VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
From Traffic Modeling to Smart Cities and Digital Democracies
Last Updated: 2026-06-01 11:31:30
Abstract
This seminar will present speakers who discuss the challenges and opportunities arising for our cities and societies with the digital revolution.
Objective
To collect credit points, students must actively contribute and give an individual, circa 20-minute presentation in the seminar on a subject agreed upon with the lecturer. After the presentation, it will be discussed and graded.
Content
This seminar will present speakers who discuss the challenges and opportunities arising for our cities and societies with the digital revolution. Besides discussing questions of automation using Big Data, AI and other digital technologies, we will also reflect on the question of how democracy could be digitally upgraded, and how citizen participation could contribute to innovation, sustainability, resilience, and quality of life. This includes questions around collective intelligence and digital platforms that support creativity, engagement, coordination and cooperation.
Resources
Literature
Dirk Helbing An Analytical Theory of Traffic Flow (collection of papers) Michael Batty, Kay Axhausen et al. Smart cities of the future Books by Michael Batty: How social influence can undermine the wisdom of crowd effect Evidence for a collective intelligence factor in the performance of human groups Optimal incentives for collective intelligence Collective Intelligence: Creating a Prosperous World at Peace Big Mind: How Collective Intelligence Can Change Our World Programming Collective Intelligence Urban architecture as connective-collective intelligence. Which spaces of interaction? Build digital democracy How to make democracy work in the digital age Digital Democracy: How to make it work? Proof of witness presence: Blockchain consensus for augmented democracy in smart cities Iterative Learning Control for Multi-agent Systems Coordination Decentralized Collective Learning for Self-managed Sharing Economies
Learning Materials (Links)
General Information
- Language
- English
- Levels
- DS , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 40
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar | From Traffic Modeling to Smart Cities and Digital Democracies |
|
2 h weekly |
Offered In
-
Wissenschaft im Kontext (Science in Perspective) (In Kursen aus dem Programm “Wissenschaft im Kontext” lernen Studierende, die MINT Fächer der ETH aus der Perspektive der Geistes-, Sozial- und Staatswissenschaften zu reflektieren. Nur die in diesem Abschnitt aufgelisteten Fächer können als "Wissenschaft im Kontext" angerechnet werden.)
-
Typ A: Förderung allgemeiner Reflexionskompetenz (WiK-Kurse werden für Bachelorstudierende nach dem ersten Studienjahr sowie für alle Masterstudierende und Doktorierende empfohlen. Alle WiK-Kurse sind in Typ A gelistet. Bei den unter Typ B aufgeführten Kursen handelt es sich lediglich um Belegungsempfehlungen für bestimmte Departemente.)
-
Typ B: Reflexion über fachspezifische Methoden und Inhalte (Fachspezifische Lerneinheiten. Relevant für alle Studierenden, die sich für diese Kurse interessieren. Diese Lerneinheiten sind alle auch unter "Typ A" aufgelistet, d.h. die Einschreibung ist allen Studierenden möglich.)
-
-