Collection of passenger flow data and development of passenger flow maps in metro stations

Author(s):  
Shao Bo Liu ◽  
Siu Ming Lo
Keyword(s):  
2014 ◽  
Vol 1065-1069 ◽  
pp. 3325-3328
Author(s):  
Xin Hua Zhang ◽  
Shu Hao Xu ◽  
Li Li Wu ◽  
Yin Hua Du ◽  
Zhi Jun Duan ◽  
...  

This paper, three subway lines converge site meet a change to the peak time for passenger flow analysis, with the analysis of passenger flow field physical statistics, image processing technology to guide passenger flow data, analysis of local area biggest traffic speed and density, traffic dynamics theory, the application of mathematical software Matlab, establish mathematical model.


2013 ◽  
Vol 416-417 ◽  
pp. 2033-2037
Author(s):  
Xiao Yu Ji ◽  
Jie He ◽  
Jin Hu Peng

Passenger flow is the circulating with purpose which is formed by human beings who want to achieve all kinds of trip activities through the help of various transportations. It is an important studying content in controlling the city traffic as well. As for the necessary monitoring of passenger flow, the primary condition is grasping the precise passenger flow data and mapping out an effective monitoring plan based on the facts and data. The paper first introduced the necessarily in monitoring and the appliance of usual calculating method of passenger flow. Based on this, the paper also put forward the managing and analysis of data information in the calculating methods of passenger flow monitoring, which is hoped to be helpful in the future research.


2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Kazuki Ishikawa ◽  
Daichi Nakayama

<p><strong>Abstract.</strong> In recent years, we can easily get various data of human mobility. Based on these data, there are many studies about human mobility all over the world. In Japan, Person Trip (PT) survey has been carried out once a decade after 1960s. With the use of PT data, we can grasp people’s flow, however, it is difficult to get such data in the modern era. In old Tokyo city, some traffic surveys were carried out by municipality. These data are limited, however, it is possible to figure out the people’s flow in the modern era by digitizing and making maps from historical documents of these surveys. The purpose of this study is to make and analyse streetcar passenger flow maps in old Tokyo city by using origin-destination (OD) data acquired through the survey conducted in 1930.</p><p>We used the OD flow data of the streetcar passenger acquired by old Tokyo city on Tuesday, June 10th, 1930. The study area was in the centre of present Tokyo 23 wards. Although the streetcars no longer exist except for one line at present, there were a lot of routes in the city in 1930. The streetcars were the important transportation for people living inside and outside the city.</p><p>To make OD flow map, we first made digital data of the OD matrix of the passengers from historical documents of the survey. There were about 400 stops, however, some adjacent stops were aggregated to save space of the document. Therefore, the OD matrix were 289 by 289. In addition, we created GIS data of streetcar’s network based on old maps and historical documents. The aggregated stops were created in a midpoint of original stops. After that, we made the OD flow map by using the visualizing method described by Wood, Dykes, &amp; Slingsby (2010).</p><p>Figure 1 shows OD flow map of streetcar passenger in 1930. The results of this study are summarized as follows; 1) There were many people who went to the direction of Tokyo station(E6), Nihonbashi(E7), and Ginza(F6) from the entire area of the city. These areas have been a centre of commerce since pre-modern era, being crowded with shoppers, tourists and workers. Particularly, there were many commuters around Tokyo station because it had many office buildings. 2) There were many people who used the terminal stations located outside the city. These stations such as Shinjuku(D1) and Shibuya(G1) have been nodal points of other railways in the western part of Tokyo. This result showed that the people moved to the suburb of Tokyo after the Great Kanto Earthquake in 1923. 3) The movements from the west of the city to the centre of Tokyo were longer than those from the east of the city, because the western area had the restrictive land uses such as high class residential area and military reservation which covered a vast area of the western part of the city. In contrast, the old urban area extended to the eastern part of the city since that era.</p>


2019 ◽  
Author(s):  
Alexis R Santos-Lozada

Hurricane María made landfall in Puerto Rico, in September 2017, causing economic damages and affecting the population by increasing temporarily increasing mortality and outgoing passenger flow. Because of the disruption in the migration flows, the volatility of this time series we must approach the production of population estimates, projections and forecasts carefully. Given that population estimates have been difficult to produce for Puerto Rico before Hurricane Maria and even more challenging following this disaster, this paper proposes an application of the demographic balancing equation using administrative records to produce population estimates on a monthly basis for Puerto Rico. A combination of data from: (1) monthly counts for deaths and births obtained from the Puerto Rico Vital Statistics Systems, (2) passenger flow data produced by the U.S. Bureau of Transportation Statistics, and (3) baseline census counts. I employ this approach to produce monthly estimates of the population for Puerto Rico, and use 2010 Census counts to assess the accuracy of the model. According to the 2010 decennial census, the population of Puerto Rico was 3,725,789 people; by employing the demographic balancing equation approach, the population was estimated to be 3,669,676 people in April 1, 2010. Using this model, I find that after Hurricane Maria, the population of Puerto Rico reached less than 3 million persons in December 2017 (2.97 million). The total population went back to over 3.0 million by January 2018 with an estimated population of 3.02 million people on September 2018.


Urban Studies ◽  
2018 ◽  
Vol 56 (6) ◽  
pp. 1267-1287 ◽  
Author(s):  
Haoran Yang ◽  
Martin Dijst ◽  
Patrick Witte ◽  
Hans van Ginkel ◽  
Jiao’e Wang

China’s High-Speed Railways (HSR) network is the biggest in the world, transporting large numbers of passengers by high-speed trains through urban networks. Little is known about the analytical meaning of the use of two types of flow data, namely, time schedule (transportation mode flow) and passenger flow data, to characterise the configuration of urban networks regarding the potential spatial effects of HSR networks on urban networks. In this article, we compare HSR passenger flow data with time schedule data from 2013 in China within the same analytical framework. The findings show great differences in the strength of cities and links generated using the two different types of flow data. These differences can be explained largely by the socio-economic attributes of the cities involved, such as tertiary employment, GDP per capita, the cities’ topological properties (closeness centrality) in HSR networks and institutional factors (hub status), especially for the difference in link strength. The strength of first-tier cities in China with high socio-economic performance and the HSR links connecting core cites and major cities within respective regions tends to be underestimated when using time schedule flows compared with passenger flows. When analysing the spatial structure of HSR and urban networks by means of flows, it is important for urban geographers and transportation planners to consider the meaning of the different types of data with the analytical results.


Author(s):  
Martin Ralphs ◽  
Rosemary Goodyear

This paper explores the major commuting areas within New Zealand and how commuting patterns have evolved between 1996 and 2006. It focuses primarily on the new insights that mapping and visualisation methods can bring to the analysis and understanding of complex flow data. In particular, we discuss some approaches to delineating labour market areas based on commuter inflow statistics and demonstrate the advantages that spider flow maps bring to the visualisation and understanding of commuting flows between areas. Spider flow maps are based on origin-destination information from the 2006 Census, but the paper also includes an historical perspective, examining changes in, the number and proportion of people commuting between areas and using different modes of transport used for commuting. Although our focus is on the advantages that these new methods can bring to the analysis of commuting data, some interesting findings arise. Both the number of commutes and the distance travelled by commuters has increased markedly since 1996, particularly around the largest cities of the Auckland. Wellington and Christchurch.       Labour markets centered on these cities go well beyond territorial authority boundaries and. particularly in the Auckland case, are becoming increasingly polycentric. Data visucalisation makes the exploration of these patterns much more accessible.


2019 ◽  
Vol 20 (1) ◽  
pp. 42-60 ◽  
Author(s):  
Ming Li ◽  
Linlin Wang ◽  
Jingfeng Yang ◽  
Zhenkun Zhang ◽  
Nanfeng Zhang ◽  
...  

Abstract Customized bus services are conducive to improving urban traffic and environment, and have attracted widespread attention. However, the problems encountered in the new customized bus mode include the large difference between the basis of customized bus passenger flow data analysis and the basis of the traditional bus passenger flow data analysis, and the difficulty in different vehicle scheduling caused by the combination of traditional and customized bus modes. We propose a customized bus passenger flow analysis algorithm and multi-destination customized bus line capacity scheduling algorithm, and display them in an intuitive way. The experimental results show that the algorithm model established in this paper can basically meet the data requirements of operation and management, and can provide decision support for customized bus line planning.


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