention is described in detail below in conjunction with accompanying drawing.

The flow process of the road trip time statistical method that the embodiment of the present invention provides, as shown in Figure 1, comprises the steps:

S101: the car plate data of compact car vehicle that is that sail into the crossing, upstream from section and that roll away from from the downstream road junction in described section are carried out gathering and store.

Particularly, car plate data gather mainly through the data acquisition equipment (electronic police, bayonet socket, electronic license plate etc.) of crossing, upstream, section and downstream road junction; Car plate data acquisition comprises: gather the setting-up time section T before current time at crossing, upstream, section ain sail the car plate data in described section into by upstream, section stop line section; The setting-up time section T before current time is gathered in section downstream road junction bin roll the car plate data in described section away from by downstream, section stop line section; For protecting the individual privacy of car owner, store after standardization encryption is carried out to the car plate data gathered.In actual applications, T awith T bcan set as the case may be.

Wherein, the vehicle type restriction of car plate data acquisition is compact car vehicle, does not gather the car plate data of the vehicle such as motorcycle, bus; Due to, during motorcycle driving, dirigibility is too strong, the fixed station of bus in city is stopped, the running time of these vehicles in section can accurately not reflect the traffic in section, by these vehicles get rid of outside the acquisition range of car plate data, with improve according to gather car plate data calculate section hourage statistical value accuracy.

S102: the car plate data of the compact car vehicle that the crossing, upstream in the inherent described section of the setting-up time section before acquisition current time and downstream road junction gather.

Particularly, the first data acquisition set and the second data acquisition set is obtained; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set.In actual applications, described setting-up time section is specially a sampling period of car plate data, and the car plate data that the car plate data in the first data acquisition set and the second data acquisition set collect for current sample period.When each sampling period arrives, obtain the car plate data of the compact car vehicle of crossing, upstream and the downstream road junction gathered in the sampling period before current time.

S103: to the crossing, upstream, described section of acquisition and the car plate data of downstream road junction, carry out car plate coupling.

Particularly, for each car plate data in the second data acquisition set, if find the car plate data matched with it in the first data acquisition set, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted.

Carry out car plate coupling, can get rid of in the sampling period by means of only crossing, upstream, described section or by means of only the car plate data of the vehicle of described section downstream road junction, avoid the scope vehicle etc. of long-time stagnation of movement being included in calculating vehicle, to improve the accuracy calculating road trip time statistical value further.

S104: for each vehicle to be counted, determines the running time of this vehicle by described section, and determines the travel speed of this vehicle by described section according to the running time determined.

Particularly, for vehicle i to be counted, after obtaining the car plate data of this vehicle to be counted, from car plate data, obtain vehicle i to be counted sails described section into moment t by crossing, upstream, section stop line section iuwith the moment t being rolled away from described section by section downstream road junction stop line section idcalculate the running time t of vehicle i to be counted by described section i: t i=t id-t iu; And then calculate the travel speed v of vehicle i to be counted by described section i: v i=L/t i, wherein L is the road section length between crossing, the upstream stop line in described section and downstream road junction stop line.

S105: according to the travel speed of each vehicle to be counted by described section, carry out abnormal speed screening, determine sample vehicle from described vehicle to be counted.

Particularly, a kind of concrete grammar carrying out abnormal speed screening can be: for each vehicle to be counted, is compared by the upper and lower limit of this vehicle to be counted by the travel speed in described section and the travel speed interval in described section; If be greater than the upper limit in described travel speed interval, then this vehicle to be counted is defined as over-speed vehicles; If be less than the lower limit in described travel speed interval, then this vehicle to be counted is defined as idling car; Statistics is defined as the quantity of over-speed vehicles, if the quantity of over-speed vehicles is less than the first proportion threshold value, then each over-speed vehicles is defined as vehicle to be screened out; Statistics is defined as the quantity of idling car, if the quantity of idling car is less than the second proportion threshold value, then each idling car is defined as vehicle to be screened out; Wait that the vehicle sieved than vehicles is sample vehicle described in determining to remove in described vehicle to be counted.

Such as: the travel speed interval [v setting described section min, v max], wherein, v minfor travel speed interval limit, v maxfor the interval upper limit of travel speed, and the travel speed interval in general acquiescence section is [5km/h, 80km/h]; If travel speed is less than v in vehicle to be counted minvehicle in total vehicle to be counted accounting lower than 20%(first proportion threshold value), or in vehicle to be counted, travel speed is greater than v maxdata vehicle in total vehicle to be counted accounting lower than 20%(second proportion threshold value), then this vehicle to be counted is defined as vehicle to be screened out, and is removed; Determine in vehicle to be counted except waiting that the vehicle sieved than vehicles is described sample vehicle.

In addition, also another kind of method of carrying out abnormal speed screening can be adopted according to actual conditions, such as: each vehicle to be counted is sorted by the travel speed in described section; The vehicle of the vehicle of sequence preceding 20% and sequence posterior 20% is filtered out, and is removed.Obviously, those skilled in the art according to the prompting of the abnormal speed screening technique provided in technical solution of the present invention, can adopt other abnormal speed screening technique; Do not departing under principle of the present invention, other abnormal speed screening technique also should be considered as protection scope of the present invention.

After carrying out abnormal speed screening, eliminate the car plate data of over-speed vehicles and idling car, such as, carry out the car plate data of the idling car of of short duration parking or oiling in described section, further increase the accuracy that hourage, statistical value calculated in described section.

S106: according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, calculate statistical value hourage in described section.

Particularly, the traffic flow difference of different time sections is comparatively large, makes each sample vehicle larger by the running time difference in described section in different time sections.Therefore, statistical value hourage calculating described section in conjunction with the time period residing for current time will be more accurate.

In technical scheme of the present invention, for the traffic flow difference of different time sections, mainly will be divided into peak period, flat peak phase and low peak period the time period, and consider the situation of peak period residing for current time, flat peak phase or low peak period, calculate statistical value hourage in described section.Introduce in detail respectively below peak period, the flat peak phase or low peak period time, according to each sample vehicle by the running time in described section, calculate described section hourage statistical value concrete grammar.

If the time period residing for current time is peak period, then according to each sample vehicle by the running time in described section, calculate described section hourage statistical value concrete grammar flow process, as shown in Figure 2, comprise the steps:

S201: the quantity determining sample vehicle; If determine, the quantity of described sample vehicle is greater than the sample value upper limit, then perform step S211; If determine, the quantity of described sample vehicle is less than sample value lower limit, then perform step S221; If determine, the quantity of described sample vehicle is between described sample value upper and lower limit, then perform step S231.

Particularly, the sample value upper limit and sample value lower limit can rule of thumb be arranged, to calculate statistical value hourage in described section more accurately.

S211: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

Particularly, calculate got rid of the small probability vehicle in sample vehicle by normal distribution criterion after described section hourage statistical value method be:

Calculate each sample vehicle in sample vehicle and pass through the arithmetic mean t of the running time in described section 0; And determine σ according to following formula 1:

σ = 1 n Σ i = 1 n ( t i - t 0 ) 2 Formula 1)

In formula 1, n is the quantity of sample vehicle, and i is natural number, t irepresent the running time of i-th sample vehicle by described section;

If | t i-t 0| running time is then t by >3 σ ivehicle get rid of as small probability vehicle.

By the running time in described section, arithmetic mean is done to each sample vehicle in the sample vehicle after eliminating small probability vehicle, obtains statistical value t hourage in described section.

S212: do to optimize further to statistical value hourage calculated, using after optimizing hourage statistical value as final statistical value hourage in described section.

Particularly, the present inventor, according to after cluster analysis, learns that the quantity of sample vehicle to be greater than in sample value in limited time, section described in current sample period hourage statistical value t for judging that traffic is not accurate enough; In fact, when in sample vehicle, each sample vehicle is greater than t by the running time in described section, each sample vehicle has generally comprised the time of each sample vehicle waiting signal lamp red light in described section by the running time in described section, and when in sample vehicle, each sample vehicle is less than t by the running time in described section, each sample vehicle does not generally comprise the time of each sample vehicle waiting signal lamp red light in described section by the running time in described section.

Therefore, do to optimize further to statistical value hourage calculated: by be less than calculate hourage statistical value t, after each sample vehicle makes arithmetic mean by the running time in described section, the mean value obtained as statistical value hourage after optimizing, and using after optimizing hourage statistical value as final statistical value hourage in described section.

S221: after the sample state of current sample period being set to disappearance, n before judgement 1whether the sample state in individual sampling period is disappearance, if the disappearance of being, then performs step S222; Otherwise, perform step S223.

Particularly, the quantity of peak period sample vehicle to be less than under sample value in limited time, be judged as that data acquisition equipment is abnormal, or abnormal cause causes traffic jam, cause the quantity of usable samples vehicle (shortage of data) very little, thus the sample state of current sample period is set to disappearance.Wherein, the sampling period number n of miss status judgement is carried out 1for the integer preset, those skilled in the art can set according to concrete condition.

S222: prompting staff carries out artificial treatment, artificial statistical value hourage issuing described section.

Particularly, after being observed by the shooting information of staff to crossing, determine the traffic in described section, and issue statistical value hourage in section described in current sample period.

S223: carry out shortage of data compensation to current sample period, obtains statistical value hourage in described section.

Particularly, the method for current sample period being carried out to shortage of data compensation is, n before obtaining current sample period 1statistical value hourage in section described in the individual sampling period; Calculate n 1section described in the individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as section described in the current sample cycle.

S231: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

If the time period residing for current time is the flat peak phase, then according to each sample vehicle by the running time in described section, calculate described section hourage statistical value concrete grammar flow process, as shown in Figure 3, comprise the steps:

S301: the quantity determining sample vehicle; If determine, the quantity of described sample vehicle is greater than the sample value upper limit, then perform step S311; If determine, the quantity of described sample vehicle is less than sample value lower limit, then perform step S321; If determine, the quantity of described sample vehicle is between described sample value upper and lower limit, then perform step S331.

S311: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

S312: do to optimize further to statistical value hourage calculated, using after optimizing hourage statistical value as final statistical value hourage in described section.

S321: after the sample state of current sample period being set to disappearance, n before judgement 2whether the sample state in individual sampling period is disappearance, if the disappearance of being, then performs step S322; Otherwise, perform step S323.

Wherein, the sampling period number n of miss status judgement is carried out 2for the integer preset, those skilled in the art can set according to concrete condition.

S322: carry out historical data compensation to current sample period, obtains statistical value hourage in described section.

Particularly, by statistical value hourage in the section in sampling period residing for the time corresponding to current time before m in historical data days, as statistical value hourage in the described section of current sample period, statistical value hourage in described section is therefore obtained.In actual applications, m is the integer preset, such as, set 7 days that within m days, are specially in one week, or multiple week.

S323: carry out shortage of data compensation to current sample period, obtains statistical value hourage in described section.

S331: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

If the time period residing for current time is low peak period, then according to each sample vehicle by the running time in described section, calculate described section hourage statistical value concrete grammar flow process, as shown in Figure 4, comprise the steps:

S401: the quantity determining sample vehicle; If determine, the quantity of described sample vehicle is greater than the sample value upper limit, then perform step S411; If determine, the quantity of described sample vehicle is less than sample value lower limit, then perform step S421; If determine, the quantity of described sample vehicle is between described sample value upper and lower limit, then perform step S431.

S411: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

S412: do to optimize further to statistical value hourage calculated, using after optimizing hourage statistical value as final statistical value hourage in described section.

S421: whether the traffic judging the last sampling period is unimpeded, if so, then performs step S422; Otherwise, perform step S423.

S422: hourage corresponding for the free flow velocity in described section is worth statistical value hourage as described section.

Particularly, the traffic in described last sampling period be according to current sample period before statistical value hourage in section in sampling period judge out; If the traffic in last sampling period is unimpeded, is then judged as the less and the coast is clear of low peak period traffic flow, result in the sample vehicle fleet size got less; Therefore hourage corresponding for free for described section flow velocity is worth statistical value hourage as described section.In actual applications, the free flow rate set in described section is the maximum travelling speed of described section design.

S423: after the sample state of current sample period being set to disappearance, n before judgement 3whether the sample state in individual sampling period is disappearance, if the disappearance of being, then performs step S424; Otherwise, perform step S425.

Wherein, the sampling period number n of miss status judgement is carried out 3for the integer preset, those skilled in the art can set according to concrete condition.

S424: prompting staff carries out artificial treatment, artificial statistical value hourage issuing described section.

S425: carry out shortage of data compensation to current sample period, obtains statistical value hourage in section described in current sample period.

S431: according to the running time of each sample vehicle by described section, adopts normal distribution criterion to calculate statistical value hourage in described section.

In fact, the above-mentioned situation in conjunction with peak period residing for current time, flat peak phase or low peak period, calculate described section hourage statistical value method can be summarized as follows:

If determine, the quantity of sample vehicle is greater than the sample value upper limit, then according to the running time of each sample vehicle by described section, normal distribution criterion is adopted to calculate the hourage in described section after statistical value, do to optimize further to statistical value hourage calculated: by be less than calculate hourage statistical value, after each sample vehicle makes arithmetic mean by the running time in described section, the mean value obtained is as statistical value hourage after optimizing; Using after optimizing hourage statistical value as final statistical value hourage in described section;

If determine, the quantity of sample vehicle is between described sample value upper and lower limit, then according to the running time of each sample vehicle by described section, adopt normal distribution criterion to calculate statistical value hourage in described section;

If determine, the quantity of sample vehicle is less than sample value lower limit, then the situation being peak period for the time period residing for current time is handled as follows: after the sample state of current sample period being set to disappearance, n before judgement 1whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 1the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of current sample period; Wherein, n 1for the round values preset;

If determine, the quantity of sample vehicle is less than sample value lower limit, be then that the situation of flat peak phase is handled as follows for the time period residing for current time: after the sample state of described current sample period being set to disappearance, n before judgement 2whether the sample state in individual sampling period is disappearance; If the disappearance of being, by statistical value hourage in the section in sampling period residing for the time corresponding to described current time before m in historical data days, as statistical value hourage in the described section of described current sample period; Otherwise, calculate described n before 2the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 2, m is respectively the round values preset.

If determine, the quantity of sample vehicle is less than sample value lower limit, then the situation being low peak period for the time period residing for current time is handled as follows: whether the traffic judging the last sampling period is unimpeded; If so, then hourage corresponding for the free flow velocity in described section is worth statistical value hourage as the described section of described current sample period; Otherwise, n before judgement 3whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 3the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 3for the round values preset, the traffic in described last sampling period be according to described current sample period before statistical value hourage in section in sampling period judge out.

The flow process of the traffic decision method that the embodiment of the present invention provides, as shown in Figure 5, comprises the steps:

S501: statistical value hourage calculating described section.

Particularly, adopt above-mentioned road trip time statistical method, calculate statistical value hourage in described section.

S502: according to statistical value hourage calculated, calculates the travel speed statistical value in described section.

Particularly, if statistical value hourage calculated is T, then the travel speed statistical value V in described section is: V=L/T, and in formula, L is the road section length between crossing, the upstream stop line in described section and downstream road junction stop line.

S503: the traffic judging described section according to the speed statistical value calculated.

Particularly, according to practical experience both domestic and external, the major parameter of the division of urban highway traffic road condition is the travel speed in section.According to the critical speed value of urban road grade and traffic state demarcation, urban highway traffic road condition is divided into block up, slow and unimpeded three grades, table 1 shows urban road traffic state partition of the level foundation.With reference to table 1, and according to the speed statistical value calculated, judge the traffic in described section.

Table 1

Based on above-mentioned road trip time statistical method, the concrete inner structure block diagram of the road trip time statistic device that the embodiment of the present invention provides, as shown in Figure 6 a, comprising: image data acquisition module 601, car plate matching module 602, abnormal speed screening module 603, hourage statistical module 604.

Image data acquisition module 601 is for obtaining the first data acquisition set and the second data acquisition set; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set.

Car plate matching module 602 is for each car plate data in the second data acquisition set of obtaining image data acquisition module 601, if find the car plate data matched with it in the first data acquisition set that image data acquisition module 601 obtains, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted.

Abnormal speed screening module 603, for for the determined each vehicle to be counted of car plate matching module 602, is determined the running time of this vehicle by described section, and is determined the travel speed of this vehicle by described section according to the running time determined; According to the travel speed of each vehicle to be counted by described section, carry out abnormal speed screening, from described vehicle to be counted, determine sample vehicle.

Hourage, statistical module 604 was for each sample vehicle of determining according to abnormal speed screening module 603 running time by described section, and in conjunction with the time period residing for described current time, calculated statistical value hourage in described section.

The concrete inner structure block diagram of the traffic decision maker that the embodiment of the present invention provides, as shown in Figure 6 b, comprising: each module in above-mentioned road trip time statistic device, and travel speed statistical module 605 and traffic determination module 606.

Travel speed statistical module 605, for statistical value hourage in section calculated according to statistical module 604 hourage, calculates the travel speed statistical value in described section.

Traffic determination module 606 judges the traffic in described section for the travel speed statistical value calculated according to travel speed statistical module 605.

In the technical scheme of the embodiment of the present invention, the collection of the car plate data of Urban road hourage and traffic accurately can not be reflected owing to eliminating motorcycle, bus etc., only gather the car plate data of compact car vehicle, and car plate coupling and abnormal speed data screening have been carried out to the car plate data gathered, statistical value hourage in section has been calculated in conjunction with the time period (peak period, flat peak phase and low peak period) residing for current time; Thus more adequately can calculate statistical value hourage in section in urban road, the accuracy that the traffic carrying out section with statistical value hourage improved according to section judges, for traveler provide more accurately transport information to go on a journey smoothly.

The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (9)

1. a road trip time statistical method, is characterized in that, comprising:
Obtain the first data acquisition set and the second data acquisition set; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set;
For each car plate data in the second data acquisition set, if find the car plate data matched with it in the first data acquisition set, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted;
For each vehicle to be counted, determine the running time of this vehicle by described section, and determine the travel speed of this vehicle by described section according to the running time determined;
According to the travel speed of each vehicle to be counted by described section, after carrying out abnormal speed screening, from described vehicle to be counted, determine that sample vehicle specifically comprises:
For each vehicle to be counted, the upper and lower limit of this vehicle to be counted by the travel speed in described section and the travel speed interval in described section is compared; If be greater than the upper limit in described travel speed interval, then this vehicle to be counted is defined as over-speed vehicles; If be less than the lower limit in described travel speed interval, then this vehicle to be counted is defined as idling car;
Statistics is defined as the quantity of over-speed vehicles, if the quantity of over-speed vehicles is less than the first proportion threshold value, then each over-speed vehicles is defined as vehicle to be screened out;
Statistics is defined as the quantity of idling car, if the quantity of idling car is less than the second proportion threshold value, then each idling car is defined as vehicle to be screened out;
Wait that the vehicle sieved than vehicles is described sample vehicle described in determining to remove in described vehicle to be counted;
According to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, calculate statistical value hourage in described section.
2. the method for claim 1, is characterized in that, described setting-up time section is specially a sampling period; And the first car plate data that collect for current sample period of car plate data in data acquisition set and the second data acquisition set.
3. method as claimed in claim 2, is characterized in that, described according to the running time of each sample vehicle by described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section specifically comprises:
After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is peak period, then:
After the sample state of described current sample period being set to disappearance, n before judgement 1whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 1the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 1for the round values preset.
4. method as claimed in claim 3, is characterized in that, described according to the running time of each sample vehicle by described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:
After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is the flat peak phase, then:
After the sample state of described current sample period being set to disappearance, n before judgement 2whether the sample state in individual sampling period is disappearance; If the disappearance of being, by statistical value hourage in the section in sampling period residing for the time corresponding to described current time before m in historical data days, as statistical value hourage in the described section of described current sample period; Otherwise, calculate described n before 2the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 2, m is respectively the round values preset.
5. method as claimed in claim 4, is characterized in that, described according to the running time of each sample vehicle by described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:
After determining that the quantity of described sample vehicle is less than sample value lower limit, if judge, the time period residing for described current time is low peak period, then:
Whether the traffic judging the last sampling period is unimpeded; If so, then hourage corresponding for the free flow velocity in described section is worth statistical value hourage as the described section of described current sample period; Otherwise, n before judgement 3whether the sample state in individual sampling period is disappearance; If the disappearance of being, then staff is pointed out to carry out artificial treatment; Otherwise, calculate described n before 3the section in individual sampling period hourage statistical value arithmetic mean; Using the arithmetic mean that calculates statistical value hourage as the section of described current sample period; Wherein, n 3for the round values preset, the traffic in described last sampling period be according to described current sample period before statistical value hourage in section in sampling period judge out.
6. method as claimed in claim 5, is characterized in that, described according to the running time of each sample vehicle by described section, and in conjunction with the time period residing for described current time, statistical value hourage calculating described section also comprises:
If determine, the quantity of described sample vehicle is greater than the sample value upper limit, then according to the running time of each sample vehicle by described section, normal distribution criterion is adopted to calculate the hourage in described section after statistical value, do to optimize further to statistical value hourage calculated: by be less than calculate hourage statistical value, after each sample vehicle makes arithmetic mean by the running time in described section, the mean value obtained is as statistical value hourage after optimizing; Using after optimizing hourage statistical value as final statistical value hourage in described section;
If determine, the quantity of described sample vehicle is between described sample value upper and lower limit, then according to the running time of each sample vehicle by described section, adopt normal distribution criterion to calculate statistical value hourage in described section.
7. a traffic decision method, is characterized in that, comprising:
Statistical value hourage in section as described in the method for employing as described in claim 1-6 calculates;
According to statistical value hourage calculated, calculate the travel speed statistical value in described section;
The traffic in described section is judged according to the speed statistical value calculated.
8. a road trip time statistic device, is characterized in that, comprising:
Image data acquisition module, for obtaining the first data acquisition set and the second data acquisition set; Wherein, include current time in the first data acquisition set before the car plate data of sailing the compact car vehicle in described section into that gather of the crossing, upstream in the inherent described section of setting-up time section; The car plate data rolling the compact car vehicle in described section away from of the downstream road junction collection in the inherent described section of the setting-up time section before including current time in the second data acquisition set;
Car plate matching module, for for each car plate data in the second data acquisition set, if find the car plate data matched with it in the first data acquisition set, then these car plate data are defined as car plate data to be counted, the vehicle with these car plate data is defined as vehicle to be counted;
Abnormal speed screening module, for for each vehicle to be counted, determines the running time of this vehicle by described section, and determines the travel speed of this vehicle by described section according to the running time determined; According to the travel speed of each vehicle to be counted by described section, after carrying out abnormal speed screening, from described vehicle to be counted, determine that sample vehicle specifically comprises:
For each vehicle to be counted, the upper and lower limit of this vehicle to be counted by the travel speed in described section and the travel speed interval in described section is compared; If be greater than the upper limit in described travel speed interval, then this vehicle to be counted is defined as over-speed vehicles; If be less than the lower limit in described travel speed interval, then this vehicle to be counted is defined as idling car;
Statistics is defined as the quantity of over-speed vehicles, if the quantity of over-speed vehicles is less than the first proportion threshold value, then each over-speed vehicles is defined as vehicle to be screened out;
Statistics is defined as the quantity of idling car, if the quantity of idling car is less than the second proportion threshold value, then each idling car is defined as vehicle to be screened out;
Wait that the vehicle sieved than vehicles is described sample vehicle described in determining to remove in described vehicle to be counted;
Hourage statistical module, for according to each sample vehicle by the running time in described section, and in conjunction with the time period residing for described current time, calculate statistical value hourage in described section.
9. a traffic decision maker, is characterized in that, comprising:
Each module in road trip time statistic device as claimed in claim 8; And
Travel speed statistical module, for statistical value hourage according to the section that described hourage, statistical module calculated, calculates the travel speed statistical value in described section;
Traffic determination module, the travel speed statistical value for calculating according to described travel speed statistical module judges the traffic in described section.
CN201310150613.9A 2013-04-26 2013-04-26 Road traveling time calculating and traffic road condition judging method and road traveling time calculating and traffic road condition judging device CN103258430B (en)

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