A5087638195- Evacuation and Crowd Dynamics
- Video Surveillance and Tracking Methods
- Anomaly Detection Techniques and Applications
- Mobile Crowdsensing and Crowdsourcing
Aerospace Information Research Institute
2022-2023
Chinese Academy of Sciences
2022-2023
University of Chinese Academy of Sciences
2022-2023
To avoid crowd evacuation simulations depending on 2D environments and real data, we propose a framework for modeling simulation by applying deep reinforcement learning (DRL) 3D physical (3DPEs). In 3DPEs, construct scenarios from the aspects of geometry, semantics physics, which include environment, agents their interactions, provide training samples DRL. DRL, design double branch feature extraction combined actor critic network as DRL policy value function use clipped surrogate objective...
At present, a common drawback of crowd simulation models is that they are mainly simulated in (abstract) 2D environments, which limits the behaviors observed real 3D environments. Therefore, we propose deep reinforcement learning-based model with human-like perceptron and policy for evacuation environments (HDRLM3D). In HDRLM3D, vision-like ray (VLRP) combine it redesigned global (or local) (GOLP) to form perception model. We double-branch feature extraction decision network (DBFED-Net) as...