iCity. Transformative Research for the Livable, Intelligent, and Sustainable City

Cycling is an emission-free and healthy mode of transportation. However, the share of cycling in the modal split is still low. Perceived safety during cycling could be a reason for that. The RouteMeSafe application is developed at Stuttgart University of Applied Sciences with the aim of tackling this issue. A safety routing function is supposed to increase the short-term safety of cycling by showing safe paths for cyclists. Long-term safety is supposed to be increased with the feedback function enabling cyclists to share their evaluation of the cycling infrastructure with the city administration. The safety routing function is currently in the design phase and the feedback function in prototype phase. To develop the application user-friendly, target groups for both functions need to be defined and their expectations considered in the development process. Two studies with infrequent and frequent cyclists have been conducted to do so. Study 1, a user experience study based on a student sample, showed that infrequent cyclists could be a target group for the safety routing function and frequent cyclists could be a target group for the feedback function. The latter was confirmed in study 2, a technology acceptance study based on a sample with frequent cyclists of Stuttgart. Future studies on the application should investigate the long-term technology acceptance of the two groups. This could help to find out whether both groups can serve as target groups on the long run.

Mobility planning is rarely individually tailored. Instead people have to make an active effort to adapt standard solutions to their requirements. Routing apps like Google Maps allow for personalization only by saving important places like home and a workplace but do not allow the user to influence the routing suggestions or choice of mode of transport based on preferences, limitations, or situation. It becomes even more difficult when different means of transport are to interact since most routing applications offer very little multimodal optimization aside from the last mile. Thus, the objective of this article is to present a concept for the utilization of artificial intelligence and regression models in order to enable individual and sustainable mobility planning. To achieve this objective, initially existing routing and mobility planning applications are examined and are conceptually expanded in order to outlay the benefits of personalized route planning. The concrete objective alongside with a method for the development of a new solution is summarized. An algorithm fulfilling these objectives based on multiple linear regression is conceptualized. Relevant factors with coefficient are identified, as well as necessary data sources and interfaces. This algorithm is then implemented in a limited prototype as a proof of concept. Finally, this prototype is tested based on a set of mobility scenarios in order to validate the achievement of the defined objective.

The target of emission reduction in Germany requires a turn from petrol/diesel motorized private transport toward emission-free transport solutions. Besides electrified cars, bicycles, scooters, and pedelecs become more and more common: easy to finance, easy to use, fast in town, reliable, and emission-free. Hence, many local authorities intend to force bicycle use significantly. Almost every German citizen owns a bicycle; however, roughly 50% are used less than once a month or not at all.

Bicycle traffic contributes just 11% to Germany’s modal split (amount of moves). Other countries nearby indicate that pedelec movement will become a significant player in people movement. The means of transports are just one side of the medal of the turn to future transport opportunities.

Is it necessary to own vehicles, bicycles, and scooters? There are plenty of scenarios, where private ownership of means of traffic does not solve transport problems and/or lacks of availability at a certain point of need.

How does sharing satisfy local transportation needs? How can sharing of emission-free vehicles contribute to a successful future transportation in Germany? The chapter will focus on a few hints to answer these questions, building on findings of studies and field tests and the view beyond the German horizon.

For intelligent mobility concepts in growing urban environments, positioning of transportation vehicles and generally moving objects is a fundamental prerequisite. Global Navigation Satellite Systems (GNSS) are commonly used for this purpose, but especially in urban environments under certain conditions, they offer limited accuracy due to buildings, tunnels, etc. that can deviate or mask the satellite signals. The use of existing built-in sensors of the vehicle and the installation of additional sensors can be utilized to describe the movement of the vehicle independently of GNSS. This conforms to the concept of dead reckoning (DR). Both systems (GNSS and DR) can be integrated and prepared to work together since they compensate their respective weaknesses efficiently. In this study, a method to integrate different inertial sensors (gyroscope and accelerometer) and GNSS is investigated. Pedelecs usually do not have many inbuilt additional sensors like it is the case in cars; therefore, additional low-cost sensors have to be used. An extended Kalman filter (EKF) is the base of calculations to perform data integration. Driving tests are realized to check the performance of the integration model. The results show that positioning in situations where GNSS data is not available can be done through dead reckoning for a short period of time. The weak point hereby is the calibration of the accelerometer. Inaccurate accelerometer data cause increasing inaccuracy of the position due to the double integration of the acceleration over time.

Work-related mobility currently makes up the biggest share of the total transport volume in passenger transport and is dominated by private motorized vehicles. The paper is based on research about environmentally friendly modes of transportation performed by students on their way to the University of Applied Sciences, Stuttgart, and whether it has an influence on the mobility behaviour of graduates in work and business traffic or not. Another goal was to find out whether or not one’s sustainable mobility behaviour would be maintained throughout the rest of one’s professional life. For this, an online survey was conducted with graduates of the University of Applied Sciences, Stuttgart. The results of the survey confirm a very high sustainability in the field of work-related mobility. Previous studies have only looked at education- and work-related mobility behaviour separately and did not research how or if the former has effects on the latter. The comparison of results from those studies with the information provided by the graduates on their behaviour in occupational mobility also confirms an above-average sustainability.

The combination of freight transport and mobility—also known as cargo-hitching—is a form of delivery that has been implemented in various modes of transport. This concept is already widely used in Europe, Africa and North America in long-distance bus transport and ensures parcel delivery via the cargo compartment of long-distance buses. This paper aims to investigate the acceptance of cargo-hitching in long-distance bus transport in Germany. For this purpose, first the term cargo-hitching is defined, and an overview of cargo-hitching concepts in long-distance bus transport worldwide is given. In the following, the principles of attitudinal acceptance are explained. A modified version of the UTAUT2 model was used as the basis for an empirical study in the form of a quantitative online survey (n = 245). The results provide information about factors influencing acceptance as well as wishes and requirements of potential users. Parts of the UTAUT2 model were verified by regression analysis. It was shown that the variables’ habit, price value, hedonic motivation, performance expectancy and social influence predict the behavioural intention to use cargo-hitching in our sample significantly (p < 0.05). Furthermore, risks, benefits and willingness to pay were determined, which could contribute to the development of a business model. These included measures to improve transparency, security and information flow of the cargo-hitching process.

Critical success factors for the efficient use of electric trucks are the operational range and the total costs of ownership. For both range and efficient use, power consumption is the key factor. Increasing precision in forecasting power consumption and, hence, maximum range will pave the way for efficient vehicle deployment. However, not only electric trucks are scarce, but also is knowledge with respect to what these vehicles are actually technically capable of. Therefore, this article focuses on power consumption and range of electric vehicles. Following a discussion on how current research handles the mileage of electric vehicles, the article illustrates how to find simple yet robust and precise models to predict power consumption and range by using basic parameters from transport planning only. In the paper, we argue that the precision of range and consumption estimates can be substantially improved compared to common approaches which usually posit a proportional relationship between energy consumption and travel distance and require substantial safety buffers.

Energy-efficient heating and cooling systems as well as intelligent systems for energy distribution are urgently required in order to be able to meet the ambitious goals of the European Union to reduce greenhouse gas emissions. The present article is intended to show that intelligent system extensions for the area of heating, cooling and electricity production for the industrial sector can lead to significant increase in efficiency. For this purpose, a simulation study for the expansion of a combined heat and power (CHP) plant with 2 MW thermal output using a 1.4 MW absorption chiller has been carried out. This shows that a heat-controlled CHP unit can significantly increase its running time. A system model was created for the initial situation and validated with existing measurement data. In the second step, this model was expanded to include the ACM module. The simulation was able to prove that in the event of a system expansion, the run time of the CHP unit can be increased by 35%. In addition to then increase of energy efficiency in the supply system, the analysis also focuses on the efficiency of the energy distribution via thermal networks in an industrial environment. The presented paper therefore also highlights the optimization potentials in the operation of thermal supply networks for industrial applications. For this purpose, a mathematical model has been developed which in addition to the components of the thermal network itself also comprises the producers and consumers. The specific construction of thermal networks for the supply of industrial properties requires adapted solutions for the simulation of such systems. Therefore, amongst other things, in the paper, solutions are shown for the modelling of direct flow local heating networks as well as for the operation of a cascade-controlled pump group.

Buildings are accountable for about one third of the greenhouse gas emissions in Germany. An important step toward the reduction of greenhouse gases is to decarbonize the power productions and heating systems. However, in an energy system with a high share of renewable energy sources, large shares of energy have to be stored in summer for the winter season. Chemical energy storages, in this case hydrogen, can provide these qualities and offer diverse opportunities for coupling different sectors.

In this work, a simulation model is introduced which combines a PEM electrolyzer, a hydrogen compression, a high-pressure storage, and a PEM fuel cell for power and heat production. Applied on a building cluster in a rural area with existing PV modules, this system is optimized for operation as a district heating system based on measured and forecasted data. Evolutionary algorithms were used to determine the optimized system parameters.

The investigated system achieves an overall heat demand coverage of 63%. However, the local hydrogen production is not sufficient to meet the fuel cell demand. Several refills of the storage tanks with delivered hydrogen would be necessary within the year studied.

A reliable charging infrastructure for electric vehicles used in individual transport including availability and accessibility is necessary because it contributes highly to the decision of purchasing a BEV (battery electric vehicle). In Germany, charging is mainly done at home; however, parking spots in car parks have the potential to densify charging infrastructure in semi-public spaces. Intelligent car parks represent further developments which add a variety of technologies, energy management tools and value-added services to parking in general. The article addresses the question of technical maturity of charging infrastructures used in intelligent car parks and their marketability. Examples are charging methods such as conductive and inductive charging or various payment options. Pilot projects are described, and possible concepts of charging in intelligent car parks are explained, thereby addressing a growing interest in the subject.

Electromobility has profound economic and ecological impacts on human society. Much of the mobility sector’s transformation is catalyzed by digitalization, enabling many stakeholders, such as vehicle users and infrastructure owners, to interact with each other in real time. This article presents a new concept based on deep reinforcement learning to optimize agent interactions and decision-making in a smart mobility ecosystem. The algorithm performs context-aware, constrained optimization that fulfills on-demand requests from each agent. The algorithm can learn from the surrounding environment until the agent interactions reach an optimal equilibrium point in a given context. The methodology implements an automatic template-based approach via a continuous integration and delivery (CI/CD) framework using a GitLab runner and transfers highly computationally intensive tasks over a high-performance computing cluster automatically without manual intervention.

The safety, proper maintenance, and renovation of tunnel structures have become a critical problem for urban management in view of the aging of tunnels. Tunnel inspection and inventory are regulated by construction laws and must be carried out at regular intervals. Advances in digitalization and machine vision technologies enable the development of an automated and BIM-based system to collect data from tunnel surfaces. In this study, a tunnel inspection system using vision-based systems and the related principles are introduced to measure the tunnel surfaces efficiently. In addition, the main components and requirements for subsystems are presented, and different challenges in data acquisition and point cloud generation are explained based on investigations during initial experiments.

Effective government management, convenient public services, and sustainable industrial development are achieved by the thorough utilization and management of green, renewable resources. The research and the study of meteorological data and its effect on devising renewable solutions as a replacement for nonrenewable ones is the motive of researchers and city planners. Sources of energy like wind and solar are free, green, and popularly being integrated into sustainable development and city planning to preserve environmental quality. Sensor networks have become a convenient tool for environmental monitoring. Wind energy generated through the use and maintenance of wind turbines requires knowledge of wind parameters such as speed and direction for proper maintenance. An augmented reality (AR) tool for interactive visualization and exploration of future wind nature analyses for experts is still missing. Existing solutions are limited to graphs, tabular data, two-dimensional space (2D) maps, globe view, and GIS tool designed for the desktop and not adapted with AR for easy, interactive mobile use. This work aims to provide a novel AR-based mobile supported application (App) that serves as a bridge between three-dimensional space (3D) temporal wind dataset visualization and predictive analysis through machine learning (ML). The proposed development is a dynamic application of AR supported with ML. It provides a user interactive designed approach, presenting a multilayered infrastructure process accessed through a mobile AR platform that supports 3D visualization of temporal wind data through future wind analysis. Thus, a novel AR visualization App with the prediction of wind nature using ML algorithms would provide city planners with advanced knowledge of wind conditions and help in easy decision-making with interactive 3D visualization.

There is increased activity in developing workflows and implementations in the context of urban energy analysis simulation based on 3D city models in smart cities. At the University of Applied Sciences Stuttgart (HFT Stuttgart), an urban energy simulation platform called ‘SimStadt’ has successfully been developed. It uses the CityGML 3D city model to simulate the heat demand, photovoltaic potential, and other scenarios that provide dynamic simulation results in both space and time dimensions. Accordingly, a tool for managing dynamic data of the CityGML models is required. Earlier, the CityGML Application Domain Extension (ADE) had been proposed to support additional attributes of the CityGML model; however, there is still a lack of open-source tools and platforms to manage and distribute the CityGML ADE data efficiently. This article evaluates and compares alternative methods to manage dynamic simulation results of the 3D city model and visualise these data on the 3D web-based smart city application, including the use of SimStadt web services, databases, and OGC SensorThings API standard.

In this chapter, we present an approach of enriching photogrammetric point clouds with semantic information extracted from images of digital cameras or smartphones to enable a later automation of BIM modelling with object-oriented models. Based on the DeepLabv3+ architecture, we extract building components and objects of interiors in full 3D. During the photogrammetric reconstruction, we project the segmented categories derived from the images into the point cloud. Based on the semantic information, we align the point cloud, correct the scale and extract further information. The combined extraction of geometric and semantic information yields a high potential for automated BIM model reconstruction.

Cities face a variety of challenges today. To react on these challenges, especially the design of public space as a space of encounter and negotiation is important. In this context, cooperative planning processes are gaining more and more popularity, as cooperation seems to offer the chance to produce solutions for a diverse urban coexistence and a collective understanding of the common good.

Despite the frequent use of the term, there is yet no clear definition of cooperative planning processes. In this regard, the article analyses the development process of the ‘Österreichischer Platz’ in Stuttgart. The project strategy included an open-ended experimental process over the course of 2 years with a multiplicity of stakeholders. The innovative cooperation of various initiatives, the civil population and representatives of the city administration and politics defines the project as a lighthouse project for urban development in Stuttgart.

According to the World Urbanization Prospects of the United Nations (United Nations, Department of Economic and Social Affairs 2018), about 68% of the overall expected world population is going to live in urban areas and cities by the year 2050. The task of transforming modern cities towards a more sustainable and ecological as well as socially likeable environment touches a plethora of disciplines like transportation, energy infrastructure, architecture, building physics, etc. and poses an intricate challenge for architects, engineers, urban planners and social scientist alike. Thanks to the technological evolution, the realization of smart city concepts and solutions has become a viable option to contribute to this goal in a significant manner. The building envelope as an indispensable part of human dwellings and working space has historically mostly taken the classic functionalities of resembling aesthetic expression and providing physical protection. Recent and upcoming technological developments will enable a shift in the role of the building envelope from its mere classical functionalities towards additional contributions to the sustainability and livability of the environment. The prospects of these contributions range from increasing the thermal and visual comfort of the inhabitants and the surrounding environment by adaptive architectural measures towards potential energy saving by energy harvesting devices and synergetic processing and treatment of material flows of the building to provide conditioned air, preprocessed water and even food. In this short essay, we will elaborate on the phenomenon of smart city in general and the role of the building envelope in the context of modern smart city development and its potential on the improvement on different aspects of life and urban environment.

Indoor temperature is one of the fundamental features of the indoor environment. It can be controlled with distributed IoT sensors, through wireless networks. It affects human indoor environment such as human thermal sensation, productivity at work, buildings’ quality, and several syndrome symptoms. In this study, we focus on the effects of the indoor temperature on the human work productivity and thermal sensation. Our research aims to develop an IoT monitoring tool to manage the challenges in smart buildings by extracting and processing relevant data. It proposes data analysis periodically and integrates newly generated data into the analytical cycle that allows improving human indoor environment.

Controlled natural ventilation in office buildings can ensure the indoor thermal comfort while reducing the life cycle energy consumption for ventilation, compared to mechanical ventilation systems (e.g. HVAC). Natural ventilation is mostly used in moderate climate zones where air conditioning is not a standard. During intermediate seasons, buildings with HVAC systems can additionally use natural ventilation to reduce energy consumption. However, in dense urban areas, natural ventilation can be problematic in terms of acoustic comfort. Here, a box-type window can serve as a compromise between thermal and acoustic comfort. Due to the more complex handling of the box-type window, an automated (electric driven) novel box-type window approach was developed within the imaF project, a part of the iCity initiative. The following article describes the basics of automated natural ventilation, acoustic characterization as well as architectural integration of this window type and the optimization of the airflow through box-type windows. The results show that the proposed geometry can provide sound insulation while providing an appropriate air exchange rate.

Two trends are currently leading to an increased risk of indoor noise pollution. Firstly, urban densification causes traffic noise sources to be closer to the building facades which makes them louder at the facades. Secondly, airtightness of buildings, due to energy regulations, leads to the need of natural or mechanical ventilation to ensure a “healthy” indoor air quality, thereby allowing noise to easily pass from outdoors to indoors. In the case of mechanical ventilation, an additional noise source is also created. This study investigates the risk reduction of an indoor noise problem by optimizing the facade elements regarding sound insulation. Noise levels of different transportation noise sources (cars, trucks, trains) are used to calculate the resulting indoor noise levels after passing through the facade elements. The amount of noise transmitted into the indoors is dependent on the frequency spectra of the sources and of the sound reduction properties of the facade elements. Facade elements such as masonry walls, open windows, and ventilators are investigated and modified regarding their sound insulation properties. Through passive means, the weighted sound reduction index of an open window and an open ventilator was increased by 12 dB and 3 dB, respectively. Also, the indoor self-noise of the ventilator was investigated and reduced for different airflow rates.

With the increasing urban densification, balconies are gaining in popularity as they improve the living quality in homes. From a technical point of view, the thermal insulation between balconies and the building’s façade is state of the art. In Germany, the most popular balcony construction is a reinforced concrete balcony, separated from the building by a thermal insulation element (TIE), which is meant to reduce the thermal energy loss and thus ensure the sustainability of intelligent buildings. The impact sound transmission from balconies, however, is a problem that has not been addressed enough to date. The paper is based on a project of the same name within the iCity research with the main goal of providing acoustic quantities, e.g. an impact sound pressure level difference, for a TIE that can be used to compare the acoustical quality of products and used to predict the impact sound pressure levels within the building using the standard EN ISO 12354-2. Experimental and numerical studies have been carried out on various ceiling-balcony mock-ups without and with TIEs, e.g. by means of experimental modal analysis and validated finite element models, respectively. These studies showed that even doubling the width of the ceiling-balcony mock-up does not change the results significantly, suggesting that the proposed test set-up is suitable for standard testing. The analysis method and results presented here are for only one test set-up with and without a TIE that underwent constructive modifications during the tests. The selected TIE shows an effective sound insulation above 400 Hz and achieves a single-number rated impact sound level difference of \( \Delta {L}_{\mathrm{w}}^{\ast}\approx 10\ \mathrm{dB} \).