[2A5-GS-10] AI application: Traffic

[2A5-GS-10-01] Trial Application of Action Detection AI to understand the Usage Situation of Street Spaces

〇Masashi Yanamawaki¹, Yutaka Utsunomiya¹, Yuichi Hiramatsu¹, Hironori Kimura¹, Toshiki Hayami¹ (1. CTI ENGINEERING CO.,LTD.)

Keywords:walkable, street space, usage situation, action detection, digital twin

In recent years, efforts are underway in cities around the world to create walkable street spaces that are comfortable and inviting to walk around. In this effort, it is important to investigate user action to understand the formation of a comfortable street space. However, performing these tasks manually is burdensome in terms of both time and cost, and is likely to result in a decline in quality. In this research, we are developing a human action detection technology using deep learning, with the aim of increasing the efficiency and sophistication of work. There are already many research developments and operational examples of action detection AI models. However, we cannot confirm anything that is specialized for this purpose and can be applied immediately. In this paper, we developed a model that detects various actions listed in the guidelines prescribed by MLIT using camera images taken of street spaces. Then, we attempted to apply this model to understanding the usage situation of actual street spaces. As a result, we were able to quantitatively understand the usage status of actual street spaces on holidays and weekdays, demonstrating the potential for effective use of this model. Based on the results, we also considered how to combine AI and digital twins for building 3D models of real street spaces and solving problems.