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Analysis Of Taxi Operation Patterns And Characteristics Based On Trajectory Data

Posted on:2021-07-09Degree:MasterType:Thesis
Country:ChinaCandidate:Y W WangFull Text:PDF
GTID:2492306293452404Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
With the continuous development of urban socio-economic level,taxis have become an important part of the urban transportation system with advantages such as comfort,convenience and point-to-point.As a provider of travel services,taxi drivers have also received more attention from researchers.Taxi drivers will form unique operation preferences due to their knowledge of urban roads and the flow of people,and affect their own income levels.At the same time,the revenue of taxi drivers is also affected by the market changes brought by transportation network companies.From the perspective of taxi drivers,this paper calculates the characteristics of taxi operations,explores the differences in taxi operation patterns,and analyzes the impact of taxis on the background of the rise of transportation network companies.In this paper,the mining operation patterns of the taxi is first studied.Taking the taxi trajectory of a working week in October 2016 as sample data,the three characteristics of the average distance of passengers-delivery trip,the distance between the center point of the trajectory and the center of the city and the radius of gyration are selected through visual analysis to establish a clustering model to mine different operation patterns of taxi.Analyzing the clustering results,the Beijing taxi drivers are divided into four types of operation patterns,which are defined as "city center short-distance type","city center comprehensive type","city edge type" and "long-distance type",of which the first two types account for about 75%,which are the mainstream operation patterns,and "long-distance type" taxis account for only 8%.Meantime,about 75% of taxi drivers maintain the same operating patterns in 5 days.On this basis,a benefit model is constructed,and the occupied ratio and income of taxi drivers under different operation patterns are analyzed.Secondly,this paper explores the spatiotemporal changes of taxi operation characteristics in different periods in combination with the development nodes of transportation network companies.The 5 days’ data of the same period in 2012,2014 and 2016 are selected to correspond to the pre-birth period,rapid development period and stable period of the transportation network companies,and the changes in the overall operation characteristics of the taxi are analyzed from three aspects: mileage index,time index and spatial distribution.The analysis results show that the e-hailing application has improved the efficiency of taxi operation and passenger delivery distance,and the revenue of taxis increased slightly in 2014.However,it’s express service introduced huge competition to the taxi industry,resulting in a significant drop in the average daily number of passenger-delivery trips.In 2016,taxi revenue decreased by 15.9% compared to 2012.In terms of spatial distribution,taxi trajectories have a tendency to spread outward,and the density of taxi trajectories outside the Fourth Ring Road in Beijing continues to increase.In the area inside the Fourth Ring Road,the density of taxis in commercial and leisure entertainment areas has decreased significantly,and more taxi drivers choose railway stations and airports to get passengers.Meantime,this paper explores the characteristics and revenue changes of the four types of taxi operation patterns previously defined in different periods.Among them,"long-distance type" taxis are less affected by transportation network companies,and their revenues are increasing year by year.Other type has been affected to a greater extent.This paper has excavated and researched the taxi operating characteristics from the above two aspects.The results of this study can help the taxi driver to choose a suitable operation patterns to a certain extent to improve the efficiency level.At the same time,it also provides data references for city managers to formulate more reasonable policies to increase the revenue of traditional taxis and reduce the impact of traditional taxis on the background of the rise of transportation network companies.
Keywords/Search Tags:GPS trajectory data, taxi operation patterns, clustering analysis, transportation network company
PDF Full Text Request
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