Cyclists’ Crossing Intentions When Interacting with Automated Vehicles: A Virtual Reality Study

Author:

Nuñez Velasco Juan Pablo,de Vries Anouk,Farah HaneenORCID,van Arem Bart,Hagenzieker Marjan P.ORCID

Abstract

Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied factors at different levels. In total, the experiment lasted 60 min. The results show that the gap size and the right of way were the primary factors affecting the crossing intentions of the individuals. The vehicle type and vehicle speed did not have a significant effect on the crossing intentions. Finally, the 360° video-based VR method scored relatively high as a research method and comparable with the results of a previous study investigating pedestrians’ crossing intentions confirming its suitability as a research methodology to study cyclists’ crossing intentions.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Publisher

MDPI AG

Subject

Information Systems

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1. How do cyclists interact with motorized vehicles at unsignalized intersections? Modeling cyclists’ yielding behavior using naturalistic data;Accident Analysis & Prevention;2023-09

2. Support systems for cyclists in automated traffic: A review and future outlook;Applied Ergonomics;2023-09

3. A Wearable Sensor Network for Cyclists Safety in Mixed Traffic, a Pilot Study;2023 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT);2023-06-06

4. Road Driven Automated Vehicles by Using Virtual Reality for Pedestrians and Cyclists;2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN);2023-04-20

5. Pedestrians and Cyclists’ Intention Estimation for the Purpose of Autonomous Driving;International Journal of Automotive Engineering;2023

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