Towards the 3rd dimension of urban transport: Is the upcoming model of advanced urban mobility just another aircraft network?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".