Dynamics of Metropolitan Landscapes and Daily Mobility Flows in the Italian Context. An Analysis Based on the Theory of Graphs

A novel approach to model the role of mobility suppression and vaccinations in containing epidemics in a network of cities

This paper presents a comprehensive agent-based model for the spread of an infection in a network of cities. Directional mobility is defined between each two cities and can take different values. The work examines the role that such mobility levels play in containing the infection with various vaccination coverage and age distributions. The results indicate that mobility reduction is sufficient to control the disease under all circumstances and full lockdowns are not a necessity. It has to be reduced to different ratios depending on the vaccination level and age distribution. A key finding is that increasing vaccination coverage above a certain level does not affect the mobility suppression level required to control the infection anymore for the cases of young population and heterogeneous age distributions. By investigating several migration and commuting patterns, it is found that shutting mobility in a few local places is favored against reducing mobility over the entire country network. In addition, commuting -and not migration-influences the spread level of the infection. The work offers an exclusive combined network-based and agent-based model that makes use of randomly generated mobility matrices.

Investigating Sustainable Commuting Patterns by Socio-Economic Factors

This research aims to analyze how modes of transportation differ according to socio-economic factors in an urban space. The study area is Ramsey County, the most densely populated county in Minnesota. The primary data used were from the recent 2012–2016 Census Transportation Planning Products (CTPP). We performed regression models to identify the relationship between mode of transport and socio-economic variables, and further analyzed disaggregate trip data to provide a more realistic evaluation of commuting patterns by use of multiple variables in combination. The research found that sustainable commuting patterns correlated significantly with both poverty and minority group status, but bore no significant relationship to older workers. Additionally, there was a significant correlation between commuting alone by car with both minority group status and older workers, but not with poverty. This research also confirmed that the sustainable commuting patterns of the working poor were mostly located in the downtown area, while causes of low-income workers driving alone typically involved much longer commutes to and from points throughout the study area, suggesting that more efficient commutes are a significant quality of life factor for the urban poor when evaluating residential and employment opportunities in the central city.

Assessing the Potential Conflict Occurrence Due to Metropolitan Transportation Planning: A Proposed Quantitative Approach

Large urban settlements are being organized in metropolitan areas, with a polarizing city influencing and shaping the landscape of the hinterland. Transport infrastructure networks are the main vectors for the permanent flux of resources, and these exchanges should be maintained undisturbed. A poor transportation network impedes the continuity of these flows, causing unsatisfaction, ultimately generating planning-based conflicts within metropolitan zones. This study aims in assessing the potential occurrence of metropolitan conflicts generated by the transportation network design. We used a quantitative approach based on a set of new proposed indexes. The methods were applied on nine metropolitan zones from Romania. The results show that each metropolitan zone has specific potential for conflict occurrence. The higher potential was recorded within the more recent established metropolitan zones. Our results raise the question on whether the Romanian metropolitan zones are fully functional and worthy of this status. The study provides a useful and usable tool in assessing the effectiveness of the transportation networks within metropolitan areas, establishing the potential conflict occurrence and it provides interesting insights about the metropolitan transportation issues, raising red flags toward local and regional decision makers and planners.

Relationship between Spatio-Temporal Travel Patterns Derived from Smart-Card Data and Local Environmental Characteristics of Seoul, Korea

With the incorporation of an automated fare-collection system into the management of public transportation, not only can the quality of transportation services be improved but also that of the data collected from users when coupled with smart-card technology. The data collected from smart cards provide opportunities for researchers to analyze big data sets and draw meaningful information out of them. This study aims to identify the relationship between travel patterns derived from smart-card data and urban characteristics. Using seven-day transit smart-card data from the public-transportation system in Seoul, the capital city of the Republic of Korea, we investigated the temporal and spatial boarding and alighting patterns of the users. The major travel patterns, classified into five clusters, were identified by utilizing the K-Spectral Centroid clustering method. We found that the temporal pattern of urban mobility reflects daily activities in the urban area and that the spatial pattern of the five clusters classified by travel patterns was closely related to urban structure and urban function; that is, local environmental characteristics extracted from land-use and census data. This study confirmed that the travel patterns at the citywide level can be used to understand the dynamics of the urban population and the urban spatial structure. We believe that this study will provide valuable information about general patterns, which represent the possibility of finding travel patterns from individuals and urban spatial traits.