CN106504528A - A kind of utilization mobile phone signaling big data and the OD scaling methods of Used in Dynamic Traffic Assignment - Google Patents
A kind of utilization mobile phone signaling big data and the OD scaling methods of Used in Dynamic Traffic Assignment Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The present invention relates to the resident trip OD matrix scaling methods of a kind of utilization mobile phone signaling big data and Used in Dynamic Traffic Assignment, its key step includes：Build urban road artificial network model, demarcated using the simulation parameter in each section in the urban road network of microwave and bayonet socket data to structure, the true traffic flow in real road net is obtained using microwave detector, the traffic flow that initial OD matrixes are obtained using mobile phone signaling data, by Used in Dynamic Traffic Assignment method, enter the true traffic flow that Mobile state adjustment is allowed to level off in road network to initial traffic flow, computer sim- ulation estimates error between traffic flow and true traffic flow, demarcate if meeting threshold value and terminate, otherwise proceed the dynamically distributes based on emulation, until demarcate terminating.The present invention is demarcated to the Dynamic OD Matrix of resident trip using mobile phone signaling big data, with the features such as data message steady sources are objective, sample size big, wide coverage, data precision are high, dynamic is strong.
Description
Technical field
The present invention relates to the OD scaling methods field of resident trip, is based especially on mobile phone signaling big data and using dynamic
State method of traffic assignment is demarcated to resident trip OD matrixes.
Background technology
The continuous development of economic society has also come increasing while urban life looks are improved to urban transportation
Pressure.At present, domestic urbanization and the vehicularized process of urban transportation become increasingly faster, in urbanization and vehicularized common
Under effect, congested in traffic problem has become restriction urban development and affects one of subject matter of quality of residents'life.In order to
Effectively solving traffic jam issue under the conditions of existing road network, setting up intelligentized traffic information system becomes solution urban transportation
The key of congested problem, and the foundation of these systems is premised on carrying out the demarcation of resident trip OD matrixes exactly.
Traditional resident trip survey data renewal speed is slow, and sample rate is low, thus the precision of its survey result exist larger
Error.With the raising of mobile phone popularity rate, mobile phone covers city overwhelming majority population, using mobile phone signalling analysis technical substitution
Traditional trip survey is possibly realized.In recent years based on mobile phone signaling data just increasingly by the Competent Authorities of Transport and Communications in each city
Pay attention to and application.Mobile phone signaling data is analyzing the friendship of the OD demands of traffic zone, the trip characteristicses of specific region, road network
There is in terms of logical running status, the generation of traffic zone and attraction unique advantage.Can be facilitated soon using mobile phone signaling data
Population development distribution, artificial abortion's flow of specific region and flow direction prompt and that obtain urbanite in real time.Used in Dynamic Traffic Assignment master
If to specific transportation network, the time-varying characteristics of transport need and each Road Expense function between known network any two points
On the premise of, determine each section, each junction traffic stream mode (flow, speed and density), running time.Final purpose is to be given
Best route is selected, and is instructed system for traffic guiding to formulate Strategy for information issuing, is optimal the spatial and temporal distributions of traffic flow, makes road
Net performance reaches certain specific objective (system optimal or user equilibrium).
Based on the static OD that mobile phone signaling data is obtained, the travelling OD matrix of resident is entered using Used in Dynamic Traffic Assignment method
Rower is fixed.The reasonable induction of traffic flow is finally realized, path resource is made full use of, the operational efficiency of Traffic Systems is improved.
Content of the invention
The present invention can real-time and efficiently obtain urbanite's distribution and flowing, trip characteristicses etc. using mobile phone signaling data
Information, in conjunction with Used in Dynamic Traffic Assignment method, demarcates to resident trip Dynamic OD Matrix.Overcome traditional folk houses investigation method
Fetched data sample size is low, the shortcoming that data precision is poor, when compensate for static traffic distribution method and can not consider transport need
Become the deficiency of feature.Its result can rationally induce distribution of the traffic flow in road network, improve the traffic efficiency of road.
The purpose of the present invention is achieved through the following technical solutions：One kind is using mobile phone signaling big data and dynamic traffic
The resident trip OD scaling methods of distribution, as follows including step：
(1) urban road network model is built based on middle sight traffic simulation instrument DTALite, including city expressway, master
Main line, secondary distributor road, branch road.
(2) for the urban road network built in step (1), by license plate identification data and microwave data to step (1)
The simulation parameter in each section of the urban road network of structure is demarcated.The main method using sectional linear fitting, to road
The traffic capacity, free stream velocity, jam density, four simulation parameters of crowded dissipation velocity of wave demarcated, and using non-linear
Two parameter alphas and β in the Impedance Function model (BPR) that the method for fitting is developed to Bureau of Public Road are demarcated.
The mathematic(al) representation of BPR function models is as follows：
In formula：Hourages of the t for vehicle pass-through section；t0Freely flow the travel time for section；Wagon flows of the q for section
Amount；C is section design capacity；α, β are parameter to be calibrated.
(3) vehicle flowrate in real road network is obtained using microwave detector.
(4) mobile phone signaling data is obtained, by the analysis to mobile phone signaling data, obtains resident little in each traffic analysis
Interval mobility status, obtain the trip distribution characteristicss of resident, so as to form initial OD demands.Specially：By a certain network
The mobile phone signaling data OD of operator is converted into general population OD, is further converted to the OD of motor vehicles, and method for transformation is as follows:
In formula：ODpeople：Permanent resident population OD is distributed；
ODmobile：It is distributed using the OD that a certain operator cellphone subscriber data draw；
α1(average ownership)：The per capita ownership (portion/people) of cellphone subscriber；
α2(penetration rate of mobile phone)：Cellphone subscriber's ratio；
α3(market share)：The market share of the operator；
α4(detection probability)：User mobile phone is detected probability.
Mobile phone number α per capita1=mobile phone number/client's number；Cellphone subscriber's ratio α2=min { client's number/permanent resident population, 1 }；City
Field occupation rate α3There is provided by operator.User mobile phone is detected probability α4Number of users/this area being detected in=mono- month
Interior register user sum.
ODvehicle=ODpeople×ρ
In formula：ODvehicle：Motor vehicles OD is distributed；ρ(split rate)：The share rate of motor vehicles.
(5) on the basis of the calibrated emulation road network of step (2), according to the reality that step (3) is obtained by microwave data
Border road traffic flow, the traffic flow between OD pair obtained by the utilization mobile phone signaling data of step (4) carry out dynamically distributes,
Obtain estimating the error between traffic flow and true traffic flow.
(6) judge to estimate whether the error between traffic flow and true traffic flow meets error function, if meeting
Demarcation terminates, and otherwise proceeds to (5th) step and is redistributed, until estimating the error between traffic flow and true traffic flow
Meet error function.
Beneficial effects of the present invention are：Overcome the limitation of traditional resident trip OD scaling methods, efficiency high and into
This is low, and sample size is big, and wide coverage, Study on Aging Hardening are good.And result of study will not be affected by subjective factorss (including when
Between, place, the experience of research worker and subjective purpose etc.), with stronger objective science.
Description of the drawings
Fig. 1 is the Hangzhou urban road network model for building；
Fig. 2 is the sectional linear fitting result schematic diagram of the overhead Feng Qi roads section microwave data in the pool-middle river on Hangzhou；
Fig. 3 is ring road and the bayonet socket of ring road stretch under the People's Hospital of province and micro- on the overhead high point road in the pool-middle river on Hangzhou
The Impedance Function nonlinear fitting result schematic diagram of the data collected by ripple；
Comparison diagrams of the Fig. 4 for simulating traffic and real traffic before Used in Dynamic Traffic Assignment；
Comparison diagrams of the Fig. 5 for simulating traffic and real traffic after Used in Dynamic Traffic Assignment.
Specific embodiment
The present invention is based on state natural sciences fund youth fund project (51508505) and Zhejiang Province's natural science base
The research of golden outstanding young project (LR17E080002), a kind of utilization mobile phone signaling big data of proposition and Used in Dynamic Traffic Assignment
Resident trip OD scaling methods.With reference to specific embodiment, the present invention is described further, but the protection model of the present invention
Enclose and be not limited to that.
Embodiment 1
Below so that Hangzhou Shang Tangzhong rivers are overhead as an example, to one kind of the invention using mobile phone signaling big data and dynamic friendship
The resident trip OD scaling methods that the reduction of fractions to a common denominator is matched somebody with somebody further are explained.As follows including step：
(1) Hangzhou road network model is built based on middle sight traffic simulation instrument DTALite, as shown in Figure 1.Wherein wrap
City expressway, trunk roads, secondary distributor road, branch road is included, and checks the connectedness of road network.
(2) for the urban road network built in step (1), by license plate identification data and microwave data to step (1)
In the urban road network of structure, the simulation parameter in each section is demarcated.Using the method for sectional linear fitting, to road typical case
The traffic capacity of section, free stream velocity, jam density, four simulation parameters of crowded dissipation velocity of wave are demarcated.Wherein, Hangzhou
Microwave data that the overhead Feng Qi roads section in the pool in city-middle river is collected carries out sectional linear fitting, as a result as shown in Fig. 2
And using two parameter alphas in the method Impedance Function model (BPR) that Bureau of Public Road is developed of nonlinear fitting and β
Demarcated.
The mathematic(al) representation of BPR function models is as follows：
In formula：Hourages of the t for vehicle pass-through section；t0Freely flow the travel time for section；Wagon flows of the q for section
Amount；C is section design capacity；α, β are parameter to be calibrated.Wherein, with the pool on Hangzhou overhead-the overhead high point road in middle river on circle
Under road to the People's Hospital of province as a example by one section of ring road, its nonlinear fitting result is as shown in Figure 3.
The calibration result of all parameters of part way, as shown in table 1.
Table 1
(3) vehicle flowrate in real road network is obtained using microwave detector.
(4) mobile phone signaling data is obtained, by the analysis to mobile phone signaling data, obtains resident little in each traffic analysis
Interval mobility status, obtain the trip distribution characteristicss of resident, so as to form initial OD demands, specially:By China Mobile
Mobile phone signaling data OD be converted into general population OD, be further converted to the OD of motor vehicles, method for transformation is as follows:
In formula：ODpeople：Permanent resident population OD is distributed；
ODmobile：It is distributed using the OD that a certain operator cellphone subscriber data draw；
α1(average ownership)：The per capita ownership (portion/people) of cellphone subscriber；
α2(penetration rate of mobile phone)：Cellphone subscriber's ratio；
α3(market share)：The market share of the operator；
α4(detection probability)：User mobile phone is detected probability.
Mobile phone number α per capita1=mobile phone number/client's number=10,690,000/992.7=1.077；Cellphone subscriber's ratio α2=min
{ client's number/permanent resident population, 1 }=min { 992.7 ten thousand/6,350,000,1 }=1；Market share α3=69.56% is carried by operator
For.Mobile phone detection probability α4Register user number=6,260,000/7,410,000 in the number of users/this area being detected in=January=
0.84.
ODvehicle=ODpeople×ρ
In formula：ODvehicle：Motor vehicles OD is distributed；ρ(split rate)：The share rate of motor vehicles.Motor vehicles share rate root
According to resident trip survey in 2010, city of Hangzhou was 13.6%.Wherein from part origin number O changing to terminal numbering D
The OD for arrivingvehicleAs shown in table 2.
Table 2
| Origin number (O) | Terminal numbers (D) | Vehicle number (veh) |
| 11676 | 11677 | 100 |
| 11678 | 11678 | 500 |
| 11679 | 11682 | 100 |
| 11680 | 11684 | 300 |
| 11682 | 11685 | 100 |
| 11683 | 11686 | 400 |
| 11684 | 11688 | 800 |
(5) on the basis of the calibrated emulation road network of step (2), according to the reality that step (3) is obtained by microwave data
Border road traffic flow, the OD scaling methods proposed using Zhou Xuesong are demarcated to resident trip Dynamic OD Matrix, specifically
For：Used in Dynamic Traffic Assignment is carried out the traffic flow between the OD matrixes obtained using mobile phone signaling data in step (4), is estimated
Normalized RMSE between meter traffic flow and true traffic flow, then judges to estimate traffic behavior and true traffic shape
Whether the Normalized RMSE between state meets predetermined threshold value (generally 10%), such as meets, then demarcate and terminate, otherwise turn
Enter to be redistributed, until estimating that the error between traffic behavior and true traffic behavior meets given threshold.
Traffic behavior estimated value and sight by comparing Fig. 4 and Fig. 5, before and after dynamic traffic assignment, with flow as index
Aggregation extent between measured value, it can be found that after dynamically distributes, simulating traffic close to observed volume, so as to demonstrate the present invention
Resident trip OD is demarcated using mobile phone signaling big data, which meets the natural law, react true road conditions, and sample size
Greatly, wide coverage, data precision are high.
Claims (1)
1. a kind of resident trip OD scaling methods of utilization mobile phone signaling big data and Used in Dynamic Traffic Assignment, it is characterised in that bag
Include step as follows：
(1) urban road network model is built based on middle sight traffic simulation instrument DTALite, including city expressway, trunk roads,
Secondary distributor road, branch road.
(2) for the urban road network built in step (1), step (1) is built by license plate identification data and microwave data
The simulation parameter in each section of urban road network demarcated.Using the method for sectional linear fitting, the current energy to road
Power, free stream velocity, jam density, four simulation parameters of crowded dissipation velocity of wave are demarcated, and the side using nonlinear fitting
Two parameter alphas and β in the Impedance Function model (BPR) that method is developed to Bureau of Public Road are demarcated.
The mathematic(al) representation of BPR function models is as follows：
In formula：Hourages of the t for vehicle pass-through section；t0Freely flow the travel time for section；Vehicle flowrates of the q for section；C is
Section design capacity；α, β are parameter to be calibrated.
(3) using the time-varying vehicle flowrate in microwave detector acquisition real road network, speed, density, the data update cycle leads to
It is often 5 minutes.
(4) mobile phone signaling data is obtained, obtains amount of flow data of the resident in each traffic analysis minizone, so as to grasp resident
The trip regularity of distribution, forms initial travelling OD matrix.Specially：By going out based on a certain mobile operator mobile phones signaling data
Row OD matrixes are converted into general population travelling OD matrix, are further converted to the OD of motor vehicles, and method for transformation is as follows：
In formula, ODpeople：Permanent resident population OD is distributed；
ODmobile：The OD distributions calculated using a certain operator cellphone subscriber data；
α1(average ownership)：The per capita ownership (portion/people) of cellphone subscriber；
α2(penetration rate of mobile phone)：Cellphone subscriber's ratio；
α3(market share)：The market share of the operator；
α4(detection probability)：User mobile phone is detected probability.
Mobile phone number α per capita1=mobile phone number/client's number；Cellphone subscriber's ratio α2=min { client's number/permanent resident population, 1 }；Market accounts for
There is rate α3There is provided by operator；User mobile phone is detected probability α4Note in the number of users/this area being detected in=month
Volume total number of users.
ODvehicle=ODpeople×ρ
In formula, ODvehicle：Motor vehicles OD is distributed；
ρ(split rate)：The share rate of motor vehicles.
(5) on the basis of the calibrated emulation road network of step (2), according to the reality obtained by microwave data in step (3)
Road traffic flow data, is carried out Used in Dynamic Traffic Assignment to the travelling OD matrix obtained using mobile phone signaling data in step (4), is obtained
To the error that estimates between traffic flow and true traffic flow.
(6) whether the error between judging to estimate between traffic flow and true traffic flow meets predetermined threshold value (generally
10%), as met, then demarcate and terminate, otherwise proceed to step (5) and redistributed, until estimating traffic flow and true friendship
Error between through-current capacity meets threshold condition.
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| CN106875686A (en) * | 2017-04-16 | 2017-06-20 | 北京工业大学 | A kind of car OD extracting methods based on signaling and floating car data |
| CN107040894A (en) * | 2017-04-21 | 2017-08-11 | 杭州市综合交通研究中心 | A kind of resident trip OD acquisition methods based on mobile phone signaling data |
| CN107679653A (en) * | 2017-09-21 | 2018-02-09 | 东南大学 | A kind of OD distribution methods based on advantage trip distance |
| CN108335485A (en) * | 2018-01-31 | 2018-07-27 | 夏莹杰 | The method of major issue traffic dynamic emulation congestion prediction based on license plate identification data |
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| CN115472006A (en) * | 2022-08-26 | 2022-12-13 | 武汉大学 | Method for estimating commuting traffic flow of newly added road section of road network by utilizing mobile phone signaling data |
| CN117475641A (en) * | 2023-12-28 | 2024-01-30 | 辽宁艾特斯智能交通技术有限公司 | Method, device, equipment and medium for detecting traffic state of expressway |
| CN117475641B (en) * | 2023-12-28 | 2024-03-08 | 辽宁艾特斯智能交通技术有限公司 | Method, device, equipment and medium for detecting traffic state of expressway |
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