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Analysis Of Residents’ Traffic Circle And Degree Of Crowdedness Based On Multi-source Data

Posted on:2019-06-24Degree:MasterType:Thesis
Country:ChinaCandidate:X Z WuFull Text:PDF
GTID:2439330590951625Subject:Logistics engineering
Abstract/Summary:
With the process of urbanization,some residents have been resettled in the suburbs.However,the imperfect traffic software and hardware have caused great inconvenience to people’s travel.Based on previous survey data,we learned that the two main factors affecting people’s travel are travel time and comfort.Therefore,in this dissertation two main factors that affect residents’ travel are discussed: travel time and congestion.The size of the travel circle directly reflects the change of travel time.This paper examines the use of public transportation and private transportation as two types of travel modes,starting from the central area and taking a half-hour and one-hour trave l,and their respective crowdedness levels.Compared with city center,Shanghai peoples Square,we take the nearby residents of Shanghai Jinhe New City as an example to analyze the subway and taxi data of 2015.4.1-2015.4.7 to reveal people’s travel situation.We chose taxis and subways to represent private cars and public transport respectively.This paper mainly has mainly analyze d two factors including comfort and travel range of the two modes of transportation.The comfort of the subway is represented by the cross-section passenger flow.For the taxi,we define it as one person,which is the most comfortable level.At the same time,we studied the half-hour and one-hour trips from Jinhe New City.The closest subway station to Jinhe New City is Songhong Ro ad Subway Station.We roughly estimate that people travel from the community to the subway station for 15 minutes.Therefore,the subway’s travel range is 1 5 minutes and 45 minutes from Songhong Road Subway Station.At the same time,we use data to indicat e the range of people traveling every hour.The accessibility of taxis and subways was studied by calculating the coverage area index and coverage point of int erest indicators.The convex hull algorithm is used to calculate the area index.The accumulative opportunity model was used to obtain points of interest for coverage,and then MAG indicators were used to compare the accessibility of the two modes of transportation.In the process of processing data,because the amount of data is too small to achieve our goal,some expansion measures have been adopted to increase the scale of the data.
Keywords/Search Tags:traffic circle, degree of crowdedness, convex hull, sparse data
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