Analysis of the Interaction between Humans and Autonomous Vehicles Equipped with External Human–Machine Interfaces: The Effect of an Experimental Reward Mechanism on Pedestrian Crossing Behavior in a Virtual Environment

Raul Almeida (), Emanuel Sousa, Dário Machado, Frederico Pereira, Susana Faria and Elisabete Freitas
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Raul Almeida: Institute for Sustainability and Innovation in Structural Engineering—ISISE, Advanced Production & Intelligent Systems—ARISE, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, Portugal
Emanuel Sousa: Centre for Computer Graphics, Campus de Azurém, 4800-058 Guimarães, Portugal
Dário Machado: Centre for Computer Graphics, Campus de Azurém, 4800-058 Guimarães, Portugal
Frederico Pereira: Centre for Computer Graphics, Campus de Azurém, 4800-058 Guimarães, Portugal
Susana Faria: Department of Mathematics, University of Minho, 4800-058 Guimarães, Portugal
Elisabete Freitas: Institute for Sustainability and Innovation in Structural Engineering—ISISE, Advanced Production & Intelligent Systems—ARISE, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, Portugal

Sustainability, 2024, vol. 16, issue 8, 1-23

Abstract: The advent of autonomous vehicles (AVs) has sparked many concerns about pedestrian safety, prompting manufacturers and researchers to integrate external Human–Machine Interfaces (eHMIs) into AVs as communication tools between vehicles and pedestrians. The evolving dynamics of vehicle–pedestrian interactions make eHMIs a compelling strategy for enhancing safety. This study aimed to examine the contribution of eHMIs to safety while exploring the impact of an incentive system on pedestrian risk behavior. Participants interacted with AVs equipped with eHMIs in an immersive environment featuring two distinct scenarios, each highlighting a sense of urgency to reach their destination. In the first scenario, participants behaved naturally without specific instructions, while in the second scenario, they were informed of an incentive aimed at motivating them to cross the road promptly. This innovative experimental approach explored whether motivated participants could maintain focus and accurately perceive genuine risk within virtual environments. The introduction of a reward system significantly increased road-crossings, particularly when the vehicle was approaching at higher speeds, indicating that incentives encouraged participants to take more risks while crossing. Additionally, eHMIs notably impacted pedestrian risk behavior, with participants more likely to cross when the vehicle signaled it would not stop.

Keywords: autonomous vehicles; vehicle–pedestrian interaction; virtual environments; pedestrian crossing; road safety; pedestrian behavior; reward system; gamification; pedestrian simulator; risk (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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