Multi-Agent Based Air Traffic Simulation System

Author(s):  
Zheng Yue ◽  
Dong Sui ◽  
Yingda Lin ◽  
Junfeng Zhang
Logistics ◽  
2009 ◽  
Author(s):  
Ming-jun Liao ◽  
Jian Sun ◽  
Ke-ping Li ◽  
Kai-ying Wang

2014 ◽  
Vol 613 ◽  
pp. 363-373
Author(s):  
Sherif E. Hussein ◽  
Sarwat Zahwi

Transportation simulations are an important part of today’s decision making process for transport infrastructure and management. While proposed changes are getting more and more complex, tools supporting the decision making process are struggling to keep up. Traditional, flow-based traffic assignment tools are limited in the number of different person groups that can be distinguished and do in most cases not offer fully time-dynamic results. Newer technologies like agent-based simulations overcome those problems. This paper presents a novel traffic simulation scheme capable of modeling chaotic motorway traffic. Different from other lane-based or following-based approaches, the proposed approach models traffic as a large navigational problem in an agent based simulation context. In addition, the approach is efficiently able to handle hard cases like overtaking, behavior at turning and aggressive driving behavior. The simulation was demonstrated at real-time rates using MATSim applied to Cairo Ring Road. It has been described as well how MATSim simulation was extended to incorporate aggressive and careless drivers' behavior.


2010 ◽  
Vol 108-111 ◽  
pp. 525-529
Author(s):  
Yi Kui Mo ◽  
Xiang Rong Qiao ◽  
Yong Yun Su

In light of the characteristics of transit passenger’s route choice behavior, this paper introduces a multi-agent based simulation approach into the study of this behavior.At first, the paper analyzes factors affecting transit passenger’s route choice behavior and then studies the rules of behavior for transit passengers when making route choices. The paper further proposes a utility function for selected routes and examines ways to investigate and analyze corresponding data so as to provide a basis for the modeling of passenger agent’s route choice behavior. Following this, the paper builds up a simulation system for transit passenger’s route choice behavior based on the multi-agent simulation software Starlogo developed by Massachusetts Institute of Technology (MIT), and explains the process that will actually take place when using the simulation system. Finally, inadequacies of the study are analyzed and the focus of further research is indicated.


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