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This paper presents a digital online tool and interaction process that supplies algorithmic analysis and predictive simulation for early-stage urban design proposals within the framework of public competitions. Specifically, the system supports the decision-making of two user groups: 1) planners in the process of developing urban designs proposals and 2) competition juries in evaluating those proposals. The system provides instant assessment of the design solutions' environmental and spatial impact regarding selected target criteria such as noise propagation or pedestrian accessibility. Enabling the easy testing of functional programs and the identification of feasible trade-offs between multiple design targets, the system supports rapid design iterations as well as the objective evaluation of proposals. Applied for the first time within an innovative tender format for a new residential and business district in Hamburg, Germany, the new toolset paves the way towards a more holistic and interactive form of sustainable urban design.

A fundamental aspect of well performing cities is successful public spaces. For centuries, understanding these places has been limited to sporadic observations and laborious data collection...

A combination of Telecom tracking data, Instagram posts, and a summary of data extracted from person-counting sensors and vehicle parking records were utilized to simulate and evaluate scenarios transferring cruise passengers from Hamburg Central Station to several cruise terminals.

Streetscape visualizations are necessary for the understanding and evaluation of urban design alternatives. Alongside blueprints and textual descriptions, these design aids can affect city-form, building-codes and regulations for decades to come. Yet despite major advancements in computer graphics, crafting high-quality streetscape visualizations is still a complex, lengthy and costly task, especially for real-time, multiparty design sessions. Here we present DeepScope, a generative, lightweight and real-time HCI platform for urban planning and cityscape visualization. DeepScope is composed of a Generative Neural Network (DCGAN) and a Tangible User Interface (TUI) designed for multi-participants urban design sessions and real-time feedback. In this paper we explore the design, development and deployment of the DeepScope platform, as well as discuss the potential implementation of DeepScope in urban design processes.

Harbors are complex sociotechnical systems in which several agents are involved. The Port City Model (PCM) is a project that investigates multimodal land transportation related to cruise tourism, focusing on comfort and efficiency from the user perspective. To do so, it combines data analysis and visualization with simulation of future scenarios. The outcome is a software tool running on an interactive hardware platform that simplifies decision-making and facilitates dialogue among the stakeholders involved in the optimization of cruise passenger routes planning. This paper offers a description of the project with special focus on Agent-Based simulations to model flows and routes linking the Hamburg Central Station to different Cruise Terminals.

This paper describes the conception, development and deployment of a novel HCI system for public participation and decision making. This system was applied for the process of allocating refugee accommodation in the City of Hamburg within the FindingPlaces project in 2016. The CityScope a rapid prototyping platform for urban planning and decision making offered a technical solution which was complemented by a workshop process to facilitate effective interaction of multiple participants and stakeholder groups. This paper presents the origins of CS and the evolution of the tangible user interface approach to urban planning and public participation. It further outlines technical features of the system, including custom hardware and software in use, utilization in real time as well as technical constraints and limitations. Special focus is on the adaptation of the CS technology to the specific demands of Hamburg FP project, whose procedures, processes, and results are reflected. The final section analyzes success factors as well as shortcomings of the approach, and indicates further R&D as well as application scenarios for the CS., Procedia Computer Science, 9 pages, 2 figures

Vibrant public spaces which consistently attract dense and diverse populations while hosting continuous social activity are an integral part of any successful urban district. The design of such places has motivated the efforts of urban planners and decision makers for centuries. In recent decades, data-driven and analytical approaches to evaluate the performance of public spaces have begun to emerge. In particular, the recent emergence of Location-Based Services data from mobile phones has created opportunities for detailed modelling of urban behavior. Previous applications of such data to urbanism have been exploratory and have occasionally lacked rigorous statistical modelling. In this paper, the relationship between physical and functional characteristics of urban environments and the propensity for dense clusters of activity to form is examined. Activity clusters are identified using a density based clustering algorithm. These clusters are modelled as the realization of an Inhomogeneous Poisson Process (IPP), where the density of the process varies in space in association with the urban features. The IPP intensity was found to be positively associated with amenities such as shopping and entertainment, the availability of parking and bus stops and the presence of natural water features. The intensity was negatively associated with the distance from the city centre and streets and with presence of hotels. Ultimately, this study suggests a methodology of ‘reversed urbanism’, where statistical relationships can offer an evidence-based approach to urban design, planning and decision making.

MIT City Science Group (CS) studies the interaction of social, economic and physical characteristics of urban areas to understand how people use and experience cities with the goal of improving urban design practices to facilitate consensus between stakeholders. Long-established processes of engagement around urban transformation have been reliant on visual communication and complex negotiation to facilitate coordination between stakeholders, including community members, administrative bodies and technical professionals. City Science group proposes a novel methodology of interaction and collaboration called CityScope, a data-driven platform that simulates the impacts of interventions on urban ecosystems prior to detail-design and execution. As stakeholders collectively interact with the platform and understand the impact of proposed interventions in real-time, consensus building and optimization of goals can be achieved. In this article, we outline the methodology behind the basic analysis and visualization elements of the tool and the tangible user interface, to demonstrate an alternate solution to urban design strategies as applied to the Volpe Site case study in Kendall Square, Cambridge, MA.

There has been an increasing interest in designing tangible user interface (TUI) systems in the context of urban planning. However, little has been done in studying the usability of such systems. In this paper, we present an observational study on a collaborative TUI system to examine the usability of the system in the urban planning process and to investigate its effect on stakeholders’ engagement and decision-making. The study suggests that TUIs and physical objects encourage collaboration and communication among stakeholders, which lead to more informative decisions.