| In recent years with the development of social economy, more and more domestic and foreign cities have urban rail transit systems. On one hand, because of the characteristics of "time" and "fast", more and more people choose rail transit traffic in travel time; on the other hand, more and more serious congestion phenomenon occurred in rail transit system is. There are two areas in rail transit system which are easily to be congested, one is station, and the other is transfer channel, this state that too many passengers gather in locomotive car, is called cowed, not congested. Station congestion means that traffic demand is beyond traffic capacity of station, which can be understood as that process capacity of station is limited and can not delivery passengers in time. Level 3 early warning mechanisms which are respectively green, yellow and red for station congestion will be released by Beijing municipal committee. Congestion phenomenon has become normal, and more and more people pay attention to it. Whether station congestion or transfer channel congestion, congestion phenomenon means that the destination is more and more difficult to reach for passengers, decreases network connectivity efficiency, seriously affects normal operation of rail transit system, and even causes the worst stampede, so that traffic administrative department need to pay high attention to congestion phenomenon. So research on dynamic process occurred on rail transit system, in-depth analysis of congestion phenomenon, and strategy of optimization for rail transit system which are used to improve communication efficiency of rail transit network, is undoubtedly a very important realistic subject placed in front of traffic administrative department. These study which can help to prevent catastrophic consequences of congestion, has important social value and economic value. Specifically, main research work is as follows:1. Based on complex network theory congestion phenomenon occurred in rail transit system is studied.(1)Reasons of congestion about stations and transfer channels are analyzed. There are two areas in rail transit system which is easily to be congested, one is station, and the other is transfer channel,. Station congestion means that traffic demand is beyond traffic capacity of station, which results into phenomenon that passengers still stay at station. There are two reasons for station congestion: one is that number of passengers who enter into station is so much that stations can not maintain, the other is that station capacity to transport passengers is very inadequate. For example, traffic flow bypass station is too large which means that locomotive car is overcrowded, that waiting passengers can't get on the car. The first reason is independent of rail transit system, and the second reason embodies unbalanced traffic flow regulated by rail transit system. Transfer channel congestion means that transfer flow is beyond capacity of transfer channel, and embodies unbalanced transfer flow regulated by rail transit system.(2)There is much relation between these two congestions. Both station congestion and transfer channel congestion all embody extension of average travel time for passengers, mean that it is more and more difficult for passengers to arrive at their destination, and operation efficiency of rail transit system declines, which belongs to the category of network connectivity; Station congestion from aspect of second reason and transfer channel congestion, can be understood as dynamics process happened on rail transit network; In addition, station congestion from aspect of first reason, that is to say that number of passengers which enter into rail transit network is so much, may result into transfer channel congestion, and these transfer passengers influx into transfer station, in turn can lead to transfer station congestion. Station congestion can be regulated by administrative department through reasonable measures such as increasing locomotive frequency and limiting number of passengers who enter into station. For transfer channel, because of its special geographical location, once congestion happens, it is often great difficult to conduct effective guidance. In view of dangers about transfer channel congestion, this paper will pay more attention to transfer channel.2. New model based on transfer behavior is proposed which is used to evaluate importance of transfer stations in Beijing rail transit system.(1)Development of Beijing rail transit system is introduced, including mile of all lines, number of stations, and passenger traffic situation. Space L model of rail transit network is reviewed, and deficiency of this model is pointed out, and deficiency lies in not considering transfer behavior, which is widespread in rail transit network.(2)New network model based on transfer behavior is proposed. ?Firstly, introduce method which is used to construct new model. According to the number of subway lines(N) which pass through transfer station, this method produces other N-1 transfer stations, there are transfer-channels between these transfer stations and each subway line passes through one transfer station. ?Secondly, the edge of new model is explained, which respectively means edge between neighbor stations and transfer channel, and physical meanings of length about these two kinds of edge are average running time between adjacent stations and transfer time, length of these two kinds of edge can be adjusted, for example, by increasing locomotive frequency length of edge between neighbor stations will be reduced accordingly, and when congestion occurs length of transfer channel will be extended. This model is actually a weighted network model. ?Thirdly, advantage of new model is pointed out. Shortest travel time path between any two stations can be calculated, which is precisely pursuit of rational passengers; Existence of transfer channel makes it possible to determine transfer flow, which is an important part in next studies about network connectivity. ?Finally basic parameters of Space L model and new model are compared through simulation.(3)Transfer behavior is of great importance in maintaining normal operation of rail transit network, it is of great significance to distinguish important transfer stations in network. Traffic flow and transfer flow at transfer station are used to assess the importance of every transfer station; a new method based on system analysis is proposed, and is applied to assess importance of transfer station in Beijing rail transit network. Results show that: in estimating traffic flow and transfer flow at transfer station, new model is more true and accurate; traffic flow and transfer flow at transfer station can better reflect importance of each transfer station, which is consistent with results obtained in method based on system analysis.3. Dynamics process on network is studied systematically based on traffic routing model which put forward new perspective of network connectivity.(1)In order to understand dynamic process on network deeply, process of two common used dynamic models were studied. This paper is concentrated on algorithm implementation process about two commonly used cascading failure models(load-capacity model and CML model). Simulations are performed in the software combined with actual cases, process of cascading failures is decomposed, and the running results are fully in line with expectations. More and more attentions are paid to research on phase transition based on traffic routing model. ?Firstly, determination of network capacity is paid more attention to. Under shortest path routing strategy and load uniform distribution strategy, two methods are used to study network capacity which respectively based on probability statistical and simulation, and results show that: Numerical calculation result and experimental result about the capacity of three different network are basically consistent; ?Secondly, in process of phase transition variations about three kinds of loads on network are focused on, which are total loads on network, loads that disappear from network and loads that are waiting for passing through some node. Through simulation, law of parameter P which means slope of time sequence for number of loads waiting to pass by node and parameter X which means slope of time sequence for number of loads disappearing from network are conducted. Results show that the node with maximum betweenness is easily to be congested, which results into unbalance between loads that enter into network and loads that disappear from network, and eventually results into network congestion; When R<Rc, the number of loads that disappear from network increases synchronously with R. When R>Rc, ratio of the number of loads that disappear from network and R decreases gradually, which means that it is more and more difficult for loads to reach their destination.(2)Concept of network connectivity based on traffic routing model is proposed. Aiming at shortcomings of previous studies about network connectivity, new concept is combined with congestion effect of transportation network, from connectivity efficiency perspective of system operation, namely that network connectivity is measured by degree of difficulty how loads arrive at destination. Considering both network topology and load transportation on network, new concept offers new perspective to explore network connectivity. Once there is congestion phenomenon on network, connectivity becomes poor, so that whether there is congestion occurred on network can be one of the most important basis to evaluate network connectivity, and network capacity is phase transition point of network from stable state to congestion state, to a certain extent, can represent network connectivity.(3)Main factors which can influence network connectivity are analyzed empirically. Through simulation influence of three topology strategies on network connectivity are studied which are respectively small-world network, scale-free network and random network; influence of two routing strategies on network connectivity are studied which are global routing strategy and local routing strategy; influence of different load distribution strategies on network connectivity are studied; two design strategies of processing capacity(equal strategy or strategy of capacity positively related to edge betweenness) are studied. All these strategies can influence dynamic process on network. Results show that: with the existence of core node, scale-free network has minimum capacity of network, and random network has the biggest network capacity. That is of great guiding significance for planning department to design road network; scale-free network connectivity under global information routing strategy is far better than local routing strategy. Under global information routing strategy, although load average travel time with ?=1 is slightly longer than ? = 0(shortest path routing strategy), network connectivity is greatly increased, which is of great significance to promote rail transit network connectivity from view point of routing strategy. Simulations show that the maximal capacity corresponds to for LRS, while the maximal capacity corresponds to for GRS; Under even load distribution strategy network connectivity is best, and when, namely that starting point of load tends to be in large degree node, regardless of destination point tend to be any case, network capacity all appears to drop sharply, which is of great guiding significance for us to conduct research about impact of morning and evening rush on rail transit system. The above strategies are to have a significant impact on dynamic process on network, and it is also foundation work which is basis to propose suitable connectivity optimization strategy of rail transit network.4. Traffic routing model based on rail transit network is proposed, and was used to analyze dynamic process on rail transit network.(1)Firstly, traffic routing model should be involved into rail transit network, which includes detailed instructions of key related concepts, and practical meaning of related parameters. For example in unit time loads which enter into network, mean loads which leave off station rather than loads which enter into station.(2)Secondly, two kinds of measures to evaluate rail transit network connectivity were proposed which are respectively network capacity and average travel time for passengers. Standing on macro management point of view, what traffic administrator pays more attention to is when congestion occurs on rail traffic network. While for passengers, it is average travel time.(3)Thirdly, suitable optimization strategy about rail transit network connectivity is proposed. When optimization strategy of network connectivity is applied to rail transit network, features of actual network should be considered. Three optimization strategies were proposed, namely routing strategy, topology-change strategy and capacity design strategy, for example routing strategy is that traffic administrator releases traffic information all the time, which can be a reasonable guide for passengers to select their optimal travel path. Topology-change strategy is to close transfer channel and adjust frequency of locomotive operation. Capacity design strategy is that planning department reasonably allocates different process capacity to different transfer channel in the planning stage. Under routing strategy, rail transit network is weighted network, and passengers will select their optimal path according to newly network model, which can improve network connectivity. Under topology-change strategy, reasonable shut down of transfer channel can result into uniform passenger flow, which can improve network connectivity. And adjusting frequency of locomotive operation can make administrator for a balance between cost and connectivity, for example at slack time, reducing frequency of locomotive operation, which will extend length of neighbor stations on newt network model, results into decline of network connectivity, but cost will have been reduced. Under capacity design strategy, transfer channels with larger edge betweenness are given larger capacity, and network connectivity is increased obviously.(4)Finally, empirical analysis shows that all above strategies can improve rail transit network connectivity. It is capacity design strategy which has the most obvious effect on network connectivity, and reasonable design strategy can double network capacity compared with equal strategy; routing strategy is followed by capacity design strategy, which failed to play a proper role due to bottleneck effect of transfer channel(60, 246), that is to say, for passengers in and out of FengBo this transfer channel is necessary path; For closure strategy of transfer channel, transfer flow are shared by fewer transfer channels, and if transfer flow is reconfigured more even, then it can improve network connectivity, otherwise likely to cause a decline of network connectivity.5. Empirical analysis about impact on rail transit network due to line fault and morning or evening rush is conducted.(1)Beijing rail transit network is used as underlying topology, and empirical analysis is conducted about impact on rail transit network due to 4th line fault. ?Firstly, impact on network topology caused by 4th line fault is analyzed. Results show that: after 4th line fault, betweenness distribution of all stations is deteriorated, and phenomenon of traffic surges in some lines happens which will aggravate degree of some station congestion; ?Secondly, due to reassignment of loads, congestion will happen in some transfer channels, average load transporting time will be extended, and connectivity of rail transit network will be degraded form 28 to 22. Secondly, strategies about how to face with failure are analyzed. Through simulation effects about topology-change strategy and routing strategy are compared, and results show that routing strategy is very useful to improve connectivity, which is promoted from 22 to 26; closing different transfer channels can lead to different results, but overall effects are not obvious.(2)Empirical analysis about impact on rail transit network due to uneven distribution of passenger flow is conducted. ?Firstly, concept of load distribution strategy is proposed. In accordance with specific features of morning rush, three different kinds of load distribution strategies are put forwarded. ? Secondly, approximate calculation method of betweenness is proposed. If load distribution is not even, betweenness can only be calculated through simulation experiment, which is based on definition of generalized betweenness, that is to say, through a large number of repeated experiments to find out statistical regularity of number of loads which pass through node(edge), as the basis of calculating node betweenness(edge). ?Thirdly, through simulation impact of three kinds of different load distributions on network connectivity are compared with. Under uneven load distribution strategy, transfer flows which pass through transfer channel have direction, and transfer flows from a-b is different from b-a. ?Finally, impacts on rail transit network by two topology-change strategies are conducted. Results show that based on even load distribution strategy, by comparing betweenness calculation results of two methods, approximate calculation of betweenness fits well with actual value; During morning rush, uneven load distribution has significant effects on connectivity of rail transit network, and more uneven load distribution is, more significant effect is; to increase locomotive operation frequency can relieve station congestion, but will worse degree of transfer channel congestion. In addition, direction and thinking in the future research about optimization strategy is put forward.Research idea of this paper is as follows: firstly, problem of network congestion occurred on rail transit is put forward, which involves two aspects, rail transit network model and congestion problem. Secondly, the problem is analyzed. Rail transit network model to be established should consider two important features, transfer behavior and effect of congestion. While congestion has two meanings, on one hand congestion means that it is more and more difficult for loads to arrive at their destination, which embodies lower connectivity efficiency of network, and belongs to category of connectivity study; on the other hand congestion embodies dynamic process occurred on rail transit network. Dynamic process based on traffic routing model is studied, from new perspective new concept of connectivity is put forward, and main factors influencing dynamic process is analyzed. Finally, solutions are put forward. Suitable optimization strategy for rail transit network connectivity is put forward.Overall, it is appropriate to study dynamic process on network through traffic routing model based on rail transit network; Three kinds of connectivity optimization strategies proposed in paper are consistent with characteristics of rail transit network, are operable in practice, and experimental effect is ideal; Line fault and morning or evening rush have a great impact on rail transit network, and traffic administrator should make contingency plans early. Analysis and conclusions of this paper can provide reference for traffic administrator at daily operation management. |
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