scholarly journals Public Transport GPS Probe and Rail Gate Data for Assessing the Pattern of Human Mobility in the Bangkok Metropolitan Region, Thailand

2021 ◽  
Vol 13 (4) ◽  
pp. 2178
Author(s):  
Songkorn Siangsuebchart ◽  
Sarawut Ninsawat ◽  
Apichon Witayangkurn ◽  
Surachet Pravinvongvuth
Keyword(s):  
Performance Assessment ◽  
Public Transport ◽  
Human Mobility ◽  
Open Data ◽  
Capital City ◽  
Metropolitan Region ◽  
Traffic Information ◽  
Mobility Patterns ◽  
Transport Planning ◽  
Java Program

Bangkok, the capital city of Thailand, is one of the most developed and expansive cities. Due to the ongoing development and expansion of Bangkok, urbanization has continued to expand into adjacent provinces, creating the Bangkok Metropolitan Region (BMR). Continuous monitoring of human mobility in BMR aids in public transport planning and design, and efficient performance assessment. The purpose of this study is to design and develop a process to derive human mobility patterns from the real movement of people who use both fixed-route and non-fixed-route public transport modes, including taxis, vans, and electric rail. Taxi GPS open data were collected by the Intelligent Traffic Information Center Foundation (iTIC) from all GPS-equipped taxis of one operator in BMR. GPS probe data of all operating GPS-equipped vans were collected by the Ministry of Transport’s Department of Land Transport for daily speed and driving behavior monitoring. Finally, the ridership data of all electric rail lines were collected from smartcards by the Automated Fare Collection (AFC). None of the previous works on human mobility extraction from multi-sourced big data have used van data; therefore, it is a challenge to use this data with other sources in the study of human mobility. Each public transport mode has traveling characteristics unique to its passengers and, therefore, specific analytical tools. Firstly, the taxi trip extraction process was developed using Hadoop Hive to process a large quantity of data spanning a one-month period to derive the origin and destination (OD) of each trip. Secondly, for van data, a Java program was used to construct the ODs of van trips. Thirdly, another Java program was used to create the ODs of the electric rail lines. All OD locations of these three modes were aggregated into transportation analysis zones (TAZ). The major taxi trip destinations were found to be international airports and provincial bus terminals. The significant trip destinations of vans were provincial bus terminals in Bangkok, electric rail stations, and the industrial estates in other provinces of BMR. In contrast, electric rail destinations were electric rail line interchange stations, the central business district (CBD), and commercial office areas. Therefore, these significant destinations of taxis and vans should be considered in electric rail planning to reduce the air pollution from gasoline vehicles (taxis and vans). Using the designed procedures, the up-to-date dataset of public transport can be processed to derive a time series of human mobility as an input into continuous and sustainable public transport planning and performance assessment. Based on the results of the study, the procedures can benefit other cities in Thailand and other countries.

scholarly journals Gender-Responsive Public Transportation in the Dammam Metropolitan Region, Saudi Arabia

2020 ◽  
Vol 12 (21) ◽  
pp. 9068 ◽  
Author(s):  
Muhammad Ahmad Al-Rashid ◽  
Kh Md Nahiduzzaman ◽  
Sohel Ahmed ◽  
Tiziana Campisi ◽  
Nurten Akgün
Keyword(s):  
Saudi Arabia ◽  
Interior Design ◽  
Public Transport ◽  
Public Transportation ◽  
Metropolitan Region ◽  
Future Research ◽  
Mobility Patterns ◽  
Structured Interviews ◽  
Sustainable Mobility ◽  
Study Results

The limited availability of public transportation in Saudi Arabia leads to an increased demand for private vehicles. An increase in using private cars does not meet the global sustainability goals, e.g., reducing energy consumption and improving the air quality. Road users should be encouraged to use sustainable mobility modes, particularly public transportation, equally accessible to both men and women However, women’s mobility has been somewhat limited and challenged in spatio-temporal terms, and partly due to socio-cultural barriers. This study attempts to understand the gender experience of a sample of public transport users and consider their aspirations and needs into daily mobility. A survey campaign (structured interviews and online questionnaires) was launched in the Dammam Metropolitan Region (DMR), taking four different types of respondents into account. The results suggest a predominant preference for taxis for shopping and leisure activities due to a poor public transport service, pivotally characterized by limited operational routes, hours, and infrastructure. This study ponders upon the adequacy of the supporting infrastructures and interior design of the public buses to women’s needs and compare them with global best practices. The results suggest that, due to the absence of a gender-responsive design and infrastructure, women are forced to use taxis, although privacy and a sense of insecurity often become concerns when traveling alone or with children. The study results allow future research to be expanded, considering women’s mobility patterns, needs, and embedded barriers by comparing the results with current transport policies, plans, and practices.

scholarly journals Exploring the Roles of Local Mobility Patterns, Socioeconomic Conditions, and Lockdown Policies in Shaping the Patterns of COVID-19 Spread

2021 ◽  
Vol 13 (5) ◽  
pp. 112
Author(s):  
Mauricio Herrera ◽  
Alex Godoy-Faúndez
Keyword(s):  
Latin American ◽  
Low Income ◽  
Large Scale ◽  
Human Mobility ◽  
Epidemiological Data ◽  
High Income ◽  
Metropolitan Region ◽  
Mobility Patterns ◽  
Large Cities

The COVID-19 crisis has shown that we can only prevent the risk of mass contagion through timely, large-scale, coordinated, and decisive actions. This pandemic has also highlighted the critical importance of generating rigorous evidence for decision-making, and actionable insights from data, considering further the intricate web of causes and drivers behind observed patterns of contagion diffusion. Using mobility, socioeconomic, and epidemiological data recorded throughout the pandemic development in the Santiago Metropolitan Region, we seek to understand the observed patterns of contagion. We characterize human mobility patterns during the pandemic through different mobility indices and correlate such patterns with the observed contagion diffusion, providing data-driven models for insights, analysis, and inferences. Through these models, we examine some effects of the late application of mobility restrictions in high-income urban regions that were affected by high contagion rates at the beginning of the pandemic. Using augmented synthesis control methods, we study the consequences of the early lifting of mobility restrictions in low-income sectors connected by public transport to high-risk and high-income communes. The Santiago Metropolitan Region is one of the largest Latin American metropolises with features that are common to large cities. Therefore, it can be used as a relevant case study to unravel complex patterns of the spread of COVID-19.

Discovery of Public Transportation Patterns Through the Use of Big Data Technologies for Urban Mobility

2019 ◽  
Author(s):  
Hugo Antunes ◽  
Paulo Figueiras ◽  
Ruben Costa ◽  
Joel Teixeira ◽  
Ricardo Jardim-Gonçalves
Keyword(s):  
Big Data ◽  
Public Transport ◽  
Public Transportation ◽  
Urban Areas ◽  
Human Mobility ◽  
Transportation Network ◽  
Transport Network ◽  
Special Focus ◽  
Mobility Patterns ◽  
Big Data Technologies

Abstract Big cities show a wide public transport network that allows people to travel within the cities. However, with the overcrowding of big urban areas, the demand for new mobility strategies has increasing. Every day, citizens need to commute fast, easily and comfortable, which is not always easy due to the complexity of the public transport network. Therefore, this paper aims to explore the ability of Big Data technologies to cope with data collected from public transportation, by inferring automatically and continuously, complex mobility patterns about human mobility, in the form of insightful indicators (such as connections, transshipments or pendular movements), creating a new perspective in public transports data analytics. With special focus on the Lisbon public transport network, the challenge addressed by this work, is to analyze the demand and supply side of transportation network of Lisbon metropolitan area, considering ticketing data provided by the different transportation operators, which until now were essentially obtained through observation methods and surveys.

scholarly journals Mobility Patterns and Mode Choice Preferences during the COVID-19 Situation

2022 ◽  
Vol 14 (2) ◽  
pp. 768
Author(s):  
Hector Monterde-i-Bort ◽  
Matus Sucha ◽  
Ralf Risser ◽  
Tatiana Kochetova
Keyword(s):  
Public Transport ◽  
Human Mobility ◽  
Mode Choice ◽  
Blind Spot ◽  
Significant Shift ◽  
Shared Services ◽  
Mobility Patterns ◽  
Two Phases ◽  
Reduced Mobility ◽  
The Impact

The empirical research on the COVID-19 epidemic’s consequences suggests a major drop in human mobility and a significant shift in travel patterns across all forms of transportation. We can observe a shift from public transport and an increase in car use, and in some cases also increase of cycling and (less often) walking. Furthermore, it seems that micromobility and, more generally, environmentally friendly and comanaged mobility (including shared services), are gaining ground. In previous research, much attention was paid to the mode choice preferences during lockdown, or early stages of the SARS-CoV-2 situation. The blind spot, and aim of this work, is how long observed changes in mode choice last and when or if we can expect the mode choice to shift back to the situation before the SARS-CoV-2 episodes. The research sample consisted of 636 cases; in total, 10 countries contributed to the sample examined in this study. The data were collected in two phases: the first in the spring of 2020 and the second in the fall of the same year. Results showed that respondents reduced mobility by car, local public transport and walking, but not bicycling during the lockdown, compared to the time before the pandemic started. When the easing came, respondents assessed their own use of the car and walking as almost back to normal. They also reported an increase in the use of public transport, but not reaching the level prior the pandemic by far. It seems that cycling was affected least by the pandemic; use of a bicycle hardly changed at all. As for the implication of our study, it is evident that special attention and actions will be needed to bring citizens back to public transport, as it seems that the impact of the pandemic on public transport use will last much longer than the pandemic itself.

scholarly journals Implementation of the Integrated TOD Spatial Model for Jakarta Metropolitan Region

2019 ◽  
Author(s):  
H M Taki ◽  
M M H Maatouk ◽  
F Ahmadi
Keyword(s):  
Urban Planning ◽  
Public Transport ◽  
Urban Areas ◽  
Spatial Model ◽  
Metropolitan Region ◽  
Transit Oriented Development ◽  
Transport Planning ◽  
Railway Stations

Jakarta Metropolitan Region (JMR) is the biggest megacity urban areas in Indonesia. However,theexistingpublictransportfacilitiesarenotadequatelyfulfillingthedemand ofitsinhabitant.Therefore,itisimportantforovercomingthoseissueswithshedlighton the integration of spatial and transportation by applying Transit Oriented Development (TOD) model. The method of this paper using the spatial and transportation approach by differentiates TOD each railway stations based on the typology. The results were that the TOD spatial model is focusing on solving public transport issues related to urban planning. Therefore, certain policy from stakeholders for this region greatly encourages transport planning in a more sustainable manner.

scholarly journals Understanding senior's daily mobility patterns in California using human mobility motifs

2021 ◽  
Vol 94 ◽  
pp. 103117
Author(s):  
Rongxiang Su ◽  
Jingyi Xiao ◽  
Elizabeth C. McBride ◽  
Konstadinos G. Goulias
Keyword(s):  
Human Mobility ◽  
Mobility Patterns ◽  
Daily Mobility

scholarly journals A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexandru Topîrceanu ◽  
Radu-Emil Precup
Keyword(s):  
Computational Models ◽  
Human Mobility ◽  
Discrete Event ◽  
Mobility Model ◽  
Hierarchical Organization ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Fine Grained ◽  
Epidemic Size ◽  
Control Of Epidemics

AbstractComputational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheless, a large proportion of recent studies, aimed at better understanding global epidemics, like influenza, measles, H1N1, SARS, and COVID-19, underestimate the role of heterogeneous mixing in populations, characterized by strong social structures and geography. Motivated by the reduced tractability of studies employing homogeneous mixing, which make conclusions hard to deduce, we propose a new, very fine-grained model incorporating the spatial distribution of population into geographical settlements, with a hierarchical organization down to the level of households (inside which we assume homogeneous mixing). In addition, population is organized heterogeneously outside households, and we model the movement of individuals using travel distance and frequency parameters for inter- and intra-settlement movement. Discrete event simulation, employing an adapted SIR model with relapse, reproduces important qualitative characteristics of real epidemics, like high variation in size and temporal heterogeneity (e.g., waves), that are challenging to reproduce and to quantify with existing measures. Our results pinpoint an important aspect, that epidemic size is more sensitive to the increase in distance of travel, rather that the frequency of travel. Finally, we discuss implications for the control of epidemics by integrating human mobility restrictions, as well as progressive vaccination of individuals.

scholarly journals Mobility Patterns in Different Age Groups in Japan during the COVID-19 Pandemic: a Small Area Time Series Analysis through March 2021

2021 ◽  
Author(s):  
Shuhei Nomura ◽  
Yuta Tanoue ◽  
Daisuke Yoneoka ◽  
Stuart Gilmour ◽  
Takayuki Kawashima ◽  
...  
Keyword(s):  
Care Delivery ◽  
Human Mobility ◽  
Age Groups ◽  
Virus Transmission ◽  
Initial Response ◽  
Health Care Delivery System ◽  
Population Characteristics ◽  
Mobility Patterns ◽  
Mobility Data ◽  
The Status

AbstractIn the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan—each defined as an area overlaid by several 125-meter grids—from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.

scholarly journals Interstates of Infection: Preliminary Investigations of Human Mobility Patterns in the COVID‐19 Pandemic

2021 ◽  
Vol 37 (2) ◽  
pp. 266-271
Author(s):  
Jacob M. Souch ◽  
Jeralynn S. Cossman ◽  
Mark D. Hayward
Keyword(s):  
Human Mobility ◽  
Mobility Patterns

scholarly journals Gender Inequality in Safety and Security Perceptions in Railway Stations

2021 ◽  
Vol 13 (7) ◽  
pp. 4007
Author(s):  
Pierluigi Coppola ◽  
Fulvio Silvestri
Keyword(s):  
Gender Gap ◽  
Public Transport ◽  
Stated Preference ◽  
Revealed Preference ◽  
Behavioral Models ◽  
Mobility Patterns ◽  
Railway Stations ◽  
Commercial Activities ◽  
Transport Services ◽  
Disaggregate Data

Recent studies have shown that gender is the personal aspect that mostly affects mobility patterns and travel behaviors. It has been observed, for instance, that female perception of unsafety and insecurity when traveling using public transport forces them to make unwanted travel choices, such as avoiding traveling at certain times of day and to specific destinations. In order to improve the attractiveness of public transport services, this gender gap must not be overlooked. This paper aims at contributing to research in gendered mobility by investigating differences in safety and security perceptions in railway stations, and by identifying which policies could be effective in bridging any existing gap. The methodology includes the collection of disaggregate data through a mixed Revealed Preference/Stated Preference survey, and the estimation of fixed and random parameters behavioral models. Results from a medium-sized Italian railway station show that female travelers feel safer in the presence of other people; they prefer intermodal infrastructures close to the entrance of the station and commercial activities in the internal premises. Moreover, unlike male travelers, they do not appreciate the presence of hedges and greenery outside stations.

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