Ori Rottenstreich
Ori Rottenstreich is an associate professor at the Department of Electrical and Computer Engineering and the Department of Computer Science at the Technion - Israel Institute of Technology. He is also a visiting researcher whose focus is on network algorithms and smart transportation. In 2015-2017 Ori was a Postdoctoral Research Fellow at the Department of Computer Science, Princeton University. He received the BSc in Computer Engineering (summa cum laude) and PhD degree from the Electrical Engineering department of the Technion, Israel. He was a recipient of the Rothschild Yad-Hanadiv postdoctoral fellowship and the Google Europe PhD Fellowship in Computer Networking as well as of the Israel Council for Higher Education Alon Fellowship. He also received the Best Paper Runner Up Award at the 2013 IEEE Infocom conference, the Best Paper Award at the 2017 ACM Symposium on SDN Research (SOSR), a Best Paper Award Candidate at the 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) and the Best Paper Award at the 2021 International Conference on Communication Systems and Networks (COMSNETS). He served as an editor for the IEEE Open Journal of the Communications Society as well as a guest editor for the IEEE Journal on Selected Areas in Communications (JSAC) and the IEEE Transactions on Network and Service Management (TNSM).
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Computing efficient traffic signal plans is often based on the amount of traffic in an intersection, its distribution over the various intersection movements and hours as well as on performance metrics such as traffic delay. In their simple and typical form plans are fixed in the same hour over weekdays. This allows low operation costs without the necessity for traffic detection and monitoring tools. A critical factor on the potential efficiency of such plans is the similarity of traffic patterns over the days along each of the intersection movements. We refer to such similarity as the traffic stability of the intersection and define simple metrics to measure it based on traffic volume and traffic delay. In this paper, we propose an automatic probe data based method, for city-wide estimation of traffic stability. We discuss how such measures can be used for signal planning such as in selecting plan resolution or as an indication as which intersections can benefit from dynamic but expensive traffic detection tools. We also identify events of major changes in traffic characteristics of an intersection. We demonstrate the framework by using real traffic statistics to study the traffic stability in the city of Haifa along its 162 intersections. We study the impact of the time of day on the stability, detect major changes in traffic and find intersections with high and low stability.
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