Our CiTyAI lab has a new website: check out to find more information aout the team and our projects at the following link: https://www.tudelft.nl/ai/cityai-lab
At the Smart Public Transport Lab we are currently undertaking a series of studies related to the corona crisis. Given the urgency and the gravity of what is at stake, we share results as soon as we are confident that we can contribute to the policy and scientific debate with sound models and empirical findings.
By now we are ready to share findings from two studies focusing on the role of mass transit and ride-sharing in spreading the virus. Welcome to check out our short articles following these links:
– Virus spreading in public transport networks: the alarming consequences of the business as usual scenario [A slightly modified version is available on ResearchGate]
And stay tuned for upcoming results from on-going studies.
Had an eventful end of last month with three PhD graduations within a week span:
On February 21, Ding Luo defended his thesis entitled “Data-driven Analytics and Modeling of Passenger Flows and Networks for Public Transport Systems“.
Then, on February 26, Menno Yap defended his thesis on “Measuring, Predicting and Controlling Disruption Impacts for Urban Public Transport”. Menno was awarded for his work with a Cum-laude designation.
And, on February 27, Panchamy Krishnakumari defended her dissertation on “Multiscale Pattern Recognition of Transport Network Dynamics and its Applications“. Panchamy was awarded for her work with a Cum-laude designation.
Congratulations to the young doctors for their wonderful achievements!
Presenting at the Transit Data 2019 – the 5th International Workshop and Symposium on research and applications on the use of massive passive data for public transport on 8th -10th July in Paris, France. Contributions include the following studies:
– Generating network-wide travel diaries using smartcard data
– Enhanced complex network representation of public transport for accessibility assessment based on General Transit Feed Specification data
– Impact analysis of a new metro line in Amsterdam using automated data sources
– Predicting and clustering station vulnerability in urban networks
– Investigating the effects of real-time crowding information (RTCI) systems in urban public transport under different demand conditions
You may find the sessions by browsing the program.
Congratulations Dr. Nadjla Ghaemi for successfully defending your PhD dissertation on “Short-turning Trains during Full Blockage in Railway Disruption Management” today!
Nadjla’s PhD work has been published in the following journal publications:
Ghaemi N., Cats O. and Goverde R.M.P. (2018). Macroscopic multiple-station short-turning model in case of complete railway blockages. Transportation Research Part C, 89, 113-132.
Ghaemi N., Cats O. and Goverde R.M.P. (2017). A Microscopic Model for Optimal Train Short-Turnings during Complete Blockages. Transportation Research Part B, 105, 423-437.
Ghaemi N., Zilko A., Yan F., Cats O., Kurowicka D. and Goverde R.M.P. (2018). Impact of Railway Disruption Predictions and Rescheduling on Passenger Delays. Journal of Rail Transport Planning & Management. Accepted.
Ghaemi N., Cats O. and Goverde R.M.P. (2017). Railway Disruption Management Challenges and Possible Solution Directions. Public Transport, 9 (1-2), 343-364.
The defense was followed by a TRAIL seminar where I gave a talk on “Robust passenger transport systems: Network, operations and user adaptations”