USING MULTI-LEVEL PROTOTYPING TO SHOWCASE STUDENT MOBILITY DESIGN CONCEPTS IN URBAN CONTEXTS
Notice bibliographique
Résumé
For the past century, cities evolved around car-centricity, where cars existed in uni-disciplinary isolation from urban planning in unchanging street layouts. Recently, urban planners and new paradigms are transitioning cities away from car-centrism to enable inter-modal streets for vehicles that exist today (e.g. bicycles, e-scooters, cars). Simultaneously, new types of vehicles are being designed for future cities, particularly in micromobility, which must be considered as new street layouts are designed. Therefore, new tools to communicate design concepts are required to ensure a multidisciplinary approach between mobility designers and urban planners. In mobility design, to develop vehicle concepts, students traditionally use digital (CAD) and physical prototyping, with virtual and augmented reality (AR and VR) levels recently emerging. These design concept prototypes have different degrees of fidelity, lower early in the process (e.g. small-scale appearance models or full-scale functional mock-ups), while progressively becoming more faithful to the final design (e.g. full-scale appearance models), particularly when creating the final showcase of the design concept. In academia, final mobility design showcases traditionally consist of vehicle-centric presentations where student designers prepare a verbal explanation, while audiences (usually other mobility designers) play a spectator role. The presentation consists of large posters and/or on-screen slide shows (including images, text, and animations), which can include a physical prototype (small-scale high-fidelity appearance model or low-fidelity full-scale mockup). Moreover, audiences are limited to 2D graphic and 3D physical off-scale representations of the vehicle concept with little context. After the presentation, they provide feedback, mostly addressing the vehicle’s design. VR prototypes are emerging for final showcases in mobility design education and allow audiences to transition from spectators to active participants, capable of experiencing aspects of the concept like materiality, user-interactions, and urban context around the vehicle. However, the lack of physicality of this prototyping level can be disorienting because of issues with scale, position, and visibility of the real environment and people. Thus, the low-fidelity physical level is often preferred over the virtual, even when higher-fidelity aspects of the design and the urban context are lost. AR serves as a bridge where the physical mockup audience members are sitting on, matches the environment they can see and touch through the AR cameras, and has VR geometry and interactivity overlayed on top, essentially creating a multi-level prototype experience. This approach also allows mobility designers to showcase their vehicle solutions and planners to contextualize the built environment in a seamless transition between both disciplines. Even though existing prototyping methodologies intend to bridge the physicality and virtuality of design concepts, none use the multi-level prototyping approach of AR (low-fidelity) in addition to VR (mid-fidelity) and 1:1 physical (low-fidelity) to showcase final design concepts to multidisciplinary stakeholders. This paper uses the case study of the final showcase of a Future Mobility Design Undergraduate studio focusing on micromobility. Two student micromobility concepts are demonstrated, and the findings are concluded based on the testimony of stakeholders in the AR/VR and urban development industries, who attended the event and tested the experience.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».