Research On Spatial-temporal Characteristics Of Urban Residents’ Travel Based On Taxi Data

With the continuous expansion of urban population and scale,the demand of urban residents for transportation services and public resources is increasing.So,it is particularly important to study the spatial and temporal characteristics of urban residents’ travel.In recent years,big data analysis has been widely used.Compared with the traditional methods,the research on the travel behavior of urban residents based on taxi trajectory has a great advantage,which provides a new perspective for the research on the travel pattern of urban residents.This paper uses the taxi trajectory data to study the spatial and temporal characteristics of residents’ travel in the main urban area of Changsha city,so as to provide support and reference for the urban traffic planning,taxi drivers’ passenger finding and passenger traffic demand.The research data in this article include the original data of taxis in Changsha City in the first week of December in 2013 and 2017,as well as data on business districts and important transportation nodes related to residents’ trips.Based on the original taxi data for two weeks in two years,this paper analyzes the structure of taxi data and the causes of data quality problems,and a set of taxi data trajectory extraction and taxi pickup point extraction processes were designed to extract two weeks Taxi drop-off point data.Based on the extracted pick-up and drop-off point data,the temporal and spatial distribution characteristics of residents based on taxi travel within the main urban area of Changsha City were explored.And the similarities and changing trends of the spatial and temporal characteristics of residents in Changsha city are analyzed based taxi data during the first week of December in 2013 and 2017.In terms of temporal characteristics,this paper compares the average daily and hourly number of pick-up and drop-off points of working days and weekends in two weeks,and calculates the proportion of trips of different travel time lengths.As for the spatial distribution,this paper compares the spatial distribution of pick-up and drop-off points within the scope of weekday and weekend at different spatial scales.The transformation near the subway station before and after the operation of metro,and change of the density of pick-up and drop-off points around bus stations and important commercial circles are also studied.Studies have shown that in terms of travel time characteristics,the daily taxi trip volume in the first week of December in 2017 has increased significantly compared to that in 2013,with more significant increase in weekend trip volume.The proportion of trips on weekends in 2013 is less than the working day as a whole,while the taxi travel time on weekends in 2017 is generally longer than the work day.The change trend of the number of pick-up and drop-off points in each time period of each day in the two years is basically the same,while the duration of the night peak in 2017 is longer than that in 2013.In terms of spatial characteristics,Yuhua District has the largest number of pickup and drop-off points in two weeks,and the number of pick-up and drop-off points in Tianxin District has grown the fastest.In 2017,the number of streets with high travel intensity is more and more decentralized than in 2013.The subway stations and bus stations aggregate taxi pick-up and drop-off points.The study also revealed the characteristics of residents ’travel to various business districts based on taxis.The Wuyi business district located in the urban center has a much higher travel intensity than other business districts,and urban residents prefer going to the Guanshaling business district on weekdays and going to the Rongwan town business district on weekends.Based on the data of taxi pick-up and drop-off points during the first week of December 2017,this paper further studied the floating characteristics in weekdays and weekends on the scale of district-level administrative divisions,calculated regional connection degree,regional flow intensity and regional flow tendency index and explored the differences in the mobility of residents traveling on both sides of the Xiangjiang River.Then on a more microscopic scale,using hexagonal grid partition for the study area,each area is divided into traffic “producing area” and “attracting area” areas.By calculating the traffic attraction index of each grid in each period,this study explores the regional dynamic change on the weekday and weekend in Changsha urban area.Taxi pick-up and drop-off points are mainly distributed in the southeast of the study area.The core business district and the railway stations have a huge impact on the attractiveness of transportation.The Wuyi business district in the middle,the railway station business district and the Changsha South Station in the southeast have been in a state of net traffic outflow for a long time.The peripheral areas of the Wuyi business district are mostly in the state of net traffic outflow from 6 o’clock to 21 o’clock,and the further away from the Wuyi commercial district,the shorter the duration of the net outflow of traffic.