The self-aware city

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 123-126).This thesis explores the idea of real-time urban space management. While increasing amounts of real-time information about the city, specifically the location of people and resources, appear, it becomes necessary to explore how different strategies of distributing real-time location information can be used as urban design tools for a more sustainable resource allocation. I focus on the study of street-parking, a system that clearly has a market situation with demand and supply, but due to lack of information is poorly managed today. I argue that an equilibrium state of the parking market in popular areas, similar to many other urban space markets, is a frequent over demand. The important challenges are therefore allocation optimization and queuing management. I propose five different strategies of using real-time location information to reduce search times and analyze the system through computer simulations and logic. Borrowing ideas from Game Theory, I try to illustrate how collaborative behavior between drivers could yield most efficient results from both the individual and the group point of view. Lastly, I outline some challenges that the use of real-time information systems introduce to the realm of urban design in general.by Andres Sevtsuk.S.M

Study of urban geometry and retail activity in Cambridge and Somerville, MA

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, September 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."August 11, 2010." Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 195-208).This dissertation investigates retail location patterns in urban settings -- a domain that has received relatively little attention in recent decades. We analyze which land use, urban form, and agglomeration factors explain observed retail patterns in an empirical case study of Cambridge and Somerville, MA. We are particularly interested in whether and how the distribution of retailers is affected by the spatial configuration of the built environment -- the physical pattern of urban infrastructure, the spacing and sizes of buildings, and the geometry of circulation routes. We argue that understanding retail location patterns in urban settings is not only important for improving retail location theory, but also essential for designing economically, socially, and environmentally sustainable urban neighborhoods. The dissertation proposes a novel graph-analysis framework in which retail location patterns can be represented under realistic constraints of urban geometry, land use distribution, and travel behavior. A series of spatial accessibility metrics, which we hypothesize to affect retail location choices, are introduced and applied in this framework using individual buildings as units of analysis. In order to test the statistical significance of these different metrics on retail location choices, we adopt the strategic interaction methodology from spatial econometrics and apply it for the first time in the context of location studies. We specify a linear probability model with a binary dependent variable and estimate how buildings' probabilities to accommodate retail establishments relate endogenously to other retailers' location choices and exogenously to both land use and urban form characteristics around each building. We apply the model to all retail and food-service establishments as a group and to different three-digit NAICS establishment categories individually. The results confirm that retail location choices in our study area are significantly related to both other retailers' endogenous location choices and exogenous land use characteristics around each building. However, controlling for both of these factors, we find that the spatial distribution of retail activity is also significantly related to the geometry of the built environment. By setting constraints on accessibility, visibility, adjacency, and density, the geometry of the built environment produces a rich landscape of information that appears to guide opportunities for business from building to building. The findings inform economists and planners about factors that attract retailers in urban settings, and urban designers about how the seemingly basic act of laying out streets, parcels and buildings can affect the location choices retail and service land uses, thereby shaping the economic structure of the city in important ways.by Andres Sevtsuk.Ph.D

The impact of street properties on cognitive maps

This paper investigates the relationship between street properties and cognitive maps. It is focused on the question of how human cognition of the built environment is affected by street properties. Building on the foundations of Kevin Lynch's studies of environmental perception (Lynch 1960) and recent configuration measurement techniques of the built environment, it addresses an important question that Lynch has left unresolved: Why do people have more complete recollections of some parts of the urban environment, and not others? This paper proposes an analytical measurement framework based on graph theory to compare the results of cognitive maps with objective spatial properties of the corresponding built environment. In order to test our hypothesis, street geometry is measured and defined based on graph theory in two selected areas with similar geometries in Kenmore, Boston and Kendall Sq., Cambridge, MA. Cognitive maps are then collected based on specifically designed map drawing surveys. Finally, the relationship between graph results and cognitive maps is examined in order to identify the ways that street properties affect human perception

Urban network analysis training in Rhinoceros3D : Barcelona, 11-13 July 2022

"ETSAB, DUOT, LUB" -- Portada"Course instructor: Andres Sevtsuk (associate professor of urban science and planning at MIT, Director of the City Form Lab)" -- Coberta"ETSAB summer masterclass" -- CobertaDescripció del recurs: 20 setembre 2023Conté: Foreword: Walking the streets: an approach to urban proximity through the analysis of pedestrian networks / Eulàlia Gómez-Escoda -- Presentation: Urban Network Analysis tools for modeling land use and transportation interactions for pedestrians and cyclists / Andres Sevtsuk -- Barcelona’s Superblocks under the spotlight: evaluating expected impact of green axes in pedestrian route choice and retail footfall / Mikel Berra-Sandín and Enric Villavieja Martínez -- The walking routes of the children of La Vila de Gràcia / André Salazar and Ricardo Sotomayor -- Walking the hills. Analysis of the walkable network around existing and planned L9 metro stations in upper Gràcia, Barcelona / Álvaro Clua, Francesc Valls and Joan Martí Elia

Exploring how socioeconomic status affects neighbourhood environments? : effects on obesity risks : a longitudinal study in Singapore

Research on how socioeconomic status interacts with neighbourhood characteristics to influence disparities in obesity outcomes is currently limited by residential segregation-induced structural confounding, a lack of empirical studies outside the U.S. and other 'Western' contexts, and an over-reliance on cross-sectional analyses. This study addresses these challenges by examining how socioeconomic status modifies the effect of accumulated exposures to obesogenic neighbourhood environments on children and mothers' BMI, drawing from a longitudinal mother-child birth cohort study in Singapore, an Asian city-state with relatively little residential segregation. We find that increased access to park connectors was associated with a decrease in BMI outcomes for mothers with higher socioeconomic status, but an increase for those with lower socioeconomic status. We also find that increased access to bus stops was associated with an increase in BMIz of children with lower socioeconomic status, but with a decrease in BMIz of children with higher socioeconomic status, while increased access to rail stations was associated with a decrease in BMIz of children with lower socioeconomic status only. Our results suggest that urban interventions might have heterogeneous effects by socioeconomic status.Peer reviewe

Mobile Surveys

In recent years, a new approach for estimating people’s movement in cities has emerged through mobile phone positioning. As opposed to the more traditional methods of traffic surveys, automated counts, or individual counters on streets, the use of aggregated and anonymous cellular network log files has shown promise for large-scale surveys with notably smaller efforts and costs. In addition, a frequent data feed from the cellular network has also been argued to demonstrate fine grain over-time variation in urban movements, which are lacking from the traditional prediction methods. However, despite the positivist approach to the new methodology, additional evidence is needed to show how cellular network signals correlate with the actual presence of vehicles and pedestrians in the city. The purpose of this paper is to address this shortcoming by presenting the results of a survey effectuated in Rome, Italy in January 2007. Using the results of the two-day experiment, we will employ statistical models to investigate the relationship between empirical pedestrian and traffic counts on the streets of rome with the simultaneous Telecom Italia Mobile (TIM) network signal and traffic prediction. Secondly, we will explore whether the mobile network data demonstrates the significant time-dependent variation that is missing from traditional fixed predictors like space syntax choice and integration analysis and could thus describe cities dynamically over time. Finally, we will also outline some general issues of accuracy in using aggregate mobile network data for estimating people’s movement in cities

Predicting pedestrian flow along city streets: a comparison of route choice estimation approaches in downtown San Francisco

Street attributes are thought to play an important role in influencing pedestrian route choices. Faced with alternatives, pedestrians have been observed to choose faster, safer, more comfortable, more interesting or more beautiful routes. Literature on pedestrian route choice has provided methods for assessing the likelihood of such options using discrete choice models. However, route choice estimation, which is data intensive and computationally challenging, remains infrequently deployed in planning mobility analysis practice. Even when coefficients from previous studies are available, operationalizing them in foot-traffic predictions has been rare due to uncertainty involved in the transferability of behavioral effects from one context to another, as well as computational challenges of predicting route choice with custom attributes. This paper explores a simpler method of route choice prediction, implemented in the Urban Network Analysis toolbox, which assigns probabilities to available route options based on distance alone. We compare the accuracy of distance-weighted approaches to the more detailed utility-weighted approach using a large dataset of observed GPS pedestrian traces that include numerous trips between same intersections pairs in downtown San Francisco as a benchmark. Even though a utility-weighted model matches observed pedestrian flows most accurately, a distance-weighted model is only marginally inferior, on average. However, shortest-distance and highest-utility route predictions are both significantly inferior to the utility-weighted and distance-weighted sample-enumeration methods. Our findings suggest that simplified assumptions can be used to predict pedestrian flow in practice with existing software, opening pedestrian flow predictions to a wider range of planning and transportation applications