CN105608896A - Traffic bottleneck identification method in urban traffic network - Google Patents
Traffic bottleneck identification method in urban traffic network Download PDFInfo
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- CN105608896A CN105608896A CN201610143775.3A CN201610143775A CN105608896A CN 105608896 A CN105608896 A CN 105608896A CN 201610143775 A CN201610143775 A CN 201610143775A CN 105608896 A CN105608896 A CN 105608896A
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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Abstract
The invention discloses a traffic bottleneck identification method in a complicated traffic environment, mainly solving the problem of serous traffic congestion because the prior art cannot satisfy the current requirement for traffic. The implementation steps of the traffic bottleneck identification method are 1) using an undirected graph with weight to represent a complex network which abstracts a practical traffic network; 2) utilizing a tolerance flow allocation algorithm to perform balanced flow allocation for a user on the abstract network topological graph; 3) distributing a weight for each road segment in the network, wherein the weight is a zero flow impedance on each road segment; 4) according to the network after the weights are distributed, searching for a minimal spanning tree for the zero flow impedance; and 5) performing priority ranking for the degree of importance of the bottlenecks in the minimal spanning tree obtained from the step 5). The traffic bottleneck identification method in an urban traffic network can provide quantitative description for the degree of importance of the bottlenecks for a traffic management department to enable the traffic management department to accurately grasp the distribution characteristics of the traffic bottlenecks, reasonably plan the traffic network topology and match the traffic demand for each road segment of a road network with the traffic capacity, and can be applied to an integrated traffic dispersion system.
Description
Technical field
The invention belongs to transport information control field, relate generally to the recognition methods of traffic bottlenecks in complicated traffic environment, availableIn the formation of supporting integrated traffic persuasion system.
Background technology
After the sixties in 20th century, famous mathematician Erdos and Renyi proposed ER Random Graph model, just openThe research road of Complex Networks Theory. After this, in decades, the research of complex network is more and more subject to each area research and learnsPerson's extensive concern, carry out in succession in the multiple fields including biology, physics, communication network and computer network etc.Related work. In this period, ER Random Graph model is the basic model of research complex network always. June 4 in 1998Day, Nature has delivered two young physicist D.J.Watts and S.H.Strogatz one section of paper about network,This paper has been explained the worldlet effect of network, and sets up first small-world network model, is called for short WS model. 1999In on October 15, in, Science has delivered again other two physicist A.L.Barabasi and another section of paper of R.Albert,This paper disclosed network without characteristics of scale, and the BA model of structure scale-free networks network has been proposed. Sending out of these two sections of papersTable has been opened a new stage for the research of complex network, has caused the research boom of complex network, has initiative. Since thenScientists has been broken through the confinement of ER Random Graph model, has carried out research, as social science, mathematics, gold in more areasMelt many scientific domains such as economic science, and communications and transportation, Communication Engineering, energy transmission, electronics science, even medical science,Numerous application branches of learning such as culinary art have all been involved in this research boom. Up to the present (2015.4.27), these two sections of papersThrough being cited respectively 11411 times and 10914 times.
Have very complicated because node and road in urban traffic network topology are intricate, between intra-node and nodeInteraction, the network operation to relate to interactively between people-Che-Lu-environment and policy management, laws and regulations etc. formerCause, causes urban traffic network to have high complexity, fundamentally solve urban transport problems, realizes holding of citySupervention exhibition, just need to be from explaining the formation of urban transport problems in essence, and this is multiple must in depth to study urban traffic networkThe Evolution of assorted network. The magical glamour of complex network has attracted vast traffic scholar. It is research urban transportationNetwork provides a new visual angle, only fully understand with grasp transportation network complexity and on behavior dynamic characteristic,Analyze network topology characteristic on the basis that affects rule of network traffic flow and clogged conditions, just can better utilizeIntelligent transport technology, provides theoretical direction to vehicle supervision department's management, design, could be to alleviate traffic congestion to formulate trafficDredging scheme, more effectively solves urban transport problems. Find urban traffic network and other by a large amount of positive researchNetwork is the same, has the architectural characteristic of complex network, as subway network, urban road network, logistics network, Sea shipping networkDeng all belonging to complex network. Proof analysis shows that urban traffic network may have without characteristics of scale or worldlet characteristic. ThisSolid foundation has been established in the interaction being found to be between characteristic and the topological structure of furtheing investigate transportation network. But, trafficThe spatial entities of network has caused it to have time space complexity, makes the abstract networks such as itself and community network, scientist's collaboration networkDifference, this point shows particularly evident in urban road network. Therefore, be necessary to examine city closely with the visual angle of complex networkCity's transportation network.
In urban traffic network, traffic bottlenecks are to produce the source of problem that blocks up, if take measures not in time, will cause gathering aroundThe vehicle flowrate in stifled section, rapidly to its section, upstream and even the diffusion of whole network, causes the unmanageable situation of blocking up. Traffic bottleNeck refers to that actual capacity can not meet section or the crossing of current transport need, directly translates into the coast is clear degree and declines,The degree of crowding increases, and the speed of a motor vehicle reduces, and then causes travel time increase, traffic environment to worsen. Traffic bottlenecks are urban transportationsWeak link, toll station, intersection, shunting junction of two streams, temporary construction section, accident origination point etc. are all bottlenecksThe normal place of sending out. Whether have predictability and stability according to the generation reason of bottleneck, traffic bottlenecks can be divided into dynamic trafficBottleneck and static traffic bottleneck. Bottleneck belongs to sporadic bottleneck, refers to the bottleneck point of dynamic change, have very strong withMachine and changeability, be difficult to prediction because easily occurring to shift on space-time. The formation reason of bottleneck and influence factor comparisonComplexity, as unreasonable in burst accident, parking offense, large-scale activity, Intersections timing etc. causing sometime in sectionThe unexpected variation of certain road traffic delay. Static bottleneck is to stablize foreseeable fixing bottleneck, and it is the basic of traffic congestion generationSource. The unreasonable region of macro-plan, station, toll station setting, crossing etc. are static bottleneck, along with traffic flowContinuous variation, static bottleneck also can present the phenomenons such as transfer, diffusion, dissipation. And certain situation bottleneck and static stateBetween bottleneck, can there is certain transforming relationship. Traffic bottlenecks often comprise very abundant and complicated transport information. These informationGeneration, evolution and dissipation law to correctly understanding and grasping traffic congestion of people have very important effect. Such as canBy identification traffic bottlenecks, improve the traffic capacity of bottleneck, thereby promote the traffic efficiency of whole transportation network. Therefore,Identification traffic bottlenecks have important directive significance to solving urban transport problems. By identification static traffic bottleneck, can look forGo out the places such as in traffic network planning, Topology Structure Design is unreasonable, the traffic capacity is not mated, can be used for instructing means of transportationImprovement scheme. Identify dynamic traffic bottleneck, need to obtain in time the transport information of road network, identify exactly and predict,Judgement will produce the section blocking up, and instructs traveler to adjust line mode, travel time and path and chooses, and also can instruct friendshipLogical management system or traffic administration person correctly manage and guide car flow, make full use of the time null resource of traffic, are not increasingUnder the prerequisite of road infrastructure, effectively alleviate and block up by improving road utilization rate.
About the problem of traffic bottlenecks identification, a lot of research work are launched at present both at home and abroad. Most of research is for opening upFlutter the scenes such as the relatively simple expressway of structure, railway, aviation and subway network, also have some work research urban transportationBottleneck identification under environment. Under the scene such as expressway, railway, do not need to consider complicated node and road, nodeThe challenges such as the interaction relationship between inside and node, these research methods and result of study are not also suitable for complicatedUrban traffic environment. Bottleneck identification under urban environment, foreign scholar focuses mostly in the microcosmic traffic properties of flow of bottleneck roadThe simulation analysis of analysis and traffic bottlenecks; The research work of domestic scholars mainly goes out the traffic road network from angle recognition qualitativelyBottleneck also provides corresponding solution countermeasure, lacks the fixing bottleneck method of discrimination of quantitative road network and supports roadnet planning and trafficThe improvement of facility, causes the result of " headache is cured head, pin pain doctor pin ", fails to solve road grid traffic bottleneck from overall aspectImprovement. Part Study achievement is that the result of distributing based on traffic is calculated saturation degree and service level, only relies on saturation degree to refer toIdentify the traffic flow character that other traffic bottlenecks can not well reflect road network reality.
Summary of the invention
The object of the invention is to the deficiency for above-mentioned prior art, the traffic bottlenecks that propose in a kind of urban traffic network are knownOther method, to improve accuracy and the traffic efficiency of bottleneck identification.
Technical thought of the present invention is: utilize Complex Networks Theory, in conjunction with user equilibrium model, by finding zero flow impedanceLittle spanning tree, the static traffic bottleneck of identification road network. And on the basis of identification bottleneck, by the important journey to bottleneck roadDegree sorts, fast location " critical bottleneck ", thus instruct traffic dispersion scheme simply, implement efficiently. Its realizationStep comprises as follows:
(1) for a known actual cities transportation network, utilize original method by abstract this network be a undirected authorized graph,Represent with G=(V, K, t). Wherein, V is vertex set, corresponding to the intersection in actual traffic network; K is limit collectionClose, corresponding to the section in actual traffic network; T is the weights on limit, cross corresponding to vehicle that respective stretch spends timeBetween;
(2) utilize Gravity Models prediction origin and destination to the transport need amount on r-s:Wherein, kr、ksPointDo not represent the quantity on the limit that the starting point r in path is connected with settled some s, lrsRepresent the limit of the shortest path from starting point r to settled some sNumber, all origin and destination are to the transport need amount q on r-srsForm O-D matrix;
(3) undirected authorized graph G is carried out to traffic flow assignment, all origin and destination that prediction is obtained are to upper transport need amountDistribute to each section in network according to the principle of equilibrium assignment, obtain the magnitude of traffic flow on each sectionWherein a tableShow section, n represents iterations;
(4) be that in network, weights, the zero flow impedance t that weights of section a are its correspondence are distributed in each section0a，t0a＝γ(ki+kj)；
(5) find zero flow impedance t0aMinimal Spanning Tree MC：
5a) input undirected authorized graph G=(V, K, t), wherein t=t0a；
5b) making U is Minimal Spanning Tree vertex set, and E is limit set;
5c) initialize: make U={V0, wherein V0For any one node in set V, E is empty set;
5d) repeat following operation, until U=V:
5d1) gather on limit the limit of choosing weights minimum in E<u, v>, wherein u=U, v=V-U, is added in spanning tree,If exist many limits all to meet above-mentioned condition simultaneously, optional one;
5d2) vertex v on the limit of finding is added in set U;
5e) with Minimal Spanning Tree vertex set U and limit set E, the Minimal Spanning Tree finally obtaining is described;
(6) significance level of the bottleneck road in Minimal Spanning Tree is sorted:
6a) calculate each origin and destination to the initial impedance on the shortest path v between r-s
Wherein, caRepresent the traffic impedance on a of section,t0aRepresent zero flow impedance on a of section,t0a＝γ(ki+kj), parameter γ is the random number of 0 to 1, ki、kjRepresent that respectively two end node i of section a and j connectThe quantity on the limit connecing, xaFor the flow on a of section, UaThe traffic capacity that represents section a, α, β are two different ginsengsNumber, α=0.15, β=4,Be used for representing that whether section a is at shortest path v, if so,Otherwise,
6b) computing network validity E0：
Wherein, N is node number total in network, dijFor the limit number of the shortest path from node i to node j;
6c) remove origin and destination to certain the section a on r-s after, return to step (3), re-start equilibrium assignment, and calculate goExcept these origin and destination after a of section between impedanceObtain section a and remove the difference of origin and destination, front and back to the upper expense of r-sIf origin and destination are to being no longer communicated with after removing section a, handicapping is anti-For infinity;
6d) remove origin and destination to certain the section a on r-s after, recalculate network efficiency Ea, obtain before section a removalThe difference DELTA E of rear network efficiencya＝Ea-E0；
6e) pass through formulaObtain the important of each section in road networkThe quantitative description of degree, wherein, DrsIn esse transport need between the starting point r in expression path and settled some s, ImaForEach section significance level in road network;
6f) significance level in each section in road network is sorted, obtain the alleviation priority of traffic bottlenecks, finally instructThe enforcement of traffic dispersion measure.
Compared with prior art, tool has the following advantages in the present invention:
1. the present invention is according to the urban transportation scene of current complexity, considered impedance and two aspects of network efficiency because ofElement is evaluated section importance, obtains the significance level in each section in network by removing the mode in section, the friendship of setting up according to thisBottleneck link recognition methods can be portrayed traffic bottlenecks from quantitative angle, contributes to traffic administration person to hold on the whole traffic shapeCondition, and then more effectively improve traffic jam issue.
2. the present invention, in the process of traffic flow assignment, has taken into full account under actual scene, and individual consumer always attempts to selectIt is consuming time or this factor of path that oil consumption is minimum from starting point to destination, carries out assignment of traffic according to the principle of equilibrium assignment,Overcome the deficiency that can not reflect well the traffic flow character in transportation network in recognition methods in the past.
Brief description of the drawings
Fig. 1 is realization flow figure of the present invention;
Fig. 2 is the road network topology structure chart of use of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing, performing step of the present invention is described in further detail.
With reference to Fig. 1, implementation step of the present invention is as follows:
Step 1: network topology is carried out abstract, and with the form storage of matrix.
As shown in Figure 2, wherein, Fig. 2 (a) is that under actual scene, railway station, Nanjing is attached to the network topology structure that this example usesNear road network topology, Fig. 2 (b) is the road network topology after utilizing mathematical tool abstract.
1a) utilize MATLAB instrument in OpenStreetMap can edit world map, to extract Fig. 2 (a) respective regionsNetwork topology data, comprise longitude and latitude, link length and the road width of intersection, according to these data by realityNetwork topology is abstract is a undirected authorized graph G=(V, K, t), and as Fig. 2 (b), wherein V is vertex set, corresponding to realityIntersection in internet topology, K is limit set, corresponding to the section in real network topology, the weights that t is limit,Cross corresponding to vehicle the time that respective stretch spends;
1b) with adjacency matrix { eij}N×NForm store undirected authorized graph G=(V, K, t), wherein N is network node sum,eijRepresent whether node i and node j interconnect, if interconnect, eij=1, otherwise eij＝0。
Step 2: the magnitude of traffic flow in prediction network topology, i.e. O-D matrix.
2a) according to adjacency matrix { eij}N×N, calculate the limit that each node i in undirected authorized graph G=(V, K, t) connectsQuantity ki，
2b) according to adjacency matrix { eij}N×N, the node i of utilizing Shortest Path Searching Algorithm to try to achieve in figure G=(V, K, t) arrives jointThe number l on the limit of the shortest path of some jij；
2c) utilize the magnitude of traffic flow of Gravity Models estimating in transportation network from start node r to terminal node s:All origin and destination are to the magnitude of traffic flow q on r-srsForm O-D matrix; O-D matrix isWherein qrsRepresent that node r is to the magnitude of traffic flow between s, r=1 ..., N, s=1 ..., N, N tableShow node number total in network, " O " derives from English Origin, refers to departure place, and " D " derives from English Destination,Refer to destination.
Step 3: whole urban traffic network is carried out to User Equilibrium.
3a) carry out netinit:
For composing weights t in every section in network0a＝γ(ki+kj), wherein t0aRepresent zero flow impedance on a of section, parameter γBe the random number of 0 to 1, ki、kjRepresent respectively the quantity on the limit that a two end node i in section are connected with j; With " completeHave completely without " O-D matrix is loaded into network by method, obtains the initial flow on a of section
In network loading procedure, each origin and destination is all assigned to and connects r and s the magnitude of traffic flow on r-sOn the section that little impedance path comprises, and connect on other paths of r and s not dispense flow rate;
Put iterations n=1;
Impedance function BPR form 3b) providing according to Bureau of Public Roads, calculates the impedance on all section a Wherein, UaRepresent the traffic capacity of section a,α, β be two differentParameter, α=0.15, β=4;
3c) according to impedanceO-D matrix is loaded on network, obtains on each section by " entirely have completely without " methodFlowIn loading procedure, each origin and destination is all assigned to and connects r and s the magnitude of traffic flow on r-sOn the section that minimum impedance path comprises, and connect on other paths of r and s not dispense flow rate;
3d) establish iteration precision ε=10-3, judge whether assignment of traffic result restrains: if meet?Convergence, stops iteration,Be final solution; If do not meet above formula, make n=n+1, return to step 3b.
Step 4: for distributing weights in each section in network.
Calculate zero flow impedance t0a＝γ(ki+kj), for composing weights t in every section in network0a。
Step 5: determine zero flow impedance Minimal Spanning Tree MC。
Minimal Spanning Tree has comprised point and part limit all in network, is each limit weight in the numerous spanning trees of connected graph of having the rightFor a tree of minimum, zero flow impedance Minimal Spanning Tree refers to zero flow impedance t0aAs the Minimal Spanning Tree of weight, it is determinedStep is as follows:
5a) input undirected authorized graph G=(V, K, t), wherein t=t0a；
5b) making U is Minimal Spanning Tree vertex set, and E is limit set;
5c) initialize: make U={V0, wherein V0For any one node in set V, E is empty set;
5d) repeat following operation, until U=V:
5d1) gather on limit the limit of choosing weights minimum in E<u, v>, wherein u=U, v=V-U, is added spanning treeIn, if exist many limits all to meet above-mentioned condition simultaneously, optional one;
5d2) vertex v on the limit of finding is added in set U;
5e) with set U and E, the Minimal Spanning Tree finally obtaining is described.
Step 6: the significance level of the bottleneck in the Minimal Spanning Tree obtaining is above carried out to prioritization.
6a) calculate each origin and destination to the initial impedance on the shortest path v between r-s
Wherein, caRepresent the traffic impedance on a of section,t0aRepresent zero flow impedance on a of section,t0a＝γ(ki+kj), parameter γ is the random number of 0 to 1, ki、kjRepresent that respectively two end node i of section a and j connectThe quantity on the limit connecing, xaFor the flow on a of section, UaThe traffic capacity that represents section a, α, β are two different ginsengsNumber, α=0.15, β=4,Be used for representing that whether section a is at shortest path v, if so,Otherwise,
6b) computing network validity E0：
Wherein, N is node number total in network, dijFor the limit number of the shortest path from node i to node j;
6c) remove origin and destination to certain the section a on r-s after, return to step (3), re-start equilibrium assignment, and calculate goExcept these origin and destination after a of section between impedanceObtain section a and remove the difference of origin and destination, front and back to the upper expense of r-sIf origin and destination are to being no longer communicated with after removing section a, handicapping is anti-For infinity;
6d) remove origin and destination to certain the section a on r-s after, recalculate network efficiency Ea, obtain before section a removalThe difference DELTA E of rear network efficiencya＝Ea-E0；
6e) pass through formulaObtain the important of each section in road networkThe quantitative description of degree, wherein, DrsIn esse transport need between the starting point r in expression path and settled some s, ImaForEach section significance level in road network;
6f) significance level in each section in road network is sorted, obtain the alleviation priority of traffic bottlenecks, finally instructThe enforcement of traffic dispersion measure.
More than describing is only example of the present invention, does not form any limitation of the invention, obviously for this areaProfessional, understanding after content of the present invention and principle, all may be in the feelings that do not deviate from the principle of the invention, structureUnder condition, carry out various corrections and change in form and details, but these correction and changes based on inventive concept still existWithin claim protection domain of the present invention.
Claims (3)
1. the traffic bottlenecks recognition methods in urban traffic network, comprises the steps:
(1), for a known actual cities transportation network, utilize original method to be one and undirectedly to have abstract this networkWeight graph, with G=(V, K, t) expression. Wherein, V is vertex set, corresponding to the crossroad in actual traffic networkMouthful; K is limit set, corresponding to the section in actual traffic network; T is the weights on limit, crosses phase corresponding to vehicleThe time of answering section to spend;
(2) utilize Gravity Models prediction origin and destination to the transport need amount on r-s:Wherein, kr、ksRepresent respectively the quantity on the limit that the starting point r in path is connected with settled some s, lrsRepresent the shortest path from starting point r to settled some sThe number on the limit in footpath, all origin and destination are to the transport need amount q on r-srsForm O-D matrix;
(3) undirected authorized graph G is carried out to traffic flow assignment, all origin and destination that prediction is obtained need upper trafficThe amount of asking is distributed to each section in network according to the principle of equilibrium assignment, obtains the magnitude of traffic flow on each sectionWherein a represents section, and n represents iterations;
(4) be that in network, weights, the zero flow impedance t that weights of section a are its correspondence are distributed in each section0a，t0a＝γ(ki+kj)；
(5) find zero flow impedance t0aMinimal Spanning Tree MC：
5a) input undirected authorized graph G=(V, K, t), wherein t=t0a；
5b) making U is Minimal Spanning Tree vertex set, and E is limit set;
5c) initialize: make U={V0, wherein V0For any one node in set V, E is empty set;
5d) repeat following operation, until U=V:
5d1) gather on limit the limit < u that chooses weights minimum in E, v >, wherein u=U, v=V-U, is added and is propped upIn support tree, if exist many limits all to meet above-mentioned condition simultaneously, optional one;
5d2) vertex v on the limit of finding is added in set U;
5e) with Minimal Spanning Tree vertex set U and limit set E, the Minimal Spanning Tree finally obtaining is described;
(6) significance level of the bottleneck road in Minimal Spanning Tree is sorted:
6a) calculate each origin and destination to the initial impedance on the shortest path v between r-s
Wherein, caRepresent the traffic impedance on a of section,t0aRepresent zero flow resistance on a of sectionAnti-, t0a＝γ(ki+kj), parameter γ is the random number of 0 to 1, ki、kjRepresent respectively two end node i of section aThe quantity on the limit being connected with j, xaFor the flow on a of section, UaThe traffic capacity that represents section a, α, β areTwo different parameters, α=0.15, β=4,Be used for representing that whether section a is at shortest path v, if so,Otherwise,
6b) computing network validity E0：
Wherein, N is node number total in network, dijFor the limit number of the shortest path from node i to node j;
6c) remove origin and destination to certain the section a on r-s after, return to step (3), re-start equilibrium assignment, and meterCalculate remove this origin and destination after a of section between impedanceObtain section a and remove origin and destination, front and back to the upper expense of r-sDifferenceIf origin and destination are to being no longer communicated with after removing section a, handicapping is anti-For infinity;
6d) remove origin and destination to certain the section a on r-s after, recalculate network efficiency Ea, obtain section a and goExcept the difference DELTA E of front and back network efficiencya＝Ea-E0；
6e) pass through formulaObtain each section in road networkThe quantitative description of significance level, wherein, DrsIn esse transport need between the starting point r in expression path and settled some s,ImaFor each section significance level in road network;
6f) significance level in each section in road network is sorted, obtain the alleviation priority of traffic bottlenecks, finalInstruct the enforcement of traffic dispersion measure.
2. method according to claim 1, wherein the O-D matrix in step (2) isWherein qrsRepresent that node r is to the magnitude of traffic flow between s, r=1 ..., N, s=1 ..., N, N represents in network totalNode number, " O " derives from English Origin, refers to departure place, and " D " derives from English Destination, refers toDestination.
3. method according to claim 1, the concrete steps of wherein said step (3) are as follows:
3a) initialize, make t0a＝γ(ki+kj), wherein, t0aFor zero flow impedance on a of section, parameter γ 0 arrivesThe random number of 1, ki、kjRepresent respectively the quantity on the limit that a two end node i in section are connected with j; With " entirely havingCompletely without " method is loaded into O-D matrix on network, obtains the flow on a of sectionPut iterations n=1;
3b) calculate the impedance on all section a Wherein, UaRepresent section a'sThe traffic capacity,α, β are two different parameters, α=0.15, β=4;
3c) according to impedanceO-D matrix is loaded on network by " entirely have completely without " method, obtains each sectionOn flow
3d) set iteration precision ε=10-3, judge whether assignment of traffic result restrains: if meetConvergence, stops iteration,Be final solution; If do not meet above formula, make n=n+1,Return to step 3b).
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