CVS prize for a study on the costs and benefits of network designs for the European high-speed rail network

Congrats Jorik Grolle for winning the second prize for his graduation thesis at the CVS transport colloquium! Jorik studied the costs and benefits of network designs for the European high-speed rail network.

Read more here in English or Dutch.


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.

Can ride-hailing replace all public transport services?

Presented last week some of our research activities together with AMS on the WeMakeTheCity festival in Amsterdam in a session devoted to the future of MaaS and PT. While I do not argue that we should replace all public transport with individual on-demand services, I think that it helps to illuminate the ramifications of hypothetically doing so and hence support the debate with research findings.

Seminar at C2Smart, New York University

Gave on January 18 a seminar at C2Smart together with Panchamy Krishnakumari, a colleague in our Smart Public Transport Lab. We were hosted by Prof. Joseph Chow.

You can watch the seminar by following this link.

Our seminar was entitled Capacity Allocation for On-demand Services, Demand-anticipatory Operations and Analyzing Demand Patterns. On-demand transit has become a common mode of transport with ride-sourcing companies like Uber, Lyft, Didi transforming the way we move. With the increase in popularity for such services, the fleet needs to adapt according to the demand and passenger demand needs to be predicted. In the seminar, we presented our work on capacity allocation for on-demand services, demand-anticipatory operations and analyzing demand patterns using spatial-temporal clustering.

Panchamy and I gave the seminar following the TRB conference in Washington DC and a project meeting with WMATA (Washington Metropolitan Area Transit Authority).