TY - JOUR A1 - Xin, Li A1 - Hijazi, Ihab Hamzi A1 - König, Reinhard A1 - Lv, Zhihan A1 - Zhong, Chen A1 - Schmitt, Gerhard T1 - Assessing Essential Qualities of Urban Space with Emotional and Visual Data Based on GIS Technique JF - ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION N2 - Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and more accurate using innovative information techniques that have become available in the era of big data. This study introduces an integrated method based on geographical information systems (GIS) and an emotion-tracking technique to quantify the relationship between people’s emotional responses and urban space. This method can evaluate the degree to which people’s emotional responses are influenced by multiple urban characteristics such as building shapes and textures, isovist parameters, visual entropy, and visual fractals. The results indicate that urban spaces may influence people’s emotional responses through both spatial sequence arrangements and shifting scenario sequences. Emotional data were collected with body sensors and GPS devices. Spatial clustering was detected to target effective sampling locations; then, isovists were generated to extract building textures. Logistic regression and a receiver operating characteristic analysis were used to determine the key isovist parameters and the probabilities that they influenced people’s emotion. Finally, based on the results, we make some suggestions for design professionals in the field of urban space optimization. KW - Stadt KW - Gefühl KW - Geoinformationssystem KW - urban form; Geographical Information System;walking experience; isovists; logistic regression Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170401-30995 ER - TY - JOUR A1 - Knecht, Katja A1 - König, Reinhard T1 - Automatische Grundstücksumlegung mithilfe von Unterteilungsalgorithmen und typenbasierte Generierung von Stadtstrukturen N2 - Dieses Arbeitspapier beschreibt, wie ausgehend von einem vorhandenen Straßennetzwerk Bebauungsareale mithilfe von Unterteilungsalgorithmen automatisch umgelegt, d.h. in Grundstücke unterteilt, und anschließend auf Basis verschiedener städtebaulicher Typen bebaut werden können. Die Unterteilung von Bebauungsarealen und die Generierung von Bebauungsstrukturen unterliegen dabei bestimmten stadtplanerischen Einschränkungen, Vorgaben und Parametern. Ziel ist es aus den dargestellten Untersuchungen heraus ein Vorschlagssystem für stadtplanerische Entwürfe zu entwickeln, das anhand der Umsetzung eines ersten Softwareprototyps zur Generierung von Stadtstrukturen weiter diskutiert wird. T3 - Arbeitspapiere Informatik in der Architektur - Nr. 15 KW - Automatisierung KW - Grundstücksumlegung KW - städtische Strukturen KW - Unterteilungsalgorithmen KW - Computational Design Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160822-26730 UR - http://infar.architektur.uni-weimar.de/service/drupal-infar/Arbeitspapiere ER - TY - CHAP A1 - König, Reinhard A1 - Schmitt, Gerhard ED - Szoboszlai, Mihály T1 - Backcasting and a new way of command in computational design : Proceedings T2 - CAADence in Architecture Conference N2 - It's not uncommon that analysis and simulation methods are used mainly to evaluate finished designs and to proof their quality. Whereas the potential of such methods is to lead or control a design process from the beginning on. Therefore, we introduce a design method that move away from a “what-if” forecasting philosophy and increase the focus on backcasting approaches. We use the power of computation by combining sophisticated methods to generate design with analysis methods to close the gap between analysis and synthesis of designs. For the development of a future-oriented computational design support we need to be aware of the human designer’s role. A productive combination of the excellence of human cognition with the power of modern computing technology is needed. We call this approach “cognitive design computing”. The computational part aim to mimic the way a designer’s brain works by combining state-of-the-art optimization and machine learning approaches with available simulation methods. The cognition part respects the complex nature of design problems by the provision of models for human-computation interaction. This means that a design problem is distributed between computer and designer. In the context of the conference slogan “back to command”, we ask how we may imagine the command over a cognitive design computing system. We expect that designers will need to let go control of some parts of the design process to machines, but in exchange they will get a new powerful command on complex computing processes. This means that designers have to explore the potentials of their role as commanders of partially automated design processes. In this contribution we describe an approach for the development of a future cognitive design computing system with the focus on urban design issues. The aim of this system is to enable an urban planner to treat a planning problem as a backcasting problem by defining what performance a design solution should achieve and to automatically query or generate a set of best possible solutions. This kind of computational planning process offers proof that the designer meets the original explicitly defined design requirements. A key way in which digital tools can support designers is by generating design proposals. Evolutionary multi-criteria optimization methods allow us to explore a multi-dimensional design space and provide a basis for the designer to evaluate contradicting requirements: a task urban planners are faced with frequently. We also reflect why designers will give more and more control to machines. Therefore, we investigate first approaches learn how designers use computational design support systems in combination with manual design strategies to deal with urban design problems by employing machine learning methods. By observing how designers work, it is possible to derive more complex artificial solution strategies that can help computers make better suggestions in the future. KW - Cognitive design computing KW - machine learning KW - backcasting KW - design synthesis KW - evolutionary optimization KW - CAD Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-25996 SP - 15 EP - 25 CY - Budapest ER - TY - JOUR A1 - König, Reinhard A1 - Knecht, Katja T1 - Comparing two evolutionary algorithm based methods for layout generation: Dense packing versus subdivision JF - Artificial Intelligence for Engineering Design, Analysis and Manufacturing N2 - We present and compare two evolutionary algorithm based methods for rectangular architectural layout generation: dense packing and subdivision algorithms.We analyze the characteristics of the two methods on the basis of three floor plan sce- narios. Our analyses include the speed with which solutions are generated, the reliability with which optimal solutions can be found, and the number of different solutions that can be found overall. In a following step, we discuss the methods with respect to their different user interaction capabilities. In addition, we show that each method has the capability to generate more complex L-shaped layouts. Finally,we conclude that neither of the methods is superior but that each of them is suitable for use in distinct application scenarios because of its different properties. KW - Architektur KW - Informatik KW - Kremlas Y1 - 2014 UR - http://www.journals.cambridge.org/abstract_S0890060414000237 N1 - Paper is only available from the journal home page. SP - 285 EP - 299 ER - TY - JOUR A1 - Klein, Bernhard A1 - König, Reinhard T1 - Computational Urban Planning: Using the Value Lab as Control Center JF - FCL Magazine, Special Issue Simulation Platform N2 - Urban planning involves many aspects and various disciplines, demanding an asynchronous planning approach. The level of complexity rises with each aspect to be considered and makes it difficult to find universally satisfactory solutions. To improve this situation we propose a new approach, which complement traditional design methods with a computational urban plan- ning method that can fulfil formalizable design requirements automatically. Based on this approach we present a design space exploration framework for complex urban planning projects. For a better understanding of the idea of design space exploration, we introduce the concept of a digital scout which guides planners through the design space and assists them in their creative explorations. The scout can support planners during manual design by informing them about potential im- pacts or by suggesting different solutions that fulfill predefined quality requirements. The planner can change flexibly between a manually controlled and a completely automated design process. The developed system is presented using an exemplary urban planning scenario on two levels from the street layout to the placement of building volumes. Based on Self-Organizing Maps we implemented a method which makes it possible to visualize the multi-dimensional solution space in an easily analysable and comprehensible form. KW - Computational Urban Design KW - Stadtgestaltung Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26011 SP - 38 EP - 45 ER - TY - CHAP A1 - König, Reinhard A1 - Bauriedel, Christian T1 - Computer-generated Urban Structures T2 - Proceedings of the Generative Art Conference N2 - How does it come to particular structure formations in the cities and which strengths play a role in this process? On which elements can the phenomena be reduced to find the respective combination rules? How do general principles have to be formulated to be able to describe the urban processes so that different structural qualities can be produced? With the aid of mathematic methods, models based on four basic levels are generated in the computer, through which the connections between the elements and the rules of their interaction can be examined. Conclusions on the function of developing processes and the further urban origin can be derived. KW - Computational Urban Design Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160623-26090 SP - 1 EP - 10 CY - Milan, Italy ER - TY - JOUR A1 - König, Reinhard T1 - Computers in the design phase - Ten thesis on their uselessness T1 - Der Computer in der Entwurfsphase - Zehn Thesen zu seiner Nutzlosigkeit JF - Der Generalist N2 - At the end of the 1960s, architects at various universities world- wide began to explore the potential of computer technology for their profession. With the decline in prices for PCs in the 1990s and the development of various computer-aided architectural design systems (CAAD), the use of such systems in architectural and planning offices grew continuously. Because today no ar- chitectural office manages without a costly CAAD system and because intensive soſtware training has become an integral part of a university education, the question arises about what influence the various computer systems have had on the design process forming the core of architectural practice. The text at hand devel- ops ten theses about why there has been no success to this day in introducing computers such that new qualitative possibilities for design result. RESTRICTEDNESS KW - computational design KW - CAD Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26075 ER - TY - CHAP A1 - Chirkin, Artem A1 - König, Reinhard T1 - Concept of Interactive Machine Learning in Urban Design Problems : proceedings N2 - This work presents a concept of interactive machine learning in a human design process. An urban design problem is viewed as a multiple-criteria optimization problem. The outlined feature of an urban design problem is the dependence of a design goal on a context of the problem. We model the design goal as a randomized fitness measure that depends on the context. In terms of multiple-criteria decision analysis (MCDA), the defined measure corresponds to a subjective expected utility of a user. In the first stage of the proposed approach we let the algorithm explore a design space using clustering techniques. The second stage is an interactive design loop; the user makes a proposal, then the program optimizes it, gets the user’s feedback and returns back the control over the application interface. KW - MCDM KW - interactive machine learning KW - urban design KW - multiple-criteria optimization KW - Stadtgestaltung Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26000 UR - http://dl.acm.org/citation.cfm?id=2898365 SP - 10 EP - 13 PB - ACM New York, NY, USA CY - San Jose, CA, USA ER - TY - CHAP A1 - König, Reinhard ED - Martens, Bob ED - Wurzer, G, Gabriel ED - Grasl, Tomas ED - Lorenz, Wolfgang ED - Schaffranek, Richard T1 - CPlan: An Open Source Library for Computational Analysis and Synthesis T2 - 33rd eCAADe Conference N2 - Some caad packages offer additional support for the optimization of spatial configurations, but the possibilities for applying optimization are usually limited either by the complexity of the data model or by the constraints of the underlying caad system. Since we missed a system that allows to experiment with optimization techniques for the synthesis of spatial configurations, we developed a collection of methods over the past years. This collection is now combined in the presented open source library for computational planning synthesis, called CPlan. The aim of the library is to provide an easy to use programming framework with a flat learning curve for people with basic programming knowledge. It offers an extensible structure that allows to add new customized parts for various purposes. In this paper the existing functionality of the CPlan library is described. KW - Architektur KW - Computer KW - CAAD KW - cplan KW - CAD Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160118-25037 SP - 245 EP - 250 PB - Vienna University of Technology CY - Vienna ER - TY - JOUR A1 - König, Reinhard T1 - Die Stadt der Agenten und Automaten JF - FORUM - Architektur & Bauforum N2 - PLANUNGSUNTERSTÜTZUNG DURCH DIE ANALYSE RÄUMLICHER PROZESSE MITTELS COMPUTERSIMULATIONEN. Erst wenn man – zumindest im Prinzip – versteht, wie eine Stadt mit ihren komplexen, verwobenen Vorgängen im Wesentlichen funktioniert, ist eine sinnvolle Stadtplanung möglich. Denn jede Planung bedeutet einen Eingriff in den komplexen Organismus einer Stadt. Findet dieser Eingriff ohne Wissen über die Funktionsweise des Organismus statt, können auch die Auswirkungen nicht abgeschätzt werden. Dieser Beitrag stellt dar, wie urbane Prozesse mittels Computersimulationen unter Zuhilfenahme so genannter Multi-Agenten-Systeme und Zellulärer Automaten verstanden werden können. von KW - Computational Urban Design KW - CAD Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26083 ER -