Data-Driven Agent-Based Simulation for Pedestrian Capacity Analysis

Author(s):  
Sing Kuang Tan ◽  
Nan Hu ◽  
Wentong Cai
2020 ◽  
Vol 86 ◽  
pp. 102469
Author(s):  
Fugen Yao ◽  
Jiangtao Zhu ◽  
Jingru Yu ◽  
Chuqiao Chen ◽  
Xiqun (Michael) Chen

2017 ◽  
Vol 2017 ◽  
pp. 1-18 ◽  
Author(s):  
Peng Wang ◽  
Ge Li ◽  
Rusheng Ju ◽  
Yong Peng

Maritime piracy is posing a genuine threat to maritime transport. The main purpose of simulation is to predict the behaviors of many actual systems, and it has been successfully applied in many fields. But the application of simulation in the maritime domain is still scarce. The rapid development of network and measurement technologies brings about higher accuracy and better availability of online measurements. This makes the simulation paradigm named as dynamic data driven simulation increasingly popular. It can assimilate the online measurements into the running simulation models and ensure much more accurate prediction of the complex systems under study. In this paper, we study how to utilize the online measurements in the agent based simulation of the maritime pirate activity. A new random finite set based data assimilation algorithm is proposed to overcome the limitations of the conventional vectors based data assimilation algorithms. The random finite set based general data model, measurement model, and simulation model are introduced to support the proposed algorithm. The details of the proposed algorithm are presented in the context of agent based simulation of maritime pirate activity. Two groups of experiments are used to practically prove the effectiveness and superiority of the proposed algorithm.


Author(s):  
John Michopoulos ◽  
Panagiota Tsompanopoulou ◽  
Elias Houstis ◽  
Anupam Joshi

2010 ◽  
Vol 40 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Zheng WANG ◽  
Tao LIU ◽  
Xiaoye DAI

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