| With the continuous development of urbanization,the status of rail transit is becoming more and more important,which has become an integral part of the large cities' development planning.However,the guide signs of rail transit in the underground space cannot meet the needs of all passengers very well.Some signs will mislead passengers visually and cause many unnecessary troubles.Therefore,it plays an important role in the passenger's travel to effectively guide the layout of signs,help passengers get the information of signs correctly and arrive at the destination accurately.The main problems of this study include:(1)Analysis of sign content.Through the analysis of big data,we can identify the influence on the passenger's information acceptance ability caused by factors such as the underground closed complex environment,the setting content of signs,and the passengers' personality characteristics.(2)The location and content of the identification.How to effectively set up guide signs in urban rail station space environment is an important research issue.In addition,the number of signs is not the more the better.If the guide signs are arranged too much,it will not only affect passengers' inability to quickly identify valid information,resulting in traffic congestion,but also cause a waste of resources.(3)The effect metric of sign setting.This paper focuses on how to find a more powerful identification verification method according to the operation uncertainty,time and result of identification setting.At the same time,it is an important basis for making correct decisions to test,explore and optimize the different identification settings.Based on the above problems,this study firstly takes the passenger OD(origin destination)data and Beijing rail transit'scomplaint data as the research object,alsouses data analysis and text mining methods to effectively identify the rail transit-oriented identification problem.Next,based on the analysis of passenger flow line data,the MIP model of rail transit guide sign system is constructed by using optimization theory.Finally,based on the simulation method,we take Beijing Xizhimen Stationas an example,the optimization of rail transit signs is studied.The main contents include:(1)Analysis of rail transit signs.Firstly,based on the analysis of OD data,this study analyzes the relationship between passenger behavior and identification issues from the perspective of 4 aspects,passenger's time at station,frequency,route and station information.Secondly,the complaint text is mined.By using subject keyword extraction,syntax dependency analysis,word clustering and keyword co-occurrence network visualization analysis,the main content,core problems and key words of rail transit logo complaints are analyzed,in order to provide data support for the analysis of logo problems.(2)Research on the standardization and systematization of rail transit sign setting.Based on the analysis of the passenger flow line,signs' location and information content are fully considered,and the optimization model of guide signs locationin urban stations is constructed,so that the passengers can reach the destination as soon as possible.By setting reasonable guide signs,passengers can pass through the shortest route,so as to reduce the stay time and the number of passengers in the station.(3)Simulation setting and model analysis of rail transit signs.In this study,Xizhimen rail transit station was investigated and analyzed.This paper mainly studies the passengers' transfer rules,the travel directionrestrictions,the indication signs and the actual guidance.In addition,based on the simulation method,this paper studies the optimization of rail transit signs.The main contents include the theoretical research of the the station identifications' optimization,the simulation model of the station identification based on Xizhimen rail transit station,the analysis of the simulation results and the optimization strategy of the station identification.By considering passenger OD data,complaint data and streamline data,the study finally formed a large data analysis and simulation model for rail transit sign optimization.The innovations of this article are as follows:(1)Big data analysis model of rail transit signs.At present,the research mainly focuses on the optimization of logo,but the causes of logo misunderstanding are rarely described.In this study,two chapters are used to analyze the problem of guiding signs through passenger's original OD and logo complaint text.First of all,the data sets needed for the research are sorted out.Then,a statistical model is constructed from the perspectives of station,route,time and passenger,and the preference of abnormal passengers is obtained.Through preprocessing the data set in and out of the same station,the data set that can reflect the characteristics is constructed,also the data relationship between the passenger behavior and the identification problem is analyzed.Secondly,the complaint text is processed by de duplication and word segmentation,and the subject words and related keywords are extracted by semantic analysis.The complaint problems are classified,and the core problems of different types of complaints are mined by keyword co-occurrence network.The results of these two chapters provide the research basis for the following optimization modeling and the rail transit signssimulation.(2)The standardized and systematic research on the setting of rail transit signs.The location of rail transit guide signs is unreasonable,which is easy to cause congestion.Too many information signs at the same location lead to excessive information.The accumulation of guide signs is complicated,which affects the passengers to obtain accurate information.Based on the analysis of the passenger flow lines at the stations,the problem of the guide signs' location setting is transformed into a mathematical optimization model,and the objective function of maximizing the amount of induced information in the study area is established.The model helps to scientifically find the optimal placement of the guide signs from multiple candidate positions to reduce the guidance errors caused by the guide signs.At the same time,the number of signs is introduced,and the number of signs is considered to minimize the total signs.The construction cost and the two sub-goals of passengers achieving the convenience are expected to minimize the total cost of passengers' access from the sign to the destination,rather than simply reducing the distance.(3)Simulation model for the rail transit signsoptimization.Considering that the identification research results can not be verified in reality,and there are many dynamic uncertainties in reality verification.Therefore,the research and application of simulation methods should be based on the passenger flowanalysis,on the Anylogic simulation platform,to determine all kinds of parameter values required in themathematical models practical application,so as to obtain a complete optimization model of signage distribution,and based on Agent method solves the model.The simulation model can express the uncertainty of operation time and result of logo setting,so as to quantify the risk and find a more powerful logo optimization solution.At the same time,the simulation can also be used to verify the feasibility of the identification optimization scheme.It provides a way to test and explore different scenarios of security identification optimization and make the right decision before making real changes. |
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