Groups and frequent visitors shaping the space dynamics

Our research is about a dynamic symbolic space model that is fed with data from the environment by a set of processing modules that receive raw data from sensor networks. For the conducted experiments we have been using data from a WiFi network as it is a widely available infrastructure in our campus. Here we propose two processing modules which will provide more information about the spaces described in the model. The first one tries to implement our human perception of the usual visitors of a place using two measures, the long term and the short term tenant level. The second one detects where groups of users emerge, how many there are and what are their dimensions. Based on this new perspective of the campus we intend to realize how the presence of people shapes the dynamics of a space.Fundação para a Ciência e a Tecnologia (FCT

A Centrality Measure for Urban Networks Based on the Eigenvector Centrality Concept.

A massive amount of information as geo-referenced data is now emerging from the digitization of contemporary cities. Urban streets networks are characterized by a fairly uniform degree distribution and a low degree range. Therefore, the analysis of the graph constructed from the topology of the urban layout does not provide significant information when studying topology–based centrality. On the other hand, we have collected geo-located data about the use of various buildings and facilities within the city. This does provide a rich source of information about the importance of various areas. Despite this, we still need to consider the influence of topology, as this determines the interaction between different areas. In this paper, we propose a new model of centrality for urban networks based on the concept of Eigenvector Centrality for urban street networks which incorporates information from both topology and data residing on the nodes. So, the centrality proposed is able to measure the influence of two factors, the topology of the network and the geo-referenced data extracted from the network and associated to the nodes. We detail how to compute the centrality measure and provide the rational behind it. Some numerical examples with small networks are performed to analyse the characteristics of the model. Finally, a detailed example of a real urban street network is discussed, taking a real set of data obtained from a fieldwork, regarding the commercial activity developed in the city

Evidence for a Conserved Quantity in Human Mobility

Recent seminal works on human mobility have shown that individuals constantly exploit a small set of repeatedly visited locations. A concurrent study has emphasized the explorative nature of human behaviour, showing that the number of visited places grows steadily over time. How to reconcile these seemingly contradicting facts remains an open question. Here, we analyse high-resolution multi-year traces of ~40,000 individuals from 4 datasets and show that this tension vanishes when the long-term evolution of mobility patterns is considered. We reveal that mobility patterns evolve significantly yet smoothly, and that the number of familiar locations an individual visits at any point is a conserved quantity with a typical size of ~25. We use this finding to improve state-of-the-art modelling of human mobility. Furthermore, shifting the attention from aggregated quantities to individual behaviour, we show that the size of an individual’s set of preferred locations correlates with their number of social interactions. This result suggests a connection between the conserved quantity we identify, which as we show cannot be understood purely on the basis of time constraints, and the ‘Dunbar number’ describing a cognitive upper limit to an individual’s number of social relations. We anticipate that our work will spark further research linking the study of human mobility and the cognitive and behavioural sciences

Human Movement Is Both Diffusive and Directed

Understanding the influence of the built environment on human movement requires quantifying spatial structure in a general sense. Because of the difficulty of this task, studies of movement dynamics often ignore spatial heterogeneity and treat movement through journey lengths or distances alone. This study analyses public bicycle data from central London to reveal that, although journey distances, directions, and frequencies of occurrence are spatially variable, their relative spatial patterns remain largely constant, suggesting the influence of a fixed spatial template. A method is presented to describe this underlying space in terms of the relative orientation of movements toward, away from, and around locations of geographical or cultural significance. This produces two fields: one of convergence and one of divergence, which are able to accurately reconstruct the observed spatial variations in movement. These two fields also reveal categorical distinctions between shorter journeys merely serving diffusion away from significant locations, and longer journeys intentionally serving transport between spatially distinct centres of collective importance. Collective patterns of human movement are thus revealed to arise from a combination of both diffusive and directed movement, with aggregate statistics such as mean travel distances primarily determined by relative numbers of these two kinds of journeys

Packing Optimization for Digital Fabrication

We present a design-computation method of design-to-production automation and optimization in digital fabrication; an algorithmic process minimizing material use, reducing fabrication time and improving production costs of complex architectural form. Our system compacts structural elements of variable dimensions within fixed-size sheets of stock material, revisiting a classical challenge known as the two-dimensional bin-packing problem. We demonstrate improvements in performance using our heuristic metric, an approach with potential for a wider range of architectural and engineering design-built digital fabrication applications, and discuss the challenges of constructing free-form design efficiently using operational research methodologies

Hot and Bothered. Exploring the Effect of Heat on Pedestrian Behavior and Accessibility

Although many cities are incentivizing non-auto modes of transportation in response to the climate crisis, their sustainable mobility transition efforts are being challenged by the rising intensity and frequency of heatwaves. Pedestrians are exposed to high levels of heat stress on hot days, which may reduce their willingness to walk. It is important to understand how heat affects pedestrian behavior and accessibility, so that climate mitigation strategies can be better targeted to support walking as a mode but also as a first-/last-mile connection to public transit. In this study, we used a dataset of pedestrian trips undertaken during the summer of 2014 in Boston, MA. Along with several route attributes (such as length, turns, sidewalk width, amenities, NDVI, and SVF), we also included a measure of heat stress (UTCI) to explain pedestrian route choice. Using path-size logit models, we established that heat stress has a considerable and statistically significant effect on the perceived walking distance. We also found that the effect was non-linear and possibly exponential. Additionally, we illustrated the extent to which heat stress can reduce pedestrian accessibility to important destinations (such as public transit). This reduction was significant on a typical summer day, with an even sharper reduction on the hottest summer day. Non-White residents were observed to have lower accessibility levels compared to all pedestrians, likely because of disparities in urban heat exposure. Our findings highlight the importance of incorporating heat into transportation planning and urban design frameworks, especially with an equity lens to address unequal consequences

Ondate di calore e mobilità attiva: implicazioni per gli spostamenti a piedi e l’accessibilità urbana

Questo studio analizza l'impatto delle ondate di calore su mobilità e accessibilità a piedi al trasporto pubblico. Utilizzando dati GPS su spostamenti pedonali a Boston, MA, nell'estate del 2014, si valuta se, e come, lo stress termico influenzi le preferenze dei pedoni nella scelta dei percorsi. In particolare, si stima la disponibilità a camminare in relazione a differenti attributi urbani quali numero di svolte, larghezza dei marciapiedi, servizi, fattore di vista del cielo e presenza di vegetazione. A questi attributi si aggiunge un indice di stress termico, rappresentato dall’indice termico climatico universale, o UTCI. I risultati indicano che lo stress termico ha un impatto significativo sulla distanza percepita. L'effetto dell'UTCI è stato analizzato in modo non uniforme per diversi range di temperatura oltre i 26 gradi. Per ogni grado di aumento, la distanza percepita aumenta di 21,7 metri per temperature tra 26°C e 29°C, 44 metri tra 29°C e 32°C, e 64,3 metri oltre i 32°C. Lo studio evidenzia come lo stress termico possa ridurre l'accessibilità a piedi al trasporto pubblico, soprattutto nei giorni di caldo estremo. Si stima che, durante un giorno estivo tipico, solo il 25,9% dei residenti (poco più di un quarto) in una distanza a piedi di 800 metri, potrebbe avere un accesso agevole. La percentuale scende a 9,5% in un giorno di caldo estremo. I risultati assumono un'importanza cruciale per la pianificazione e la mobilità urbana sostenibile