activity
20202022
most citedTravel time prediction for congested freeways with a dynamic linear model

26 citations · 26 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SI2022

A Hybrid Microscopic Model for Multimodal Traffic with Empirical Observations from Aerial Footage

Georg Anagnostopoulos, Nikolas Geroliminis

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are negl…

eess.SY2022

A Pricing Mechanism for Balancing the Charging of Ride-Hailing Electric Vehicle Fleets

Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis

Both ride-hailing services and electric vehicles are becoming increasingly popular and it is likely that charging management of the ride-hailing vehicles will be a significant part…

cs.LG2021

Traffic signal prediction on transportation networks using spatio-temporal correlations on graphs

Semin Kwak, Nikolas Geroliminis, Pascal Frossard

Multivariate time series forecasting poses challenges as the variables are intertwined in time and space, like in the case of traffic signals. Defining signals on graphs relaxes su…

cs.LG202026 cited

Travel time prediction for congested freeways with a dynamic linear model

Semin Kwak, Nikolas Geroliminis

Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction…

physics.soc-ph2020

On the inefficiency of ride-sourcing services towards urban congestion

Caio Vitor Beojone, Nikolas Geroliminis

The advent of shared-economy and smartphones made on-demand transportation services possible, which created additional opportunities, but also more complexity to urban mobility. Co…