Nowadays autonomous cars are a point of contention in a variety of realms. Upcoming true autonomy in vehicles which is to bring along different innovations such as electrification, sharing economy, and connectivity is believed to bring new meanings and opportunities into our lives. Although numerous research has been done on the technical parameters in order to attain complete autonomous mobility systems, there is a restricted amount of study conducted to understand the human-centered design challenges. How people will perceive, engage with, and what meanings they will attach to fully autonomous mobility systems are ambiguous subjects at the moment. Thus, this research study aims to remove this ambiguity by gaining knowledge of the new set of meanings that people attach to future mobility with the focus on fully autonomous vehicles by understanding the overall perception as well as unearthing new meaningful opportunities so that the upcoming design community of AVs can prioritize particular characteristics of the vehicles to align with such meaningful opportunities. Lastly, the new metaphors are targeted to extract and visualize for the sake of internalizing the acquired insights and getting robust inspiration for the new potential use scenarios. In order to achieve these objectives, the Zaltman Metaphor Elicitation Technique (ZMET), which could unearth the deep insights that are based on the core meanings, and the Design for Meaning Framework of Giacomin (2017), which provides a clear structure and effective clustering of data, will be applied.
Oggigiorno le auto autonome sono un punto di contesa in una varietà di regni. Imminente vera autonomia nei veicoli che è quello di portare con sé diverse innovazioni come l'elettrificazione, sharing economy, e la connettività si crede di portare nuovi significati e opportunità nella nostra vita. Sebbene siano state fatte numerose ricerche sui parametri tecnici al fine di raggiungere sistemi di mobilità autonoma completi, esiste una quantità limitata di studi condotti per comprendere le sfide di progettazione centrate sull'uomo. Il modo in cui le persone percepiranno, interagiranno e quali significati attribuiranno ai sistemi di mobilità completamente autonomi sono argomenti ambigui al momento. Pertanto, questo studio di ricerca mira a rimuovere questa ambiguità acquisendo conoscenza del nuovo insieme di significati che le persone attribuiscono alla mobilità futura con l'attenzione sui veicoli completamente autonomi comprendendo la percezione generale e scoprendo nuove opportunità significative in modo che la prossima comunità di design di AVs possa dare priorità a particolari caratteristiche dei veicoli per allinearsi a tali opportunità significative. Infine, le nuove metafore sono mirate a estrarre e visualizzare per interiorizzare le intuizioni acquisite e ottenere una solida ispirazione per i nuovi potenziali scenari di utilizzo. Per raggiungere questi obiettivi, verranno applicate il Zaltman Metaphor Elicitation Technique (ZMET), che potrebbe portare alla luce le profonde intuizioni che si basano sui significati principali, e il Design for Meaning Framework di Giacomin (2017), che fornisce una struttura chiara e un efficace clustering di dati.
Design for meaning framework for future mobility with a focus on fully autonomous vehicles
Yagsan, Ayse Selin
2020/2021
Abstract
Nowadays autonomous cars are a point of contention in a variety of realms. Upcoming true autonomy in vehicles which is to bring along different innovations such as electrification, sharing economy, and connectivity is believed to bring new meanings and opportunities into our lives. Although numerous research has been done on the technical parameters in order to attain complete autonomous mobility systems, there is a restricted amount of study conducted to understand the human-centered design challenges. How people will perceive, engage with, and what meanings they will attach to fully autonomous mobility systems are ambiguous subjects at the moment. Thus, this research study aims to remove this ambiguity by gaining knowledge of the new set of meanings that people attach to future mobility with the focus on fully autonomous vehicles by understanding the overall perception as well as unearthing new meaningful opportunities so that the upcoming design community of AVs can prioritize particular characteristics of the vehicles to align with such meaningful opportunities. Lastly, the new metaphors are targeted to extract and visualize for the sake of internalizing the acquired insights and getting robust inspiration for the new potential use scenarios. In order to achieve these objectives, the Zaltman Metaphor Elicitation Technique (ZMET), which could unearth the deep insights that are based on the core meanings, and the Design for Meaning Framework of Giacomin (2017), which provides a clear structure and effective clustering of data, will be applied.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/188438