Slideo: Bicycle-to-Vehicle Communication to Intuitively Share Intention to Turn with Automated Vehicles

Verstegen, Jochem; Bazilinskyy, Pavlo · 2024 · Crossref

DOI: 10.54941/ahfe1005210

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses the lack of intuitive communication methods for cyclists to share their intentions with automated vehicles (AVs). While existing research focuses on external Human-Machine Interfaces (eHMIs) that inform vulnerable road users (VRUs) about AV intentions, this study explores bicycle-to-vehicle (B2V) communication, allowing cyclists to signal their intent to turn via Vehicle-to-Everything (V2X) networks. The authors argue that such technology should enhance cycling comfort and efficiency rather than serve as a mandatory safety requirement, which remains the responsibility of AVs. The study employed a design sprint methodology to develop and evaluate interaction concepts. Initially, four physical interaction concepts involving hands, feet, hips, and knees were assessed via an online questionnaire completed by 27 participants. The results indicated a generally negative attitude toward the concepts, largely due to concerns about accidental activation and the belief that AVs should independently ensure cyclist safety. However, the hand-based interaction received the highest scores for intuitiveness, clarity, and willingness to use. Consequently, the researchers developed a final prototype featuring sliding handlebars that communicate turn intentions to nearby AVs. The prototype included vibration motors in each handle to provide haptic feedback. A user test with nine participants evaluated two variations of haptic feedback: Variant A provided feedback at the start, during, and at the end of the communication process, while Variant B provided feedback only at the beginning and end. Participants viewed a first-person cycling video synchronized with the prototype’s vibrations. Six out of nine participants correctly interpreted the feedback patterns after the first viewing. Preferences for the feedback variants were mixed; those who understood the intermediate "processing" signal preferred Variant A for its transparency, while others preferred Variant B for its simplicity. The study concluded that the clarity of the feedback was generally understood, but preference depended on individual desires for information density. The significance of this work lies in proposing a non-distracting, physical B2V interaction that complements future connected traffic systems. The authors conclude that while such devices should not be required for safety, they offer value in improving predictability and comfort. The findings suggest that B2V interfaces should allow for personalization, enabling users to toggle feedback elements or adjust intensity based on personal preference. The study also highlights the need for further research into compatible handlebar designs, low-power hardware, and V2X protocol integration to make such technology feasible for widespread adoption.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

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

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• ehmi external hmi
• vru facing ehmi