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Loop detectors are the oldest and widely used traffic data source. On urban arterials, they are mainly installed for signal control. Recently state-of-the art Bluetooth MAC Scanners (BMS) has significantly captured the interest of stakeholders for exploiting it for area-wide traffic monitoring. Loop detectors provide flow – a fundamental traffic parameter; whereas BMS provides individual vehicle travel time between BMS stations. Hence, these two data sources complement each other, and if integrated should increase the accuracy and reliability of the traffic state estimation.

This paper proposed a model that integrates loops and BMS data for seamless travel time and density estimation for urban signalised network. The proposed model is validated using both real and simulated data and the results indicate that the accuracy of the proposed model is over 90%.