Editorial: Interaction between automated vehicles and other road users

Wintersberger, Philipp; Dey, Debargha; Löcken, Andreas · 2023 · Crossref

DOI: 10.3389/frobt.2023.1228093

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Summary

This editorial introduces a Research Topic in *Frontiers in Robotics and AI* focused on the interaction between automated vehicles (AVs) and other road users. The authors highlight that as AVs become prevalent, the absence of human drivers necessitates new communication methods with vulnerable road users (VRUs), such as pedestrians and cyclists, and manual vehicle drivers. While previous research has largely examined simple scenarios, such as single pedestrian crossings, this collection addresses the need for more complex investigations involving groups of users, diverse demographics, and intricate environments like roundabouts or shared urban spaces. The editorial aims to foster systematic inquiry into external Human-Machine Interfaces (eHMIs) and Internet of Things (IoT) technologies to enhance traffic safety, cooperation, and empathy. The text summarizes nine accepted articles within the Research Topic, detailing their methodologies and findings. Fabricius et al. conducted a systematic literature review on interactions between heavy trucks and VRUs, calling for deeper empirical studies. Loew et al. utilized a wizard-of-oz method in real-world settings, finding that three eHMI concepts were positively rated for acceptance and perceived safety compared to a baseline. Zhang et al. analyzed interactions at traffic-light-controlled intersections, identifying three communication patterns between right-turning motorists and cyclists to inform AV strategies for efficiency and safety. Hoggenmueller et al. employed human-centered design and virtual reality (VR) evaluations for an eHMI in pedestrianized spaces, arguing for a holistic design approach in complex scenarios. Hensch et al. compared impressions of eHMIs between younger and elderly participants, noting that elderly users assessed the systems more positively, suggesting designs must address specific user group requirements. Further studies explored behavioral impacts and technological innovations. Lau et al. conducted an online study demonstrating that eHMIs can negatively affect pedestrian crossing behavior if they do not align with vehicle kinematics. Sahin et al. used a gamified VR environment to reveal that pedestrians jaywalk more frequently when encountering AVs, with behavior influenced by perceived risks, vehicle type, and social control. Mirnig et al. summarized seven studies across three European countries regarding external communication solutions for automated shuttles. Finally, Tran et al. evaluated wearable augmented reality (AR) concepts in VR experiments, finding that while wearable AR may reduce cognitive load by providing clear crossing signals, adoption willingness depends on various factors. The significance of this collection lies in its shift from simple, isolated interactions to complex, real-world traffic dynamics. By addressing diverse demographics and scenarios, the research underscores the importance of designing eHMIs that are not only technically functional but also socially acceptable and safe. The findings suggest that successful AV integration requires holistic design approaches, alignment between communication signals and vehicle dynamics, and consideration of specific user needs to foster trust and cooperation in mixed traffic environments.

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StageOutcomeToolModelPromptAttemptsCompleted
discover success Crossref 1 2026-06-18
archive success canonical_url 1 2026-06-25
extract success pdftotext 2 2026-06-26
clean success clean 1 2026-06-26
chunk success chunk 1 2026-06-26
embed success embed Qwen/Qwen3-Embedding-8B 1 2026-06-26
enrich success openalex 1 2026-06-20
promote success 1 2026-06-18
summarize success llm qwen3.6-27b-prismaquant summ-v5 1 2026-06-26
tag success vector_similarity 6 2026-06-26
verify partial 1 2026-06-26

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified_with_issues.

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