Journal
SUSTAINABILITY
Volume 12, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/su12031113
Keywords
complex network; origination-destination; travel time; correlation; big data
Funding
- Natural Science Foundation of Zhejiang Province [LY20EO80011]
- Key Project of National Natural Science Foundation of China [51638004]
- Basic Research Program of Science and Technology Commission Foundation of Jiangsu Province [BK20180775]
- National Natural Science Foundation of China [71701099]
Ask authors/readers for more resources
The information level of the urban public transport system is constantly improving, which promotes the use of smart cards by passengers. The OD (origination-destination) travel time of passengers reflects the temporal and spatial distribution of passenger flow. It is helpful to improve the flow efficiency of passengers and the sustainable development of the city. It is an urgent problem to select appropriate indexes to evaluate OD travel time and analyze the correlation of these indexes. More than one million OD records are generated by the AFC (Auto Fare Collection) system of Nanjing metro every day. A complex network method is proposed to evaluate and analyze OD travel time. Five working days swiping data of Nanjing metro are selected. Firstly, inappropriate data are filtered through data preprocessing. Then, the GD travel time indexes can be divided into three categories: time index, complex network index, and composite index. Time index includes use time probability, passenger flow between stations, average time between stations, and time variance between stations. The complex network index is based on two models: Space P and ride time, including the minimum number of rides, and the shortest ride time. Composite indicators include inter site flow efficiency and network flow efficiency. Based on the complex network model, this research quantitatively analyzes the Pearson correlation of the indexes of OD travel time. This research can be applied to other public transport modes in combination with big data of public smart cards. This will improve the flow efficiency of passengers and optimize the layout of the subway network and urban space.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available