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Record W7111784105

Towards the 3rd dimension of urban transport: Is the upcoming model of advanced urban mobility just another aircraft network?

2025· article· en· W7111784105 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsAviationCivil aviationEuropean unionDimension (graph theory)Agency (philosophy)Air traffic controlAviation safetyLiabilityAviation law
DOInot available

Abstract

fetched live from OpenAlex

European cities are increasingly facing challenges such as traffic congestion, environmental pressures, limited spatial resources, and rising demands for mobility. Urban Air Mobility (UAM), facilitated by electric vertical take-off and landing aircraft (eVTOL) and other unmanned aircraft systems (UAS), is emerging as a potential solution to these issues by adding a third dimension to urban transport. While technological advancements in this area are progressing rapidly, the existing legal framework remains fragmented and inadequately adapted to the unique conditions of low-altitude, on-demand air operations over EU cities. This dissertation explores the legal implications of integrating UAM into urban environments across Europe. It examines how UAM fits within current mobility concepts, evaluates its operational interactions with the European Union and international aviation law, and assesses whether existing regulations are sufficient for large-scale deployment. Key topics discussed include aviation safety and certification, airspace access and the related questions of municipal or regional airspace sovereignty, the legal status of vertiports, and liability frameworks under the Montreal and Rome Conventions, as well as EU passenger regulations. The influence of important institutions, such as the European Union Aviation Safety Agency (EASA), EUROCONTROL, and the International Civil Aviation Organization (ICAO), is analysed in relation to shaping future regulatory paths. Through doctrinal legal analysis and case studies of Hamburg and Astypalaia, this dissertation identifies significant gaps in the current regulatory system. It argues that existing frameworks only partially address UAM and that a coherent, multifaceted approach is necessary to ensure safety, legal certainty, and public acceptance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.209
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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