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Study on Public Transportation Passenger Flow Distribution

Author: FangXueJiao
Tutor: GuanHongZhi
School: Beijing University of Technology
Course: Transportation Planning and Management
Keywords: Rail and bus passenger transfer Sort by Select Model Tobit model Matching data Method (CVM)
CLC: F572.88
Type: Master's thesis
Year: 2010
Downloads: 189
Quote: 3
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Abstract

Positive development intensive , energy-saving and environmental protection traffic is subject to the laws of modern urban development . Therefore , give priority to the development of public transport , has become the consensus of the development of the Metropolitan Transportation . Rail transportation as a solution to the big city 's traffic congestion problem , one of the most efficient means of transport for travelers quick in traffic demand , the major cities in speeding up the construction of new rail transit lines . This strong impact not only to private traffic , but also to some extent compete with conventional buses . However , rail transport and conventional bus is integral to the city bus system , the two parts complement each other , only deal with the public transport system within the way of competition and collaboration relationships , to form a moderate proportion of passenger traffic between the two balance , in order to achieve the public transport optimal system overall . In this paper, based on analysis of factors influencing urban rail transit and conventional bus passenger Beijing as an example , conventional bus travel SP investigation willingness matching data , quantitative analysis fares , travel time than characteristics transfer of the travelers personal property on the city bus system passenger ( mainly the transfer of conventional public transport to rail transport ) affect the ranking selection model were established , and the interception of the regression model , found that sex, occupation , monthly income , the cost of bus travel and subway and bus travel the longer than subway fare threshold shift transit users significantly affect the odds ratio , the marginal effect and point elasticity analysis of the impact of the variable , and to explore the advantages and disadvantages of the two models for the prediction of the subway fare prepare . Finally, the use of Oprobit (3-8) and Tobit models forecast for 2010 and 2015 in the brush bus adult card continues to enjoy a 4 % discount , set the different subway fare corresponding to the different time than under conventional bus travel by rail transit transfer of passenger flow ratio. After the comparison of different prediction methods and the correction of the consumer price index , the final recommendations of the subway fare in 2010 and 2015 should be set at 3.2 yuan and 3.6 yuan , to ensure that the ground transportation average daily passenger traffic up to 1400 , and 15 million people respectively .

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CLC: > Economic > Transportation and economic > Urban transport economy > China's urban transportation economy > Local urban transport economy
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