Communication between Autonomous Vehicles and Pedestrians: An Experimental Study Using Virtual Reality

Author:

Zhanguzhinova SymbatORCID,Makó EmeseORCID,Borsos AttilaORCID,Sándor Ágoston PálORCID,Koren CsabaORCID

Abstract

One of the major challenges of autonomous vehicles (AV) is their interaction with pedestrians. Unofficial interactions such as gestures, eye contact, waving, and flashing lights are very common behavioral patterns for drivers to express their intent to give priority. In our research we composed a virtual reality experiment for a pedestrian crossing in an urban environment in order to test pedestrians’ reactions on an LED light display mounted on a virtual AV. Our main research interest was to investigate whether communication patterns influence the decision making of pedestrians when crossing the road. In a VR environment, four scenarios were created with a vehicle approaching a pedestrian crossing with different speeds and displaying a special red/green sign to pedestrians. Here, 51 persons participating in the experiment had to decide when crossing is safe. Results show that the majority of people indicated they would cross in the time windows when it was actually safe to cross. Male subjects made their decision to cross slightly faster but no significant differences were found in the decision making by gender. It was found that age is not an influencing factor, either. Overall, a quick learning process was experienced proving that explicit communication patterns are self-explaining.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference32 articles.

1. WHO (2018). Global Status Report on Road Safety 2018, WHO.

2. Vulnerable road users and the coming wave of automated vehicles: Expert perspectives;Tabone;Transp. Res. Interdiscip. Perspect.,2021

3. External HMIs and their effect on the interaction between pedestrians and automated vehicles;Song;Adv. Intell. Syst. Comput.,2018

4. Hochman, M., Parmet, Y., and Oron-gilad, T. (2022, January 8–10). Pedestrians’ Understanding of a Fully Autonomous Vehicle’ s Intent to Stop: Utilizing Video-based Crossing Scenarios. Proceedings of the RSS 2022, Athens, Greece.

5. Clamann, M., Aubert, M., and Cummings, M. (2017, January 8–12). Evaluation of Vehicle-to-Pedestrian Communication Displays for Autonomous Vehicles. Proceedings of the 96th Annual Transportation Research Board Meeting, Washington, DC, USA.

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