A Parametric Framework to Assess Generative Urban Design Proposals for Transit-Oriented Development

Transit-oriented development (TOD) is a topic that is currently much discussed by architects. Besides discussed by architects, TOD is also much considered by people of various disciplines, such as urban designer, urban planner, property developer, policy developer, etc. The TOD concept understood by architects may be different from the one understood by people of other disciplines. This article compares the TOD concept followed by (candidates of) architecture graduates with the TOD concept that is discussed by people of different disciplines. This article examines the TOD concept that is understood and applied to the architectural design of three architecture graduate candidates with the state of the art of the TOD concept. The comparison is carried out through direct observation of the architectural designing process of the three candidates and reading of the articles written by the candidates recording and summarizing their designing process and the rationales of their designs. It is found that the candidates are very familiar with the regional physical design aspect of TOD (i.e., land-use, density and street network) but are not very familiar with other elements (i.e., residents’ mobility, built environment development staging, and transit and property market and development financing). While the candidates applied TOD principles on land-use, density, and street network in their designs, they did not apply TOD principles on the mentioned other aspects. This article shows the TOD concept as understood by architecture graduates and the understanding’s position within the state of the art of the TOD concept; this article may serve as the shared footing for people of various disciplines to plan and design TOD.

New developments in Artificial Intelligence (AI) and digital ubiquity bring revelations of emerging smart cities. However, urban designers are particularly reluctant to become digital and use software that automatically generates cities. Instead, they return to traditional design skills such as creating scale models, sketching, notations and drafting. There is an increasing advocacy for design to a human scale, placemaking and liveable cities. This viewpoint asks questions about the application of AI and generative algorithms in digitizing urban design practices. It reflects on the possibilities of conjoining urban morphology and design theory into City Information Modelling (CIM) as a new digital tool for urban designers and reveals challenges in the ongoing development of new CIM software. Urban designers work within intricate design worlds with toolboxes that consist of customized design elements and symbologies. The design worlds consist of elements, rules and patterns and they act as holding environments for their unique diagrammatic design knowledge. CIM and AI should understand design worlds with customized toolboxes and provide help to automate repetitive behaviour patterns while designing.

Public transportation ridership and walkability of urban district can be enhanced through high quality of TOD(Transit Oriented Development) elements. Generally, TOD have been evaluated several physical components such as the diversity of land use pattern, accessibility of public transportation and aspects of urban design around the station area. Especially, Spatial characteristics of TOD planning elements have many potential dependent when considering the characteristics of Rail Station-Influenced Area Development which is performing around subway station. Therefore, researchers should be considering the variation of spatial properties for planning elements according the set of spatial area and their socioeconomic factors. However, existing many cases related TOD does not consider about this point. In this paper, the changes of TOD characteristics were analyzed by different spatial units surrounding subway station in Busan Metropolitan City. Multiple Regression Analysis was performed for an investigation of effective spatial unit of TOD planning elements in this area using subway ridership data. In addition, the application validity of socioeconomic variables was examined through a comparative analysis of regression results with the multiple regression that implied only physical TOD elements. As the result, the variation of spatial properties for TOD planning elements according to the set of spatial unit was found. Furthermore, the specific spatial unit to applicable TOD elements in this area was derived. And the multiple regression model which added socioeconomic variables was derived more improved estimate results than the multiple regression model that implied only physical TOD elements. KEYWORDS : Transit Oriented Development(TOD), TOD Planning Elements, Spatial Characteristics, Subway Ridership

Residential dissonance in TOD neighborhoods

Planning of transit-oriented development is acceptable among urban and transport planners as an urban form strategy to reduce automobile dependency, thus promoting transport sustainability. Apart from the mixed land use, high density and the “smart growth” philosophy behind the transit-oriented development concept which offer potential for a sustainable built environment, the impacts of transit-oriented development on the formation of sustainable communities have not yet been thoroughly studied. This paper aims to assess a rail-based transit-oriented development in Hong Kong for the formation of a sustainable community. A new town highly integrated with the transit-oriented development concept is studied, with a focus on its achievements and challenges in promoting transport and urban sustainability through greener travel, mixed land use development, as well as other daily life experiences altered by the transit-oriented concept, such as liveable streets and fair access to daily opportunities. The...

This paper focuses on how to solve the demand of how to quickly explore more urban space design and layout in terms of the conservation and reuse of historical blocks under computer-aided design technology. Referring to urban inductive patterns, the author establishes an urban space design grammar of historical districts based on shape grammar and pattern language. It forms a complete generative urban space design method involving morphological analysis, rule-making, and scheme generation. Furthermore, taking the typical Russian-style historical block along the Chinese Eastern Railway—the historical district in front of Anda Station as an application example—this paper completed the generative urban space design process of block redevelopment and environmental reconstruction, which, using computer-aided technology, was under the premise of protecting the original historic block fabric. The final two group results of the experimental plot and the other plots of the historical district show that this method can quickly and accurately generate lots of urban space design schemes that meet the designers’ pre-thinking, and these schemes can be modified by real-time calculation and interactive operation.

Additive manufacturing (AM) is a “game-changing” digital fabrication technology that can fundamentally alter the way products are designed and manufactured. In nuclear engineering, the application of additive manufacturing can enable advanced reactor designs with better performance, lower cost, and quicker deployment. To exploit the maximum potential of additive manufacturing, design for additive manufacturing (DfAM) is needed, DfAM can leverage the complexity freedom offered by additive manufacturing technology to break traditional design constraints and achieve enhanced performance. Generative design, one of the key technologies in DfAM, is an iterative exploration method using AI-driven algorithms to generate a series of design solutions that meet specified constraints. In this work, a generative design platform for micro-reactors is developed based on DASSULT SIMULIA Isight. To simulate and analyze the multi-physics performance of the reactor design, various multi-physics simulation codes are integrated on this generative design platform, including RMC for neutron physics analysis, ANSYS Fluent for computational fluid dynamics analysis, and ANSYS Mechanical for structural mechanics analysis. A multi-objective optimization method is used to explore geometric parameters and fuel configurations to achieve better neutronics, thermal-fluidics, and structural mechanics performance. The generative design solution is a 4 MW helium-cooled nuclear reactor which includes 3D-printed silicon carbide (SiC) matrix embedded with tri-structural isotropic (TRISO) particle fuel. Helium at 3 MPa is chosen as the coolant, and the cross-shaped coolant channels are distributed within the matrix to remove the heat generated by fission. According to the multiphysics analysis, the reactor has a initial keff of 1.0571, power peaking factor FQ of 1.50, and operating lifetime of 1200 EFPD (Effective Full Power Days), with a maximum temperature of 1331 K and a peak thermal stress of 141.3 MPa. The generative design method and platform provide a systematic and efficient approach for the design of additively manufactured micro-reactors, and the generative design solution demonstrates the feasibility and effectiveness of the proposed method.

Transit-oriented development in a high-density city: Identifying its association with transit ridership in Seoul, Korea

Doha, the capital of the State of Qatar, has seen rapid growth in recent years, resulting in challenges that can be addressed through sustainable urban design strategies. Such approaches, including Transit-Oriented Development, aim to provide compact urban forms with mixed-use development enabling easy access to the city’s transit services. In light of such objectives, and with the 2022 World Cup being hosted in Qatar, the government has invested heavily in its public transportation system and in implementing Transit-Oriented Development. This work presents an analysis of the current status of Transit-Oriented Development in the knowledge hub in Doha known as Education City. A case study methodology was used, which included site observation, photographic documentation, mapping, and statistical analysis based on recent census data. The analysis shows that the use of public transportation throughout the site is relatively low, largely due to the region’s hot climate and the local mobility culture, in which there is a general preference for private vehicle use. The culmination of this investigation is a master plan for the study area, which foresees further enhancement of the area while still holding to the aims of Transit-Oriented Development. To this end, key recommendations for modifying the prevailing mobility culture are suggested, such as increasing the availability of multimodal transportation in order to improve public transportation functionality and modifying certain aspects of the public transportation system so that it is convenient and comfortable, even during periods of very hot weather. The findings of this study highlight the potential of urban design to change people’s behavior and increase awareness of multimodal transport options.

Human experience in an architectural space is defined as the state of mind that is reflected on their physiological, emotional, and cognitive statuses. Ergonomic data, as an objective manifestation of quantifiable signals generated by the human body during specific spatial perception processes, serves as a vital foundation for spatial evaluation and guidance for optimization. Electroencephalogram (EEG) signals, as quantifiable sensory indicators directly arising from the interaction between individuals and external stimuli, hold substantial potential as a data-driven force and as a means of optimization assessment in the study of generative design. Although existing research has effectively established a unidirectional relationship between EEG and spatial-environment assessment, there is still a notable deficiency in addressing the creation of a two-way, mutually informative feedback mechanism. This study investigates the applicability of EEG signals as a data-driven basis for generative design across universal methods. It delves into various scales and scenarios of digital design, from the microscopic to the macroscopic, encompassing planar and volumetric visual elements, the design of architectural spatial environmental characteristics, and urban space design grounded in human perceptual sightlines. The research examines the viability and appropriateness of an interactive generative design method based on form generation, predicated on human-factor physiological data exemplified by EEG signals. This paper initially conducts a methodological and tool-based examination of current research in ergonomics-driven design and the use of EEG for design assessment, thereby discussing the objective feasibility of employing EEG in interactive generative design. Subsequently, the study establishes an integrated data flow system encompassing multiple hardware and software components to form a comprehensive workflow. Following this setup, empirical studies based on this method are conducted at different scales of application, yielding corresponding form-generative outcomes. Finally, this paper substantiates the rationality and feasibility of this framework in multi environment design domains.

Establishing the conditions for effective transit-oriented development in China: the case of Dalian

There has been a boom in American rail transit construction in the past two decades. That new investment has prompted the question of what planners can do to support rail transit. One popular answer has been transit-oriented development (TOD), increasingly described as a comprehensive strategy for rail-based land-use planning throughout an urban area. This is most clearly illustrated by Bernick and Cervero’s (1997) description of how such projects can link together to create “transit metropolises” where rail is a viable transportation option for many of the region’s residents. In addition, TOD provides an opportunity to examine the regulatory issues discussed in chapter 6, both because it is an explicit attempt to use urban design as transportation policy and because the intergovernmental issues are especially stark in relation to these developments. Having discussed how travelers behave in the first part of this book, we now ask what we know about how cities behave. Stated in general form, the question is rather broad. It concerns the process by which cities and other land-use authorities decide where to put streets, how to structure the local hierarchy of streets, when to develop more or less densely, how to position employment centers relative to residential areas, and so on. Still, the feasibility of land-use plans with transportation goals depends critically on how such authorities behave. Any discussion of the effectiveness of these strategies must address both how communities plan for transportation and how travelers respond to those plans. The primary transportation goal of TOD generally, as currently practiced, is to coordinate land-use policies to support rail transit. In particular, focusing both residential and commercial development near rail transit stations is aimed at increasing rail ridership (e.g., Bernick, 1990; Bernick and Hall, 1990; Calthorpe, 1993; Cervero, 1993; Bernick and Cervero, 1997). Some evidence suggests that residents near rail transit stations are two to five times more likely to commute by rail when compared with persons living elsewhere in the same urban area (Pushkarev and Zupan, 1977; Bernick and Carroll, 1991; Cervero, 1994d).

Continuous urbanization and climate change degrade urban living conditions. Nature-based solutions in architectural and urban design offer promising remedies but are often hindered by time, cost, and early design phase challenges. To address this, we present a Generative Design System framework utilizing AI-generated images and learning-to-rank algorithms. This system generates numerous image solutions to inspire architects and urban planners, significantly accelerating early design stages. To manage the overwhelming volume of images, we introduce a dilemma-based learning approach that employs learning-to-rank and smart bubble sorting algorithms to prioritize images based on user preference. A case study demonstrates the framework’s potential, providing valuable insights into its application, benefits, and limitations in urban design.

This paper puts forward some reflections on the great change of thoughts and mythologies in urban design by technological breakthrough an presents the application of artificial intelligence in urban design. Firstly, it reviews and rethinks on the traditional philosophical bases and original thinking paradigms in urban design, facing up to the limitations and problems of existing design methods. Then by using philosophy of new materialism, new technologies such as machine learning and new data represented by multi-source urban data those having emerged in recent years in order to clarify the possibility of new technologies for urban analysis and design simulation. In particular, convolution neural network has been used to make a large-scale and fine discriminant on the style of urban texture and land use classification. Finally, based on discussions, the paper further clarifies the main direction of current research, which is the possibility of artificial intelligence intervening in urban complex systems and new technologies for urban analysis, designs and simulations. The authors believe that these explorations not only provide more accurate and intuitive analysis in research methods, but also provide the possibility to innovate existing design thoughts and methods by applying artificial intelligence technology to serve urban design research.

Human settlement is associated with shelter for the people and their daily needs (employment, recreation including other activities) which influence their travel behaviour. Furthermore, the provision of housing near the transportation system is significant to enable people to reach their desired destinations. This paper aims to explore how housing provision In Transit-Oriented Development (TOD) areas contributes towards achieving sustainable development objectives by examining the relationship between TOD, housing and sustainable development. Transit- oriented development concepts and principles including the implementation of such a concept towards sustainability will be elaborated based on evidence found in related articles from the past research. Thus, the integration of key components such as transportation and land-use are the pre-requisites and must be supported by a comprehensive plan, good governance and, coordination between agencies at federal, state and, local levels towards ensuring the success of TOD objectives. However, such integration for TOD planning, especially in existing urban areas, remains a challenge. The challenges include existing urban areas with limited space to accommodate housing in the area. The study conducts qualitative research and semi-structured interview with nine (9) respondents who were selected based on their profession and position in their respective organisations. This paper will substantiate the above claims and reinforce the idea of why planning for housing in TOD areas is important in supporting sustainable development objectives.