scholarly journals Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

2014 ◽  
Vol XL-1 ◽  
pp. 167-172 ◽  
Author(s):  
X. Huang ◽  
J. Tan
Keyword(s):  
Urban Areas ◽  
Weighted Graph ◽  
Human Movement ◽  
Travel Behaviour ◽  
Transportation Systems ◽  
Global Network ◽  
Mobility Patterns ◽  
Urban Dynamics ◽  
Spatio Temporal ◽  
Using Data

Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. <br><br> Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G &equiv; (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

Human Movement Analysis Using Heterogeneous Data Sources

2013 ◽  
Vol 4 (3) ◽  
pp. 98-117 ◽  
Author(s):  
João Peixoto ◽  
Adriano Moreira
Keyword(s):  
Intelligent Transportation Systems ◽  
Real Data ◽  
Human Movement ◽  
Heterogeneous Data ◽  
Transportation Systems ◽  
Temporal Data ◽  
Urban Mobility ◽  
Multiple Sources ◽  
Urban Dynamics ◽  
Spatio Temporal

The analysis of urban mobility has been attracting the interest of the research community recently. The research challenges in this domain are diverse and include data acquisition and representation, human movement modeling and the visualization of dynamic geo-referenced data. Some of the direct applications for these studies are urban planning, security, intelligent transportation systems and wireless networks optimization. One of the drivers for recent work in this area is the availability of large datasets representing many aspects of the urban dynamics. Quite often, the proposed approaches are highly dependent on the data type. However, the analysis of urban dynamics could benefit from the combined and simultaneous use of multiple sources of spatio-temporal data. This paper describes the definition of a set of basic concepts for the representation and processing of spatio-temporal data, sufficiently flexible to deal with various types of mobility data and to support multiple forms of processing and visualization of the urban mobility. For this purpose the authors define a set of concepts and describe how real data from heterogeneous sources is mapped into the proposed framework. Available results obtained by the integration of geometric and symbolic data reveal the adequacy of the proposed concepts, and uncover new possibilities for the fusion of heterogeneous datasets.

scholarly journals Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

2020 ◽  
Vol 13 (1) ◽  
pp. 112
Author(s):  
Helai Huang ◽  
Jialing Wu ◽  
Fang Liu ◽  
Yiwei Wang
Keyword(s):  
Waiting Time ◽  
Urban Areas ◽  
Transportation Systems ◽  
Trajectory Data ◽  
Peak Period ◽  
Important Indicator ◽  
Destination Attractiveness ◽  
Urban Accessibility ◽  
Spatio Temporal ◽  
Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

scholarly journals Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

2020 ◽  
Vol 12 (7) ◽  
pp. 3012 ◽  
Author(s):  
Panrawee Rungskunroch ◽  
Yuwen Yang ◽  
Sakdirat Kaewunruen
Keyword(s):  
Urban Areas ◽  
High Speed ◽  
Technical Information ◽  
Transportation Systems ◽  
Sustainable Transportation ◽  
City Development ◽  
High Speed Rail ◽  
Large Cities ◽  
Urban Dynamics ◽  
Practical Factors

At present, many countries around the world have significantly invested in sustainable transportation systems, especially for high-speed rail (HSR) infrastructures, since they are believed to improve economies, and regenerate regional and business growth. In this study, we focus on economic growth, dynamic land use, and urban mobility. The emphasis is placed on testing a hypothesis about whether HSRs can enable socio-economic development. Real case studies using big data from large cities in China, namely Shanghai province and Minhang districts, are taken into account. Socio-technical information such as employment rate, property pricing, and agglomeration in the country’s economy is collected from the China Statistics Bureau and the China Academy of Railway Sciences for analyses. This research aims to re-examine practical factors resulting from HSR’s impact on urban areas by using ANOVA analysis and dummy variable regression to analyse urban dynamics and property pricing. In addition, this study enhances the prediction outcomes that lead to urban planning strategies for the business area. The results reveal that there are various effects (i.e., regional accessibility, city development plans, and so on) required to enable the success of HSR infrastructure in order to enrich urban dynamics and land pricing. This paper also highlights critical perspectives towards sustainability, which are vital to social and economic impacts. In addition, this study provides crucial perspectives on sustainable developments for future HSR projects.

scholarly journals INVESTIGATING THE POTENTIAL OF ACTIVITY TRACKING APP DATA TO ESTIMATE CYCLE FLOWS IN URBAN AREAS

2016 ◽  
Vol XLI-B2 ◽  
pp. 515-519
Author(s):  
J. Haworth
Keyword(s):  
Temporal Variation ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Temporal Structure ◽  
Transportation Systems ◽  
Spatial And Temporal Variation ◽  
Linear Regression Models ◽  
Activity Tracking ◽  
Spatio Temporal ◽  
On The Road

Traffic congestion and its associated environmental effects pose a significant problem for large cities. Consequently, promoting and investing in green travel modes such as cycling is high on the agenda for many transport authorities. In order to target investment in cycling infrastructure and improve the experience of cyclists on the road, it is important to know where they are. Unfortunately, investment in intelligent transportation systems over the years has mainly focussed on monitoring vehicular traffic, and comparatively little is known about where cyclists are on a day to day basis. In London, for example, there are a limited number of automatic cycle counters installed on the network, which provide only part of the picture. These are supplemented by surveys that are carried out infrequently. Activity tracking apps on smart phones and GPS devices such as Strava have become very popular over recent years. Their intended use is to track physical activity and monitor training. However, many people routinely use such apps to record their daily commutes by bicycle. At the aggregate level, these data provide a potentially rich source of information about the movement and behaviour of cyclists. Before such data can be relied upon, however, it is necessary to examine their representativeness and understand their potential biases. In this study, the flows obtained from Strava Metro (SM) are compared with those obtained during the 2013 London Cycle Census (LCC). A set of linear regression models are constructed to predict LCC flows using SM flows along with a number of dummy variables including road type, hour of day, day of week and presence/absence of cycle lane. Cross-validation is used to test the fitted models on unseen LCC sites. SM flows are found to be a statistically significant (p&lt;0.0001) predictor of total flows as measured by the LCC and the models yield R squared statistics of ~0.7 before considering spatio-temporal variation. The initial results indicate that data collected using fitness tracking apps such as Strava are a promising data source for traffic managers. Future work will incorporate the spatio-temporal structure in the data to better account for the spatial and temporal variation in the ratio of SM flows to LCC flows.

scholarly journals Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies

2020 ◽  
Author(s):  
Miguel Ribeiro ◽  
Nuno Nunes ◽  
Valentina Nisi ◽  
Johannes Schöning
Keyword(s):  
Public Transportation ◽  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Tracking System ◽  
Human Mobility ◽  
Transportation Systems ◽  
Mobility Patterns ◽  
Systematic Analysis ◽  
Long Term Study

Abstract In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people’s mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.

The Complex Properties of Chinese Ship-Transport Networks

2014 ◽  
Vol 556-562 ◽  
pp. 6483-6486 ◽  
Author(s):  
Di Cui
Keyword(s):  
Transportation Systems ◽  
Gravity Models ◽  
Global Network ◽  
Mobility Patterns ◽  
Transport Networks ◽  
Heavy Tailed Distribution ◽  
Heavy Tailed ◽  
Chinese Trade ◽  
Definition Of ◽  
Oil Tankers

Transportation systems are of great importance to the development of a country and are important indicators of its economic growth With 30 per cent of Chinese trade carried by sea and with 90 percent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 187260 ships during the year 2010 to construct a network of links between ports. The network has several features that set it apart from other transportation networks are shown. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil &LNG gas tankers. These three categories do not only differ in the ships’ physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analyzed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade. We also study the traffic flow of Chinese ship-transport networks (CSTN) based on the weighted network representation, and demonstrate the weight distribution can be described by power-law or exponential function depending on the assumed definition of network topology. Other features related to Chinese ship-transport networks (CSTN) are also investigated.

scholarly journals TRAVEL BEHAVIOUR IN SAUDI ARABIA AND THE ROLE OF SOCIAL FACTORS

Transport ◽  
2014 ◽  
Vol 29 (3) ◽  
pp. 269-277 ◽  
Author(s):  
Attiyah Al-Atawi ◽  
Wafaa Saleh
Keyword(s):  
Saudi Arabia ◽  
Social Factors ◽  
Urban Areas ◽  
Waiting Times ◽  
Travel Behaviour ◽  
Discrete Choice Models ◽  
Transportation Systems ◽  
Transport Systems ◽  
The Social ◽  
Travel Decisions

Travel behaviour research indicates that travel decisions are usually influenced by accessibility as well as characteristics of the transport systems. Factors such as travel times, travel costs, waiting times, walking times have the most significant contributions in mode choice and travel decisions. In the case of developing countries however, the most influencing factors for travel behaviour and decisions are the social factors. This is very important for transport modellers and decision makers to realise in order to achieve appropriate design and implementations of various transport policies. The influence of social and economic factors on travel behaviour are discussed and investigated in this paper. In Saudi Arabia, a randomly selected sample of 1220 households was interviewed in the Tabuk city of the Saudi Arabia and data on their socio-economic and trip-making behaviour was obtained. The relative impact of socioeconomic variables on household travel behaviour was discussed and discrete choice models were calibrated. These types of studies can be useful in the development of plans, programs and policies for the improvement of transportation systems in urban areas of the Saudi Arabia and other similar countries in the region. The findings show that the social factors have the most important impact on travel behaviour in Saudi Arabia.

scholarly journals Understanding the Heterogeneity of Human Mobility Patterns: User Characteristics and Modal Preferences

2021 ◽  
Vol 13 (24) ◽  
pp. 13921
Author(s):  
Laiyun Wu ◽  
Samiul Hasan ◽  
Younshik Chung ◽  
Jee Eun Kang
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Mobility Models ◽  
Mobility Patterns ◽  
User Characteristics ◽  
Transit System ◽  
Demographic Groups ◽  
Urban Dynamics ◽  
User Groups ◽  
Spatio Temporal

Characterizing individual mobility is critical to understand urban dynamics and to develop high-resolution mobility models. Previously, large-scale trajectory datasets have been used to characterize universal mobility patterns. However, due to the limitations of the underlying datasets, these studies could not investigate how mobility patterns differ over user characteristics among demographic groups. In this study, we analyzed a large-scale Automatic Fare Collection (AFC) dataset of the transit system of Seoul, South Korea and investigated how mobility patterns vary over user characteristics and modal preferences. We identified users’ commuting locations and estimated the statistical distributions required to characterize their spatio-temporal mobility patterns. Our findings show the heterogeneity of mobility patterns across demographic user groups. This result will significantly impact future mobility models based on trajectory datasets.

scholarly journals To fear or not to fear? Exploring the temporality of topophobia in urban environments

2020 ◽  
Vol 28 (4) ◽  
pp. 308-321
Author(s):  
Petr Šimáček ◽  
Miloslav Šerý ◽  
David Fiedor ◽  
Lucia Brisudová
Keyword(s):  
Urban Areas ◽  
Fear Of Crime ◽  
Urban Environments ◽  
Temporal Dimension ◽  
Empirical Survey ◽  
Mental Mapping ◽  
Local Decision ◽  
Spatio Temporal ◽  
Using Data ◽  
Over Time

AbstractThe concept of topophobia has been known in Geography for decades. Places which evoke fear in people’s minds can be found in almost every city. The perception of fear within an urban environment shows a certain spatio-temporal concentration and is often represented by fear of crime. The meaning of topophobic places, however, derived from the experience of fear of crime changes over time, and thus can alter the usual patterns of population behaviours in relation to time (in the time of the day and over longer periods) and space. A spatiotemporal understanding of these changes is therefore crucial for local decision-makers. Using data from the Czech Republic, this paper deals with the analysis of topophobic places, and is based on an empirical survey of the inhabitants of four cities, using the concept of mental mapping. In contrast to most similar geographical studies, the paper emphasises the temporal dimension of the fear of crime. The results have shown that over time there are significant differences in the meanings of topophobic places, and they have demonstrated the necessity of taking local specifics into account. The paper shows how the intensity of and the reasons for fears vary, depending on time and place. In general, the results provide support for the idea of place as a process and contain useful information for spatial planning and policy in urban areas.

scholarly journals Connectivity Between Pedestrian Ways and BRT Shelter in Banyumanik and Pedurungan, Semarang

2018 ◽  
Vol 20 (2) ◽  
pp. 56-64
Author(s):  
Diah Intan Dewi ◽  
Anita Ratnasari Rakhmatulloh
Keyword(s):  
Urban Areas ◽  
Human Movement ◽  
Transportation Systems ◽  
City Government ◽  
The Other ◽  
High Rate ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Gis Applications ◽  
Pedestrian Networks

The increasing number of human activities from sub urban areas causes high movements in urban areas. The high rate of human movement drives the need for human circulation pathways and adequate transportation systems. To solve this problem, the Semarang City government has actually built transportation facilities in the form of BRT (Bus Rapid Transit) along with pedestrian ways. However, in reality the pedestrian ways that acts as a link to the door to door service is not well connected so it is less secure and comfortable and unable to accommodate the needs of the urban community. The purpose of this study was to examine the connectivity between pedestrian networks and BRT shelter in Semarang. The method of analysis in this study used GIS applications to evaluate access pedestrian connectivity to BRT shelther in Banyumanik and Pedurungan, Semarang. The results of the study are the connectivity between pedestrian ways and BRT shelter  in Banyumanik is good on the other side the connectivity in Pedurungan is not good and optimally configured

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