In this paper, we focus on the development of intelligent construction vehicles to improve the safety of workers in construction sites. Generally, global navigation satellite system positioning is utilized to obtain the position data of workers and construction vehicles. However, construction fields in urban areas have poor satellite positioning environments. Therefore, we have developed a 3D sensing unit mounted on a construction vehicle for worker position data acquisition. The unit mainly consists of a multilayer laser scanner. We propose a real-Time object measurement, classification and tracking methodology with the multilayer laser scanner. We also propose a methodology to estimate and visualize object behaviors with a spatial model based on a space subdivision framework consisting of agents, activities, resources, and modifiers. We applied the space subdivision framework with a geofencing approach using real-Time object classification and tracking results estimated from temporal point clouds. Our methodology was evaluated using temporal point clouds acquired from a construction vehicle in drilling works.
|ジャーナル||ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences|
|出版ステータス||Published - 2020 8月 3|
|イベント||2020 24th ISPRS Congress - Technical Commission IV on Spatial Information Science - Nice, Virtual, France|
継続期間: 2020 8月 31 → 2020 9月 2
ASJC Scopus subject areas