Unpacking the message: visual cues to reduce bystander uncertainty about delivery drones in public spaces
Artikel i vetenskaplig tidskrift, 2026

As drones are deployed in public spaces for tasks such as package delivery, drones will encounter the public as bystanders passing by. The distinctive character of bystanders is that they are not the package recipients, so they lack prior information about the drone. Clear communication of drone intentions is essential to reduce uncertainty and improve public safety and trust. Limited research, however, has examined how a drone's communication strategies affect bystanders. This online questionnaire study investigated how a drone's visual cues affect bystanders' uncertainty about a drone's intentions. Participants (N = 150) viewed software simulated scenarios of drones delivering packages either by landing or by cable drop, each with or without visual interfaces (on-board lights, on-board display, or ground projection). Participants rated the scenarios for uncertainty, convincingness, predictability, understandability, and trust, and provided qualitative feedback through textual comments. Results illustrate that explicit communication improves bystanders' ability to predict drone actions and influence bystanders' intentions. While lights posed challenges with visual clarity, displays were effective for conveying drone movements, and projections were most preferred for indicating landing locations and safety zones. We recommend adapting interfaces, particularly ground projection, to provide instructions to bystanders on how to act (e.g., whether or not to cross) during drone operations. Our study contributes to the introduction of safe and trustworthy drones in public spaces.

Public

Uncertainty

Human-machine interfaces

Delivery application

Drones

Human-robot interaction

Författare

Shiva Nischal Lingam

Technische Universiteit Eindhoven

Royal Netherlands Aerosp Ctr

Sebastiaan Martinus Petermeijer

Royal Netherlands Aerosp Ctr

Mohammad Obaid

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Göteborgs universitet

Marieke Martens

Nederlandse Organisatie voor toegepast-natuurwetenschappelijk onderzoek (TNO)

AI and Society

0951-5666 (ISSN) 1435-5655 (eISSN)

Vol. In Press

Ämneskategorier (SSIF 2025)

Annan teknik

Människa-datorinteraktion (interaktionsdesign)

DOI

10.1007/s00146-026-02903-3

Mer information

Senast uppdaterat

2026-04-02