VLDB 2026 Research / reviewers in the wild / expert
Andrea C. Kao
dblp:264/7399
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 87% Usability and user experience research · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction › automated vehicle interaction
automated vehicle-pedestrian interaction |
0.4 | 1 | 2020 | A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle - Pedestrian Interaction · CHI 2020 |
Human-robot interaction › automated vehicles
external human-machine interface |
0.4 | 1 | 2020 | A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle - Pedestrian Interaction · CHI 2020 |
Usability and user experience research › user experience research
user experience over time |
0.1 | 1 | 2020 | A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle - Pedestrian Interaction · CHI 2020 |
Methods — techniques the papers use, named apart from their topics
subjective evaluation · 0.4longitudinal video study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle - Pedestrian InteractionabstractWith self-driving vehicles (SDVs), pedestrians cannot rely on communication with the driver anymore. Industry experts and policymakers are proposing an external Human-Machine Interface (eHMI) communicating the automated status. We investigated whether additionally communicating SDVs' intent to give right of way further improves pedestrians' street crossing. To evaluate the stability of these eHMI effects, we conducted a three-session video study with N=34 pedestrians where we assessed subjective evaluations and crossing onset times. This is the first work capturing long-term effects of eHMIs. Our findings add credibility to prior studies by showing that eHMI effects last (acceptance, user experience) or even increase (crossing onset, perceived safety, trust, learnability, reliance) with time. We found that pedestrians benefit from an eHMI communicating SDVs' status, and that additionally communicating SDVs' intent adds further value. We conclude that SDVs should be equipped with an eHMI communicating both status and intent. Stefanie M. Faas, Andrea C. Kao, Martin Baumann 0001 |
CHI | 2 |