Acoustic Vehicle Alerting System Using Deep Learning and Directional Speaker

Abstract

Acoustic Vehicle Alerting System (AVAS) alerts pedestrians to the approach of the electric vehicle with a low noise level when traveling at a low speed. This system may annoy pedestrians depending on the surrounding environment and conditions. Therefore, a system that is highly acceptable to pedestrians while maintaining safety is required. In this study, the AVAS that uses deep learning to determine pedestrians who need to present information and appropriately presents information to those pedestrians by directional speakers was devised. Then, the safety and acceptability of the system were evaluated by actual vehicle experiments. The experimental results show that this AVAS tends to provide information only to appropriate pedestrians while maintaining safety.