Urban Mobility Networks Research Articles

Unveiling the rich-club phenomenon in urban mobility networks through the spatiotemporal characteristics of passenger flow

With increasing passenger flows and rapid urbanization, the Mass Transit Railway (MTR) systems in Hong Kong have entered into an era of complex networking operation, which enables people to travel across 18 local districts and enhance sustainable transport accessibility. The urban mobility flow patterns typically encoded as origin–destination (OD) matrices inspire the constitution of the temporal urban mobility networks (TUMNs), which are represented as the directed weighted networks. The dynamics of the TUMNs have significant implications for transportation systems, urban traffic planning, and mobility pattern exploration. This paper provides a thorough analysis of the rich-club phenomenon of TUMNs in Hong Kong during different time periods. Additionally, the space–time characteristics of passenger flow are analyzed and based on which we build the directed weighted TUMNs where the nodes are the stations, and the weighted links represent the number of trips between nodes. By using the outgoing-strength and incoming-strength global rich-club coefficient, local rich-club coefficient, community detection, and assortativity coefficient, we quantitatively identify the rich-club phenomenon in the TUMNs during both the peak hours (8:00–9:00 and 18:00–19:00) and non-peak hours (10:00–11:00, 15:00–16:00, and 20:00–21:00). The findings uncover the rich-club phenomenon in the TUMNs, and the distribution of the rich-club members evolving over time. The findings of this research pave the way towards a richer spectrum of complex real-world networks and are useful for transport infrastructure planning.

Topological indexes and community structure for urban mobility networks: Variations in a business day.

Topological analysis and community detection in mobility complex networks have an essential role in many contexts, from economics to the environmental agenda. However, in many cases, the dynamic component of mobility data is not considered directly. In this paper, we study how topological indexes and community structure changes in a business day. For the analyzes, we use a mobility database with a high temporal resolution. Our case study is the city of São José dos Campos (Brazil)—the city is divided into 55 traffic zones. More than 20 thousand people were asked about their travels the day before the survey (Origin-Destination Survey). We generated a set of graphs, where each vertex represents a traffic zone, and the edges are weighted by the number of trips between them, restricted to a time window. We calculated topological properties, such as degree, clustering coefficient and diameter, and the network’s community structure. The results show spatially concise community structures related to geographical factors such as highways and the persistence of some communities for different timestamps. These analyses may support the definition and adjustment of public policies to improve urban mobility. For instance, the community structure of the network might be useful for defining inter-zone public transportation.

Resolving urban mobility networks from individual travel graphs using massive-scale mobile phone tracking data

Human movements and interactions with cities are characterized by urban mobility networks. Many studies that address urban mobility are inspired by complex networks. The models of complex networks require a large amount of empirical data. However, current works relied on traditional survey data and were unable to take full advantage of the capabilities offered by complex networks; thus, the possibility of quantifying urban mobility networks by considering individual travel patterns has not yet been addressed. This study presents a data-driven approach for characterizing urban mobility networks based on massive-scale mobile phone tracking data. Individual travel motifs are first extracted using a graph-based approach. The global urban mobility network (G-UMN) and the motif-dependent urban mobility subnetworks (MD-UMNs) are then constructed. Next, network properties, including statistical measures and scaling relations between the basic measures, are proposed for characterizing mobility networks. We have conducted experiments focusing on Shenzhen, China. The results demonstrated that (1) the individual travel motifs are structurally and spatially heterogeneous, (2) the G-UMN exhibits a evolutionary hierarchical structure, and (3) the MD-UMNs show many behavioral differences in their spatial and topological properties, reflecting the impacts of the heterogeneity of the individual travel motifs. These results bridge the gap between complex network properties and urban mobility patterns and provide crucial implications and policies for data-informed urban planning.

Mobility, energy, environment and disruptive innovation: Challenges, opportunities and perspective for new sustainable integrated approaches to planning

The transport sector represents approximately 30% of the final energy consumption in the Eu-ropean Union. Cars, trucks and light vehicles are responsible for 70% of the final energy con-sumed in the transport sector (source: Eurostat). The process of decarbonisation of mobility is represented by a combination of technological, behavioural and policy dynamics to be effec-tively fostered and combined in order to maximise their impact. The introduction provides a review of the main mobility and energy integrated planning ap-proaches represented by Sustainable Urban Mobility Plans (SUMPs) and Sustainable Energy and Climate Action Plans (SECAPs), as well as a brief overview of the expected impacts of disruptive innovation and their inclusion in the revised approach towards mobility planning in Europe. This picture provides the framework for the presentation of the papers selected for the 2020 EPEE special issue on sustainable mobility, and their contribution to the progress of economic research to increase the knowledge of innovation trends that strongly influence the evolution of urban mobility networks.

Ranking places in attributed temporal urban mobility networks.

Drawing on the recent advances in complex network theory, urban mobility flow patterns, typically encoded as origin-destination (OD) matrices, can be represented as weighted directed graphs, with nodes denoting city locations and weighted edges the number of trips between them. Such a graph can further be augmented by node attributes denoting the various socio-economic characteristics at a particular location in the city. In this paper, we study the spatio-temporal characteristics of “hotspots” of different types of socio-economic activities as characterized by recently developed attribute-augmented network centrality measures within the urban OD network. The workflow of the proposed paper comprises the construction of temporal OD networks using two custom data sets on urban mobility in Rome and London, the addition of socio-economic activity attributes to the OD network nodes, the computation of network centrality measures, the identification of “hotspots” and, finally, the visualization and analysis of measures of their spatio-temporal heterogeneity. Our results show structural similarities and distinctions between the spatial patterns of different types of human activity in the two cities. Our approach produces simple indicators thus opening up opportunities for practitioners to develop tools for real-time monitoring and visualization of interactions between mobility and economic activity in cities.

Long-term application potential of urban air mobility complementing public transport: an upper Bavaria example.

In this paper, the required models and methods to analyze and quantify the potential demand for urban air mobility (UAM) complementing public transport and possible impacts were defined and applied to the Munich Metropolitan region. An existing agent-based transport model of the study area were used and extended to cover socio-demographic changes up to the year 2030 and intermodal UAM services. An incremental logit model for UAM was derived to simulate demand for this new mode. An airport access model was developed as well. Three different UAM networks with different numbers of vertiports were defined. Sensitivity studies of ticket fare and structure, flying vehicle cruise speed, passenger process times at vertiports and different Urban Air Mobility networks sizes were performed. For the reference case, UAM accounts for a modal share of 0.5%. The absolute UAM demand is concentrated on very short routes; hence, UAM vehicle flight speed variation shows low UAM demand impacts. Kilometer-based fare, number of UAM vehicles per vertiport and passenger process times at vertiports show a significant impact on UAM demand.

Distributed Dynamic Backhauling in Aerial Heterogeneous Networks

Congestion management of urban mobile network under heavy capacity and coverage demand by the moving dense users has become a denotable challenge to the Network Service Providers (NSPs). We have previously termed the ‘capacity in motion’ demand as the Place Time Capacity (PTC) problem and to address this problem, we have proposed the concept of Hovering Ad-Hoc Network (HANET) as a deployment of a fleet of airborne mobile tower vehicles to follow and serve the moving users was proposed. With aerial vehicles in a heterogeneous network environment, backhauling the heavy user data might be a problem. In this paper, we attempt to introduce the concept of Distributed Dynamic Backhauling for the Aerial Architecture (DDBAA) and analyse a situation of HANET serving PTC. We investigate the performance of the network served by the HANET, wherein every aerial device is following an intelligent backhaul mechanism to offload the heavy user data. This paper, lastly, concludes by discussing the observed results and indicating the future research work.

Unveiling socioeconomic differences in colombia by means of urban mobility complex networks

Social stratification lead to marked differences between people in several aspects of their lives, such as income, education, work, welfare and mobility. Here, we aim to analyze urban mobility by socioeconomic differences of travelers. In order to do so, we represent urban mobility by a complex network approach. We show that the topological properties of the networks allow to characterize mobility flows and to recognize differences in the dynamics of socioeconomic strata. We use data from origin destination surveys made for the two most populated cities in Colombia and we represent it in the form of a weighted and directed network. We found that urban mobility networks have structural differences if analyzed by socioeconomic strata of the population and unveil segregation patterns in the highest and lowest income strata.

A Mathematical Framework to Evaluate Flexible Outdoor User Association in Urban Two-Tier Cellular Networks

In this paper, we present a mathematical framework to evaluate the performance of a typical outdoor user in an urban two-tier mobile network under a biased user association. The urban environment is abstracted by a Boolean scheme of blockages, which affects the deployment of outdoor base stations (BSs) and indoor small cell BSs, and the signal propagation characteristics of the wireless channels. A building is served by an indoor small cell BS with a certain probability, which we denote as occupation probability. Employing tools from stochastic geometry, we derive mathematical expressions for the coverage probability and the average spectral efficiency of a typical outdoor user. Numerical evaluations are carried out with the third generation partnership project compliant outdoor BS scenarios. Our results show that the increasing blockage density has a negative impact on the spectral efficiency in sparse outdoor BSs scenarios, but it has a positive impact on the performance of the network in dense outdoor BSs scenarios. We build our analysis on several assumptions, which are verified by extensive Monte Carlo simulations.

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

This paper proposes a novel approach to identify the pockets of activity or the community structure in a city network using multi-layer graphs that represent the movement of disparate entities (i.e. private cars, buses and passengers) in the network. First, we process the trip data corresponding to each entity through a Voronoi segmentation procedure which provides a natural null model to compare multiple layers in a real world network. Second, given nodes that represent Voronoi cells and link weights that define the strength of connection between them, we apply a community detection algorithm and partition the network into smaller areas independently at each layer. The partitioning algorithm returns geographically well connected regions in all layers and reveal significant characteristics underlying the spatial structure of our city. Third, we test an algorithm that reveals the unified community structure of multi-layer networks, which are combinations of single-layer networks coupled through links between each node in one network layer to itself in other layers. This approach allows us to directly compare the resulting communities in multiple layers where connection types are categorically different.

Learning from co-housing initiatives: Between Passivhaus engineers and active inhabitants

Following the UN world summits on Climate Change (Paris 2015) and Habitat (Quito 2016), most European cities assume an active role to implement internationally agreed goals related to climate change, translated in the so-called New Urban Agenda. At the same time, the urban housing market is increasingly inaccessible for low- and middle-income households. To overcome problems such as failing housing supply and high energy-bills, groups of residents take initiatives to create and manage housing projects collectively; these initiatives are further indicated as ‘co-housing’. The aim of this study is to create deeper understanding of the current rise of co-housing in Europe, and what it could mean in urban policies addressing energy transition and climate change. There are two domains where co-housing can become an important asset for urban development: design and maintenance of (semi-)public space for climate change mitigation, and the transition to a circular metabolism in housing. Based on empirical data, this thesis concludes that co-housing projects present relevant models and approaches for reducing the energy consumption and for integrating renewable energies in the general housing stock. Engineers can learn from co-housing pioneers to advance the targets for energy-transition and further develop sustainable cities. The thesis contributes to the emerging body of knowledge with a new understanding of co-housing, analysing its ‘key-features’ with an interdisciplinary framework, in a European context. It adds a new perspective to existing co-housing research, which is dominated by social sciences, by drawing attention to the physical characteristics of co-housing, produced in architectural, planning and engineering processes (the technosphere). The choices made during design and building are not only shaped by the residents’ aims and perception of sustainability, but also influenced by technosphere-related institutions, such as the building-components industry, energy or waste networks and providers, and planning regulations. The professional partners for the projects, such as housing associations and engineers, are equally affected by the institutional context, but their position is different from that of residents. They may for example be more anchored in governmental or professional regulations. To structure this dynamic, the research distinguishes three interrelated aspects: ACTORS / involved in the (realisation of) projects: social practices of residents and their professional partners in co-creation. CONTEXT / the structural forces surrounding the projects, specifically the macroinstitutional regimes. This also includes culturally determined interpretations of sustainability, technology, participation, societal roles, sharing, and so on. TECHNOSPHERE / specifically building technology and utilities, focussing on energyrelated design and engineering of the co-housing projects. The thesis is primarily based on qualitative methods, as it found that reliable quantitative data are as yet unavailable. Looking for effective low-impact energysolution in co-housing, quantitative data remain however necessary and this thesis elaborates on pitfalls and possibilities for their accumulation. Empirical material from Dutch case-studies form the core of the research. Examples were also taken from countries where the re-emergence of co-housing is most visible and articulate: Belgium, France, Germany, the UK and Switzerland. Co-housing continues to develop and gain experiences with competences, such as communication skills and the ability to work cross-disciplinarily. The building industry and engineering professions increasingly call for such capabilities, but resident-led urban development have not yet entered the urbanism and engineering curricula. Therefore, opportunities should be provided for future professionals not only to acquire such capabilities but also to address fundamental questions related to residentinvolvement and democracy. This will enable future professionals to create a balance between ‘bottom-up’ articulated needs on the quality of living environments with large-scale investments in new urban energy, mobility and mutual care networks.

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

Abstract This paper proposes a novel approach to identify the pockets of activity or the community structure in a city network using multi-layer graphs that represent the movement of disparate entities (i.e. private cars, buses and passengers) in the network. First, we process the trip data corresponding to each entity through a Voronoi segmentation procedure which provides a natural null model to compare multiple layers in a real world network. Second, given nodes that represent Voronoi cells and link weights that define the strength of connection between them, we apply a community detection algorithm and partition the network into smaller areas independently at each layer. The partitioning algorithm returns geographically well connected regions in all layers and reveal significant characteristics underlying the spatial structure of our city. Third, we test an algorithm that reveals the unified community structure of multi-layer networks, which are combinations of single-layer networks coupled through links between each node in one network layer to itself in other layers. This approach allows us to directly compare the resulting communities in multiple layers where connection types are categorically different.

Learning from co-housing initiatives — Between Passivhaus engineers and active inhabitants

Following the UN world summits on Climate Change (Paris 2015) and Habitat (Quito 2016), most European cities assume an active role to implement internationally agreed goals related to climate change, translated in the so-called New Urban Agenda. At the same time, the urban housing market is increasingly inaccessible for low- and middle-income households. To overcome problems such as failing housing supply and high energy-bills, groups of residents take initiatives to create and manage housing projects collectively; these initiatives are further indicated as ‘co-housing’. The aim of this study is to create deeper understanding of the current rise of co-housing in Europe, and what it could mean in urban policies addressing energy transition and climate change. There are two domains where co-housing can become an important asset for urban development: design and maintenance of (semi-)public space for climate change mitigation, and the transition to a circular metabolism in housing. Based on empirical data, this thesis concludes that co-housing projects present relevant models and approaches for reducing the energy consumption and for integrating renewable energies in the general housing stock. Engineers can learn from co-housing pioneers to advance the targets for energy-transition and further develop sustainable cities. The thesis contributes to the emerging body of knowledge with a new understanding of co-housing, analysing its ‘key-features’ with an interdisciplinary framework, in a European context. It adds a new perspective to existing co-housing research, which is dominated by social sciences, by drawing attention to the physical characteristics of co-housing, produced in architectural, planning and engineering processes (the technosphere). The choices made during design and building are not only shaped by the residents’ aims and perception of sustainability, but also influenced by technosphere-related institutions, such as the building-components industry, energy or waste networks and providers, and planning regulations. The professional partners for the projects, such as housing associations and engineers, are equally affected by the institutional context, but their position is different from that of residents. They may for example be more anchored in governmental or professional regulations. To structure this dynamic, the research distinguishes three interrelated aspects: • ACTORS / involved in the (realisation of) projects: social practices of residents and their professional partners in co-creation. • CONTEXT / the structural forces surrounding the projects, specifically the macroinstitutional regimes. This also includes culturally determined interpretations of sustainability, technology, participation, societal roles, sharing, and so on. • TECHNOSPHERE / specifically building technology and utilities, focussing on energyrelated design and engineering of the co-housing projects. The thesis is primarily based on qualitative methods, as it found that reliable quantitative data are as yet unavailable. Looking for effective low-impact energysolution in co-housing, quantitative data remain however necessary and this thesis elaborates on pitfalls and possibilities for their accumulation. Empirical material from Dutch case-studies form the core of the research. Examples were also taken from countries where the re-emergence of co-housing is most visible and articulate: Belgium, France, Germany, the UK and Switzerland. Co-housing continues to develop and gain experiences with competences, such as communication skills and the ability to work cross-disciplinarily. The building industry and engineering professions increasingly call for such capabilities, but resident-led urban development have not yet entered the urbanism and engineering curricula. Therefore, opportunities should be provided for future professionals not only to acquire such capabilities but also to address fundamental questions related to residentinvolvement and democracy. This will enable future professionals to create a balance between ‘bottom-up’ articulated needs on the quality of living environments with large-scale investments in new urban energy, mobility and mutual care networks.

Limits—Urban Density and Mobility Networks in West Berlin during the Period of Containment

If space may be conceptualized as a natural resource, much like gas, oil, or minerals, then its production and use can also be thought of as something to be properly managed, taken care of, and not wasted. Limiting the expansion of the footprint of built-up land in urban areas forces this particular resource (space) to be used more efficiently—in a sense, compelling it to be more creative and productive. These spatial constraints on urban areas generate different kinds of densification processes within the existing city, propagating densification, and with it new patterns and uses in urban development, as well as novel approaches to mitigating the hazards of dense urban environments. This paper examines the case of how spatial containment in West Berlin during the period of the Berlin Wall (1961–1989) produced such outcomes. West Berlin during this period can be considered a unique case of spatial containment, where a relatively large and vibrant modern city had to work around a clear and indelible limit to its physical expansion. This paper will discuss ways in which the containment influenced patterns of development in West Berlin toward densification and connectivity, focusing on the expansion of its infrastructural networks, and discuss the development of a new building culture around transformation and densification, including hybrid architectures and mitigation devices to deal with difficult sites produced by the densification.

A system model for assessing vehicle use-phase water consumption in urban mobility networks

Water consumption is emerging as an important issue potentially influencing the composition of future urban transportation networks, especially as projected urban populations are expected to outpace water availability and as alternative fuels and vehicles are being implemented in such regions. National and State policies aimed at reducing dependence on imported fuels and energy can increase local production of fuels and energy, impacting demand on local water resources. This article details the development of a model-based assessment on water consumption and withdrawal pertaining to the use-phase of conventional and alternative transportation modes based on regional energy and fuel production. An extensive literature review details water consumption from fuel extraction, processing, and distribution as well as power plant operations. Using Model-Based Systems Engineering principles and the Systems Modeling Language, a multi-level, multi-modal framework was developed and applied to the Metro Atlanta transportation system consisting of conventional and alternative vehicles across varying conditions. According to the analysis, vehicles powered by locally produced biofuels and electricity (assuming average local grid mix for charging) consume more water than locally refined gasoline and CNG-powered vehicles. Improvements in power plant technologies, electricity generation (e.g., use of solar and wind versus hydro power) and vehicle efficiencies can reduce such water consumption significantly. Total water withdrawal for each vehicle and fuel is significantly greater than water consumption.

Soft Mobility and Pedestrian Networks in Urban Areas

By referring to the wider strategies set up, starting from the middle of the Nineties, by the European cities to promote a sustainable urban mobility and to the more recent concept of soft mobility, which generally includes pedestrian and cycling mobility, this contribution focuses on pedestrian mobility in urban areas, outlining criteria and methods for planning and designing networks of urban public open spaces, such as roads and squares, devoted to an exclusive or prevailing pedestrian use. First of all, the paper analyzes the multiple roles played by roads and squares within the cities: “axes” supporting different mobility flows, including the pedestrian ones, and in the meanwhile urban places in which different activities (commercial activities, meeting, and so on) take place. Grounding on that, the main reasons driving toward an organization of such spaces as urban networks have been outlined. Then, some guidelines and methodological elements, both for planning pedestrian networks and designing their elements taking into account the correspondence between foreseen uses and spatial features of each element, have been provided. Furthermore, the links between the pedestrian networks and the main junctions of other urban mobility networks, as well as between the first ones and the urban contexts have been stressed. Suggested guidelines and methodological elements have been applied and tested both on historical and suburban areas of the city of Naples; nevertheless they represent only a first step towards the setting up of a method for pedestrian networks planning and design in urban areas.

Performance of received power and traffic-driven handover algorithms in urban cellular networks

This article presents an investigation of the handover algorithms suitable for implementation in urban mobile cellular networks based on TDMA. More precisely, the class of received power and traffic-driven handover algorithms, which are based on absolute and relative measured values of received power and on actual traffic load, is analyzed. The algorithms usually investigated in the literature (and often implemented in actual mobile networks) belong to this class. We show the performance of traditional algorithms, and also propose some new ones, in an effort to reduce the probability of dropout due to sudden changes of received power and to distribute the traffic load over several cells; they show performance improvements with respect to those previously known from the literature. The performance of the different handover algorithms is evaluated by means of a simulation tool that allows the consideration of complex scenarios, suitable mobility and propagation models, power control, cell sectorization, nonuniform user distribution, and so on. The metrics used for performance comparison are the outage, blocking, dropout, and satisfaction probabilities, whose different definitions are discussed in the article, and the average number of handovers per call. Several urban scenarios, characterized by uniform and nonuniform traffic distributions, are taken into account. Our results show that one of the proposed algorithms, based on traffic estimates, yields the best performance of all the considered scenarios.