CN105070073A - Geomagnetism-based region self-optimization signal control method and device - Google Patents

Abstract

The invention relates to a geomagnetism-based region self-optimization signal control method, and mainly relates to the field of region road network intersection signal optimization control. Through the integrated application of a novel geomagnetism vehicle detection device, dynamic detection and signal optimization of the traffic state of a number of intersections on a region road network are realized. The method comprises the steps of geomagnetism detection device installation, data acquisition and communication, region road network self-optimization signal processing calculation, and signal instruction issuing and control. The invention further provides a geomagnetism-based region self-optimization signal control device. According to the invention, an active geomagnetism detection technology is used; the real-time traffic state of a number of intersections in a region road network can be accurately detected; a region optimization signal control scheme is developed; real-time decisions and emergency processing information are provided for traffic management and control; and the operation efficiency and the service level of the region toad network traffic are enhanced.

Description

A kind of region self-optimizing signal control method based on earth magnetism and device

Technical field

The present invention relates to the traffic signal optimization control field at the multiple crossing of Regional Road Network, specifically a kind of region self-optimizing signal control method based on earth magnetism and device.

Background technology

City friendship is blocked up and accident takes place frequently day by day, particularly section, crossing event of blocking up is serious, traffic control system that is advanced, that be suitable for is one of the most effective approach solving urban traffic congestion, and traffic signalization is the core of traffic control system, Regional Road Network traffic signal optimization controls to play regional traffic induction advantage to greatest extent, improves road traffic operational efficiency.

Earth magnetism vehicle testing techniques is that the road by blocking up at complex or easily formed installs earth magnetism collecting device, passing automobile quantity, speed, occupation rate are detected, the data collected are passed back by cable network the technology that server-centric carries out processing, dynamic traffic signal control can be carried out by the traffic parameter of Real-time Collection, realize effective rule induction of traffic flow, reduce traffic congestion to greatest extent.

At present, signal control method mainly comprises timing controlled, multi-period control, induction control and adaptive control etc., traditional model algorithm too stiff the change according to certain traffic parameter setting threshold value carry out signal optimizing, system can be caused the erroneous judgement of state; The present invention proposes a kind of region self-optimizing signal control method based on earth magnetism, the real-time detection of index and comprehensive analysis is run by crossing, the signal extracting the multiple crossing of Regional Road Network controls self-optimizing algorithm, greatly can improve the operational efficiency of Regional Road Network road traffic.

Summary of the invention

A kind of region self-optimizing signal control method based on earth magnetism and device, the equipment used in the method comprises geomagnetism detecting equipment, data communications equipment, data store and standardized server, Regional Road Network self-optimizing processing server signal and signal issue terminal equipment, between described each equipment, signal connects in order, and the method comprises the steps:

(1) in crossing, each importer upwards installs earth magnetism vehicle equipment, and the position that detecting device is buried underground is at 10-25 rice, stop line front;

(2) crossing of Regional Road Network is numbered in order, then the detecting device of each crossing is numbered according to clockwise direction, the section numbering belonging to crossing and detecting device are numbered and binds;

(3) by earth magnetism vehicle equipment, the traffic flow of Real-time Collection detector segments and car speed parameter information, described parameter information is through data communications equipment, and real-time returned data stores and standardized server, carries out real-time data memory and standardization;

(4) extract the real time traffic data of storage server, calculate detector segments average traffic current density parameter, and calculate real-time section traffic operation index according to average traffic current density;

(5) according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, polymerization calculates intersection traffic and runs index, run by intersection traffic the cycle that index-signal period relational model calculates integrative design intersection, and then draw the signal period of each crossing;

(6) according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, calculate crossing arterial traffic and run index, COMPREHENSIVE CALCULATING Regional Road Network intersection traffic runs exponential average;

(7) run exponential average-split model based on Regional Road Network intersection traffic, according to main line priority principle, the split of each crossing main line of zoning road network, then calculates each crossing main signal and controls red light and green time;

(8) utilize signal issue terminal equipment, served by calling data bank interface, sent to by the real-time parameter of integrative design intersection signal to control lamp, control lamp by signal and each crossing traffic of Regional Road Network is dynamically induced.

A kind of region self-optimizing signal control method based on earth magnetism and device, it is characterized in that: the traffic circulation exponential model based on earth magnetism builds, traffic circulation index-signal period relational model builds, and runs exponential average-split model with Regional Road Network intersection traffic;

The described traffic circulation exponential model based on earth magnetism builds, and comprises road section traffic volume and runs index, intersection traffic operation index, crossing arterial traffic operation index and Regional Road Network traffic circulation exponential average 4 parts;

(A) extract traffic flow data and the speed data in each track of geomagnetism detecting section, calculate average traffic stream parameter and the average velocity parameter of detector segments at Spatial Dimension and time dimension aspect respectively;

Average traffic stream parameter pass through formula calculate, wherein, n is track, place, and N is the total number in track in section, q _nit is the traffic flow in the n-th track; Average velocity parameter v _npass through calculate, wherein, v _nbe the speed in the n-th track, for the average velocity of unit granularity period;

(B) average traffic current density parameter pass through formula calculate;

(C) road section traffic volume operation index RTPI passes through formula

$RTPI=\left\{\begin{array}{c}2\&times;\frac{\stackrel{\&OverBar;}{k}}{x}\left(0\&le;\stackrel{\&OverBar;}{k}\&le;x\right)\\ 2+2\&times;\frac{\stackrel{\&OverBar;}{k}-x}{y-x}\left(x<\stackrel{\&OverBar;}{k}\&le;y\right)\\ 4+2\&times;\frac{\stackrel{\&OverBar;}{k}-y}{z-y}\left(y<\stackrel{\&OverBar;}{k}\&le;z\right)\\ 6+2\&times;\frac{\stackrel{\&OverBar;}{k}-z}{p-z}\left(z<\stackrel{\&OverBar;}{k}\&le;p\right)\\ 8+2\&times;\frac{\stackrel{\&OverBar;}{k}-p}{m-p}\left(p<\stackrel{\&OverBar;}{k}\&le;m\right)\\ 10\left(\stackrel{\&OverBar;}{k}>m\right)\end{array}\right.$ Calculate, wherein x, y, z, p, m value is that road traffic congestion experiences Optimal Parameters;

(D) intersection traffic operation index ITPI passes through formula

ITPI=RTPI ₁* ω ₁+ RTPI ₂* ω ₂+ ... ,+RTPI _j* ω _jcalculate, wherein ω ₁, ω ₂..., ω _jfor each importer to weighting coefficient;

(E) crossing arterial traffic operation index IATPI passes through publicity

IATPI=RTPI ₁* ω ₁+ RTPI ₂* ω ₂+ ... ,+RTPI _h* ω _hcalculate, wherein ω ₁, ω ₂..., ω _hfor the weighting coefficient in main line section, crossing;

Described traffic circulation index-signal period relational model builds, and signal period parameter C=T*ITPI/10, T are preset signals cycle parameters;

Described Regional Road Network intersection traffic runs exponential average-split model construction, and Regional Road Network intersection traffic runs exponential average AITPI _mean, crossing main line split parameter crossing main line green time G _i=C _i× r _i, crossing main line red time R _i=C _i-G _i-Y, IATPI _ibe the crossing arterial traffic operation index of i-th crossing, C _ibe the signal control cycle time of i-th crossing, G _ibe the green time of i-th crossing Regional Road Network, R _ibe the red time of i-th crossing Regional Road Network, Y represents yellow time.

The present invention adopts active geomagnetic technology, accurately can detect the real-time traffic states of the multiple crossing of Regional Road Network, formulate Regional Road Network optimization signal timing plan, for traffic administration and control provide Real-time Decision and emergency processing information, the operational efficiency of lifting region road grid traffic and service level.

Accompanying drawing explanation

Fig. 1 is workflow diagram of the present invention;

System equipment scheme of installation used in Fig. 2 Fig. 1;

System equipment connection diagram used in Fig. 3 Fig. 1.

Embodiment

A kind of region self-optimizing signal control method based on earth magnetism as illustrated in fig. 1 and 2 and device, the equipment used in the method comprises earth magnetism vehicle equipment 1, data communications equipment 2, for data storing and standardized server 3, Regional Road Network self-optimizing processing server 4 and issue terminal equipment 5, between described each equipment, signal connects in order, and the method comprises following step:

S1, in crossing, each importer upwards installs earth magnetism vehicle equipment, and the position that detecting device is buried underground is at 10-25 rice, stop line front;

S2, the crossing of Regional Road Network to be numbered in order, then the detecting device of each crossing to be numbered according to clockwise direction, the section numbering belonging to crossing and detecting device are numbered and binds;

S21, the crossing on Regional Road Network to be numbered in order, crossing be numbered I _i, i is crossing sequence label, and I is total number of crossing on Regional Road Network, i≤I;

The type of S22, crossing has multiple, common are five forks in the road, crossroad, T-shaped crossing, and this method is classified according to the number (J) in crossing inlet direction.

S23, to each crossing I _ibe numbered detecting device according to clockwise direction, detecting device is numbered D _ij, i be crossing numbering, j be importer to numbering, j≤J;

S24, geomagnetism detecting device are embedded in 10-25 rice, stop line front, and detection faces covers all tracks, section, and the equipment scheme of installation of general crossroad is as Fig. 2.

S3, by earth magnetism vehicle equipment, the traffic flow of Real-time Collection detector segments and car speed parameter information, described parameter information is through data communications equipment, and real-time returned data stores and standardized server, carries out real-time data memory and standardization;

The real time traffic data of S4, extraction storage server, calculates detector segments average traffic current density parameter, and calculates real-time section traffic operation index according to average traffic current density;

S41, average traffic current density

The data layout of ground magnetic machine real-time report is (t, n, q, v), t represents and calls time, and n represents track, place, and q represents traffic flow data, and v represents flow speeds data, the unit of (t, n, q, v) be respectively second, 1 ,/hour/track and thousand ms/h.

Suppose that sample data collection can be expressed as S={ (t, 1, q ₁, v ₁), (t, 2, q ₂, v ₂) ..., (t, n, q _n, v _n), the average traffic stream of section to be measured Spatial Dimension and time dimension in timing statistics the average velocity in unit particle size cycle the average traffic density of section to be measured Spatial Dimension and time dimension (unit :/km/track), then

$\stackrel{\&OverBar;}{q}=\underset{n=1}{\overset{N}{\&Sigma;}}{q}_n/N---\left(1\right)$

$\stackrel{\&OverBar;}{v}=\underset{n=1}{\overset{N}{\&Sigma;}}{v}_n/N---\left(2\right)$

$\stackrel{\&OverBar;}{k}=\frac{\stackrel{\&OverBar;}{q}}{\stackrel{\&OverBar;}{v}}---\left(3\right)$

In above-mentioned formula: n is track, place; N is the total number in track in section; q _nit is the traffic flow in the n-th track; v _nbe the speed in the n-th track.

S42, road section traffic volume run index

Build road section traffic volume and run index RTPI (RoadTrafficPerformanceIndex) and average traffic current density functional relationship model,

$RTPI=\left\{\begin{array}{c}2\&times;\frac{\stackrel{\&OverBar;}{k}}{x}\left(0\&le;\stackrel{\&OverBar;}{k}\&le;x\right)\\ 2+2\&times;\frac{\stackrel{\&OverBar;}{k}-x}{y-x}\left(x<\stackrel{\&OverBar;}{k}\&le;y\right)\\ 4+2\&times;\frac{\stackrel{\&OverBar;}{k}-y}{z-y}\left(y<\stackrel{\&OverBar;}{k}\&le;z\right)\\ 6+2\&times;\frac{\stackrel{\&OverBar;}{k}-z}{p-z}\left(z<\stackrel{\&OverBar;}{k}\&le;p\right)\\ 8+2\&times;\frac{\stackrel{\&OverBar;}{k}-p}{m-p}\left(p<\stackrel{\&OverBar;}{k}\&le;m\right)\\ 10\left(\stackrel{\&OverBar;}{k}>m\right)\end{array}\right.---\left(4\right)$

Wherein x, y, z, p, m value is that road traffic congestion experiences Optimal Parameters, needs to utilize questionnaire and data analysis the Fitting Calculation, and different categories of roads, and parameter size is also different, and suggesting system for wearing initialized reference value is as table 1.

Table 1 road section traffic volume runs exponential model parameter

S5, according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, polymerization calculates intersection traffic and runs index, run by intersection traffic the cycle that index-signal period relational model calculates integrative design intersection, and then draw the signal period of each crossing;

Index is run in S51, crossing

It is run to road section traffic volume the polymerization analysis that the basis of index is carried out each importer of crossing to calculate that index ITPI (IntersectionTrafficPerformanceIndex) is run in crossing,

ITPI＝RTPI ₁*ω ₁+RTPI ₂*ω ₂+,...,+RTPI _j*ω _j(5)

ω ₁, ω ₂..., ω _jfor each importer to weighting coefficient;

RTPI _jthe road section traffic volume calculated for each entrance ingress detecting device of crossing runs index;

The weighting coefficient in crossing inlet direction is relevant with category of roads, in table 2:

Table 2 category of roads and crossing weight relationship table

Category of roads	Through street	Trunk roads	Secondary distributor road	Branch road
					Weighted value	P1	P2	P3	P4

The some importers in crossing to weighted value computing formula as follows:

${\mathrm{\&omega;}}_j=\frac{{{\mathrm{\&omega;}}_j}^{\&prime;}}{\underset{1}{\overset{J}{\&Sigma;}}{{\mathrm{\&omega;}}_j}^{\&prime;}}---\left(6\right)$

Wherein:

ω _j' be importer to weighted value corresponding to category of roads;

J is the total number in crossing inlet direction, j be importer to numbering, j≤J;

S52, integrative design intersection cycle

According to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, polymerization calculates intersection traffic and runs index, runs by intersection traffic the cycle that index-signal period relational model calculates integrative design intersection;

C＝T*ITPI/10(7)

Wherein,

C is the signal control cycle time;

T is preset signals cycle parameter;

S6, according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, calculate crossing arterial traffic and run index, COMPREHENSIVE CALCULATING Regional Road Network intersection traffic runs exponential average;

S61, crossing arterial traffic run index IATPI

IATPI＝RTPI ₁*ω ₁+RTPI ₂*ω ₂+,...,+RTPI _h*ω _h(8)

ω ₁, ω ₂..., ω _hfor the weighting coefficient in main line section, crossing;

S62, Regional Road Network intersection traffic run exponential average AITPI _mean

${\mathrm{AITPI}}_{mean}=\frac{\underset{i}{\overset{I}{\&Sigma;}}{\mathrm{ITPI}}_i}{I}---\left(9\right)$

ITPI _iit is the intersection traffic operation index of i-th crossing;

I is total number of crossing on Regional Road Network;

S7, based on Regional Road Network intersection traffic run exponential average-split model, the split r of each crossing main line of zoning road network _i, then calculate each crossing main signal and control green light G _iwith red time R _i;

$r_i=\frac{{\mathrm{IATPI}}_i}{{\mathrm{AITPI}}_{mean}+{\mathrm{IATPI}}_i}---\left(10\right)$

G _i＝C _i×r _i(11)

R _i＝C _i-G _i-Y(12)

Wherein,

C _iit is the signal control cycle time of i-th crossing;

G _iit is the green time of i-th crossing Regional Road Network;

R _iit is the red time of i-th crossing Regional Road Network;

Y represents yellow time.

S8, enter issue terminal 5, served by calling data bank interface, the signal in equipment 4 is controlled real-time parameter and send to signal to control lamp, control lamp by signal and crossing traffic is dynamically induced.

The present invention make use of the traffic flow of Geomagnetism Information collecting device fully and car speed parameter carries out data mining analysis, the road section traffic volume constructed based on earth magnetism runs exponential model and crossing operation exponential model, achieve the self-optimizing control of each crossing signals of Regional Road Network, for traffic administration and control provide Real-time Decision and emergency data, reduce traffic hazard, crossing operational efficiency can be increased, the service level of lifting region road network road traffic.

Those skilled in the art will be appreciated that; above embodiment is only used to the present invention is described; and be not used as limitation of the invention; as long as within spirit of the present invention, the suitable change do above embodiment and change all drop within the scope of protection of present invention.

Claims (5)

1. the region self-optimizing signal control method based on earth magnetism and device, the equipment used in the method comprises geomagnetism detecting equipment, data communications equipment, data store and standardized server, region self-optimizing processing server signal and signal issue terminal equipment, between described each equipment, signal connects in order, it is characterized in that: the method comprises the steps:

(1) in crossing, each importer upwards installs earth magnetism vehicle equipment, and the position that detecting device is buried underground is at 10-25 rice, stop line front;

(2) crossing of Regional Road Network is numbered in order, then the detecting device of each crossing is numbered according to clockwise direction, the section numbering belonging to crossing and detecting device are numbered and binds;

(3) by earth magnetism vehicle equipment, the traffic flow of Real-time Collection detector segments and car speed parameter information, described parameter information is through data communications equipment, and real-time returned data stores and standardized server, carries out real-time data memory and standardization;

(4) extract the real time traffic data of storage server, calculate detector segments average traffic current density parameter, and calculate real-time section traffic operation index according to average traffic current density;

(5) according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, polymerization calculates intersection traffic and runs index, run by intersection traffic the cycle that index-signal period relational model calculates integrative design intersection, and then draw the signal period of each crossing;

(6) according to the traffic circulation exponential sum section road class attribute of each importer of crossing to section, calculate crossing arterial traffic and run index, COMPREHENSIVE CALCULATING Regional Road Network intersection traffic runs exponential average;

(7) run exponential average-split model based on Regional Road Network intersection traffic, according to main line priority principle, the split of each crossing main line of zoning road network, then calculates each crossing main signal and controls red light and green time;

(8) utilize signal issue terminal equipment, served by calling data bank interface, sent to by the real-time parameter of integrative design intersection signal to control lamp, control lamp by signal and each crossing traffic of Regional Road Network is dynamically induced.

2. a kind of region self-optimizing signal control method based on earth magnetism according to claim 1 and device, it is characterized in that: the traffic circulation exponential model based on earth magnetism builds, traffic circulation index-signal period relational model builds, and runs exponential average-split model with Regional Road Network intersection traffic.

3. a kind of region self-optimizing signal control method based on earth magnetism according to claim 2 and device, it is characterized in that, the described traffic circulation exponential model based on earth magnetism builds, and comprises road section traffic volume and runs index, intersection traffic operation index, crossing arterial traffic operation index and Regional Road Network traffic circulation exponential average 4 parts;

(31) extract traffic flow data and the speed data in each track of geomagnetism detecting section, calculate average traffic stream parameter and the average velocity parameter of detector segments at Spatial Dimension and time dimension aspect respectively;

Average traffic stream parameter pass through formula calculate, wherein, n is track, place, and N is the total number in track in section, q _nit is the traffic flow in the n-th track; Average velocity parameter v _npass through calculate, wherein, v _nbe the speed in the n-th track, for the average velocity of unit granularity period;

(32) average traffic current density parameter pass through formula calculate;

(33) road section traffic volume operation index RTPI passes through formula

calculate, wherein x, y, z, p, m value is that road traffic congestion experiences Optimal Parameters;

(34) intersection traffic operation index ITPI passes through formula

ITPI=RTPI ₁* ω ₁+ RTPI ₂* ω ₂+ ... ,+RTPI _j* ω _jcalculate, wherein ω ₁, ω ₂..., ω _jfor each importer to weighting coefficient;

(35) crossing arterial traffic operation index IATPI passes through publicity

IATPI=RTPI ₁* ω ₁+ RTPI ₂* ω ₂+ ... ,+RTPI _h* ω _hcalculate, wherein ω ₁, ω ₂..., ω _hfor the weighting coefficient in main line section, crossing.

4. a kind of region self-optimizing signal control method based on earth magnetism according to claim 2 and device, it is characterized in that: described traffic circulation index-signal period relational model builds, signal period parameter C=T*ITPI/10, T are preset signals cycle parameters.

5. a kind of region self-optimizing signal control method based on earth magnetism according to claim 2 and device, it is characterized in that: described Regional Road Network intersection traffic runs exponential average-split model construction, Regional Road Network intersection traffic runs exponential average AITPI _mean, crossing main line split parameter crossing main line green time G _i=C _i× r _i, crossing main line red time R _i=C _i-G _i-Y, IATPI _ibe the crossing arterial traffic operation index of i-th crossing, C _ibe the signal control cycle time of i-th crossing, G _ibe the green time of i-th crossing Regional Road Network, R _ibe the red time of i-th crossing Regional Road Network, Y represents yellow time.