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CN109272204B - Method for evaluating network reserve capacity of urban subway - Google Patents

Method for evaluating network reserve capacity of urban subway Download PDF

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CN109272204B
CN109272204B CN201810972687.3A CN201810972687A CN109272204B CN 109272204 B CN109272204 B CN 109272204B CN 201810972687 A CN201810972687 A CN 201810972687A CN 109272204 B CN109272204 B CN 109272204B
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段征宇
雷曾翔
李玮峰
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Abstract

The invention relates to an assessment method of urban subway network reserve capacity, which comprises the following steps: 1) defining a turn-back section, and taking the turn-back section as a basic analysis unit of the reserve capacity of the subway network; 2) defining the reserve capacity of the subway network, and specifically defining the reserve capacity as follows: in a certain damage scene, the minimum value of the ratio of the section traffic capacity to the passenger flow in the subway station; 3) obtaining traffic demands according to subway ticket data, obtaining passenger flow of each basic analysis unit of the subway network, and calculating the reserve capacity of the subway network; 4) and identifying a bottleneck section under the condition of normal operation of the subway network and a potential bottleneck section under the condition of subway accident or fault outage. Compared with the prior art, the method has the advantages of considering dynamic passenger flow influence, comprehensively evaluating, identifying accurately and the like.

Description

Method for evaluating network reserve capacity of urban subway
Technical Field
The invention relates to the field of traffic planning and management, in particular to an assessment method for urban subway network reserve capacity.
Background
Subway networks play an important role in urban traffic systems, and the operation interruption caused by accidents or faults can bring impact to the modes of subway networks, conventional public transport, road traffic and the like. Therefore, it is necessary to analyze and evaluate the vulnerability of the subway network. That is, the impact of damage or disruption on the subway network service capabilities is analyzed.
In the traditional vulnerability evaluation of the subway network, a complex network method is mainly adopted to analyze the topological performance change of the subway network under random and deliberate attacks, such as: connectivity, scale-free characteristics, etc. But the topology model is not consistent with the actual operation condition of the subway network. For example, after an accident occurs at a certain station or road section, one section usually stops operating; subway passenger flow distribution in different periods is different, and the influence of interrupted operation on a subway network is different. Some scholars propose analysis methods for the influence of the outage on the passenger flow, but do not consider the influence of a certain part of passengers on finding alternative paths in the subway network and the dynamic change of the passenger flow. Therefore, it is difficult to support emergency management of the subway network.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an assessment method for the reserve capacity of an urban subway network.
The purpose of the invention can be realized by the following technical scheme:
a method for evaluating the reserve capacity of an urban subway network comprises the following steps:
1) defining a turn-back section, and taking the turn-back section as a basic analysis unit of the reserve capacity of the subway network;
2) defining the reserve capacity of the subway network, and specifically defining the reserve capacity as follows:
in a certain damage scene, the minimum value of the ratio of the section traffic capacity to the passenger flow in the subway station;
3) obtaining traffic demand according to subway ticket data, obtaining passenger flow of each basic analysis unit of the subway network, and calculating reserve capacity of the subway network, wherein the reserve capacity mu of the subway networkbThe smaller (ω) is, the weaker the ability of the subway network to cope with an accident or failure is, and if μ isb(ω) is less than 1, indicating that the network cannot take up the current traffic demand.
In the step 1), the turning-back section is defined as a section between two adjacent subway turning-back stations, and a turning-back line for realizing the back-and-forth running of the train is arranged between the subway turning-back stations.
In the step 2), the storage capacity of the subway network is expressed as follows:
Figure BDA0001776621290000021
Figure BDA0001776621290000022
Figure BDA0001776621290000023
wherein, mub(omega) is the reserve capacity of the subway network under a demand scene b and a damage scene omega, the demand scene b is the hourly traffic demand and represents the dynamic change of the traffic demand, the damage scene omega is the combination of the damage conditions of the basic analysis units, caFor the traffic capacity of the turn-back section a, A is the basic analysis unit set of the subway network, va(q) is the passenger flow on the turnaround section a, qijIs the traffic demand from station i to station j, and i, j belongs to V, dij(omega) is whether the station i is communicated with the station j under the damage scene omega, 1 is taken when the station i is communicated with the station j, 0 and delta are taken when the station i is not communicated with the station jarIs variable from 0 to 1, 1 is taken when the shortest path r uses the turn-back interval a, otherwise 0 is taken, V is a subway network station set, P is a shortest path set, tij(ω) is the travel time corresponding to the shortest path between station i to station j in the damage scenario ω,
Figure BDA0001776621290000024
the travel time, t, corresponding to the shortest path between station i and station j under normal conditions*An acceptable travel time increment for the passenger.
The method further comprises the following steps:
4) and identifying a bottleneck section under the condition of normal operation of the subway network and a potential bottleneck section under the condition of subway accident or fault outage.
In the step 4), the determination conditions of the bottleneck section under the normal operation condition of the subway network are as follows:
the section with passenger flow saturation greater than 0.9 is a bottleneck section, and the passenger flow saturation saThe expression of (a) is:
Figure BDA0001776621290000025
wherein, caTo turn back the traffic capacity of section a.
In the step 4), the identification of the potential bottleneck section under the condition of subway accident or fault shutdown is specifically as follows:
41) and acquiring a damage combination set omega among all the basic analysis units under different demand scenes b by adopting a Monte Carlo method, wherein the quantity of the damage combination scenes among all the basic analysis units is as follows:
Figure BDA0001776621290000031
wherein n is the total number of basic analysis units in the subway network, omegaiA scene with i damaged basic analysis units;
42) setting the quantity of demand scenes as N (B), adopting a traffic distribution method aiming at different damage scenes to calculate the saturation of the sections and judge whether the sections are bottleneck sections, if the probability N (a) that the return section a becomes the bottleneck sections is more than or equal to 10%, judging the return section a as a potential bottleneck section after the damage occurs, and calculating the probability P (a) that the return section a becomes the bottleneck section:
Figure BDA0001776621290000032
where n (a) is the number of times segment a becomes a bottleneck segment in all damage scenarios.
Compared with the prior art, the invention has the following advantages:
the invention has the beneficial effects that: the invention considers the influence of dynamic passenger flow, evaluates the reserve capacity of the subway network, identifies the daily bottleneck section and the potential bottleneck section of the subway network, the reserve capacity can reflect the bearing capacity of the subway network to the passenger flow when a certain line is interrupted in operation due to an accident or a fault, the daily bottleneck section and the potential bottleneck section reflect the section or station with insufficient traffic capacity in the subway network under the conditions of normality and the accident, can assist in making a traffic demand management and emergency evacuation scheme, comprehensively evaluates the vulnerability of the subway network, and can provide a basis for the emergency management and network planning of the subway network.
Drawings
Fig. 1 shows the result of analyzing the reserve capacity in the normal operation of the Shanghai subway network, in which fig. (1a) shows the reserve capacity at the early peak and fig. (1b) shows the reserve capacity at the late peak.
Fig. 2 shows a bottleneck section in a normal operation of the Shanghai subway network, wherein fig. 2a shows a bottleneck section in an early peak upstream and fig. 2b shows a bottleneck section in a late peak downstream.
Fig. 3 shows potential bottleneck sections of the Shanghai subway network in case of accident or outage, wherein fig. (3a) shows potential bottleneck sections during early peak ascending and fig. (3b) shows potential bottleneck sections during late peak descending.
FIG. 4 is a flow chart of the method of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example (b):
the invention provides an assessment method of urban subway network reserve capacity, which specifically comprises the following steps:
1) defining the 'turn-back section' as a basic analysis unit of the reserve capacity of the subway network:
the "turnaround area" refers to a section between two adjacent subway "turnaround stations". In urban subway networks in China, only between the switchback stations is the small traffic routes conditionally organized to realize the back-and-forth operation of trains.
The 'turn-back section' is defined as a basic analysis unit of the reserve capacity of the subway network. A corruption scenario is defined as a combination of these elementary analysis units corruption.
2) Defining reserve capacity of the subway network:
reserve capacity mu of a subway networkbAnd (omega) is defined as the minimum value of the ratio of the section traffic capacity to the passenger flow in the subway station under a certain damage scene. Mu.sbThe larger (omega) is, the larger the redundant traffic capacity of the subway network is, and the better the service capacity of the current passenger flow is.
μbThe mathematical definition of (ω) is as follows:
Figure BDA0001776621290000041
wherein, mub(omega) is the reserve capacity of the subway network in the demand scene b, the damage scene omega, caFor the traffic capacity of section a, a belongs to A, A is the basic analysis unit (section) set of the subway network, va(q) is the traffic volume on section a.
va(q) is obtained by the following formula:
Figure BDA0001776621290000042
wherein q isijThe traffic demand from a station i to a station j is shown, i, j belongs to V, and V is a subway station set; dij(omega) is a damage scene omega, whether the station i is communicated with the station j or not is judged, the communication is 1, otherwise, the communication is 0 and deltaarAnd the variable is 0-1, if the path r uses the interval a to take 1, otherwise, 0 is taken, r belongs to P, a belongs to A, and P is the shortest path set.
dij(ω) is determined by the following formula:
Figure BDA0001776621290000043
wherein, tij(omega) is the travel time corresponding to the shortest path between the station i and the station j under the damage scene omega, and i, j belongs to V;
Figure BDA0001776621290000044
under normal conditions, the travel time corresponding to the shortest route between the station i and the station j belongs to V; t is t*Represents an acceptable travel time increment for the passenger;
3) analyzing the reserve capacity of the subway network:
and obtaining traffic demands of different periods according to the subway ticket business data. And calculating the passenger flow of each basic analysis unit by adopting a traffic distribution method. Then, according to the definition of the reserve capacity, the reserve capacity of the subway network is calculated.
Fig. 1 shows the result of analyzing the reserve capacity in the case of normal operation of the shanghai subway network, in which fig. (1a) shows the reserve capacity at the early peak and fig. (1b) shows the reserve capacity at the late peak. From the average value of the reserve capacity, as the number of damaged units increases, the growing trend of the reserve capacity is not obvious, namely, the number of damaged units is increased, the number of shifts of subways is increased to improve the operation capacity, and the increase is related to a specific damage scene. However, the reserve capacity corresponding to a few damaged scenes is far smaller than 1, which indicates that the service capacity of the subway network is seriously insufficient at the moment, and more passenger flows need to be evacuated in ways of emergency buses and the like.
4) Identifying a bottleneck section under the condition of normal operation of the subway network:
and defining the section with the passenger flow saturation degree larger than 0.9 as a bottleneck section. Saturation s of section a passenger flowaComprises the following steps:
Figure BDA0001776621290000051
wherein, caFor passage capacity of section a, va(q) is the volume of traffic in block a, a ∈ A.
And calculating the saturation of each basic analysis unit according to the passenger flow of each basic analysis unit. Thereby, a bottleneck section of the subway network is obtained.
Fig. 2 shows the bottleneck sections in the normal operation of the shanghai subway network, wherein fig. (2a) shows the bottleneck sections in the early peak uplink and fig. (2b) shows the bottleneck sections in the late peak downlink. For the Shanghai subway network, the bottleneck sections of the early peaks are mainly distributed on the part of the entering route accessing the fourth line and the first line and the second line of the central urban area, and the bottleneck sections of the whole subway network are positioned in the connecting section of the entering direction of the fifth line and the first line, the connecting section of the entering direction of the ninth line and the fourth line and the two-way section of the second line from the people square to the Tokyo road.
5) Identifying potential bottleneck sections in subway accidents or outage situations
And acquiring a damage combination set omega among all the basic analysis units under different demand scenes b by adopting a Monte Carlo method. Is provided withThere are n basic analysis units in the network, so there are m damaged scenes omegamIn an amount of
Figure BDA0001776621290000052
The number of bad combination scenes among all the basic analysis units is
Figure BDA0001776621290000053
And setting the number of the required scenes as N (B), calculating the saturation of the section by adopting a traffic distribution method aiming at different damaged scenes, and judging whether the section is a bottleneck section. The probability of section a becoming a bottleneck section is calculated as follows:
Figure BDA0001776621290000054
where n (a) is the number of times that the section a becomes a bottleneck section in all damage scenarios. If N (a) is more than or equal to 10%, the section a is a potential bottleneck section after damage occurs.
Fig. 3 shows potential bottleneck sections of the Shanghai subway network in case of accident or outage, wherein fig. (3a) is a potential bottleneck section at early peak ascending time, and fig. (3b) is a potential bottleneck section at late peak descending time. Comparing fig. 3 and 2, it can be seen that the newly added bottlenecks are mainly concentrated between the eleven-line Jiangsu road to the university of transportation and Xunju, the section of the one-line from the northern Tibet road to the people square, and the section of the six-line from the Gaokui road to the blue village. These segments normally do not saturate more than 50%, but can become a bottleneck in the overall network after the network is damaged.
The invention takes the 'turn-back section' as a basic analysis unit, considers the influence of dynamic passenger flow, can evaluate the reserve capacity of the subway network when a subway accident or a fault stops, supports the emergency management of the subway network and the planning of a line network, and has better application value.

Claims (5)

1. A method for evaluating the reserve capacity of an urban subway network is characterized by comprising the following steps:
1) defining a turn-back section, and taking the turn-back section as a basic analysis unit of the reserve capacity of the subway network;
2) defining the reserve capacity of the subway network, and specifically defining the reserve capacity as follows:
under a certain damage scene, the minimum value of the ratio of the section traffic capacity to the passenger flow in the subway station and the expression of the reserve capacity of the subway network are as follows:
Figure FDA0003068874590000011
Figure FDA0003068874590000012
Figure FDA0003068874590000013
wherein, mub(omega) is the reserve capacity of the subway network under a demand scene b and a damage scene omega, the demand scene b is the hourly traffic demand and represents the dynamic change of the traffic demand, the damage scene omega is the combination of the damage conditions of the basic analysis units, caFor the traffic capacity of the turn-back section a, A is the basic analysis unit set of the subway network, va(q) is the passenger flow on the turnaround section a, qijIs the traffic demand from station i to station j, and i, j belongs to V, dij(omega) is whether the station i is communicated with the station j under the damage scene omega, 1 is taken when the station i is communicated with the station j, 0 and delta are taken when the station i is not communicated with the station jarIs variable from 0 to 1, 1 is taken when the shortest path r uses the turn-back interval a, otherwise 0 is taken, V is a subway network station set, P is a shortest path set, tij(ω) is the travel time corresponding to the shortest path between station i to station j in the damage scenario ω,
Figure FDA0003068874590000014
the travel time, t, corresponding to the shortest path between station i and station j under normal conditions*Travel time increments acceptable to the passenger;
3) obtaining traffic demand according to subway ticket data, obtaining passenger flow of each basic analysis unit of the subway network, and calculating reserve capacity of the subway network, wherein the reserve capacity mu of the subway networkbThe smaller (ω) is, the weaker the ability of the subway network to cope with an accident or failure is, and if μ isb(ω) is less than 1, indicating that the network cannot take up the current traffic demand.
2. The method according to claim 1, wherein in step 1), a retracing section is defined as a section between two adjacent subway retracing stations, and a retracing line is provided between the subway retracing stations for realizing the back-and-forth movement of trains.
3. The method for estimating the reserve capacity of the urban subway network according to claim 1, wherein the method further comprises the following steps:
4) and identifying a bottleneck section under the condition of normal operation of the subway network and a potential bottleneck section under the condition of subway accident or fault outage.
4. The method for evaluating the reserve capacity of the urban subway network according to claim 3, wherein in the step 4), the determination condition of the bottleneck section under the normal operation condition of the subway network is as follows:
the section with passenger flow saturation greater than 0.9 is a bottleneck section, and the passenger flow saturation saThe expression of (a) is:
Figure FDA0003068874590000021
wherein, caTo turn back the traffic capacity of section a.
5. The method for evaluating the reserve capacity of the urban subway network according to claim 1, wherein in the step 4), the identifying of the potential bottleneck section in the case of subway accident or fault outage is specifically:
41) and acquiring a damage combination set omega among all the basic analysis units under different demand scenes b by adopting a Monte Carlo method, wherein the quantity of the damage combination scenes among all the basic analysis units is as follows:
Figure FDA0003068874590000022
wherein n is the total number of basic analysis units in the subway network, omegaiA scene with i damaged basic analysis units;
42) setting the quantity of demand scenes as N (B), adopting a traffic distribution method aiming at different damage scenes to calculate the saturation of the sections and judge whether the sections are bottleneck sections, if the probability N (a) that the return section a becomes the bottleneck sections is more than or equal to 10%, judging the return section a as a potential bottleneck section after the damage occurs, and calculating the probability P (a) that the return section a becomes the bottleneck section:
Figure FDA0003068874590000023
where n (a) is the number of times segment a becomes a bottleneck segment in all damage scenarios.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201023495Y (en) * 2007-04-29 2008-02-20 余亚莉 Vehicle mounted railway traffic passenger transport capacity and operation safety intelligence monitoring and prewarning system
WO2011127363A2 (en) * 2010-04-09 2011-10-13 Carnegie Mellon University Crowd-sourcing of information for shared transportation vehicles
CN102376075A (en) * 2010-08-18 2012-03-14 北京交通大学 Rail transit line transporting capacity evaluating method based on CBTC (Communication Based Train Control)
CN104217297A (en) * 2014-09-16 2014-12-17 北京交通大学 Dynamic security risk assessment method of rail transit station
CN106991542A (en) * 2017-06-06 2017-07-28 北京航空航天大学 A kind of crowded bottleneck identification method of rail network based on seepage theory
CN107392435A (en) * 2017-06-28 2017-11-24 北京交通大学 A kind of track traffic station emergency evacuation capability evaluation system
CN107766969A (en) * 2017-09-28 2018-03-06 东南大学 A kind of major station cable release distribution method based on the identification of subway service ability bottleneck section
CN108364093A (en) * 2018-02-01 2018-08-03 北京市地铁运营有限公司 The road network passenger flow Collaborative Control optimization method of strategy is discongested based on ability bottleneck

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7880767B2 (en) * 2005-08-22 2011-02-01 Andrew Chinigo Security system for mass transit and mass transportation

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201023495Y (en) * 2007-04-29 2008-02-20 余亚莉 Vehicle mounted railway traffic passenger transport capacity and operation safety intelligence monitoring and prewarning system
WO2011127363A2 (en) * 2010-04-09 2011-10-13 Carnegie Mellon University Crowd-sourcing of information for shared transportation vehicles
CN102376075A (en) * 2010-08-18 2012-03-14 北京交通大学 Rail transit line transporting capacity evaluating method based on CBTC (Communication Based Train Control)
CN104217297A (en) * 2014-09-16 2014-12-17 北京交通大学 Dynamic security risk assessment method of rail transit station
CN106991542A (en) * 2017-06-06 2017-07-28 北京航空航天大学 A kind of crowded bottleneck identification method of rail network based on seepage theory
CN107392435A (en) * 2017-06-28 2017-11-24 北京交通大学 A kind of track traffic station emergency evacuation capability evaluation system
CN107766969A (en) * 2017-09-28 2018-03-06 东南大学 A kind of major station cable release distribution method based on the identification of subway service ability bottleneck section
CN108364093A (en) * 2018-02-01 2018-08-03 北京市地铁运营有限公司 The road network passenger flow Collaborative Control optimization method of strategy is discongested based on ability bottleneck

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
《城市轨道交通车站内客流集散瓶颈识别及排序方法》;汪瑞琪 等;《交通信息与安全》;20170228(第1期);第71-79页 *

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