Toward Defining Driving Automation from a Human-Centered Perspective

Yang, Ji Hyun; Han, Jimin; Park, Jung‐Mi

doi:10.1145/3027063.3053101

Cited by 9 publications

(11 citation statements)

References 3 publications

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“…Existing frameworks, despite their benefits, have been criticized for being based on detailed technical and functional taxonomies (e.g., [18] [14] [7]), and that they do not provide any basis for design (e.g., [9] [16]). In order to reflect what users are looking for when trying to make sense of the interaction with a DAS, the design work needs to consider the users perception of such systems [1].…”

Section: Discussionmentioning

confidence: 99%

Design for Perception - A Systematic Approach for the Design of Driving Automation Systems based on the Users’ Perception

Novakazi

Eriksson

Bligård

2022

Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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While there is significant potential for driving automation to increase traffic safety and enhance comfort, it is important that these systems are designed in such a way that drivers are supported in building a correct understanding of the system's capabilities and limitations. Hence, it is necessary to understand both the process by which drivers understand a driving automation system and the factors that influence their perception. During three workshops, six practitioners participated in a participatory action research study around a design use case, aiming to enhance mode awareness in a vehicle offering several levels of automation. This facilitated the development of a card deck, which supports practitioners to 1. explore possible solutions driven through a systematic approach, 2. identify areas of improvement through applying the lens of the user, 3. ideate and evaluate design decisions through a guided process. CCS CONCEPTS• Human-centered computing → Interaction design; Interaction design process and methods; User centered design.

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Section: Discussionmentioning

confidence: 99%

Design for Perception - A Systematic Approach for the Design of Driving Automation Systems based on the Users’ Perception

Novakazi

Eriksson

Bligård

2022

Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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“…Even though existing frameworks for describing different levels of automated driving have benefits (Endsley, 2018; Kaber, 2018) they have also been criticized for being based on detailed technical and functional taxonomies (e.g., Seppelt et al, 2018; Yang et al, 2017) or as having too narrow a function allocation approach (e.g., Lee, 2018). Several authors have therefore argued the need for a more human-centric taxonomy of automation types (e.g., Kaber & Endsley, 2004; Jamieson and Skraaning (2018); Seppelt et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…For example Homans et al (2020) conclude, based on a survey, that users’ understanding of automation levels is not in line with the taxonomies, and in another study Seppelt et al (2018) found that consumers had low to moderate understanding of different types of automation and that the proposed taxonomy produced confusion regarding responsibilities. Acknowledging these issues, attempts have been made to decrease users’ confusion, for example by investigating how the names of the DAS are associated with different LoAs (Abraham et al, 2017), by rephrasing the descriptions of responsibilities (e.g., Yang et al, 2017) or by framing the driver’s responsibility in terms of “driving” and “riding” only (Seppelt et al, 2018). The addition to SAE J3016 (SAE International, 2019) aims to describe the LoAs through simpler language and a graphical representation, exemplifying what the driver has to do and what the system does in each automation level.…”

Section: Discussionmentioning

confidence: 99%

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Levels of What?Investigating Drivers’ Understanding of Different Levels of Automation in Vehicles

Novakazi

Johansson

Strömberg

2021

Journal of Cognitive Engineering and Decision Making

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Extant levels of automation (LoAs) taxonomies describe variations in function allocations between the driver and the driving automation system (DAS) from a technical perspective. However, these taxonomies miss important human factors issues and when design decisions are based on them, the resulting interaction design leaves users confused. Therefore, the aim of this paper is to describe how users perceive different DASs by eliciting insights from an empirical driving study facilitating a Wizard-of-Oz approach, where 20 participants were interviewed after experiencing systems on two different LoAs under real driving conditions. The findings show that participants talked about the DAS by describing different relationships and dependencies between three different elements: the context (traffic conditions, road types), the vehicle (abilities, limitations, vehicle operations), and the driver (control, attentional demand, interaction with displays and controls, operation of vehicle), each with associated aspects that indicate what users identify as relevant when describing a vehicle with automated systems. Based on these findings, a conceptual model is proposed by which designers can differentiate LoAs from a human-centric perspective and that can aid in the development of design guidelines for driving automation.

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“…These actions not only endanger the life of the user/driver but also other road users (pedestrians, cyclists other vehicles) and tarnish the image of autonomous vehicles in the public eye (Lee and Kolodge, 2020). Possible solutions to overcome these challenges that are being investigated include, designing a human-centered perspective of explaining autonomous vehicle functions (Yang et al, 2017) or providing driver training before purchasing a vehicle (Boelhouwer et al, 2020).  Communication between the AV and users: Calibration of trust is the active management of trustworthiness and reliability as discussed previously.…”

Section: Communicationmentioning

confidence: 99%

Designing for Calibrated Trust: Exploring the Challenges in Calibrating Trust Between Users and Autonomous Vehicles

2021

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Trust is an important factor in building acceptance of autonomous vehicles within our society, but the complex nature of trust makes it challenging to design for an appropriate level of trust. This can lead to instances of mistrust and/or distrust between users and AV’s. Designing for calibrated trust is a possible option to address this challenge. Existing research on designing for calibrated trust focuses on the human machine interaction (HMI), while from literature we infer that trust creation beings much before the first interaction between a user and an AV. The goal of our research is to broaden the scope of calibrated trust, by exploring the pre-use phase and understand the challenges faced in calibration of trust. Within our study 16 mobility experts were interviewed and a thematic analysis of the interviews was conducted. The analysis revealed the lack of clear communication between stakeholders, a solutionism approach towards designing and lack of transparency in design as the prominent challenges. Building on the research insights, we briefly introduce the Calibrated Trust Toolkit as our design solution, and conclude by proposing a sweet spot for achieving calibration of trust between users and autonomous vehicles.

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Toward Defining Driving Automation from a Human-Centered Perspective

Cited by 9 publications

References 3 publications

Design for Perception - A Systematic Approach for the Design of Driving Automation Systems based on the Users’ Perception

Design for Perception - A Systematic Approach for the Design of Driving Automation Systems based on the Users’ Perception

Levels of What?Investigating Drivers’ Understanding of Different Levels of Automation in Vehicles

Designing for Calibrated Trust: Exploring the Challenges in Calibrating Trust Between Users and Autonomous Vehicles

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