Alvaro Cabrejas-Egea
Alvaro Cabrejas-Egea
Fujitsu Research of Europe, University of Warwick
Verified email at
Cited by
Cited by
Assessment of reward functions for reinforcement learning traffic signal control under real-world limitations
A Cabrejas-Egea, S Howell, M Knutins, C Connaughton
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020
Reinforcement Learning for Traffic Signal Control: Comparison with Commercial Systems
A Cabrejas-Egea, R Zhang, N Walton
Transportation Research Procedia 58, 638-645, 2021
Design choices for productive, secure, data-intensive research at scale in the cloud
D Arenas, J Atkins, C Austin, D Beavan, A Cabrejas-Egea, ...
arXiv preprint arXiv:1908.08737, 2019
Estimating baseline travel times for the UK strategic road network
A Cabrejas-Egea, P de Ford, C Connaughton
2018 21st International Conference on Intelligent Transportation Systems …, 2018
Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations
A Cabrejas-Egea, C Connaughton
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
Wavelet Augmented Regression Profiling (WARP): improved long-term estimation of travel time series with recurrent congestion
A Cabrejas-Egea, C Connaughton
2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020
New applications of data science for intelligent transportation systems
A Cabrejas Egea
University of Warwick, 2020
Even busier than usual: modelling excess congestion on the Strategic Road Network
A Boustati, A Cabrejas-Egea, C Connaughton, P De Ford González, ...
Estimating Baseline Travel Times
A Cabrejas-Egea, P De Ford, C Connaughton
The system can't perform the operation now. Try again later.
Articles 1–9