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Characteristics Of Beijing Urban Rail Transit Passenger Flows During Holidays In 2014

Posted on:2017-04-24Degree:MasterType:Thesis
Country:ChinaCandidate:C WangFull Text:PDF
GTID:2272330485957837Subject:Transportation planning and management
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It is necessary to study on characteristics of urban rail transit passenger flows during holidays to grasp rules for changes of passenger flows during holidays, to provide reality basis to operation and passenger organization, at the same time, to support the formulation of transportation policies. As a result, during holidays, the urban rail transit system can operation much more rapidly and efficiently, and get released from the passenger volume pressure.This study focus on the time and spatial features for typical lines and stations during various holidays. On this basis, important aspects for operation of lines and passenger transport organization have been came up. An experimental case has been studied combined with the urban rail transit passenger volume in Beijing,2014.The main work and conclusions of this paper are as follows.(1) Holidays and the urban rail transit lines are classified. Holidays are divided into 3-days holidays, the Spring Festival and the National Day. The urban rail transit lines are also divided into 3 types:urban lines, regional lines and suburb lines, and regional lines contains diameter lines and radius lines. Besides, this study has paid attention to factors influencing the travel behaviors, including the development level of cities, characteristics of urban rail transit system and features of passengers.(2) Studying on characteristics of passenger flows during holidays for urban rail transit lines from 3 aspects:daily passenger volume, passenger volume over equivalent time and section passenger volume. Based on the characteritics of lines, some suggestions have been came up.The case study of Beijing indicates:the passenger volumes for typical lines during various holidays are lagerer than the average value of passenger volume for weekends. The trend of passenger flows during the Dragon Festival and the Mid-autumn, which are both traditional festivals, is same. As for lines, the changing trend of passenger flows for line 1, line 2 and Batong line is same, while line 8, representative of regional radius lines, is specific.During holidays, the passenger volume over equvilent time for all typical lines become more balanced and the peak periods of passenger volume are 9:00-11:00 and 16:30-18:30. The passenger flow during the Spring Festival is the most balanced, while during the same holiday, the passenger flows of surburb lines are less balanced. The inequality extent has been increased for section passenger volume for all typical lines. The section passenger volume near to famous scenic spots will increase a lot and the peak sections of lines passing this type of session may change.(3) Studying on characteristics of passenger flows during holidays for urban rail transit stations from 2 aspects:passenger volume to get into stations, and transfer passenger volume of transfer stations. Based on characteritics of stations, some suggestions have been came up.The case study of Beijing indicates:during holidays, the passenger volume to get into stations near scenic spots and shopping malls will increase a lot, while the peak periods of stations near scenic spots are 12:00-18:00 and the peak periods of stations near shopping malls are 14:00-21:00. For the stations near residential or area with a complex land-use pattern, the passenger volume stays constant. While for the stations near offices or area with simple land-use pattern, the passenger volume shows a significant decrease.During different holidays, the transfer passenger volume of transfer stations, the proportion of transfer passengers of which are less than 0.8, will change less than the passenger volume to get into stations. Moreover, when the transfer passenger volume increase, each transfer direction will not increase at the same time.
Keywords/Search Tags:urban rail transit, holidays, time and spatial features of passenger flows, travel behavior
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