The Research And Implementation Of Guidance System Of Passenger Flow On Urban Rail Transit

Existing passenger flow guidance system of urban rail transit is based on emergency preparedness. It is about using broadcasting and artificial grooming to solve unexpected problems of passenger flow. But, there are gaps in the field of day-to-day travel path guidance for urban rail transit. With the expansion of the transport network, a large number of passengers will get together in the path having best distance or time between OD without guidance. A big problem of congestion will appear in that case. So, both related road traffic theory and the characteristics of rail transit are taken into consideration. Main work of this paper is carrying out research and realization with urban rail transit system in Beijing as background. The contents of this paper can be summarized as follows:1. On the basis of research for optimum route search model ( basic theory of traffic guidance system), comprehensive travel impedance function including both deterministic and non-deterministic factors and a O(NlogN) Dijkstra algorithm implementation with Java PriorityQueue is given.2. After traffic assignment theory study, minimum path assignment model is choosed to achieve calculation of 5-minute interval section passenger flow. It is realized by assigning OD passenger flow to section with Java program.3. A large numbers of historical station and section passenger flow samples are analysed to determin the characteristics of passenger flow distribution. The result turns out that fitting passenger flow distribution by least square method is a reasonable scheme.4. Some conclusions about BP neutral networks are summarized: Transfer function whose derivative function has larger value range will perform better convergence speed in training. A scaled conjugate gradient algorithm (SCG) is emphasized after comparison of common BP training algorithms about training convergence speed and memory consuming. Early Stopping is a useful technology to improving generalization.5. Take passenger flow into and out of a station of Beijing urban rail transit system called XiZhiMen for example, this paper discusses BP neutral network model for date and time prediction from aspect of times series. Trial-and-error method is still the best way to determine the topological structure of BP net. A BP neutral network with high convergence speed, low memory consumption and good generalization is established by Tan-Sigmoid transfer function, SCG algorithm and Early Stopping technology. The mapping relationship between passenger flow of history and that of short-term future within a certain margin of error can be revealed by this BP neutral network.6. A new integrated framework called SSH is used in this paper to achieve a kind of J2EE Web Development with high cohesion, low coupling and easy maintenance. SSH framework is made of Hibernate (for persistence layer), Struts (for presentation layer) and Spring (for business logic layer and framework integration). Finally, a high quality passenger flow guidance software system of Beijing urban rail transit with B/S model is made by this SSH framework combine with Flash technology for vectorgraph and animation. Both passenger flow information and guidance result can be displayed by graphic interaction.