Optimization of Multi-Target Tracking in a Multi-Agent Architecturewith Multi-Sensor Data Fusion

This article presents a Surveillance Multi-Agen System (S-MAS) architecture which focuses on the fusion of data from multi sensors for enhanced automotive safety andtraffic efficiency. In S-MAS tools will be introduced asautonomous agents for implementing a multi-sensor data fusionat architectural level: surveillance–sensor agents, a fusionagent, interface agents, record agents, planning agents, etc.They differ in their ability to carry out a specific surveillancetask. A surveillance–sensor agent controls and manages individual sensors. In this work we focus on the fusion agent, addressing specific problems of on-line sensor alignment, registration, bias removal and data fusion. We show how theinclusion of this fusion agent guarantees that objects of interestare successfully tracked across the whole area.

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