Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development

Modelling urban spatial change: a review of international and South African modelling initiatives

August 2013Urban growth and land use change models have the potential to become important tools for urban spatial planning and management. Before embarking on any modelling, however, GCRO felt it was important to take note of, and critically assess lessons to be learnt from international experience and scholarship on spatial modelling, as well as a number of South African experiments that model future urban development. In 2012, GCRO initiated preliminary research into current international and South African modelling trends through a desktop study and telephone, email and personal interviews. This Occasional paper sets out to investigate what urban spatial change modelling research is currently being undertaken internationally and within South Africa. At the international level, urban modelling research since 2000 is reviewed according to five main categories: land use transportation (LUT), cellular automata, urban system dynamics, agent-based models (ABMs) and spatial economics/econometric models (SE/EMs). Within South Africa, urban modelling initiatives are categorised differently and include a broader range of urban modelling techniques. Typologies used include: provincial government modelling initiatives in Gauteng; municipal government modelling initiatives; other government-funded modelling research; and academic modelling research. The various modelling initiatives described are by no means a comprehensive review of all urban spatial change modelling projects in South Africa, but provide a broad indication of the types of urban spatial change modelling underway. Importantly, the models may form the basis for more accurate and sophisticated urban modelling projects in the future. The paper concludes by identifying key urban modelling opportunities and challenges for short- to long-term planning in the GCR and South Africa.Written by Chris Wray, Josephine Musango and Kavesha Damon (GCRO) Koech Cheruiyot (NRF:SARChI chair in Development Planning and Modelling at Wits

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

The Spatial Distribution of Welfare in Ireland

In this thesis welfare is examined in a spatial context. A broader definition of welfare is taken so that it includes more than just income. In-kind benefits, indirect costs, life-satisfaction, locational effects are all examined in a spatial context. The impact of these welfare drivers on the spatial distribution is examined with each chapter focusing on a different welfare driver. Differences between areas may be psychical (e.g. climate) or structural (e.g. high education attainment) using a spatial approach can account for some of this variation. An interaction exists between space and the economy which results in agglomeration economies and clustering based on social class. However, there are market failures (e.g. congestion) which can reduce welfare. A broader measure of welfare which includes additional components and not just monetary income acknowledges the spatial heterogeneity that exists across space. A small area examination allows for pockets of deprivation and poverty to be identified. Some of the reasons behind the inequality that exist between and within areas is explored and described. Taking each component in isolation has the power to show the effects of that driver on welfare. International studies are often limited by a lack of income data at a small area level. This thesis uses the output from a spatial microsimulation model to overcome the lack of income data at a spatial scale. This income data is enhanced through a data fusion process to create and include additional spatially rich welfare data. Spatial methods such as interpolation and network analysis tools are utilised to calculate and create new small area datasets. Mapping tools such as GIS provide the added benefit of displaying results in an effective way. This newly created data can be used to calculate how welfare varies spatially depending upon the definition of welfare used. The broader definition of welfare adopted is based on conceptual underpinnings that any benefits/costs which increase/decrease individual potential to consume should be included in a measure of welfare. Drivers of welfare examined include intertemporal effects, housing, commuting, labour markets, spatial attributes and exposure to flooding. The sensitivity and impact of each component on individual welfare is examined. By using a spatial approach differences in the impact of each driver across space can be measured. Due to the heterogeneous nature of welfare, some drivers can have positive benefits in some areas but negative in others. By adopting a spatial approach these differences can be identified. Measuring welfare at a disaggregated spatial scale is required before we attempt to understand why the spatial distribution of welfare looks the way it does. Research such as this is crucial to evaluate and recommend policies that improve welfare and reduce spatial inequalities. Due to their limited nature, identifying areas with greater “need” allows resources to be targeted more efficiently. This thesis makes a number of recommendations in this regard as to why policy should adopt a more holistic approach to welfare. It highlights particular challenges in the area of data collection and the need for greater focus on spatial impacts of various policy measures at a small area level

The Spatial Distribution of Welfare in Ireland

In this thesis welfare is examined in a spatial context. A broader definition of welfare is taken so that it includes more than just income. In-kind benefits, indirect costs, life-satisfaction, locational effects are all examined in a spatial context. The impact of these welfare drivers on the spatial distribution is examined with each chapter focusing on a different welfare driver. Differences between areas may be psychical (e.g. climate) or structural (e.g. high education attainment) using a spatial approach can account for some of this variation. An interaction exists between space and the economy which results in agglomeration economies and clustering based on social class. However, there are market failures (e.g. congestion) which can reduce welfare. A broader measure of welfare which includes additional components and not just monetary income acknowledges the spatial heterogeneity that exists across space. A small area examination allows for pockets of deprivation and poverty to be identified. Some of the reasons behind the inequality that exist between and within areas is explored and described. Taking each component in isolation has the power to show the effects of that driver on welfare. International studies are often limited by a lack of income data at a small area level. This thesis uses the output from a spatial microsimulation model to overcome the lack of income data at a spatial scale. This income data is enhanced through a data fusion process to create and include additional spatially rich welfare data. Spatial methods such as interpolation and network analysis tools are utilised to calculate and create new small area datasets. Mapping tools such as GIS provide the added benefit of displaying results in an effective way. This newly created data can be used to calculate how welfare varies spatially depending upon the definition of welfare used. The broader definition of welfare adopted is based on conceptual underpinnings that any benefits/costs which increase/decrease individual potential to consume should be included in a measure of welfare. Drivers of welfare examined include intertemporal effects, housing, commuting, labour markets, spatial attributes and exposure to flooding. The sensitivity and impact of each component on individual welfare is examined. By using a spatial approach differences in the impact of each driver across space can be measured. Due to the heterogeneous nature of welfare, some drivers can have positive benefits in some areas but negative in others. By adopting a spatial approach these differences can be identified. Measuring welfare at a disaggregated spatial scale is required before we attempt to understand why the spatial distribution of welfare looks the way it does. Research such as this is crucial to evaluate and recommend policies that improve welfare and reduce spatial inequalities. Due to their limited nature, identifying areas with greater “need” allows resources to be targeted more efficiently. This thesis makes a number of recommendations in this regard as to why policy should adopt a more holistic approach to welfare. It highlights particular challenges in the area of data collection and the need for greater focus on spatial impacts of various policy measures at a small area level

Assessing the Impact of Bicycle Infrastructure and Modal Shift on Traffic Operations and Safety Using Microsimulation

A transportation system designed to prioritize the mobility of automobiles cannot accommodate the growing number of road users. The Complete Streets policy plays a crucial part in transforming streets to accommodate multiple modes of transportation, especially active modes like biking and walking. Complete streets are referred to as streets designed for everyone and enable safety and mobility to all users. A strategy of complete streets transformation is to connect isolated complete street segments to form a complete network that improves active mobility and public transit ridership. This research assessed the impact of efficiently and equitably connecting and expanding the biking network using dedicated lanes on the safety and operation of the network in Atlanta, Georgia. These connections are aimed at increasing the multimodal use of the streets in midtown and downtown Atlanta and achieving the mobility and public health goals through the integration of various modes of travel. The evaluation was done by modeling a well-calibrated and validated network of Midtown and Downtown Atlanta in VISSIM using existing travel demand and traffic design conditions (i.e., the baseline or Scenario 0). A total of three different conditions: existing, proposed, and alternative conditions, were modeled to see the effectiveness of bike infrastructure design improvement and expansion. Three scenarios were then modeled as variations of modal demand of the different condition models. Scenarios modeled are based on input from the City and Community stakeholders. Using the trajectory data from microsimulation, the surrogate safety assessment model (SSAM) from FHWA was used to analyze the safety effect on the bike infrastructure improvement and expansion. Results of this study showed a positive impact of complete streets transformation on the streets of Midtown and Downtown Atlanta. These impacts are quantified in this thesis