Planning for Connected, Autonomous and Shared Mobility: A Synopsis of Practitioners’ Perspectives
Bibliographic record
Abstract
This paper contributes to a growing discussion on how communities plan to prepare for new mobility opportunities offered by technological innovations, specifically shared mobility services, electric vehicles, connected and autonomous vehicles, and Mobility as a Service. Literature in this field predominantly concentrates on technology and operation, market research and impact assessment. There is a clear gap in understanding how practitioners anticipate the planning considerations and research needs to prepare for the transformation of the transportation system. Taking a participatory approach, this research attempts to fill this gap through focus group sessions that capture the perspectives of practicing planners. The issues identified by the participants of this study include regulations/policy for emerging technologies, standardization of infrastructure design, rethinking land use planning, and foreseeing economic benefit and equity issues. This study reveals a set of planning considerations ranging from infrastructure provisions in the short-term to an adaptive approach in writing policy for the long-term. Given the uncertainty of newer technologies, the participants emphasized that practitioners need more information, such as the evolution of technologies, land use implications and design potentials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".