Urban systems design arises from disparate current planning approaches (urban design, Planning Support Systems, and community engagement), compounded by the reemergence of rational planning methods from new technology (Internet of Things (IoT), metric based analysis, and big data). The proposed methods join social considerations (Human Well-Being), environmental needs (Sustainability), climate change and disaster mitigation (Resilience), and prosperity (Economics) as the four foundational pillars. Urban systems design integrates planning methodologies to systematically tackle urban challenges, using IoT and rational methods, while human beings form the core of all analysis and objectives. Our approach utilizes an iterative three-phase development loop to contextualize, evaluate, plan and design scenarios for the specific needs of communities. An equal emphasis is placed on feedback loops through analysis and design, to achieve the end goal of building smart communities.
A new age of mobility is upon us, and the way we analyze our transportation network and future development projects must move into this new age. Large-scale changes to our transportation system are coming with the introduction of disruptive technologies and services like autonomous vehicles, electric vertical takeoff and landing (eVTOL) air taxis, and Mobility-as-a-Service (MaaS) platforms. Transportation modeling has long been used as a tool to measure the impact, positively or negatively, of a proposed network change or new land development. Transportation modeling has become more complex as it has shifted from the traditional four-step model, but it is still used in new development traffic impact studies, activity-based models, and most recently, agent-based models like those of MATSim. This increased complexity has made way for more comprehensive measures of effectiveness that can be useful in planning and design. However, there tends to be a gap between design occurring, tool utilization, and actual implementation of new technologies and big data effectively into these proven modeling and simulation platforms. Among five specific issues in travel forecasting, modeling is used as a reactive tool instead of a proactive tool with the purpose of influencing design and planning. Urban Systems Design has the potential to fill these gaps in methodology, which are occurring together in the modeling, planning, and design professions. An example of these new methodologies is presented using the city of Urawa Misono in metropolitan Tokyo, Japan, as a case study. As technology becomes more enhanced, so shall our methodologies, as we attempt to enact system changes in a more complex way. The feedback loop of analysis and design within Urban Systems Design methodologies could produce greater outcomes for the transportation network, for new development, and increase both the mobility and accessibility for the users of our urban networks.
Meeting the needs of increasing environmental and systematic pressures in urban settlements requires the use of integrated and wholistic approaches. The Urban Systems Design (USD) Conceptual Framework joins the metric-based modeling of rationalized methods with human-driven goals to form a combined iterative design and analysis loop. The framework processes information for the fundamental element of cities—humans—to large-scale modeling and decision-making occurring in district- and ward-level planning. There is a need in the planning and design profession to better integrate these efforts at a greater scale to create smart communities that are inclusive and comprehensive in aspects from data management to energy and transportation networks. The purpose of this study is to examine the applicability of this method as it pertains to a model and design integrated approach. Northern Sumida Ward, located in Tokyo, exemplifies the contextualized needs of Tokyo, and Japan, while forming a coherent internal community. Focusing on methodology, our process explores the creation of typologies, metric-based analysis, and design-based approaches that are integrated into modeling. The results of the analyses provide initial evidence regarding the validity of the USD approach in modeling changes to complex systems at differing design scales, connecting various qualities of the built environment, building and urban forms, and diagnostic comparisons between baseline and change conditions. Because of some inconsistencies and the need for further evidence gathering, the methods and processes show that there is much work to be done to strengthen the model and to continue building a more productive field of USD. However, in this framework’s continuing evolution, there is increasing evidence that combining the planning and design of urban systems creates a more resilient, economically viable, sustainable, and comfortable city.
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