Detection of Crossing Pedestrians and Control Support in Autonomous Vehicles using Edge-devices
Yuki Ebizuka, Yuto Shimizu, Shin Kato, Makoto Itami · 2019
The National Institute of Advanced Industrial Science and Technology aims to implement new means of transportation with autonomous vehicles. In autonomous vehicles, pedestrian recognition and control decisions are one of many important issues. In this study, a machine-learning-based-image analysis method is used to verify control judgment for pedestrian recognition, including their direction and their use of mobile phones. In addition, by using an edge computing system that utilizes multiple edge devices, we are aiming for recognition outside the vehicle that is not affected by communication failures. The results of the demonstration carried out for verification of the same have been reported in this paper.