ABSTRACT. When looking from the aspect of facility location problems, hubs are special nodes in networks where flows are consolidated in order to reduce transportation costs between nodes. In complex networks, which model systems with many nodes, nodes having the most influence are chosen as hubs. The problem that arises is the choice of measure which should point to the most important nodes. Hub detection is done with the usage of various centrality measures, where each centrality measure has its own biases. In this paper we will, with the usage of proper centrality measure, develop a heuristic for solving the uncapacited single allocation hub covering problem.

ABSTRACT. The first step for planning the implementation strategy is to provide foundation of knowledge on BSS topic. Exploring existing information in the field of the research, someone can notice main methodologies and research techniques, followed by successful implementation examples of BSS. Identify main ideas, conclusion and theories while trying to establish similarities and avoid bad practices. In any bike-sharing program, one of the keys to success is the location and the distribution of bike stations. However, most authors and studies tend to give only general recommendations regarding the station implementation. In this paper a different approach of the implementation of a BSS will be described. As part of the IRIS project in the city of Alexandroupoli, a new vibrant BSS was proposed, focusing on installing stations for a holistic and efficient coverage of the city, using a beyond present approach.

ABSTRACT. We study the distribution of neighborhoods across a set of global cities and find that the distribution of neighborhood sizes follows exponential decay across all cities under consideration. We are able to analytically show that this exponential distribution of neighborhood sizes is consistent with the observed Zipf’s Law for city sizes. We attempt to explain the emergence of exponential decay in neighborhood size using a model of neighborhood dynamics where migration into and movement within the city are mediated by wealth. We find that, as observed empirically, the model generates exponential decay in neighborhood size distributions for a range of parameter specifications. The use of a comparative wealth-based metric to assess the relative attractiveness of a neighborhood combined with a stringent affordability threshold in mediating movement within the city are found to be necessary conditions for the emergence of the exponential decay in neighborhood size. While an analytical treatment is difficult due to the globally coupled dynamics, we use a simple two-neighborhood system to illustrate the precise dynamics yielding far from equal equilibrium neighborhood size distributions.

ABSTRACT. The spontaneous emergence of spatial patterns, which arise from microscopic rules and break the intrinsic symmetry of space, is ubiquitous in nature, from the skin pigmentation of some animals to the regular shape of snowflakes, or the embryonic cellular structure. Curious patterns can also be found in urban areas, constituted by the different specific use of each piece of land. Each city is characterized by its own particular pattern; the land use pattern is strictly related to the mobility, the social structure of the city and, more in general, to its livability. Clearly, the organization of land use affects mobility and travel demand of people and has an impact on how the transport lines (be they highways, metro lines, or long connections in general) are built, and viceversa. We here propose a simple framework for simulating urban land use patterns starting from microscopic rules which determine the local benefit and cost of assigning a particular typology to each building, i.e. Residential, Commercial and Business, Industrial and Green or empty areas. The theoretical city that we obtain with the proposed model follows a temporal evolution before reaching a stable configuration, where the four typologies coexist, shaping peculiar aggregation patterns. By tuning a segregation parameter, we can vary between a mixed-use landscape (à la Jane Jacobs) and a more orderly configuration where each zone of the city is devoted to a unique or almost unique function. The degree of heterogeneity in the distribution of buildings is quantified by using a measure of entropy. This framework opens the perspective to many considerations in terms of accessibility and livability of the different configurations of cities corresponding to different levels of land use mixing. Moreover, we observe how the eventual organization of land use is modified by inserting the transportation system at different stages of the city growth.

ABSTRACT. Roads network construction result of a subtle balance between fine service to space and rapid access to important or strategic points. To evaluate and improve territorial accessibility, it is fundamental to understand road networks dynamics of evolution. In this work we conduct a morphological analysis of road patterns over time based on geo-historical data (provided by historical maps), we use a prime mapping approach and a characterization by indicator to compare their topological features in three different cities over three historical periods, to understand their logic of development. In a prospective vision, this work aims to study multiple topological variables of historical road networks, which will allow us to understand mechanisms leading their evolution. Studying road networks morphogenesis to detect indicators stability or variation logic over time, and to identify similar behaviors despite geographic and cultural distances, is of major support for better understanding their impact on accessibility and mobility

ABSTRACT. To date, the only effective means to respond to the spreading of COVID-19 pandemic are non-pharmaceutical interventions (NPIs), which entail policies to reduce social activity and mobility restrictions. Quantifying their effect is difficult, but it is key to reduce their social and economical consequences Here, we introduce two different modeling paradigms able to model the spreading of COVID-19, explicitly accounting for spatial resolution at different scales. The introduced models are valuable forecast tools, as well as support systems to perform what-if analyses and inform the application of containment policies in urban environments (or wider ones). First, we introduce a meta-population spatially-resolved model based on temporal networks, calibrated on the COVID-19 outbreak data in Italy and apt to evaluate the outcomes of these two types of NPIs. Our approach combines the advantages of granular spatial modeling of meta-population models with the ability to realistically describe social contacts via activity-driven networks. We provide a valuable framework to assess the viability of different NPIs, varying with respect to their timing and severity, at different spatial scales, from city neighborhoods to entire countries. Furthermore, an agent-based modeling platform to simulate the spreading of COVID-19 at the resolution of a single individual in small towns and cities is proposed and demonstrated on real data from New Rochelle, NY —where the first outbreak was registered in the United States. The model explicitly considers disease transmission in residential buildings and different public locations within a statistically realistic population, and accounts for different types of testing. Results suggest that the effects of mobility restrictions largely depend on the possibility to implement timely NPIs in the early phases of the outbreak, whereas activity reduction policies should be prioritized afterwards.

ABSTRACT. Commuting across cities creates opportunities to meet and establish relationships to a wide set of people. Contrary, living and work around the same neighborhood limits the possibilities to develop social ties towards diverse communities. In this paper we test the influence of urban mobility on the structure and assortativity of social connections. We follow the mobility of individuals through their geolocated Twitter messages in the top 50 metropolitan areas of the US. After identifying the home and work location of users and constructing their online social network, we enclose socio-economic information from census data to their main locations. Our findings show that commuting to distant locations increases the number of connections people can develop and acts against closed, highly clustered social ties. Moreover, commuting to work at a distant location increases the chance to form ties towards people from different socio-economic background. The study provides a large-scale, data-driven approach to investigate relationship between social ties and urban mobility.

ABSTRACT. The structure of complex networks has long been understood to play a role in transmission and spreading phenomena on a graph. This behavior is difficult to model analytically and is most often modeled numerically. Such networks form an important part of the structure of society, including transportation networks. As society fights to control the COVID-19 pandemic, an important question is to choose the optimum balance between the full opening of transport networks and the control of epidemic spread. In this paper we investigate how recent advances in analyzing network structure using information theory could inform decisions regarding the opening of such networks. By virtue of the richness of data available we focus upon the worldwide airline network, but these methods are in principle applicable to any transport network. We are able to demonstrate that it is possible to substantially open the airline network and have some degree of control on the spread of the virus.

ABSTRACT. Cities are often thought as systems of systems, that grew like living organisms. Their scope goes beyond buildings, roads and people, as there is a spacetime dimension where relations and activities happen, conditioning our perceptions and transforming the city [2]. As these infrastructural, ecological and social components are strongly interrelated [3], in this paper we propose a discussion about the city from the point of view of complexity studies, with the aim of analyzing the interrelations between the built environment (hard components) and the social dynamics. (soft components) that characterize and transform urban life. The relation between urban hard and soft components can be tackled through the analysis of urban flows of information and activities. In the contemporary city, these flows happen not only at the physical level, but also on a virtual dimension, challenging once again the concept of what the city is and where are its limits. Michael Batty [4] distinguished two different rhythms that characterize urban dynamics: high frequency, operating at the level of human time frames (e.g.: seconds, days, months), and low frequency, operating over longer periods, sometimes several years or generations. Some former low frequency urban pulses are turning into high frequency, or at least increasingly working at both timeframes. Some examples are related to important innovations in mobility and telecommunications, which accelerated the rhythm of life and led to new multipolarized and heterogeneous urban patterns, since physical proximity ceased to be a first necessity for exchanges [1, p. 62-63]. Pedestrian movement is one of them, with the spreading of smart phones’ apps, associated to shared soft mobility devices. Mode commuting is increasingly easier, from walking to shared bicycles or electric scooters, along with subway or bus. Each mode contributes to support pedestrian mobility in the city, producing a multilayer network of flows on the traditional street network and transforming it. The research problem under analysis is: What are the main factors conditioning pedestrian movement patterns in the urban system? This paper is part of an ongoing research project focused on this question, raising the hypothesis that beyond the built environment, spatiotemporal factors affect movement patterns in the urban fabric. The theory of natural movement [6] demonstrated that spatial morphology is a primary factor influencing movement [9]. Other studies suggest that the articulation between existent urban fabric elements such as transport accessibility, street network and land use are strongly related to pedestrian activity [5, 7]. However, each of these elements are static constituents of the spatial environment, located in a fixed area of the urban grid. The proposed analysis argues that movement patterns are also affected by spatiotemporal factors like events or activities. The goal of the paper is to present a comparative analysis of the main properties of the public space network of Lisbon: a) as a spatial infrastructure and b) as a structure for space-time flows. Firstly, we present and discuss a theoretical framework on complexity and network science in the context of urban dynamics, followed by the description of the public space network in study. Space syntax axial map representation model will be used, which is defined by the topological relations between spaces, rather than Euclidean distance. Each mode of transportation (pedestrian, shared bicycles, and electric scooters) will be represented in a layer. Next, flows’ data will be collected from multiple sources, such as local and national institutions, shared mobility suppliers API’s and Mobile Crowd Sensing (MCS) systems within a 24h timeframe. Each layer of the network will be weighted with collected data, using Voronoi diagrams to solve nearest neighbor problems [8]. It is expected that, while the analysis of the dynamics of the network as a communication channel will reveal its primary properties, the flows’ operating on the network will make several transformations of these properties through time, uncovering spatiotemporal cycles.

References 1. Ascher, F.: Novos Princípios de Urbanismo Seguido de Novos Compromissos Urbanos: Um Léxico. Livros Horizonte, Lisbon (2010) 2. Batty, M.: The New Science of Cities. The MIT Press, London (2013) 3. Bettencourt, L., West, G.: A unified theory of urban living. Nature 467, 912–913 (2010) 4. Batty, M.: Digital twins. Environment and Planning B: Urban Analytics and City Science 45(5), 817–820 (2018) 5. Dhanani, A., Tarkhanyan, L., Vaughan, L.: Estimating pedestrian demand for active transport evaluation and planning. Transport Research Part A 103, 54–69 (2018) 6. Hillier, B., Penn, A., Hanson, J., Xu, J.: Natural movement: or, configuration and attraction in urban pedestrian movement. Environment and Planning B: Planning and Design 20, 29–66 (2018) 7. Koohsari, M., Oka, K., Owen, N., Sugiyama, T.: Natural movement: A space syntax theory linking urban form and function with walking for transport. Health and Place 58 (2019) 8. Li, Y., Liu, G., Gao, J., He, Z., Bai, M., Li, C.: Efficient spatial nearest neighbor queries based on multi-layer voronoi diagrams (2019) 9. Volchenkov, D., Blanchard, P.: Discovering important nodes through graph entropy encoded in urban space syntax (2007)

ABSTRACT. Urban water infrastructures are an essential part of urban areas. For their construction and maintenance, major investments are required to ensure an efficient and reliable function. A vital part of the urban water infrastructures are the water distribution networks (WDNs), in which the water is transported from the production (sources) to the spatial distributed consumers (sinks). To minimize the costs and at the same time maximize the resilience of such a system, multi-objective optimization procedures are performed. Assessing the hydraulic behavior of WDNs in such an optimization procedure is not a trivial task; therefore, WDNs are categorized as complex networks. For a deeper insight into functional properties of these optimal transport networks and assess the quality of the optimization process, a dual graph approach for WDN is developed and applied in this work. Therefore, the dual characteristics of 100 pareto-optimal WDNs, including the pathway for optimization from random initialization to pareto-optimal solutions, are investigated (in total 2,700 networks). By that an answer to the question is sought: when is a sufficient optimization stage achieved, and how can that be assessed? It was found that the number of dual nodes decreases with increasing generations, i.e., the more optimal the solutions get. Therefore, the number of dual nodes can be seen as an indicator to assess how optimal the obtained solutions are.

ABSTRACT. We present a network science approach to characterize accessibility and potential use of parks in cities based on Geographical Information Systems (GIS) and daily individual trajectories. We consider two types of nodes: home regions, which partition the city, and park regions, which are public outdoor/recreational spaces. We build a bipartite weighted network among them, with links' weight representing the number of possible access from a home node to a park node on an average weekday.

We apply the proposed methodology to the Los Angeles Metropolitan area and the Great Boston area, with census tracts as home regions, and park amenities from OpenStreetMaps as park regions. Daily mobility is obtained from TimeGeo, an individual mobility model representative of each city's total population and based on Call Detailed Records (CDRs).

We associate tract's park access and the park's potential use to their network strength (sum of links' weight), founding similar distributions in both cities. The split of the network into communities results mainly in home tracts mostly connect with neighboring geographical tracts.

ABSTRACT. Networks provide a powerful representation of complex systems of interacting components. In addition to a wide range of available analytical and computational tools, networks also offer a visual interface for exploring large data in a uniquely intuitive fashion. However, the size and complexity of many networks render static visualizations on common screen or paper sizes impractical and result in proverbial 'hairballs'. Here, we introduce an immersive Virtual Reality (VR) platform that overcomes these limitations and unlocks the full potential of visual, interactive exploration of large networks. Our platform is designed towards maximal customization and extendibility, with key features including import of custom code for data analysis, easy integration of external databases, and design of arbitrary user interface elements. Our platform represents a first-of-its-kind, general purpose VR data exploration platform in which human intuition can work seamlessly together with state-of-the-art analysis methods for large and diverse data.

ABSTRACT. Cities are the innovation centers of the US economy, but disruptions from technology may exclude workers and inhibit a middle class. Therefore, urban policy must promote the jobs and skills that increase worker pay, create employment, and make their economy resilient to downturns. In this paper, we describe the beginnings of a framework for achieving such predictive capability. We model labor market resilience in cities with an ecologically-inspired employment matching process on the job network constructed from the similarity of occupations' skill requirements. Despite regional and historical differences, we find that the economic resilience of cities is universally and uniquely determined by the connectivity between jobs within a city's job network. First, we observe that US cities with greater job connectivity experienced lower unemployment rates during the Great Recession. Further, cities that increase their job connectivity see increasing wage bills, and workers of occupations with high degree within a city's job network enjoy higher wages than their peers elsewhere. Finally, we show how job connectivity may clarify the augmenting and deleterious impact of automation in US cities. Following from these results, policy that promotes connected occupations may grow local labor markets and promote general economic resilience capable of addressing technology-driven labor trends.

ABSTRACT. The era of the automobile has seriously degraded the quality of urban life through costly travel and visible environmental effects. A new urban planning paradigm must be at the heart of our roadmap for the years to come. The one where, within minutes, inhabitants can access their basic living needs by bike or by foot. In this work, we present novel insights of the interplay between the distributions of facilities and population that maximize accessibility over the existing road networks. Results in six cities reveal that travel costs could be reduced in half through redistributing facilities. In the optimal scenario, the average travel distance can be modeled as a functional form of the number of facilities and the population density. As an application of this finding, it is possible to estimate the number of facilities needed for reaching a desired average travel distance given the population distribution in a city.

Note: This is a paper recently published, in case there is room to attend and presented it here. This venue is ideal :)

ABSTRACT. Street parking spots for automobiles are a scarce commodity in most urban environments. The heterogeneity of car sizes makes it inefficient to rigidly define fixed-sized spots. Instead, unmarked streets in cities like New York leave placement decisions to individual drivers, who have no direct incentive to maximize street utilization.

This paper explores the effectiveness of two different behavioral interventions designed to encourage better parking, namely (1) educational campaigns to encourage drivers to ``kiss the bumper'' and reduce the distance between themselves and their neighbors, or (2) painting appropriately-spaced markings on the street and urging drivers to ``hit the line''. Through analysis and simulation, the paper establishes that the greatest densities are achieved when lines are painted to create spots roughly twice of the expected cars length and the minimum gap between two adjacent cars.

ABSTRACT. The ability to take into account the particular context of urban environments remains complex when it comes to addressing challenges such as the ecological transition to sustainability. Indeed, activities or projects developed in cities are not all coherent due to heterogeneous city components, different political orientations across time or available budgets. To help identify city’s situation and projects to be implemented to improve city strategy coherence, a novel computation method is proposed. Based on research literature and field cities feedbacks collected during workshops we organized, a model of smart city profile characterization is given, as well as a smart city model to ensure an implementation of relevant activities through a new use cases methodology.

ABSTRACT. Collecting and receiving information about the state of a transportation system is essential to effective planning for intelligent transportation systems, whether it be on the part of individual users or managers of the system. However, efforts to collect or convey information about a system’s status often require considerable investment in infrastructure/technology. Moreover, given variations in the development and use of transportation systems over time, uncertainties exist as to where and when demand for such services may be needed. To address these problems, a model for minimizing the cost of siting and/or collecting information while ensuring specified levels of expected demand are served is proposed. In order to demonstrate the characteristics of the proposed formulation, it is coupled with another planning objective and applied to identify optimal sites for information provision/collection in a transportation system. Model solutions are then derived for multiple scenarios of system flow to explore how variations in the use of a transportation system can impact siting configurations.