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May 5, 2024 · Experimental results show that our proposed method has high path planning efficiency and can generate more realistic pedestrian trajectories in ...
Jun 28, 2024 · In this study, we propose a novel crowd evacuation path planning approach based on the learning curve–deep deterministic policy gradient (LC‐ ...
A fast and multifactor evacuation model based on deep reinforcement learning was proposed to quickly calculate evacuation paths with the lowest cumulative ...
We propose a framework for crowd evacuation modeling and simulation by applying deep reinforcement learning (DRL) and 3D physical environments (3DPEs).
To solve the problem, this paper combines social force model (SFM) with deep learning into a novel pedestrian detection method. Firstly, several deep learning ...
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We propose the efficient multi-agent deep deterministic policy gradient (E-MADDPG) algorithm for crowd-evacuation path planning.
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The agent-based simulation is achieved by using a simulation software named AnyLogic, which is able to simulate the routes and evacuation process for airports ...
A multi‐exit evacuation simulation based on deep reinforcement learning (DRL), referred to as the MultiExit‐DRL, which involves a deep neural network (DNN) ...
This paper proposed an end-to-end intelligent evacuation guidance method based on deep reinforcement learning, and designed an interactive simulation ...
Nov 5, 2019 · It offers an easily adaptable framework for realistic navigation of single pedestrians as well as crowds in microscopic approaches to pedestrian ...