The common description of the configuration of stuff in a room, one of order (tidy) and chaos (messy), fails to explain the phenomenon that artifacts create structures around people and activities in a space, with both functional and cognitive properties. This form of organization, that is recognizable on various scale levels, emerges spontaneously in the system, without the conscious intention of ordering. Following the growing insight in different disciplines that a theory of complexity can more adequately describe real-world phenomena than the classical causal-mechanistic model, a theory is proposed in which a third state, one of self-organization, is added to the order-chaos dichotomy. Stuff systems are considered complex systems, whose global patterns and properties unfold in time, generated through local interactions between the parts. When projecting models that describe complex system dynamics on stuff systems, much of what we observe in a house can be explained, such as the rise of order parameters structuring the parts, life cycles of accumulation, growth, restructuring and renewal, and interdependencies across scales.

The problem here, is that the constant reconfiguration of stuff can only be explained through interaction with human beings, but does not solely follow a path of top-down design. A theory is proposed that links the self-organization of stuff to action identification theory. This theory from psychology explores the cognitive construct of the action (“what one thinks one is doing”) as an order parameter filtering incoming information and thus structuring behavior. Action identification and affordance creation act in parallel and can be considered a doubly complex system creating and created by the self-organization of stuff.

Because of the process through which it emerges, this form of order is functionally optimized, cognitively logic and endlessly more complex than could be designed by drawing lines on paper. Architecture is always about order, while this order comes completely for free. The proposal following this theoretical explanation is therefore a house that uses these network-like structures as the organizational pattern of the design, instead of the traditional orthogonal ‘grid’. Three designer tools that are created following the research and a simulation through agent-based modeling in Netlogo are used in the design process to make this possible.

Automated driving is propagated to make travel more efficient and to enhance urban spaces. This research invests both these aspects integrally from the perspective of the residential location choice, to find the impacts of automated driving on urban development.
This thesis is the graduation work to conclude my Civil Engineering Master at the Delft University of Technology. This thesis has been part of a larger context of a research which also included my graduation for my other Master in Architecture, Urbanism and Building science, track Urbanism which I obtained in October 2017. The Urbanism report can be found here; http://resolver.tudelft.nl/uuid:bfc126dc-c3fb-4165-a719-7269817abc43

New ideas and innovation are the fuel to the modern knowledge economy. The university has for centuries been part of the innovation system responsible for the development of new ideas. Today, the interdisciplinary character and complexity of societal issues makes that there is a need for new methods to support innovation development at university. This thesis has sought for these methods from two different perspectives: that of the urban design of the university city (Section 1) and that of the learning process of its students (Section 2). Section 1 aims at developing an urban design approach for creating innovation space in the university city by conducting design-based research. Section 2 uses critical reflection as a method to give insight in the integration of design and research in Section 1.

Metaphorical and analogical thinking is a major aspect of how human intelligence tackles complex tasks in the discipline of urban design and planning. However, there is little research on this subject within urban design and planning, and the research approaches in closely related design disciplines lack a comprehensive view on its presence and roles on a disciplinary level. This paper argues that different metaphors/analogies play different roles to support different cognitive processes in urban design and planning, by constructing a framework to clarify the contexts, roles, and characteristics of M-A thinking. With case analyses, it further demonstrates that distinct characteristics related to the different roles can be explained with underlying cognitive patterns “organising” basic-form M-As, and that these patterns are inter-transformable. This framework could help lay the foundation of systematic research on this subject in urban design and planning, leading to addressing its wider implications.

Conventional spatial planning deals with hazards by bouncing back to the pre-existing situation. Intensifying manifestations of climate risk lead to unforeseen cascading effects that often surpass the level of protection offered by this type of approach (e.g. Hurricane Katrina) . In this thesis. spatial planning approach is developed that embraces uncertainties, including potential cascading effects. It provides the potential to bounce forward in space to better cope with a disaster.

Critical infrastructure networks (transport, water, energy lines) are interdependent and embedded in space. The proposal spatially understands recovery patterns offered by these networks during a crisis to inform long term growth trajectories of the urban system that can ‘grow with risk’. The principal objective is mainstreaming the role of spatial planning for risk reduction.

The research and design draws from quantitative conclusions of engineering, transport and seismic studies in the context of resilience planning. A spatial disaster event chain is proposed based on theories of complex networks and cascading effects. Risks are projected in space to simulate evacuation behavior on road networks using ArcGIS Network Analyst. With spatial reconfiguration as a central aim, ‘urban design’ iterations form a principal research component for an aggregate understanding of risks in space. The test case utilized in the San Francisco Bay which is at risk of a sea level rise by 2100 and is a hotbed of seismic activity.

Understanding recovery patterns due to incremental risk on infrastructure helps derive the gradient of spatial vulnerability. This informs the ‘critical web’ of the urban region to reconfigure land management and density distribution. A coherent spatial assessment framework is established to identify the ‘middle ground’ that absorbs intensive growth and vulnerable sites that must transition for better adaptivity.

The research highlights lack of cohesion in planning practice to pursue long term implementation strategies such as resilience in land use management, looking beyond building back’ and investing in incremental gain models that grow with risk .It aims to address this vital knowledge gap between engineering simulations and planning in the real world and how we can build a framework to sync them for long range risk reduction.
In conclusion, the project acknowledges risk in space and finds ways to sustain life in the light of urgencies.

Extensive research conducted by the World Health Organization suggests that stress is one of the primary health challenges of the Twenty-First century. When the stress response does not switch off, it not only affects the immune system, but also raises the risk of psychiatric diseases. Recent research elucidates that the risk of schizophrenia and other mental-health disorders keep rapidly increasing, and city life is one of the main factors leading to such crises. According to a study in Nature, published by psychiatrists Florian Lederbogen et al., city dwellers are more sensitive and susceptible to certain stress stimuli in opposition to countryside dwellers, further proving that city life makes a significant difference (Lederbogen, 2011). Although cities have abundant benefits such as convenience of life and copious job opportunities, such problems can not be neglected now since over half of the population live in cities world-wide.

According to Adli, social density and social isolation are the main causes of stress in cites (Adli, 2013). He proposes various solutions to reduce the problem, and minimizing the density is one of the solutions to counter the problems arising from high density. Despite appearing to be the most direct and effective way to reduce the problem, reasons such as the economic pursuit from the land and social need of gathering in most cities renders it unfeasible.
The situation raises an interesting question: how to reduce the stress level while maintaining or even increasing the density in the city?

This is a problem and a question that is highly related to living environment in the field of urbanism, but there is limited research or design in the field to explore this discourse from this perspective based on my preliminary research. To advance this discussion, I intend to carry out an explorative research exploring the dynamic relationship between stress (wellbeing of people) and the city (high density). The research tries to uncover the possible spatial measures to reduce the stress in the context of high density. It is carried out and illustrated in the case of Chinese urban immigrants who are highly vulnerable to stress related issues and have to live in highly dense living environment (urban village) in cities.

Complex urban planning problems comprise socio-spatial conditions, human behaviour and external factors (e.g. technological developments). The perspective of urban planners and designers is crucial to comprehend these problems from a holistic point of view but does not possess the skills to grapple the full problem. Cities bear characteristics of complex systems in which the interaction between decision makers is an important factor in the manifestation of urban change. Quantitative and computational methods are becoming increasingly capable at evaluating this aspect of urban planning problems. Computational models, although a simplification of reality, can help to evaluate many data and therefore extend the thinking capacity. Design thinking can interpret model outcomes in the broader socio-spatial context. But integration between these engineering-based methods on the one hand and the conventional urban planning and design methods proves challenging. This research investigates how an integrated methodology can lead to better understanding of urban planning problems. Models that comprehend built environment dynamics, can be used as design evaluation tool. The uncertainty around the spatial impacts of automated driving is used as case study for a complex urban planning problem. How automated driving will affect cities depends on the development and the deployment of the technology but also on how human agents adapt their behaviour. Mobility aspects (and therefore automated driving) relate to the built environment through the concept of accessibility and by the integration of the transportation system in space. An important condition to employ computational models within a research process is to explicitly define the system one evaluates. This research narrows down to households and their location choice behaviour as important behavioural aspect in urban development. The residential location choice depends on characteristics of the households itself and on dwelling, environment and location attributes. Automated vehicles are propagated to be more efficient in terms of infrastructure demands and travel efficiency compared to conventional vehicles. Therefore, this technology relates to the decision factors of households through spatial quality and accessibility effects. A scenario approach is employed to grapple the uncertainty around automated driving. In four scenarios, different development paths of automated driving are assumed. The province of Utrecht in the Netherlands is used as case study to provide for context and data. This research employs a residential location choice model to examine the changes in moving behaviour of households in space caused by the development of automated driving. The accessibility effects are studied with a transport model and the spatial quality effects are obtained by research and design. The residential location choice model evaluates these factors. The result is a change in urban development pattern. The results are interpreted in an urban strategy where the results of previous research steps are synthesised and assessed, to provide for interpretation of the research outcome from a holistic socio-spatial perspective. Computational models ask for explicit data which complicates the compatibility between various research steps. This research shows that it is possible to implement qualitative design methods within the data collection process. Design-based research methods are easier to apply and therefore relate directly towards the context of the problem. For using a computational model, this requires often for an operational model before one can comprehend the context. This makes for a more complicated research process. Therefore, employing an integrated methodology in urban planning research proves challenging but helps to approach the urban planning problem from a holistic perspective. An integrated approach broadens both perspectives to consider and combine the most important variables. By explicitly defining the problem, core principles reveal and computational models help to explain the dynamics between these core principles. Interpretation of the results in the socio-spatial context allows to account for the values that are inherent to urban planning problems. The method is labour intensive and does not guarantee more inspiring and detailed plans or designs. But the outcomes for proposed actions relate better to the factors that are significant to the system and elaborate more accurately on the uncertainty and dynamics the urban planning problem encompass. This research, is in which this report is established, is part of the graduation process for both the master of Urbanism at the faculty of Architecture and the master of Transport & Planning at the faculty of Civil Engineering. This report is submitted for the partial fulfilment of the Urbanism exam. The Transport & Planning report can be found here: http://resolver.tudelft.nl/uuid:5e88d71c-3878-4c4e-967b-0b5727bd0d8f