40 citations · 73 across the 4 of their papers we have counts for
7 papers
How do you go where? Improving next location prediction by learning travel mode information using transformers
Ye Hong, Henry Martin, Martin Raubal
Predicting the next visited location of an individual is a key problem in human mobility analysis, as it is required for the personalization and optimization of sustainable transpo…
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis
Yanan Xin, Natasa Tagasovska, Fernando Perez-Cruz +1
Artificial intelligence (AI) is revolutionizing many areas of our lives, leading a new era of technological advancement. Particularly, the transportation sector would benefit from…
National-scale bi-directional EV fleet control for ancillary service provision
Lorenzo Nespoli, Nina Wiedemann, Esra Suel +3
Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this pap…
Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Christian Eichenberger, Moritz Neun, Henry Martin +34
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggrega…
Traffic Forecasting on Traffic Moving Snippets
Nina Wiedemann, Martin Raubal
Advances in traffic forecasting technology can greatly impact urban mobility. In the traffic4cast competition, the task of short-term traffic prediction is tackled in unprecedented…
Applications of deep learning in traffic congestion detection, prediction and alleviation: A survey
Nishant Kumar, Martin Raubal
Detecting, predicting, and alleviating traffic congestion are targeted at improving the level of service of the transportation network. With increasing access to larger datasets of…