@inproceedings{cee1b096ebe347d882e617205c7628d9,
title = "Exploring Emotion Responses toward Pedestrian Crossing Actions for Designing In-vehicle Empathic Interfaces",
abstract = "While affective non-verbal communication between pedestrians and drivers has been shown to improve on-road safety and driving experiences, it remains a challenge to design driver assistance systems that can automatically capture these affective cues. In this early work, we identify users' emotional self-report responses towards commonly occurring pedestrian actions while crossing a road. We conducted a crowd-sourced web-based survey (N=91), where respondents with prior driving experience viewed videos of 25 pedestrian interaction scenarios selected from the JAAD (Joint Attention for Autonomous Driving) dataset, and thereafter provided valence and arousal self-reports. We found participants' emotion self-reports (especially valence) are strongly influenced by actions including hand waving, nodding, impolite hand gestures, and inattentive pedestrian(s) crossing while engaged with a phone. Our findings provide a first step towards designing in-vehicle empathic interfaces that can assist in driver emotion regulation during on-road interactions, where the identified pedestrian actions serve as future driver emotion induction stimuli.",
keywords = "actions, drivers, emotion, empathic, in-vehicle interface, pedestrians",
author = "Surjya Ghosh and {Pons Rodriguez}, Gerard and Shruti Rao and {El Ali}, Abdallah and Pablo Cesar",
year = "2022",
doi = "10.1145/3491101.3519764",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery (ACM)",
booktitle = "CHI 2022 - Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems",
address = "United States",
note = "2022 CHI Conference on Human Factors in Computing Systems, CHI EA 2022 ; Conference date: 30-04-2022 Through 05-05-2022",
}