The vibrotactile modality has great potential for presenting takeover requests (TORs) to get distracted drivers back into the control loop. However, few studies investigate the effectiveness of directional vibrotactile TORs. Whether TORs should be directed toward the direction of hazard (stimulus-response incompatibility) or the direction of avoidance action (stimulus-response compatibility) remains inconclusive. The present study explored the impact of directional vibrotactile TORs (toward-hazard, toward-action, and non-directional) on takeover performance. The influences of TORs lead time (3 s, 4 s, 6 s, and 8 s) and non-driving related tasks (NDRTs) (playing Tetris games and monitoring the road) on the effect of directional TORs were also probed. A total of 48 participants were recruited for our simulated driving study. Results showed that when drivers were engaged in NDRTs during automated driving, directional TORs were more effective than non-directional TORs. Specifically, at the lead times of 6 s and 8 s, both toward-hazard and toward-action TORs could shorten steering response times, compared with the non-directional TORs. At the lead times of 3 s and 4 s, toward-action TORs were more beneficial, as the maximum lateral acceleration was smaller than toward-hazard and non-directional TORs. However, when drivers monitored the road during automated driving, no obvious difference existed between directional and non-directional TORs, regardless of how long the lead time was. The findings in the present study shed light on the design and implementation of the tactile takeover system for automobile designers.

Automated Shuttle buses (ASB) are considered an essential and sustainable direction for the future application of autonomous driving technology in public transportation. As the driver’s role gradually decreases and disappears, the Human–Machine Interface (HMI) for information exchange and communication between users and ASB takes a more prominent role and progressively becomes a hotspot in research. However, the unpredictability and complexity of autonomous driving, an exceptionally fast-growing technology, have hindered its future study. This work first reviewed related literature in three categories: internal, external, and station of the ASB. Secondly, the importance of systemic and speculative design is affirmed by exploring existing HMI designs for ASB. Thirdly, the concepts for ASB resulting from three parallel workshops were analyzed. Finally, online questionnaires and interviews completed the critical reflection and discussion. The results show that the introduction of tools and methods related to systemic and speculative design into the design process of the HMI for ASB may help designers to think critically about the future uncertainty of ASB and to deal with the complexity of the system.

Automated shuttle buses entail adopting new technologies and modifying users’ practices, cultural and symbolic meanings, policies, and markets. This results in a paradigmatic transition for a typical sociotechnical system: the transport system. However, the focus of the extant literature often lacks an overall vision, addressing a single technology, supply chain, or societal dimension. Although systemic design can manage multiple-level and long-term transitions, the literature does not discuss how systemic design tools can support implementation. This paper takes the four strategies proposed by Pereno and Barbero in 2020 as the theoretical framework to fill this literature gap, discussing the specific systemic design methods applicable to the design of automated shuttle bus systems. A six-week workshop to facilitate the exploration of future autonomous public transportation is taken as a case study. The systemic design approach was applied to enrich the Human–Machine Interaction (HMI) and functional architecture of automated shuttle buses.

There is increasing interest of design for paradigmatic and sociotechnical changes, in which the significance of actor is recognized. However, design studies that aim to connect actors at the micro level and sociotechnical systems at the macro level is limited. Based on institutional theory in sociotechnical theory, this paper proposes reflexivity as a useful concept to be associated with matters of scale in Design. Based on literature review, we explore the ways “cultivating reflexivity” has been applied in critical design, norm creative innovation and service ecosystem design. This preliminary work seems to suggest an evolution in the application of reflexivity, from a focus on individuals and their own critical attitudes, to the facilitation of a more reflexive design process to the facilitation of collective feedback loops of reflexivity and reformation of institutions and their socio-material manifestations, pointing toward a very relevant area of study for Design and sociotechnical transitions.

Postphenomenology has become increasingly influential in HCI for analyzing technologically mediated experience. However, existing approaches primarily focus on discrete human–technology relations, offering limited support for articulating how mediation is organized within complex technological configurations. Drawing on Robert Rosenberger’s notion of the field of awareness, this paper introduces the Mediation Composition Diagram (MCD), an analytical diagrammatic tool for mapping configurations of technological mediation across mediation granularities. Rather than treating artifacts as isolated units, the MCD conceptualizes experience as a compositional field in which mediation relations are foregrounded, backgrounded, and distributed differentially within situated awareness. Building on concepts of transparency, forefronting, and field composition, we develop a visual grammar for articulating these configurations. The approach is illustrated through an automated driving case, demonstrating how different configurations reorganize the driver’s field of awareness. The MCD contributes a field-oriented analytical perspective for postphenomenological HCI design research in complex technological environments.

Due to the emergence of future transportation technologies represented by autonomous driving, people's manual driving will be transformed into a state where people and vehicles drive together, or as a term used in this PhD research: co-driving, which implies that we need to pay attention to the impact of the artificial agency of vehicles on the sense of agency of drivers. In addition, the traditional state of kinesthetic integration of driver and car in driving is considered an important source of driving pleasure (Sheller, 2004), and the prominence of car agency means that the agency involved in the activity of driving will be redistributed, which will break this driver-car assemblage (Dant, 2004, 2014) in driving practice (Shove et al., 2012). At the same time, intelligent & connected vehicles are also thought to offer increasingly multisensory, multimodal interactive experiences (Tan et al., 2020), which may in part also provide design materials for innovative new patterns of people's driving pleasure. This PhD research focuses on the above-mentioned future driving scenarios and aims to draw on a combination of methods from Reflective Lifeworld Research (Dahlberg et al., 2008), Anticipatory Ethnography (Lindgren et al., 2021; Lindley et al., 2014) and Research through Design (Zimmerman et al., 2007) to explore: 1. How does access to driving pleasure correlate with driver's need for sense of agency in different driving contexts with/in autonomous vehicles of different levels of automation? 2. How can we design for people's driving pleasure in the future co-driving practice based on the above understanding? Taking a practical approach to conducting this PhD study, the focus would be on the so-called smart cockpit (Sun et al., 2018) as the context of human-machine interface (HMI). As such, this PhD aims to generate a guideline/set of principles on designing for future car HMI for driving pleasure with a focus on the driver's sense of agency in different driving conditions with corresponding design tactics.