Pedestrian-centric Augmented Reality Visualization of Real-time Autonomous Vehicle Dynamics

• Published in: Proceedings (IEEE International Conference on Cloud Networking. Online) pp. 460 - 465
• Main Authors: Cheng, Yiwei, Nakazato, Jin, Javanmardi, Ehsan, Chang, Chia-Ming, Tsukada, Manabu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2023
• Subjects: Connected autonomous vehicle; intelligent transportation system; Pedestrians; proof-of-concept; Real-time systems; Safety; Surveys; Transportation; Urban areas; Vehicle dynamics; visualization
• DOI: 10.1109/CloudNet59005.2023.10490048

Connected Autonomous Vehicles (CAVs) produce a variety of information within their systems. With the advancement of communication and V2X (Vehicle-to-Everything) communication technology, there is a growing challenge to effectively convey this information to pedestrians and enhance their sense of safety when encountering such vehicles. Efforts to communicate this information to pedestrians have been made through various means, with Augmented Reality (AR) emerging as a notable approach. However, previous studies have yet to integrate a functional AR application with a real-world autonomous driving system. In response to this gap, we proposed an architecture for an AR application that visualizes real-time data from an active CAV and subsequently developed the system. Furthermore, we conducted field experiments using this developed system and conducted user surveys during exhibitions to gather insights into the public's perception of the system. Our results showed that the system can effectively transmit information from the CAV, and when provided with additional information, people tend to feel safer regarding the vehicle.