Keynote Lectures

Abstract

Since there is no clear definition of the term “Smart City”, we are confronted with a wide range of connotations and their manifestations as digital city, virtual city, ubiquitous city, interactive city, adaptive city, responsive city, etc. Among the many interpretations, green city and sustainable city play an increasingly popular role. The goal of this keynote is therefore to shed some light on the various opportunities as well as challenges we face when designing and implementing “smart” cities. Our citizen-centered approach connects sustainability to the goal that cities should be self-aware and cooperative as described below.

Smart cities pose new challenges for all stake holders: urban planners, city administration, public and industrial infrastructure and service providers, community organizations, businesses and last, but not least the citizens. There is a need to reflect the current hype about smart cities and technology-driven urban developments. A citizen-centered design approach is necessary for developing citizen-oriented solutions, reconciling people and technology, so that they can gain acceptance by all stake holders involved. We characterize this as moving beyond “smart-only” cities.

The goal of a city should be more than providing infrastructures. The city should be defined and view itself as a cooperation partner supporting its inhabitants. Being cooperative requires also to be self-aware about its status and processes and sharing this knowledge with the citizens. The overall goal is to design a humane, sociable and cooperative city which knows about itself (self-awareness) and to decide which technologies and specific design objectives are appropriate to meet the needs of the citizens. In this context, we propose a Citizen-Cooperative-City-Contract (C⁴) as an approach to address the different design trade-offs.

Due to the central role of “smart” technologies, we must also reflect on the underlying rationale, its implications and challenges. What does “smart” mean? Intelligent? Artificial Intelligence? Automated? Autonomous – with no humans involved? How much should our life depend on smart technologies? How about: keeping the human in the loop and in control?  How about: Smart spaces make people smarter and not more dependent? These open issues require to rethink and redefine the “Smart-Everything” paradigm, we are confronted with in many realms of our environment, indoors in the smart home, outdoors in the smart city, in an industrial context in the smart factory, and in general in our society.

Selected Reference:
Norbert Streitz (2018). Beyond 'Smart-Only' Cities: Redefining the 'Smart-Everything' Paradigm.
Journal of Ambient Intelligence and Humanized Computing. pp. 1 - 22.
Available as First-online: https://link.springer.com/article/10.1007/s12652-018-0824-1

Abstract
In general, the Smart City idea is focusing on the implementation of new technologies (mostly ICT) on the background of specific urban challenges: Climate change and urban competitiveness are used as specific argumentation lines for the introduction of ICT into the city for mitigating emissions and for increasing infrastructure efficiency. Along with the digitization of cities, recently the idea and use of collective intelligence, derived from complex data analysis, came up; and new forms of ‘intelligence’ and value creation are increasingly in academic discussion. Along with this trend, Smart City activities are becoming more specialized in terms of different key fields of urban development and more important regarding local innovative processes.

In this contribution, I want to look at the possibilities how to generate an integrated collective knowledge regarding the energetic transformation of urban neighbourhoods. Beyond the general discussion of understanding, I will describe how Smart City technology in form of a dashboard can help in a place based approach supporting an effective energetic transformation process. Beside its features, the possibilities and obstacles to use such a dashboard in an ‘open innovation’ process for scenario building are discussed. This dashboard was developed in the Austrian project E-Profil: Quartiers-profile für optimierte energietechnische Transformationsprozesse’ subsidized by the Austrian Research Funding Association FFG. Finally, some conclusions regarding the meaning of ‘open innovations’ in the Smart City development will be derived.

Abstract

Autonomous vehicles do not intrinsically improve traffic since they optimize towards reaching their own goals. Cooperative driving, on the other hand, aims for optimizing the collective behavior, thus having the potential to improve the traffic system. Connectivity is instrumental for cooperative driving because traffic participants can express and share their intention more easily and precisely. When combined with vehicle automation, a powerful approach arises for improving traffic efficiency and safety.

A well-known application of cooperative automated driving (CAD) is cooperative adaptive cruise control (CACC) or platooning, which improves traffic throughput by adopting very short intervehicle distances. This is particularly of interest in automated transit systems (people movers) which, when used for first-/last-mile transportation, must have a high transport capacity. Also truck platooning is a promising application because fuel consumption decreases due to reduced aerodynamic drag at short distances. To fully exploit these potential benefits, a platoon needs to be string stable, which refers to attenuation of the effects of disturbances in upstream direction along the platoon. String stability contributes to safety, but it is only a necessary condition, not a sufficient one. To also guarantee safety in the presence of failing communication or common threats such as cutting in of other vehicles, additional measures are required which are only addressed in literature to a limited extent.

Next to ongoing developments in the field of platooning, cooperative automated maneuvering attracts attention to an increasing extent, acknowledging the fact that traffic is not a one-dimensional string of vehicles. Many approaches are still investigated in this field. One such approach relies on explicit decision making, employing so-called interaction protocols; This approach was illustrated by i-GAME, a European-funded project, whereas other projects, such as Autonet2030, adopt an optimization-based approach for path planning.

In summary, CACC and platooning are promising first applications of CAD, but further research and development in the field of safety is required, especially when considering the current world-wide standardization and road approval activities. At the same time, the application domain is extended towards cooperative automated maneuvering, ultimately leading to a truly ‘automated intelligent transportation system’.