Communication Strategies for Effective Interaction With Pedestrians and Automated Service Vehicles in Japanese Parking Areas

AbstractOne of the challenges in introducing automated service vehicles (ASVs) to parking areas is guiding pedestrians to make quick and appropriate crossing decisions based on an understanding of what the ASV typically does. This study aims to find effective communication strategies for ASVs for pedestrian crossings in Japanese parking areas. Virtual Reality experiments were conducted with 40 participants facilitating vehicle behavior (Normal Deceleration, Early Deceleration, Early Stop) and text-based external human-machine interfaces (eHMIs; No eHMI, “After you,” “I’ll stop,” “In Automated Driving”) as tools of communication with two types of ASVs (bus and golf cart) in parking areas. The results indicated that vehicle behavior significantly influenced pedestrian crossing decisions, and pedestrians began to cross when the ASV decelerated early and stopped not too far from them (Early Deceleration). Self-reported measure analyses revealed that text messages containing the intent of the ASV's actions or instruction (After you, I’ll stop) with Early Deceleration would probably lead to pedestrians’ favorable attitudes toward automated buses. These findings contribute to communication designs based on implicit communication for pedestrian crossing decision-making in parking areas with a clear interpretation of ASV’s intentions.Keywords: External human-machine interfaceautomated vehiclepedestrian crossingservice mobilityparking area AcknowledgementsThe authors thank Jun Soshiroda and Kosuke Takizawa for their help in data collection.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study is based on the results obtained from the project JPNP18012, commissioned by the New Energy and Industrial Technology Development Organization (NEDO).Notes on contributorsJieun LeeJieun Lee is an assistant professor in the Department of Safety Engineering at Pukyong National University also a collaborative researcher in Mobility Culture Research Center at Keio University Global Research Institute. Jieun received her Ph.D. in Engineering from University of Tsukuba in 2020. Her research interests include designing human-machine systems.Tatsuru DaimonTatsuru Daimon is a professor in the Faculty of Science and Technology at Keio University. Tatsuru earned his Ph.D. in Engineering at Keio University in 1995. His research interests include driver assistance of intelligent transportation systems.