Hybrid operations of human driving vehicles and automated vehicles with data-driven agent-based simulation

2020 ◽  
Vol 86 ◽  
pp. 102469
Author(s):  
Fugen Yao ◽  
Jiangtao Zhu ◽  
Jingru Yu ◽  
Chuqiao Chen ◽  
Xiqun (Michael) Chen
Keyword(s):  
Data Driven ◽  
Automated Vehicles ◽  
Agent Based Simulation ◽  
Agent Based

scholarly journals Random Finite Set Based Data Assimilation for Dynamic Data Driven Simulation of Maritime Pirate Activity

2017 ◽  
Vol 2017 ◽  
pp. 1-18 ◽  
Author(s):  
Peng Wang ◽  
Ge Li ◽  
Rusheng Ju ◽  
Yong Peng
Keyword(s):  
Data Assimilation ◽  
Rapid Development ◽  
Measurement Model ◽  
Data Driven ◽  
Agent Based Simulation ◽  
Dynamic Data ◽  
Agent Based ◽  
Random Finite Set ◽  
Finite Set ◽  
Online Measurements

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.

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