news
News and updates
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Our paper accepted for MT-ITS
Two of our papers got accepted for MT-ITS conference organised by TU Munich. One on MaaSSim simulator and second one on Bus Bunching (with Arek Drabicki).
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Malte Schroder visit
Next Thu (4th Feb) we will host Malte Schroder (Center for Advancing Electronics Dresden (cfaed), TU Dresden) to discuss their highly intriguing paper in Nature Communications.
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Arjan at TRB 2021
Arjan presented our study with Oded Cats and Hans van Lint on the Evolution of Labour Supply in Ridesourcing at TRB meeting in Washington DC.
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Our study at TRB2021
Oded presents our study with Uber at TRB2021 in Washington DC: Beyond the Dichotomy: How Uber Competes with as well as Complements Public Transport (submitted to JoTG).
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Pre-print about virus spreading now on arXIV
ArXiv preprint of our virus spreading work with Oded Cats and Julian Sienkiewicz (Warsaw University of Technology) - under review in SciRep.
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MaaSSim now available on arXiv
Preprint of open-source two-sided mobilty simulator MaaSSim published at arXiv , submitted to SoftwareX.
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OPUS grant
I received funding from NCN Poland for 3 year personal grant for me and two PhD students to research Shared Mobility in the context of COVID more
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Seminar-at-MIMUW
Gave seminar at Warsaw University (MIMUW) - invited by Pawel Gora - on youtube in Polish
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Our simulations with Andres input in Transportmetrica:A
We published our stochastic simulations of late-arrival of ride-pooling travellers, with a great Game-Theory input from Andres Fielbaum (TU Delft) in Transportmetrica:A
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Our algorithm published
Our demand-driven ride-pooling algorithm cutting the combinatorial search-space of practical problems published in Part:B with Oded.
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Our studies published in JAT
Studies of induced traffic in Krakow with a novel non-parametric model published in JAT
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Our poster presented at TRB2020
Yesterday Guido Cantelmo (TUM) presented our poster on big mobility data in Washington at #TRBAM. We collected data on millions of city bike trips from NYC and started thinking how to synthesize them. We came up with this idea of ‘vector of movement’ that aggregates mobility pattern into a single vector. With this we may now cluster big datasets into groups of similar patterns and provide more accurate mobility predictions (including weather).