Peter Buš

CityHeat: visualizing cellular automata-based traffic heat in Unity3D

Cellular Automata (CA) based simulation can be employed to understand traffic heat emission at micro scale level. Simulation space is divided into cubes of various sizes that encapsulate temperature within the cubes volume at different time stamps. Using this simulation result, we introduce CityHeat, a visualization tool to observe traffic heat distribution developed using Unity3D. Game engine is employed as a tool to reach interdisciplinary stakeholder groups that might not be coming from engineering background to understand the domain problem.

CAD integrated workflow with urban simulation-design loop process

The urban space nowadays is considered as an aggregate of large amount of complex characteristics. Information collected by means of urban big data approaches play a crucial role in how to understand, interpret and model urban environments. Simulation models are the best solution for architects, urban planners and designers to integrate various information about urban complexity into the design process. The connection between several simulation approaches within one user interface is still a big challenge to make the design process faster, more accurate and visually convenient. The interface would be involved in the modelling process, pre-processing, simulation, post-processing and visualisation. A CAD integrated user interface is proposed where all these particular components are embedded into one system. The whole process would be based on a workflow loop whereby each component will be depending on the previous cycle. As a case-study of such a principle we establish an extendable modelling and simulation platform connected to a user through the game-engine Unity3D in order to achieve a robust interactive environment. The model platform operates with real urban conditions of an existing part of the city of Singapore and simulates the distribution of traffic’s heat within the investigated environment. Based on the simulation results the user can configure more proper spatial scenarios within the urban plan in different variations. The proposed system would help architects and urban planners to enhance their decision repertoire during the design phase and allows them taking into account more complex information about the urban entirety. The result of the research is therefore a computational decision-making tool with enhanced visual output.

Machine learning approaches to understand the influence of urban environments on human’s physiological response

Abstract This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency unification, signal pairing, signal filtering, signal quantification, and data labeling. Furthermore, this paper contributes to human-environment interaction research, where a field study to understand the influence of environmental features such as varying sound level, illuminance, field-of-view, or environmental conditions on humans’ perception was proposed. In the study, participants of various demographic backgrounds walked through an urban environment in Zurich, Switzerland while wearing physiological and environmental sensors. Apart from signal processing, four machine learning techniques, classification, fuzzy rule-based inference, feature selection, and clustering, were applied to discover relevant patterns and relationship between the participants’ physiological responses and environmental conditions. The predictive models with high accuracies indicate that the change in the field-of-view corresponds to increased participant arousal. Among all features, the participants’ physiological responses were primarily affected by the change in environmental conditions and field-of-view.

Fish Trap – A floating Proto-assembly for Responsive Cities: Towards Citizen-Driven Customised Water Urban Spaces

Urban water spaces, lakes and rivers have an impact on the image of the city and have played a key role in the socioeconomic development of cities throughout the centuries. This positive trend makes the redevelopment of waterfronts an ideal test-bed for new concepts of citizen engagement and adaptive and responsive architectural designs. Unfortunately, waterfronts often change and change is activated from bottom-up, but even today, we can not actively engage the users in the design process. Hence, in this project, we will build a floating proto-architectural system, consisting of a set of simple pre-defined modules which can be assembled, re-assembled and assembled again in different configurations by the end users (citizens) on-site, leading to a diverse number of more complex architectural and spatial variants. Water, as a key environmental and architectural feature of a given space, will serve as a medium for adaptability, flexibility and interaction with the city. Our proto-assembly will behave like an ancient FISH TRAP; but this time in London, in waters of Thames; our novel fish trap will harness latest material, technological and computational achievements and digital fabrication methods together with robust architectural design practices. The users will transform the old design idea of simple fish trap to a unique proto-architecture.

Interactive Urban Synthesis

In this paper, we present a method for generating fast conceptual urban design prototypes. We synthesize spatial configurations for street networks, parcels and building volumes. Therefore, we address the problem of implementing custom data structures for these configurations and how the generation process can be controlled and parameterized. We exemplify our method by the development of new components for Grasshopper/Rhino3D and their application in the scope of selected case studies. By means of these components, we show use case applications of the synthesis algorithms. In the conclusion, we reflect on the advantages of being able to generate fast urban design prototypes, but we also discuss the disadvantages of the concept and the usage of Grasshopper as a user interface.

Interactive Urban Synthesis: Computational Methods for Fast Prototyping of Urban Design Proposals

In this paper, we present a method for generating fast conceptual urban design prototypes. We synthesize spatial configurations for street networks, parcels and building volumes. Therefore, we address the problem of implementing custom data structures for these configurations and how the generation process can be controlled and parameterized. We exemplify our method by the development of new components for Grasshopper/Rhino3D and their application in the scope of selected case studies. By means of these components, we show use case applications of the synthesis algorithms. In the conclusion, we reflect on the advantages of being able to generate fast urban design prototypes, but we also discuss the disadvantages of the concept and the usage of Grasshopper as a user interface.

Interactive Urban Synthesis: Computational Methods for Fast Prototyping

In this paper, we present a method for generating fast conceptual urban design prototypes. We synthesize spatial configurations for street networks, parcels and building volumes. Therefore, we address the problem of implementing custom data structures for these configurations and how the generation process can be controlled and parameterized. We exemplify our method by the development of new components for Grasshopper/Rhino3D and their application in the scope of selected case studies. By means of these components, we show use case applications of the synthesis algorithms. In the conclusion, we reflect on the advantages of being able to generate fast urban design prototypes, but we also discuss the disadvantages of the concept and the usage of Grasshopper as a user interface.