The performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...

Socially-aware traffic management exploits social signals to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end-user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. In the talk we show interdisciplinary efforts between communication networks and social ne...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

Real-time incident-responsive traffic control and management is vital to development of advanced incident management systems in ITS. More importantly, it provides, from an academic point of view, the linkages between incident detection, incident management, and traffic signal control. This study explores the application of a stochastic optimal control approach to real-time incident-responsive t...

Traffic Management involves planning, designing, integration of traffic signal system to achieve efficiency, safety, reliability. Designing of signal system which will provide real time feedback of traffic conditions for dynamic functionality to control traffic signals to optimize traffic management. In this paper, I have used Infrared Transceivers (sensors) for collecting real time data and Mi...