Development of a Multi-Agent Based Model for Heterogeneous Traffic Flow Analysis

2017 ◽  
Vol 50 (2) ◽  
pp. 114-120
Author(s):  
Naheem Olakunle Adesina ◽  
◽  
Abiodun Alani Ogunseye ◽  
Akindele Opeyemi Areegbe ◽  
Thomas Kokumo Yesufu
Keyword(s):  
Traffic Flow ◽  
Flow Analysis ◽  
Heterogeneous Traffic ◽  
Agent Based Model ◽  
Agent Based ◽  
Multi Agent ◽  
Traffic Flow Analysis

Vietnamese vehicles speed detection with video-based and deep learning for real-time traffic flow analysis system

2021 ◽  
Author(s):  
Phuoc Ha Quang ◽  
Phong Pham Thanh ◽  
Tuan Nguyen Van Anh ◽  
Son Vo Phi ◽  
Binh Le Nhat ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Traffic Flow ◽  
Flow Analysis ◽  
Real Time Traffic ◽  
Analysis System ◽  
Traffic Flow Analysis

An Autonomous Multi-Agent Simulation Model for Acute Inflammatory Response

2013 ◽  
pp. 218-233 ◽  
Author(s):  
John Wu ◽  
David Ben-Arieh ◽  
Zhenzhen Shi
Keyword(s):  
Simulation Model ◽  
Focal Point ◽  
Therapeutic Interventions ◽  
Prognostic Indicators ◽  
Simulation Approach ◽  
Agent Based Model ◽  
Agent Based ◽  
Initial Stage ◽  
Agent Simulation ◽  
Multi Agent

This research proposes an agent-based simulation model combined with the strength of systemic dynamic mathematical model, providing a new modeling and simulation approach of the pathogenesis of AIR. AIR is the initial stage of a typical sepsis episode, often leading to severe sepsis or septic shocks. The process of AIR has been in the focal point affecting more than 750,000 patients annually in the United State alone. Based on the agent-based model presented herein, clinicians can predict the sepsis pathogenesis for patients using the prognostic indicators from the simulation results, planning the proper therapeutic interventions accordingly. Impressively, the modeling approach presented creates a friendly user-interface allowing physicians to visualize and capture the potential AIR progression patterns. Based on the computational studies, the simulated behavior of the agent–based model conforms to the mechanisms described by the system dynamics mathematical models established in previous research.

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