Mehdi Keyvan-Ekbatani

LecturerMehdi Keyvan-Ekbatani

Internal Phone: 95121

Research Interests

The last few years, I worked mainly in the area of traffic flow modeling and control. To be more specific, I am interested in modeling the traffic dynamics on motorways and urban networks, both at the macroscopic and microscopic level. Developing control strategies to mitigate the traffic congestion in large-scale urban networks under over-saturated traffic regime is also one of my main research interests.

Recent Publications

  • Corman F., Henken J. and Keyvan-Ekbatani M. (2019) Macroscopic fundamental diagrams for train operations - are we there yet? Kraków, Poland: 6th International Conference on Models and Technologies for Intelligent Transportation Systems, 5-7 Jun 2019.
  • Johari M., Keyvan-Ekbatani M., Ngoduy D. and Badia H. (2019) Effects of Near-Side and Far-Side Bus Stops on NFD of Bi-Modal Urban Network. Auckland, New Zealand: IEEE Intelligent Transportation Systems, 26 Oct 2019. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
  • Keyvan-Ekbatani M., Gao XS., Gayah VV. and Knoop VL. (2019) Traffic-responsive signals combined with perimeter control: investigating the benefits. Transportmetrica B: Transport Dynamics 7(1): 1402-1425.
  • Lee S., Ngoduy D. and Keyvan-Ekbatani M. (2019) Integrated deep learning and stochastic car-following model for traffic dynamics on multi-lane freeways. Transportation Research Part C: Emerging Technologies 106: 360-377.
  • Lee S., Xie K., Ngoduy D. and Keyvan-Ekbatani M. (2019) An advanced deep learning approach to real-time estimation of lane-based queue lengths at a signalized junction. Transportation Research Part C: Emerging Technologies 109: 117-136.